Intelligent, Self-Diagnostic Thermal Protection System for Future Spacecraft

NASA Technical Reports Server (NTRS)

Hyers, Robert W.; SanSoucie, Michael P.; Pepyne, David; Hanlon, Alaina B.; Deshmukh, Abhijit

2005-01-01

The goal of this project is to provide self-diagnostic capabilities to the thermal protection systems (TPS) of future spacecraft. Self-diagnosis is especially important in thermal protection systems (TPS), where large numbers of parts must survive extreme conditions after weeks or years in space. In-service inspections of these systems are difficult or impossible, yet their reliability must be ensured before atmospheric entry. In fact, TPS represents the greatest risk factor after propulsion for any transatmospheric mission. The concepts and much of the technology would be applicable not only to the Crew Exploration Vehicle (CEV), but also to ablative thermal protection for aerocapture and planetary exploration. Monitoring a thermal protection system on a Shuttle-sized vehicle is a daunting task: there are more than 26,000 components whose integrity must be verified with very low rates of both missed faults and false positives. The large number of monitored components precludes conventional approaches based on centralized data collection over separate wires; a distributed approach is necessary to limit the power, mass, and volume of the health monitoring system. Distributed intelligence with self-diagnosis further improves capability, scalability, robustness, and reliability of the monitoring subsystem. A distributed system of intelligent sensors can provide an assurance of the integrity of the system, diagnosis of faults, and condition-based maintenance, all with provable bounds on errors.

Support vector machine in machine condition monitoring and fault diagnosis

NASA Astrophysics Data System (ADS)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

A Wireless and Batteryless Intelligent Carbon Monoxide Sensor.

PubMed

Chen, Chen-Chia; Sung, Gang-Neng; Chen, Wen-Ching; Kuo, Chih-Ting; Chue, Jin-Ju; Wu, Chieh-Ming; Huang, Chun-Ming

2016-09-23

Carbon monoxide (CO) poisoning from natural gas water heaters is a common household accident in Taiwan. We propose a wireless and batteryless intelligent CO sensor for improving the safety of operating natural gas water heaters. A micro-hydropower generator supplies power to a CO sensor without battery (COSWOB) (2.5 W at a flow rate of 4.2 L/min), and the power consumption of the COSWOB is only ~13 mW. The COSWOB monitors the CO concentration in ambient conditions around natural gas water heaters and transmits it to an intelligent gateway. When the CO level reaches a dangerous level, the COSWOB alarm sounds loudly. Meanwhile, the intelligent gateway also sends a trigger to activate Wi-Fi alarms and sends notifications to the mobile device through the Internet. Our strategy can warn people indoors and outdoors, thereby reducing CO poisoning accidents. We also believe that our technique not only can be used for home security but also can be used in industrial applications (for example, to monitor leak occurrence in a pipeline).

A Wireless and Batteryless Intelligent Carbon Monoxide Sensor

PubMed Central

Chen, Chen-Chia; Sung, Gang-Neng; Chen, Wen-Ching; Kuo, Chih-Ting; Chue, Jin-Ju; Wu, Chieh-Ming; Huang, Chun-Ming

2016-01-01

Carbon monoxide (CO) poisoning from natural gas water heaters is a common household accident in Taiwan. We propose a wireless and batteryless intelligent CO sensor for improving the safety of operating natural gas water heaters. A micro-hydropower generator supplies power to a CO sensor without battery (COSWOB) (2.5 W at a flow rate of 4.2 L/min), and the power consumption of the COSWOB is only ~13 mW. The COSWOB monitors the CO concentration in ambient conditions around natural gas water heaters and transmits it to an intelligent gateway. When the CO level reaches a dangerous level, the COSWOB alarm sounds loudly. Meanwhile, the intelligent gateway also sends a trigger to activate Wi-Fi alarms and sends notifications to the mobile device through the Internet. Our strategy can warn people indoors and outdoors, thereby reducing CO poisoning accidents. We also believe that our technique not only can be used for home security but also can be used in industrial applications (for example, to monitor leak occurrence in a pipeline). PMID:27669255

Tool path strategy and cutting process monitoring in intelligent machining

NASA Astrophysics Data System (ADS)

Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei

2018-06-01

Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

Hybrid Modeling Improves Health and Performance Monitoring

NASA Technical Reports Server (NTRS)

2007-01-01

Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

Reconfigurable intelligent sensors for health monitoring: a case study of pulse oximeter sensor.

PubMed

Jovanov, E; Milenkovic, A; Basham, S; Clark, D; Kelley, D

2004-01-01

Design of low-cost, miniature, lightweight, ultra low-power, intelligent sensors capable of customization and seamless integration into a body area network for health monitoring applications presents one of the most challenging tasks for system designers. To answer this challenge we propose a reconfigurable intelligent sensor platform featuring a low-power microcontroller, a low-power programmable logic device, a communication interface, and a signal conditioning circuit. The proposed solution promises a cost-effective, flexible platform that allows easy customization, run-time reconfiguration, and energy-efficient computation and communication. The development of a common platform for multiple physical sensors and a repository of both software procedures and soft intellectual property cores for hardware acceleration will increase reuse and alleviate costs of transition to a new generation of sensors. As a case study, we present an implementation of a reconfigurable pulse oximeter sensor.

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2011 CFR

2011-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

Simulation of Smart Home Activity Datasets

PubMed Central

Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

2015-01-01

A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation. PMID:26087371

Simulation of Smart Home Activity Datasets.

PubMed

Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

2015-06-16

A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

NASA Astrophysics Data System (ADS)

Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

2017-04-01

With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications, hydraulic modelling to assess the likely impact that severe flood events will have on a bridges foundation, particularly due to scour. The process of reading and validating data from the WILD and BIRD buffer servers is outlined, as is the transmission protocol used for the sending of recorded data to a centralized repository for further use and analysis. Finally, the development of a centralized repository for the collection of data from the WILD and BIRD devices is presented. Eventually the big data solution would be used to receive, store and send the monitored data to the hydrological models, whether existing or developed, and the results would be transmitted to the intelligent decision support system based on a web-based platform, for managing, planning and executing data, processes and procedures for bridge assets. The development of intelligent hydroinformatic system is an important tool for the protection of key infrastructure assets from the increasingly common effects of climate change. Acknowledgement The authors wish to acknowledge the financial support of the European Commission, through the Marie Curie Industry-Academia Partnership and Pathways Network BRIDGE SMS (Intelligent Bridge Assessment Maintenance and Management System) - FP7-People-2013-IAPP- 612517.

Active and intelligent packaging systems for a modern society.

PubMed

Realini, Carolina E; Marcos, Begonya

2014-11-01

Active and intelligent packaging systems are continuously evolving in response to growing challenges from a modern society. This article reviews: (1) the different categories of active and intelligent packaging concepts and currently available commercial applications, (2) latest packaging research trends and innovations, and (3) the growth perspectives of the active and intelligent packaging market. Active packaging aiming at extending shelf life or improving safety while maintaining quality is progressing towards the incorporation of natural active agents into more sustainable packaging materials. Intelligent packaging systems which monitor the condition of the packed food or its environment are progressing towards more cost-effective, convenient and integrated systems to provide innovative packaging solutions. Market growth is expected for active packaging with leading shares for moisture absorbers, oxygen scavengers, microwave susceptors and antimicrobial packaging. The market for intelligent packaging is also promising with strong gains for time-temperature indicator labels and advancements in the integration of intelligent concepts into packaging materials. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Application Research of Modern Intelligent Cold Chain Distribution System Based on Internet of Things Technology

NASA Astrophysics Data System (ADS)

Fan, Dehui; Gao, Shan

This paper implemented an intelligent cold chain distribution system based on the technology of Internet of things, and took the protoplasmic beer logistics transport system as example. It realized the remote real-time monitoring material status, recorded the distribution information, dynamically adjusted the distribution tasks and other functions. At the same time, the system combined the Internet of things technology with weighted filtering algorithm, realized the real-time query of condition curve, emergency alarming, distribution data retrieval, intelligent distribution task arrangement, etc. According to the actual test, it can realize the optimization of inventory structure, and improve the efficiency of cold chain distribution.

Hybrid intelligent monironing systems for thermal power plant trips

NASA Astrophysics Data System (ADS)

Barsoum, Nader; Ismail, Firas Basim

2012-11-01

Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

PubMed

Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

2012-01-01

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

PubMed Central

Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

2012-01-01

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions. PMID:23112650

Application of intelligent sensors in the integrated systems health monitoring of a rocket test stand

NASA Astrophysics Data System (ADS)

Mahajan, Ajay; Chitikeshi, Sanjeevi; Utterbach, Lucas; Bandhil, Pavan; Figueroa, Fernando

2006-05-01

This paper describes the application of intelligent sensors in the Integrated Systems Health Monitoring (ISHM) as applied to a rocket test stand. The development of intelligent sensors is attempted as an integrated system approach, i.e. one treats the sensors as a complete system with its own physical transducer, A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements associated with the rocket tests stands. These smart elements can be sensors, actuators or other devices. Though the immediate application is the monitoring of the rocket test stands, the technology should be generally applicable to the ISHM vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent sensors (PIS) and Virtual Intelligent Sensors (VIS).

Expert System Software

NASA Technical Reports Server (NTRS)

1989-01-01

C Language Integrated Production System (CLIPS) is a software shell for developing expert systems is designed to allow research and development of artificial intelligence on conventional computers. Originally developed by Johnson Space Center, it enables highly efficient pattern matching. A collection of conditions and actions to be taken if the conditions are met is built into a rule network. Additional pertinent facts are matched to the rule network. Using the program, E.I. DuPont de Nemours & Co. is monitoring chemical production machines; California Polytechnic State University is investigating artificial intelligence in computer aided design; Mentor Graphics has built a new Circuit Synthesis system, and Brooke and Brooke, a law firm, can determine which facts from a file are most important.

Intelligent Chemical Sensor Systems for In-space Safety Applications

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Measuring up to speech intelligibility.

PubMed

Miller, Nick

2013-01-01

Improvement or maintenance of speech intelligibility is a central aim in a whole range of conditions in speech-language therapy, both developmental and acquired. Best clinical practice and pursuance of the evidence base for interventions would suggest measurement of intelligibility forms a vital role in clinical decision-making and monitoring. However, what should be measured to gauge intelligibility and how this is achieved and relates to clinical planning continues to be a topic of debate. This review considers the strengths and weaknesses of selected clinical approaches to intelligibility assessment, stressing the importance of explanatory, diagnostic testing as both a more sensitive and a clinically informative method. The worth of this, and any approach, is predicated, though, on awareness and control of key design, elicitation, transcription and listening/listener variables to maximize validity and reliability of assessments. These are discussed. A distinction is drawn between signal-dependent and -independent factors in intelligibility evaluation. Discussion broaches how these different perspectives might be reconciled to deliver comprehensive insights into intelligibility levels and their clinical/educational significance. The paper ends with a call for wider implementation of best practice around intelligibility assessment. © 2013 Royal College of Speech and Language Therapists.

Intelligent Sensors: Strategies for an Integrated Systems Approach

NASA Technical Reports Server (NTRS)

Chitikeshi, Sanjeevi; Mahajan, Ajay; Bandhil, Pavan; Utterbach, Lucas; Figueroa, Fernando

2005-01-01

This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Real-Time Implementation of Intelligent Actuator Control with a Transducer Health Monitoring Capability

NASA Technical Reports Server (NTRS)

Jethwa, Dipan; Selmic, Rastko R.; Figueroa, Fernando

2008-01-01

This paper presents a concept of feedback control for smart actuators that are compatible with smart sensors, communication protocols, and a hierarchical Integrated System Health Management (ISHM) architecture developed by NASA s Stennis Space Center. Smart sensors and actuators typically provide functionalities such as automatic configuration, system condition awareness and self-diagnosis. Spacecraft and rocket test facilities are in the early stages of adopting these concepts. The paper presents a concept combining the IEEE 1451-based ISHM architecture with a transducer health monitoring capability to enhance the control process. A control system testbed for intelligent actuator control, with on-board ISHM capabilities, has been developed and implemented. Overviews of the IEEE 1451 standard, the smart actuator architecture, and control based on this architecture are presented.

Intelligent Tires Based on Measurement of Tire Deformation

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a ‘safe’ reference value.

Intelligent tires for improved tire safety using wireless strain measurement

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

2008-03-01

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a 'safe' reference value.

Intelligent Software Agents: Sensor Integration and Response

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

Kulesz, James J; Lee, Ronald W

2013-01-01

Abstract In a post Macondo world the buzzwords are Integrity Management and Incident Response Management. The twin processes are not new but the opportunity to link the two is novel. Intelligent software agents can be used with sensor networks in distributed and centralized computing systems to enhance real-time monitoring of system integrity as well as manage the follow-on incident response to changing, and potentially hazardous, environmental conditions. The software components are embedded at the sensor network nodes in surveillance systems used for monitoring unusual events. When an event occurs, the software agents establish a new concept of operation at themore » sensing node, post the event status to a blackboard for software agents at other nodes to see , and then react quickly and efficiently to monitor the scale of the event. The technology addresses a current challenge in sensor networks that prevents a rapid and efficient response when a sensor measurement indicates that an event has occurred. By using intelligent software agents - which can be stationary or mobile, interact socially, and adapt to changing situations - the technology offers features that are particularly important when systems need to adapt to active circumstances. For example, when a release is detected, the local software agent collaborates with other agents at the node to exercise the appropriate operation, such as: targeted detection, increased detection frequency, decreased detection frequency for other non-alarming sensors, and determination of environmental conditions so that adjacent nodes can be informed that an event is occurring and when it will arrive. The software agents at the nodes can also post the data in a targeted manner, so that agents at other nodes and the command center can exercise appropriate operations to recalibrate the overall sensor network and associated intelligence systems. The paper describes the concepts and provides examples of real-world implementations including the Threat Detection and Analysis System (TDAS) at the International Port of Memphis and the Biological Warning and Incident Characterization System (BWIC) Environmental Monitoring (EM) Component. Technologies developed for these 24/7 operational systems have applications for improved real-time system integrity awareness as well as provide incident response (as needed) for production and field applications.« less

Distributed intelligent monitoring and reporting facilities

NASA Astrophysics Data System (ADS)

Pavlou, George; Mykoniatis, George; Sanchez-P, Jorge-A.

1996-06-01

Distributed intelligent monitoring and reporting facilities are of paramount importance in both service and network management as they provide the capability to monitor quality of service and utilization parameters and notify degradation so that corrective action can be taken. By intelligent, we refer to the capability of performing the monitoring tasks in a way that has the smallest possible impact on the managed network, facilitates the observation and summarization of information according to a number of criteria and in its most advanced form and permits the specification of these criteria dynamically to suit the particular policy in hand. In addition, intelligent monitoring facilities should minimize the design and implementation effort involved in such activities. The ISO/ITU Metric, Summarization and Performance management functions provide models that only partially satisfy the above requirements. This paper describes our extensions to the proposed models to support further capabilities, with the intention to eventually lead to fully dynamically defined monitoring policies. The concept of distributing intelligence is also discussed, including the consideration of security issues and the applicability of the model in ODP-based distributed processing environments.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil.

PubMed

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-11-11

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters.

Proposal of an intelligent wayside monitoring system for detection of critical ice accumulations on railway vehicles

NASA Astrophysics Data System (ADS)

Michelberger, Frank; Wagner, Adrian; Ostermann, Michael; Maly, Thomas

2017-09-01

At railway lines with ballasted tracks, under unfavourable conditions, the so-called flying ballast can occur predominantly for trains driving at high speeds. Especially in wintertime, it is highly likely that the causes are adhered snow or ice deposits, which are falling off the vehicle. Due to the high kinetic energy, the impact can lead to the removal of ballast stones from the structure of the ballasted track. If the stones reach the height of vehicles underside, they may be accelerated significantly due to the collision with the vehicle or may detach further ice blocks. In the worst case, a reinforcing effect occurs, which can lead to considerable damage to railway vehicles (under-floor-area, vehicle exteriors, etc.) and infrastructure (signal masts, noise barriers, etc.). Additionally the flying gravel is a significant danger to people in the nearby area of the tracks. With this feasibility study the applicability and meaningfulness of an intelligent monitoring system for identification of the critical ice accumulation to prevent the ballast fly induced by ice dropping was examined. The key findings of the research are that the detection of ice on railway vehicles and the development of an intelligent monitoring seem to be possible with existing technologies, but a proof of concept in terms of field tests is necessary.

Intelligent transient transitions detection of LRE test bed

NASA Astrophysics Data System (ADS)

Zhu, Fengyu; Shen, Zhengguang; Wang, Qi

2013-01-01

Health Monitoring Systems is an implementation of monitoring strategies for complex systems whereby avoiding catastrophic failure, extending life and leading to improved asset management. A Health Monitoring Systems generally encompasses intelligence at many levels and sub-systems including sensors, actuators, devices, etc. In this paper, a smart sensor is studied, which is use to detect transient transitions of liquid-propellant rocket engines test bed. In consideration of dramatic changes of variable condition, wavelet decomposition is used to work real time in areas. Contrast to traditional Fourier transform method, the major advantage of adding wavelet analysis is the ability to detect transient transitions as well as obtaining the frequency content using a much smaller data set. Historically, transient transitions were only detected by offline analysis of the data. The methods proposed in this paper provide an opportunity to detect transient transitions automatically as well as many additional data anomalies, and provide improved data-correction and sensor health diagnostic abilities. The developed algorithms have been tested on actual rocket test data.

On the use of multi-agent systems for the monitoring of industrial systems

NASA Astrophysics Data System (ADS)

Rezki, Nafissa; Kazar, Okba; Mouss, Leila Hayet; Kahloul, Laid; Rezki, Djamil

2016-03-01

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.

FPGA Based "Intelligent Tap" Device for Real-Time Ethernet Network Monitoring

NASA Astrophysics Data System (ADS)

Cupek, Rafał; Piękoś, Piotr; Poczobutt, Marcin; Ziębiński, Adam

This paper describes an "Intelligent Tap" - hardware device dedicated to support real-time Ethernet networks monitoring. Presented solution was created as a student project realized in Institute of Informatics, Silesian University of Technology with support from Softing A.G company. Authors provide description of realized FPGA based "Intelligent Tap" architecture dedicated for Real-Time Ethernet network monitoring systems. The practical device realization and feasibility study conclusions are presented also.

Current topics in active and intelligent food packaging for preservation of fresh foods.

PubMed

Lee, Seung Yuan; Lee, Seung Jae; Choi, Dong Soo; Hur, Sun Jin

2015-11-01

The purpose of this review is to provide an overview of current packaging systems, e.g. active packaging and intelligent packaging, for various foods. Active packaging, such as modified atmosphere packaging (MAP), extends the shelf life of fresh produce, provides a high-quality product, reduces economic losses, including those caused by delay of ripening, and improves appearance. However, in active packaging, several variables must be considered, such as temperature control and different gas formulations with different product types and microorganisms. Active packaging refers to the incorporation of additive agents into packaging materials with the purpose of maintaining or extending food product quality and shelf life. Intelligent packaging is emerging as a potential advantage in food processing and is an especially useful tool for tracking product information and monitoring product conditions. Moreover, intelligent packaging facilitates data access and information exchange by altering conditions inside or outside the packaging and product. In spite of these advantages, few of these packaging systems are commercialized because of high cost, strict safety and hygiene regulations or limited consumer acceptance. Therefore more research is needed to develop cheaper, more easily applicable and effective packaging systems for various foods. © 2015 Society of Chemical Industry.

Design and Development of Intelligent Electrodes for Future Digital Health Monitoring: A Review

NASA Astrophysics Data System (ADS)

Khairuddin, A. M.; Azir, K. N. F. Ku; Kan, P. Eh

2018-03-01

Electrodes are sensors used in electrocardiography (ECG) monitoring system to diagnose heart diseases. Over the years, diverse types of electrodes have been designed and developed to improve ECG monitoring system. However, more recently, with the technological advances and capabilities from the Internet of Things (IoT), cloud computing and data analytics in personalized healthcare, researchers are attempting to design and develop more effective as well as flexible ECG devices by using intelligent electrodes. This paper reviews previous works on electrodes used in electrocardiography (ECG) monitoring devices to identify the key ftures for designing and developing intelligent electrodes in digital health monitoring devices.

Two examples of intelligent systems based on smart materials

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

Unsworth, J.

1994-12-31

Two intelligent systems are described which are based on smart materials. The operation of the systems also rely on conventional well known technologies such as electronics, signal conditioning, signal processing, microprocessors and engineering design. However without the smart materials the development and integration into the intelligent systems would not have been possible. System 1 is a partial discharge monitor for on-line continuous checking of the condition of electrical power transformers. The ultrasonic and radio frequency detectors in this system rely on special piezoelectric composite integrated with a compact annular metal ring. Partial discharges set up ultrasonic and radio frequency signalsmore » which are received by the integrated detectors. The signals are amplified, conditioned, signal processed, the time interval between the two signals measured and the level of partial discharge activity averaged and assessed for numerous pairs and alarms triggered on remote control panels if the level is dangerous. The system has the capability of initiating automatic shutdown of the transformer once it is linked into the control computers of the electrical power authority. System 2 is called a Security Cradle and is an intelligent 3D shield designed to use the properties of electro active polymers to prevent hardware hackers from stealing valuable of sensitive information from memory devices (e.g., EPROMS) housed in computer or microprocessor installations.« less

Intelligent Sensors: An Integrated Systems Approach

NASA Technical Reports Server (NTRS)

Mahajan, Ajay; Chitikeshi, Sanjeevi; Bandhil, Pavan; Utterbach, Lucas; Figueroa, Fernando

2005-01-01

The need for intelligent sensors as a critical component for Integrated System Health Management (ISHM) is fairly well recognized by now. Even the definition of what constitutes an intelligent sensor (or smart sensor) is well documented and stems from an intuitive desire to get the best quality measurement data that forms the basis of any complex health monitoring and/or management system. If the sensors, i.e. the elements closest to the measurand, are unreliable then the whole system works with a tremendous handicap. Hence, there has always been a desire to distribute intelligence down to the sensor level, and give it the ability to assess its own health thereby improving the confidence in the quality of the data at all times. This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines some fundamental issues in the development of intelligent sensors under the following two categories: Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Architecture for Adaptive Intelligent Systems

NASA Technical Reports Server (NTRS)

Hayes-Roth, Barbara

1993-01-01

We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring.

Operations Monitoring Assistant System Design

DTIC Science & Technology

1986-07-01

Logic. Artificial Inteligence 25(1)::75-94. January.18. 41 -Nils J. Nilsson. Problem-Solving Methods In Artificli Intelligence. .klcG raw-Hill B3ook...operations monitoring assistant (OMA) system is designed that combines operations research, artificial intelligence, and human reasoning techniques and...KnowledgeCraft (from Carnegie Group), and 5.1 (from Teknowledze). These tools incorporate the best methods of applied artificial intelligence, and

Intelligent Control and Health Monitoring. Chapter 3

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Overnight non-contact continuous vital signs monitoring using an intelligent automatic beam-steering Doppler sensor at 2.4 GHz.

PubMed

Batchu, S; Narasimhachar, H; Mayeda, J C; Hall, T; Lopez, J; Nguyen, T; Banister, R E; Lie, D Y C

2017-07-01

Doppler-based non-contact vital signs (NCVS) sensors can monitor heart rates, respiration rates, and motions of patients without physically touching them. We have developed a novel single-board Doppler-based phased-array antenna NCVS biosensor system that can perform robust overnight continuous NCVS monitoring with intelligent automatic subject tracking and optimal beam steering algorithms. Our NCVS sensor achieved overnight continuous vital signs monitoring with an impressive heart-rate monitoring accuracy of over 94% (i.e., within ±5 Beats-Per-Minute vs. a reference sensor), analyzed from over 400,000 data points collected during each overnight monitoring period of ~ 6 hours at a distance of 1.75 meters. The data suggests our intelligent phased-array NCVS sensor can be very attractive for continuous monitoring of low-acuity patients.

Smart packaging systems for food applications: a review.

PubMed

Biji, K B; Ravishankar, C N; Mohan, C O; Srinivasa Gopal, T K

2015-10-01

Changes in consumer preference for safe food have led to innovations in packaging technologies. This article reviews about different smart packaging systems and their applications in food packaging, packaging research with latest innovations. Active and intelligent packing are such packaging technologies which offer to deliver safer and quality products. Active packaging refers to the incorporation of additives into the package with the aim of maintaining or extending the product quality and shelf life. The intelligent systems are those that monitor the condition of packaged food to give information regarding the quality of the packaged food during transportation and storage. These technologies are designed to the increasing demand for safer foods with better shelf life. The market for active and intelligent packaging systems is expected to have a promising future by their integration into packaging materials or systems.

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil

PubMed Central

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-01-01

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. PMID:26569243

An Intelligent Sensor Array Distributed System for Vibration Analysis and Acoustic Noise Characterization of a Linear Switched Reluctance Actuator

PubMed Central

Salvado, José; Espírito-Santo, António; Calado, Maria

2012-01-01

This paper proposes a distributed system for analysis and monitoring (DSAM) of vibrations and acoustic noise, which consists of an array of intelligent modules, sensor modules, communication bus and a host PC acting as data center. The main advantages of the DSAM are its modularity, scalability, and flexibility for use of different type of sensors/transducers, with analog or digital outputs, and for signals of different nature. Its final cost is also significantly lower than other available commercial solutions. The system is reconfigurable, can operate either with synchronous or asynchronous modes, with programmable sampling frequencies, 8-bit or 12-bit resolution and a memory buffer of 15 kbyte. It allows real-time data-acquisition for signals of different nature, in applications that require a large number of sensors, thus it is suited for monitoring of vibrations in Linear Switched Reluctance Actuators (LSRAs). The acquired data allows the full characterization of the LSRA in terms of its response to vibrations of structural origins, and the vibrations and acoustic noise emitted under normal operation. The DSAM can also be used for electrical machine condition monitoring, machine fault diagnosis, structural characterization and monitoring, among other applications. PMID:22969364

Putting intelligent structured intermittent auscultation (ISIA) into practice.

PubMed

Maude, Robyn M; Skinner, Joan P; Foureur, Maralyn J

2016-06-01

Fetal monitoring guidelines recommend intermittent auscultation for the monitoring of fetal wellbeing during labour for low-risk women. However, these guidelines are not being translated into practice and low-risk women birthing in institutional maternity units are increasingly exposed to continuous cardiotocographic monitoring, both on admission to hospital and during labour. When continuous fetal monitoring becomes routinised, midwives and obstetricians lose practical skills around intermittent auscultation. To support clinical practice and decision-making around auscultation modality, the intelligent structured intermittent auscultation (ISIA) framework was developed. The purpose of this discussion paper is to describe the application of intelligent structured intermittent auscultation in practice. The intelligent structured intermittent auscultation decision-making framework is a knowledge translation tool that supports the implementation of evidence into practice around the use of intermittent auscultation for fetal heart monitoring for low-risk women during labour. An understanding of the physiology of the materno-utero-placental unit and control of the fetal heart underpin the development of the framework. Intelligent structured intermittent auscultation provides midwives with a robust means of demonstrating their critical thinking and clinical reasoning and supports their understanding of normal physiological birth. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Microinjection Monitoring System Design Applied to MRI Scanning].

PubMed

Xu, Yongfeng

2017-09-30

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

Intelligent model-based diagnostics for vehicle health management

NASA Astrophysics Data System (ADS)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Integrated intelligent systems in advanced reactor control rooms

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

Beckmeyer, R.R.

1989-01-01

An intelligent, reactor control room, information system is designed to be an integral part of an advanced control room and will assist the reactor operator's decision making process by continuously monitoring the current plant state and providing recommended operator actions to improve that state. This intelligent system is an integral part of, as well as an extension to, the plant protection and control systems. This paper describes the interaction of several functional components (intelligent information data display, technical specifications monitoring, and dynamic procedures) of the overall system and the artificial intelligence laboratory environment assembled for testing the prototype. 10 refs.,more » 5 figs.« less

An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

NASA Astrophysics Data System (ADS)

Li, De Z.; Wang, Wilson; Ismail, Fathy

2017-11-01

Induction motors (IMs) are commonly used in various industrial applications. To improve energy consumption efficiency, a reliable IM health condition monitoring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is proposed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are synthesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air-gap eccentricity diagnosis. The effectiveness of the proposed harmonic synthesis technique is examined experimentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-04-23

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

Condition Monitoring Techniques for Electromechanical Equipment Used in Air Force Ground C3I (Command, Control, Communications and Intelligence) Systems.

DTIC Science & Technology

1983-08-01

Proc. 2nd Congress National de flabilite, Perros -Guirec, Sept. 17-20, 1974, pp. 639-653. Published by CNET, Lannion (France). 53. Love, A. E. H., A...96. C. Rosiaux, Fiabilite des allumeurs determinee a partir des ventes-echanges, Proc. 2nd Congres National de fiabilite, Perros Guirec, Sept. 17-20

Emotional Intelligence and Interpersonal Relations.

ERIC Educational Resources Information Center

Schutte, Nicola S.; Malouff, John M.; Bobik, Chad; Coston, Tracie D.; Greeson, Cyndy; Jedlicka, Christina; Rhodes, Emily; Wendorf, Greta

2001-01-01

Presents the results of seven studies that focused on the link between emotional intelligence and interpersonal relations. Tests emotional intelligence with empathy and self-monitoring, social skills, cooperation, relations with others, and marital satisfaction. Explores preference for emotionally intelligent partners in the final study. Includes…

Self-Monitoring of Listening Abilities in Normal-Hearing Children, Normal-Hearing Adults, and Children with Cochlear Implants

PubMed Central

Rothpletz, Ann M.; Wightman, Frederic L.; Kistler, Doris J.

2012-01-01

Background Self-monitoring has been shown to be an essential skill for various aspects of our lives, including our health, education, and interpersonal relationships. Likewise, the ability to monitor one’s speech reception in noisy environments may be a fundamental skill for communication, particularly for those who are often confronted with challenging listening environments, such as students and children with hearing loss. Purpose The purpose of this project was to determine if normal-hearing children, normal-hearing adults, and children with cochlear implants can monitor their listening ability in noise and recognize when they are not able to perceive spoken messages. Research Design Participants were administered an Objective-Subjective listening task in which their subjective judgments of their ability to understand sentences from the Coordinate Response Measure corpus presented in speech spectrum noise were compared to their objective performance on the same task. Study Sample Participants included 41 normal-hearing children, 35 normal-hearing adults, and 10 children with cochlear implants. Data Collection and Analysis On the Objective-Subjective listening task, the level of the masker noise remained constant at 63 dB SPL, while the level of the target sentences varied over a 12 dB range in a block of trials. Psychometric functions, relating proportion correct (Objective condition) and proportion perceived as intelligible (Subjective condition) to target/masker ratio (T/M), were estimated for each participant. Thresholds were defined as the T/M required to produce 51% correct (Objective condition) and 51% perceived as intelligible (Subjective condition). Discrepancy scores between listeners’ threshold estimates in the Objective and Subjective conditions served as an index of self-monitoring ability. In addition, the normal-hearing children were administered tests of cognitive skills and academic achievement, and results from these measures were compared to findings on the Objective-Subjective listening task. Results Nearly half of the children with normal hearing significantly overestimated their listening in noise ability on the Objective-Subjective listening task, compared to less than 9% of the adults. There was a significant correlation between age and results on the Objective-Subjective task, indicating that the younger children in the sample (age 7–12 yr) tended to overestimate their listening ability more than the adolescents and adults. Among the children with cochlear implants, eight of the 10 participants significantly overestimated their listening ability (as compared to 13 of the 24 normal-hearing children in the same age range). We did not find a significant relationship between results on the Objective-Subjective listening task and performance on the given measures of academic achievement or intelligence. Conclusions Findings from this study suggest that many children with normal hearing and children with cochlear implants often fail to recognize when they encounter conditions in which their listening ability is compromised. These results may have practical implications for classroom learning, particularly for children with hearing loss in mainstream settings. PMID:22436118

Ambient intelligence application based on environmental measurements performed with an assistant mobile robot.

PubMed

Martinez, Dani; Teixidó, Mercè; Font, Davinia; Moreno, Javier; Tresanchez, Marcel; Marco, Santiago; Palacín, Jordi

2014-03-27

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

Ambient Intelligence Application Based on Environmental Measurements Performed with an Assistant Mobile Robot

PubMed Central

Martinez, Dani; Teixidó, Mercè; Font, Davinia; Moreno, Javier; Tresanchez, Marcel; Marco, Santiago; Palacín, Jordi

2014-01-01

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile. PMID:24681671

[Intelligent videosurveillance and falls detection: Perceptions of professionals and managers].

PubMed

Lapierre, Nolwenn; Carpentier, Isabelle; St-Arnaud, Alain; Ducharme, Francine; Meunier, Jean; Jobidon, Mireille; Rousseau, Jacqueline

2016-02-01

Gerontechnologies can be used to detect accidental falls. However, existing systems do not entirely meet users' expectations. Our team developed an intelligent video-monitoring systems to fill these gaps. Authors advocate consulting potential users at the early stages of the design of gerontechnologies and integrating their suggestions. This study aims to explore health care workers' opinion regarding the intelligent video monitoring to detect falls by older adults living at home. This qualitative study explored the opinions of 31 participants using focus groups. Transcripts were analyzed using predetermined codes based on the competence model. Participants reported several advantages for using the intelligent video monitoring and provided suggestions for improving its use. The participants' suggestions and comments will help to improve the system and match it to users' needs. © CAOT 2015.

Software for Intelligent System Health Management

NASA Technical Reports Server (NTRS)

Trevino, Luis C.

2004-01-01

This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

An intelligent remote monitoring system for artificial heart.

PubMed

Choi, Jaesoon; Park, Jun W; Chung, Jinhan; Min, Byoung G

2005-12-01

A web-based database system for intelligent remote monitoring of an artificial heart has been developed. It is important for patients with an artificial heart implant to be discharged from the hospital after an appropriate stabilization period for better recovery and quality of life. Reliable continuous remote monitoring systems for these patients with life support devices are gaining practical meaning. The authors have developed a remote monitoring system for this purpose that consists of a portable/desktop monitoring terminal, a database for continuous recording of patient and device status, a web-based data access system with which clinicians can access real-time patient and device status data and past history data, and an intelligent diagnosis algorithm module that noninvasively estimates blood pump output and makes automatic classification of the device status. The system has been tested with data generation emulators installed on remote sites for simulation study, and in two cases of animal experiments conducted at remote facilities. The system showed acceptable functionality and reliability. The intelligence algorithm also showed acceptable practicality in an application to animal experiment data.

From pilot's associate to satellite controller's associate

NASA Technical Reports Server (NTRS)

Neyland, David L.; Lizza, Carl; Merkel, Philip A.

1992-01-01

Associate technology is an emerging engineering discipline wherein intelligent automation can significantly augment the performance of man-machine systems. An associate system is one that monitors operator activity and adapts its operational behavior accordingly. Associate technology is most effectively applied when mapped into management of the human-machine interface and display-control loop in typical manned systems. This paper addresses the potential for application of associate technology into the arena of intelligent command and control of satellite systems, from diagnosis of onboard and onground of satellite systems fault conditions, to execution of nominal satellite control functions. Rather than specifying a specific solution, this paper draws parallels between the Pilot's Associate concept and the domain of satellite control.

An overview of Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET) Project

NASA Technical Reports Server (NTRS)

Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

1991-01-01

A software application to assist end-users of the link evaluation terminal (LET) for satellite communications is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving (220/110 Mbps) capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. The HBR LET can determine the bit error rate (BER) under various atmospheric conditions by comparing the transmitted bit pattern with the received bit pattern. An algorithm for power augmentation will be applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions.

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

PubMed

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

2008-01-01

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

Development of a head impact monitoring "Intelligent Mouthguard".

PubMed

Hedin, Daniel S; Gibson, Paul L; Bartsch, Adam J; Samorezov, Sergey

2016-08-01

The authors present the development and laboratory system-level testing of an impact monitoring "Intelligent Mouthguard" intended to help with identification of potentially concussive head impacts and cumulative head impact dosage. The goal of Intelligent Mouthguard is to provide an indicator of potential concussion risk, and help caregiver identify athletes needing sideline concussion protocol testing. Intelligent Mouthguard may also help identify individuals who are at higher risk based on historical dosage. Intelligent Mouthguard integrates inertial sensors to provide 3-degree of freedom linear and rotational kinematics. The electronics are fully integrated into a custom mouthguard that couples tightly to the upper teeth. The combination of tight coupling and highly accurate sensor data means the Intelligent Mouthguard meets the National Football League (NFL) Level I validity specification based on laboratory system-level test data presented in this study.

Intelligent Monitoring of Rocket Test Systems

NASA Technical Reports Server (NTRS)

Duran, Esteban; Rocha, Stephanie; Figueroa, Fernando

2016-01-01

Stephanie Rocha is an undergraduate student pursuing a degree in Mechanical Engineering. Esteban Duran is pursuing a degree in Computer Science. Our mentor is Fernando Figueroa. Our project involved developing Intelligent Health Monitoring at the High Pressure Gas Facility (HPGF) utilizing the software GensymG2.

Improving the All-Hazards Homeland Security Enterprise Through the Use of an Emergency Management Intelligence Model

DTIC Science & Technology

2013-09-01

Office of the Inspector General OSINT Open Source Intelligence PPD Presidential Policy Directive SIGINT Signals Intelligence SLFC State/Local Fusion...Geospatial Intelligence (GEOINT) from Geographic Information Systems (GIS), and Open Source Intelligence ( OSINT ) from Social Media. GIS is widely...and monitor make it a feasible tool to capitalize on for OSINT . A formalized EM intelligence process would help expedite the processing of such

Intelligibility of clear speech: effect of instruction.

PubMed

Lam, Jennifer; Tjaden, Kris

2013-10-01

The authors investigated how clear speech instructions influence sentence intelligibility. Twelve speakers produced sentences in habitual, clear, hearing impaired, and overenunciate conditions. Stimuli were amplitude normalized and mixed with multitalker babble for orthographic transcription by 40 listeners. The main analysis investigated percentage-correct intelligibility scores as a function of the 4 conditions and speaker sex. Additional analyses included listener response variability, individual speaker trends, and an alternate intelligibility measure: proportion of content words correct. Relative to the habitual condition, the overenunciate condition was associated with the greatest intelligibility benefit, followed by the hearing impaired and clear conditions. Ten speakers followed this trend. The results indicated different patterns of clear speech benefit for male and female speakers. Greater listener variability was observed for speakers with inherently low habitual intelligibility compared to speakers with inherently high habitual intelligibility. Stable proportions of content words were observed across conditions. Clear speech instructions affected the magnitude of the intelligibility benefit. The instruction to overenunciate may be most effective in clear speech training programs. The findings may help explain the range of clear speech intelligibility benefit previously reported. Listener variability analyses suggested the importance of obtaining multiple listener judgments of intelligibility, especially for speakers with inherently low habitual intelligibility.

The design of the intelligent monitoring system for dam safety

NASA Astrophysics Data System (ADS)

Yuan, Chun-qiao; Jiang, Chen-guang; Wang, Guo-hui

2008-12-01

Being a vital manmade water-control structure, a dam plays a very important role in the living and production of human being. To make a dam run safely, the best design and the superior construction quality are paramount; moreover, with working periods increasing, various dynamic, alternative and bad loads generate little by little various distortions on the dam structure inevitably, which shall lead to potential safety problems or further a disaster (dam burst). There are many signs before the occurrence of a dam accident, so the timely and effective surveying on the distortion of a dam is important. On the basis of the cause supra, two intelligent (automatic) monitoring systems about the dam's safety based on the RTK-GPS technology and the measuring robot has been developed. The basic principle, monitoring method and monitoring process of these two intelligent (automatic) monitoring systems are introduced. It presents examples of monitor and puts forward the basic rule of dam warning based on data of actual monitor.

A Review of Passive RFID Tag Antenna-Based Sensors and Systems for Structural Health Monitoring Applications.

PubMed

Zhang, Jun; Tian, Gui Yun; Marindra, Adi M J; Sunny, Ali Imam; Zhao, Ao Bo

2017-01-29

In recent few years, the antenna and sensor communities have witnessed a considerable integration of radio frequency identification (RFID) tag antennas and sensors because of the impetus provided by internet of things (IoT) and cyber-physical systems (CPS). Such types of sensor can find potential applications in structural health monitoring (SHM) because of their passive, wireless, simple, compact size, and multimodal nature, particular in large scale infrastructures during their lifecycle. The big data from these ubiquitous sensors are expected to generate a big impact for intelligent monitoring. A remarkable number of scientific papers demonstrate the possibility that objects can be remotely tracked and intelligently monitored for their physical/chemical/mechanical properties and environment conditions. Most of the work focuses on antenna design, and significant information has been generated to demonstrate feasibilities. Further information is needed to gain deep understanding of the passive RFID antenna sensor systems in order to make them reliable and practical. Nevertheless, this information is scattered over much literature. This paper is to comprehensively summarize and clearly highlight the challenges and state-of-the-art methods of passive RFID antenna sensors and systems in terms of sensing and communication from system point of view. Future trends are also discussed. The future research and development in UK are suggested as well.

Augmented reality enabling intelligence exploitation at the edge

NASA Astrophysics Data System (ADS)

Kase, Sue E.; Roy, Heather; Bowman, Elizabeth K.; Patton, Debra

2015-05-01

Today's Warfighters need to make quick decisions while interacting in densely populated environments comprised of friendly, hostile, and neutral host nation locals. However, there is a gap in the real-time processing of big data streams for edge intelligence. We introduce a big data processing pipeline called ARTEA that ingests, monitors, and performs a variety of analytics including noise reduction, pattern identification, and trend and event detection in the context of an area of operations (AOR). Results of the analytics are presented to the Soldier via an augmented reality (AR) device Google Glass (Glass). Non-intrusive AR devices such as Glass can visually communicate contextually relevant alerts to the Soldier based on the current mission objectives, time, location, and observed or sensed activities. This real-time processing and AR presentation approach to knowledge discovery flattens the intelligence hierarchy enabling the edge Soldier to act as a vital and active participant in the analysis process. We report preliminary observations testing ARTEA and Glass in a document exploitation and person of interest scenario simulating edge Soldier participation in the intelligence process in disconnected deployment conditions.

Measuring Emotional Intelligence: Where We Are Today.

ERIC Educational Resources Information Center

Finegan, Jane E.

Emotional intelligence has been defined as "the ability to monitor one's own and others' feelings and emotions, to discriminate among them, and to use this information to guide one's thinking and actions" (P. Salovey and J. Mayer, 1990). As a subset of social intelligence and of personal intelligences (H. Gardner, 1983), emotional…

A Strain-Based Method to Detect Tires' Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development.

PubMed

Yunta, Jorge; Garcia-Pozuelo, Daniel; Diaz, Vicente; Olatunbosun, Oluremi

2018-02-06

Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire's loss of grip and estimations of the lateral friction coefficient.

A Strain-Based Method to Detect Tires’ Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development

PubMed Central

Garcia-Pozuelo, Daniel; Diaz, Vicente; Olatunbosun, Oluremi

2018-01-01

Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire’s loss of grip and estimations of the lateral friction coefficient. PMID:29415513

A Universal Intelligent System-on-Chip Based Sensor Interface

PubMed Central

Mattoli, Virgilio; Mondini, Alessio; Mazzolai, Barbara; Ferri, Gabriele; Dario, Paolo

2010-01-01

The need for real-time/reliable/low-maintenance distributed monitoring systems, e.g., wireless sensor networks, has been becoming more and more evident in many applications in the environmental, agro-alimentary, medical, and industrial fields. The growing interest in technologies related to sensors is an important indicator of these new needs. The design and the realization of complex and/or distributed monitoring systems is often difficult due to the multitude of different electronic interfaces presented by the sensors available on the market. To address these issues the authors propose the concept of a Universal Intelligent Sensor Interface (UISI), a new low-cost system based on a single commercial chip able to convert a generic transducer into an intelligent sensor with multiple standardized interfaces. The device presented offers a flexible analog and/or digital front-end, able to interface different transducer typologies (such as conditioned, unconditioned, resistive, current output, capacitive and digital transducers). The device also provides enhanced processing and storage capabilities, as well as a configurable multi-standard output interface (including plug-and-play interface based on IEEE 1451.3). In this work the general concept of UISI and the design of reconfigurable hardware are presented, together with experimental test results validating the proposed device. PMID:22163624

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition.

PubMed

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-03-27

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K -nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction.

INTEGRATED MONITORING HARDWARE DEVELOPMENTS AT LOS ALAMOS

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

R. PARKER; J. HALBIG; ET AL

1999-09-01

The hardware of the integrated monitoring system supports a family of instruments having a common internal architecture and firmware. Instruments can be easily configured from application-specific personality boards combined with common master-processor and high- and low-voltage power supply boards, and basic operating firmware. The instruments are designed to function autonomously to survive power and communication outages and to adapt to changing conditions. The personality boards allow measurement of gross gammas and neutrons, neutron coincidence and multiplicity, and gamma spectra. In addition, the Intelligent Local Node (ILON) provides a moderate-bandwidth network to tie together instruments, sensors, and computers.

Intelligent monitoring and control of semiconductor manufacturing equipment

NASA Technical Reports Server (NTRS)

Murdock, Janet L.; Hayes-Roth, Barbara

1991-01-01

The use of AI methods to monitor and control semiconductor fabrication in a state-of-the-art manufacturing environment called the Rapid Thermal Multiprocessor is described. Semiconductor fabrication involves many complex processing steps with limited opportunities to measure process and product properties. By applying additional process and product knowledge to that limited data, AI methods augment classical control methods by detecting abnormalities and trends, predicting failures, diagnosing, planning corrective action sequences, explaining diagnoses or predictions, and reacting to anomalous conditions that classical control systems typically would not correct. Research methodology and issues are discussed, and two diagnosis scenarios are examined.

Intelligent Integrated Health Management for a System of Systems

NASA Technical Reports Server (NTRS)

Smith, Harvey; Schmalzel, John; Figueroa, Fernando

2008-01-01

An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3) analical software tools that assist in reasoning about the condition, (4) sharing of information via network communication hardware and software, and (5) software tools that aid in making decisions to remedy unacceptable conditions or improve performance.

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

NASA Technical Reports Server (NTRS)

Lin, Paul P.; Jules, Kenol

2002-01-01

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.

Intelligent monitoring and diagnosis systems for the Space Station Freedom ECLSS

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.; Carnes, James R.

1991-01-01

Specific activities in NASA's environmental control and life support system (ECLSS) advanced automation project that is designed to minimize the crew and ground manpower needed for operations are discussed. Various analyses and the development of intelligent software for the initial and evolutionary Space Station Freedom (SSF) ECLSS are described. The following are also discussed: (1) intelligent monitoring and diagnostics applications under development for the ECLSS domain; (2) integration into the MSFC ECLSS hardware testbed; and (3) an evolutionary path from the baseline ECLSS automation to the more advanced ECLSS automation processes.

Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems

PubMed Central

Lampoltshammer, Thomas J.; de Freitas, Edison Pignaton; Nowotny, Thomas; Plank, Stefan; da Costa, João Paulo Carvalho Lustosa; Larsson, Tony; Heistracher, Thomas

2014-01-01

The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors' by use of local sensors' intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units. PMID:24618777

Intelligent Energy Management System for PV-Battery-based Microgrids in Future DC Homes

NASA Astrophysics Data System (ADS)

Chauhan, R. K.; Rajpurohit, B. S.; Gonzalez-Longatt, F. M.; Singh, S. N.

2016-06-01

This paper presents a novel intelligent energy management system (IEMS) for a DC microgrid connected to the public utility (PU), photovoltaic (PV) and multi-battery bank (BB). The control objectives of the proposed IEMS system are: (i) to ensure the load sharing (according to the source capacity) among sources, (ii) to reduce the power loss (high efficient) in the system, and (iii) to enhance the system reliability and power quality. The proposed IEMS is novel because it follows the ideal characteristics of the battery (with some assumptions) for the power sharing and the selection of the closest source to minimize the power losses. The IEMS allows continuous and accurate monitoring with intelligent control of distribution system operations such as battery bank energy storage (BBES) system, PV system and customer utilization of electric power. The proposed IEMS gives the better operational performance for operating conditions in terms of load sharing, loss minimization, and reliability enhancement of the DC microgrid.

Use of local intelligence to reduce energy consumption of wireless sensor nodes in elderly health monitoring systems.

PubMed

Lampoltshammer, Thomas J; Pignaton de Freitas, Edison; Nowotny, Thomas; Plank, Stefan; da Costa, João Paulo Carvalho Lustosa; Larsson, Tony; Heistracher, Thomas

2014-03-11

The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors' by use of local sensors' intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units.

Advanced Monitoring to Improve Combustion Turbine/Combined Cycle Reliability, Availability & Maintainability

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

Leonard Angello

2005-09-30

Power generators are concerned with the maintenance costs associated with the advanced turbines that they are purchasing. Since these machines do not have fully established Operation and Maintenance (O&M) track records, power generators face financial risk due to uncertain future maintenance costs. This risk is of particular concern, as the electricity industry transitions to a competitive business environment in which unexpected O&M costs cannot be passed through to consumers. These concerns have accelerated the need for intelligent software-based diagnostic systems that can monitor the health of a combustion turbine in real time and provide valuable information on the machine's performancemore » to its owner/operators. EPRI, Impact Technologies, Boyce Engineering, and Progress Energy have teamed to develop a suite of intelligent software tools integrated with a diagnostic monitoring platform that, in real time, interpret data to assess the 'total health' of combustion turbines. The 'Combustion Turbine Health Management System' (CTHMS) will consist of a series of 'Dynamic Link Library' (DLL) programs residing on a diagnostic monitoring platform that accepts turbine health data from existing monitoring instrumentation. CTHMS interprets sensor and instrument outputs, correlates them to a machine's condition, provide interpretative analyses, project servicing intervals, and estimate remaining component life. In addition, the CTHMS enables real-time anomaly detection and diagnostics of performance and mechanical faults, enabling power producers to more accurately predict critical component remaining useful life and turbine degradation.« less

Advanced integrated real-time clinical displays.

PubMed

Kruger, Grant H; Tremper, Kevin K

2011-09-01

Intelligent medical displays have the potential to improve patient outcomes by integrating multiple physiologic signals, exhibiting high sensitivity and specificity, and reducing information overload for physicians. Research findings have suggested that information overload and distractions caused by patient care activities and alarms generated by multiple monitors in acute care situations, such as the operating room and the intensive care unit, may produce situations that negatively impact the outcomes of patients under anesthesia. This can be attributed to shortcomings of human-in-the-loop monitoring and the poor specificity of existing physiologic alarms. Modern artificial intelligence techniques (ie, intelligent software agents) are demonstrating the potential to meet the challenges of next-generation patient monitoring and alerting. Copyright © 2011 Elsevier Inc. All rights reserved.

Research on human physiological parameters intelligent clothing based on distributed Fiber Bragg Grating

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Li, Hongqiang

2008-12-01

A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.

A Review of Passive RFID Tag Antenna-Based Sensors and Systems for Structural Health Monitoring Applications

PubMed Central

Zhang, Jun; Tian, Gui Yun; Marindra, Adi M. J.; Sunny, Ali Imam; Zhao, Ao Bo

2017-01-01

In recent few years, the antenna and sensor communities have witnessed a considerable integration of radio frequency identification (RFID) tag antennas and sensors because of the impetus provided by internet of things (IoT) and cyber-physical systems (CPS). Such types of sensor can find potential applications in structural health monitoring (SHM) because of their passive, wireless, simple, compact size, and multimodal nature, particular in large scale infrastructures during their lifecycle. The big data from these ubiquitous sensors are expected to generate a big impact for intelligent monitoring. A remarkable number of scientific papers demonstrate the possibility that objects can be remotely tracked and intelligently monitored for their physical/chemical/mechanical properties and environment conditions. Most of the work focuses on antenna design, and significant information has been generated to demonstrate feasibilities. Further information is needed to gain deep understanding of the passive RFID antenna sensor systems in order to make them reliable and practical. Nevertheless, this information is scattered over much literature. This paper is to comprehensively summarize and clearly highlight the challenges and state-of-the-art methods of passive RFID antenna sensors and systems in terms of sensing and communication from system point of view. Future trends are also discussed. The future research and development in UK are suggested as well. PMID:28146067

Making intelligent systems team players. A guide to developing intelligent monitoring systems

NASA Technical Reports Server (NTRS)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Advancing satellite operations with intelligent graphical monitoring systems

NASA Technical Reports Server (NTRS)

Hughes, Peter M.; Shirah, Gregory W.; Luczak, Edward C.

1993-01-01

For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

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

PubMed

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

2017-05-10

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

Research on intelligent scenic security early warning platform based on high resolution image: real scene linkage and real-time LBS

NASA Astrophysics Data System (ADS)

Li, Baishou; Huang, Yu; Lan, Guangquan; Li, Tingting; Lu, Ting; Yao, Mingxing; Luo, Yuandan; Li, Boxiang; Qian, Yongyou; Gao, Yujiu

2015-12-01

This paper design and implement security monitor system within a scenic spot for tourists, the scenic spot staff can be automatic real time for visitors to perception and monitoring, and visitors can also know about themselves location in the scenic, real-time and obtain the 3D imaging conditions of scenic area. Through early warning can realize "parent-child relation", preventing the old man and child lost and wandering. Research results to the further development of virtual reality to provide effective security early warning platform of the theoretical basis and practical reference.

Pervasive sensing

NASA Astrophysics Data System (ADS)

Nagel, David J.

2000-11-01

The coordinated exploitation of modern communication, micro- sensor and computer technologies makes it possible to give global reach to our senses. Web-cameras for vision, web- microphones for hearing and web-'noses' for smelling, plus the abilities to sense many factors we cannot ordinarily perceive, are either available or will be soon. Applications include (1) determination of weather and environmental conditions on dense grids or over large areas, (2) monitoring of energy usage in buildings, (3) sensing the condition of hardware in electrical power distribution and information systems, (4) improving process control and other manufacturing, (5) development of intelligent terrestrial, marine, aeronautical and space transportation systems, (6) managing the continuum of routine security monitoring, diverse crises and military actions, and (7) medicine, notably the monitoring of the physiology and living conditions of individuals. Some of the emerging capabilities, such as the ability to measure remotely the conditions inside of people in real time, raise interesting social concerns centered on privacy issues. Methods for sensor data fusion and designs for human-computer interfaces are both crucial for the full realization of the potential of pervasive sensing. Computer-generated virtual reality, augmented with real-time sensor data, should be an effective means for presenting information from distributed sensors.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition

PubMed Central

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-01-01

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K-nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction. PMID:28346385

DYNACLIPS (DYNAmic CLIPS): A dynamic knowledge exchange tool for intelligent agents

NASA Technical Reports Server (NTRS)

Cengeloglu, Yilmaz; Khajenoori, Soheil; Linton, Darrell

1994-01-01

In a dynamic environment, intelligent agents must be responsive to unanticipated conditions. When such conditions occur, an intelligent agent may have to stop a previously planned and scheduled course of actions and replan, reschedule, start new activities and initiate a new problem solving process to successfully respond to the new conditions. Problems occur when an intelligent agent does not have enough knowledge to properly respond to the new situation. DYNACLIPS is an implementation of a framework for dynamic knowledge exchange among intelligent agents. Each intelligent agent is a CLIPS shell and runs a separate process under SunOS operating system. Intelligent agents can exchange facts, rules, and CLIPS commands at run time. Knowledge exchange among intelligent agents at run times does not effect execution of either sender and receiver intelligent agent. Intelligent agents can keep the knowledge temporarily or permanently. In other words, knowledge exchange among intelligent agents would allow for a form of learning to be accomplished.

Intelligent robotic tracker

NASA Technical Reports Server (NTRS)

Otaguro, W. S.; Kesler, L. O.; Land, K. C.; Rhoades, D. E.

1987-01-01

An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

Northeast Artificial Intelligence Consortium Annual Report. Volume 2. 1988 Discussing, Using, and Recognizing Plans (NLP)

DTIC Science & Technology

1989-10-01

Encontro Portugues de Inteligencia Artificial (EPIA), Oporto, Portugal, September 1985. [15] N. J. Nilsson. Principles Of Artificial Intelligence. Tioga...FI1 F COPY () RADC-TR-89-259, Vol II (of twelve) Interim Report October 1969 AD-A218 154 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL...7a. NAME OF MONITORING ORGANIZATION Northeast Artificial Of p0ilcabe) Intelligence Consortium (NAIC) Rome_____ Air___ Development____Center

Energy Change Detection to Assist in Tactical Intelligence Production

DTIC Science & Technology

2009-06-01

COVERED Master’s Thesis 4. TITLE AND SUBTITLE Energy Change Detection to Assist in Tactical Intelligence Production 6. AUTHOR( S ) Derek Anthony Filipe...5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000 8. PERFORMING...ORGANIZATION REPORT NUMBER 9. SPONSORING /MONITORING AGENCY NAME( S ) AND ADDRESS(ES) N/A 10. SPONSORING/MONITORING AGENCY REPORT NUMBER 11

Increasing Awareness of Emotional Intelligence in a Business Curriculum

ERIC Educational Resources Information Center

Myers, Laura L.; Tucker, Mary L.

2005-01-01

Emotional intelligence (EI) is a type of social intelligence that involves the ability to monitor one's own and others' emotions, to discriminate among them, and to use the information to guide one's thinking and actions. EI theory provides another venue for business communication faculty in presenting the importance of how students can…

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.

Designing a patient monitoring system for bipolar disorder using Semantic Web technologies.

PubMed

Thermolia, Chryssa; Bei, Ekaterini S; Petrakis, Euripides G M; Kritsotakis, Vangelis; Tsiknakis, Manolis; Sakkalis, Vangelis

2015-01-01

The new movement to personalize treatment plans and improve prediction capabilities is greatly facilitated by intelligent remote patient monitoring and risk prevention. This paper focuses on patients suffering from bipolar disorder, a mental illness characterized by severe mood swings. We exploit the advantages of Semantic Web and Electronic Health Record Technologies to develop a patient monitoring platform to support clinicians. Relying on intelligently filtering of clinical evidence-based information and individual-specific knowledge, we aim to provide recommendations for treatment and monitoring at appropriate time or concluding into alerts for serious shifts in mood and patients' non response to treatment.

Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

DTIC Science & Technology

1989-10-01

Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

The 1990 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1990-01-01

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Higher social intelligence can impair source memory.

PubMed

Barber, Sarah J; Franklin, Nancy; Naka, Makiko; Yoshimura, Hiroki

2010-03-01

Source monitoring is made difficult when the similarity between candidate sources increases. The current work examines how individual differences in social intelligence and perspective-taking abilities serve to increase source similarity and thus negatively impact source memory. Strangers first engaged in a cooperative storytelling task. On each trial, a single word was shown to both participants, but only 1 participant was designated to add a story sentence, using this assigned word. As predicted, social intelligence negatively predicted performance in a subsequent source-monitoring task. In a 2nd study, preventing participants from being able to anticipate their partner's next contribution to the story eliminated the effect.

Wireless Monitoring of Automobile Tires for Intelligent Tires

PubMed Central

Matsuzaki, Ryosuke; Todoroki, Akira

2008-01-01

This review discusses key technologies of intelligent tires focusing on sensors and wireless data transmission. Intelligent automobile tires, which monitor their pressure, deformation, wheel loading, friction, or tread wear, are expected to improve the reliability of tires and tire control systems. However, in installing sensors in a tire, many problems have to be considered, such as compatibility of the sensors with tire rubber, wireless transmission, and battery installments. As regards sensing, this review discusses indirect methods using existing sensors, such as that for wheel speed, and direct methods, such as surface acoustic wave sensors and piezoelectric sensors. For wireless transmission, passive wireless methods and energy harvesting are also discussed. PMID:27873979

A design for an intelligent monitor and controller for space station electrical power using parallel distributed problem solving

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1990-01-01

The emphasis is on defining a set of communicating processes for intelligent spacecraft secondary power distribution and control. The computer hardware and software implementation platform for this work is that of the ADEPTS project at the Johnson Space Center (JSC). The electrical power system design which was used as the basis for this research is that of Space Station Freedom, although the functionality of the processes defined here generalize to any permanent manned space power control application. First, the Space Station Electrical Power Subsystem (EPS) hardware to be monitored is described, followed by a set of scenarios describing typical monitor and control activity. Then, the parallel distributed problem solving approach to knowledge engineering is introduced. There follows a two-step presentation of the intelligent software design for secondary power control. The first step decomposes the problem of monitoring and control into three primary functions. Each of the primary functions is described in detail. Suggestions for refinements and embelishments in design specifications are given.

Atmospheric effects on voice command intelligibility from acoustic hail and warning devices.

PubMed

Bostron, Jason H; Brungart, Timothy A; Barnard, Andrew R; McDevitt, Timothy E

2011-04-01

Voice command sound pressure levels (SPLs) were recorded at distances up to 1500 m. Received SPLs were related to the meteorological condition during sound propagation and compared with the outdoor sound propagation standard ISO 9613-2. Intelligibility of received signals was calculated using ANSI S3.5. Intelligibility results for the present voice command indicate that meteorological condition imposes little to no effect on intelligibility when the signal-to-noise ratio (SNR) is low (<-9 dB) or high (>0 dB). In these two cases the signal is firmly unintelligible or intelligible, respectively. However, at moderate SNRs, variations in received SPL can cause a fully intelligible voice command to become unintelligible, depending on the meteorological condition along the sound propagation path. These changes in voice command intelligibility often occur on time scales as short as minutes during upward refracting conditions, typically found above ground during the day or upwind of a sound source. Reliably predicting the intelligibility of a voice command in a moderate SNR environment can be challenging due to the inherent variability imposed by sound propagation through the atmosphere.

Integrated Planning for Telepresence With Time Delays

NASA Technical Reports Server (NTRS)

Johnston, Mark; Rabe, Kenneth

2009-01-01

A conceptual "intelligent assistant" and an artificial-intelligence computer program that implements the intelligent assistant have been developed to improve control exerted by a human supervisor over a robot that is so distant that communication between the human and the robot involves significant signal-propagation delays. The goal of the effort is not only to help the human supervisor monitor and control the state of the robot, but also to improve the efficiency of the robot by allowing the supervisor to "work ahead". The intelligent assistant is an integrated combination of an artificial-intelligence planner and a monitor of states of both the human supervisor and the remote robot. The novelty of the system lies in the way it uses the planner to reason about the states at both ends of the time delay. The purpose served by the assistant is to provide advice to the human supervisor about current and future activities, derived from a sequence of high-level goals to be achieved.

Understanding the Impact of Intelligent Tutoring Agents on Real-Time Training Simulations

DTIC Science & Technology

2011-01-01

environments has increased. Intelligent Tutoring Systems (ITS) technology may include reactive or proactive simulation agents that monitor and... environments . These reactive agents monitor the trainee’s progress and provide hints or other feedback only when there is sufficient variance from... agents have a higher computational cost in that they need to sense and understand more about the trainee, environment and training context, but are

Privacy Implications Arising From Intelligent Vehicle-Highway Systems

DOT National Transportation Integrated Search

1993-12-08

INTELLIGENT VEHICLE-HIGHWAY SYSTEMS, ("IVHS") INVOLVE ELECTRONIC MONITORING AND SOMETIMES IDENTIFICATION OF AND COMMUNICATION WITH MOTOR VEHICLES OPERATING ON PUBLIC HIGHWAYS FOR THE PURPOSE OF IMPROVING TRAFFIC SAFETY, EFFICIENCY AND CONVENIENCE. IV...

Effects of speech intelligibility level on concurrent visual task performance.

PubMed

Payne, D G; Peters, L J; Birkmire, D P; Bonto, M A; Anastasi, J S; Wenger, M J

1994-09-01

Four experiments were performed to determine if changes in the level of speech intelligibility in an auditory task have an impact on performance in concurrent visual tasks. The auditory task used in each experiment was a memory search task in which subjects memorized a set of words and then decided whether auditorily presented probe items were members of the memorized set. The visual tasks used were an unstable tracking task, a spatial decision-making task, a mathematical reasoning task, and a probability monitoring task. Results showed that performance on the unstable tracking and probability monitoring tasks was unaffected by the level of speech intelligibility on the auditory task, whereas accuracy in the spatial decision-making and mathematical processing tasks was significantly worse at low speech intelligibility levels. The findings are interpreted within the framework of multiple resource theory.

System interface for an integrated intelligent safety system (ISS) for vehicle applications.

PubMed

Hannan, Mahammad A; Hussain, Aini; Samad, Salina A

2010-01-01

This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS) that includes an airbag deployment decision system (ADDS) and a tire pressure monitoring system (TPMS). A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.

System Interface for an Integrated Intelligent Safety System (ISS) for Vehicle Applications

PubMed Central

Hannan, Mahammad A.; Hussain, Aini; Samad, Salina A.

2010-01-01

This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS) that includes an airbag deployment decision system (ADDS) and a tire pressure monitoring system (TPMS). A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications. PMID:22205861

The Role of Human Intelligence in Computer-Based Intelligent Tutoring Systems.

ERIC Educational Resources Information Center

Epstein, Kenneth; Hillegeist, Eleanor

An Intelligent Tutoring System (ITS) consists of an expert problem-solving program in a subject domain, a tutoring model capable of remediation or primary instruction, and an assessment model that monitors student understanding. The Geometry Proof Tutor (GPT) is an ITS which was developed at Carnegie Mellon University and field tested in the…

Intelligent on-line fault tolerant control for unanticipated catastrophic failures.

PubMed

Yen, Gary G; Ho, Liang-Wei

2004-10-01

As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.

Sensor Web in Antarctica: Developing an Intelligent, Autonomous Platform for Locating Biological Flourishes in Cryogenic Environments

NASA Technical Reports Server (NTRS)

Delin, K. A.; Harvey, R. P.; Chabot, N. A.; Jackson, S. P.; Adams, Mike; Johnson, D. W.; Britton, J. T.

2003-01-01

The most rigorous tests of the ability to detect extant life will occur where biotic activity is limited by severe environmental conditions. Cryogenic environments are among the most severe-the energy and nutrients needed for biological activity are in short supply while the climate itself is actively destructive to biological mechanisms. In such settings biological activity is often limited to brief flourishes, occurring only when and where conditions are at their most favorable. The closer that typical regional conditions approach conditions that are actively hostile , the more widely distributed biological blooms will be in both time and space. On a spatial dimension of a few meters or a time dimension of a few days, biological activity becomes much more difficult to detect. One way to overcome this difficulty is to establish a Sensor Web that can monitor microclimates over appropriate scales of time and distance, allowing a continuous virtual presence for instant recognition of favorable conditions. A more sophisticated Sensor Web, incorporating metabolic sensors, can effectively meet the challenge to be in "the right place in the right time". This is particularly of value in planetary surface missions, where limited mobility and mission timelines require extremely efficient sample and data acquisition. Sensor Webs can be an effective way to fill the gap between broad scale orbital data collection and fine-scale surface lander science. We are in the process of developing an intelligent, distributed and autonomous Sensor Web that will allow us to monitor microclimate under severe cryogenic conditions, approaching those extant on the surface of Mars. Ultimately this Sensor Web will include the ability to detect and/or establish limits on extant microbiological activity through incorporation of novel metabolic gas sensors. Here we report the results of our first deployment of a Sensor Web prototype in a previously unexplored high altitude East Antarctic Plateau "micro-oasis" at the MacAlpine Hills, Law Glacier, Antarctica.

Integrating Intelligence and Acquisition to Meet Evolving Threats: Interview With Dr. Sean Kirkpatrick of the Defense Intelligence Agency

DTIC Science & Technology

2015-06-01

CIPs ) We have drafted policy language that Defense Acquisition, Technology, and Logistics now is coordinating that will make it a requirement for at...least Acquisition Category I programs to identify CIPs early and for the intelligence community to monitor those and report breaches throughout the...are coming. Two important ones are the Critical Intelligence Parameters ( CIPs ) policy and the change to the System Threat Assessment Re- port (STAR

Vision-based algorithms for near-host object detection and multilane sensing

NASA Astrophysics Data System (ADS)

Kenue, Surender K.

1995-01-01

Vision-based sensing can be used for lane sensing, adaptive cruise control, collision warning, and driver performance monitoring functions of intelligent vehicles. Current computer vision algorithms are not robust for handling multiple vehicles in highway scenarios. Several new algorithms are proposed for multi-lane sensing, near-host object detection, vehicle cut-in situations, and specifying regions of interest for object tracking. These algorithms were tested successfully on more than 6000 images taken from real-highway scenes under different daytime lighting conditions.

Microsensors to monitor missile storage and maintenance needs

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

Mee, D.K.; Thundat, T.G.; Oden, P.I.

1997-10-30

Accurate assessments of reliability and condition based maintenance can only be implemented where a good understanding of ammunition stockpile condition exists. Use of miniaturized intelligent sensors provides an inexpensive means of nondestructively gaining insight into stockpile condition while keeping costs low. In the past, evaluation of ammunition lifetimes has utilized humidity, temperature, pressure, shock, and corrosion. New technologies provide the possibility of obtaining these environmental parameters, as well as a number of other indicators of propellant degradation, including NOx by utilizing a microsensor with capability for remote wireless monitoring. Micro-electro-mechanical systems (MEMS) like microcantilevers promise to revolutionize the field ofmore » sensor design. In the automobile industry, micromachined acceleration sensors are now used for triggering airbags and pressure sensors adjust the air-fuel intake ratio in the engine. By applying coatings to the sensor`s surface the behavior of the microdevice can be measurably altered to respond to chemical species as demonstrated by ORNL using microcantilevers to detect mercury vapor and humidity. Ultimately, single-chip detectors with electronics and telemetry could be developed with conceivably hundreds of individual microsensors on each chip to simultaneously monitor identify, and quantify many important chemical species for ammunition as well as measure environmental parameters.« less

Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design

PubMed Central

Hall, Travis; Nguyen, Tam Q.; Mayeda, Jill C.; Lie, Paul E.; Lopez, Jerry; Banister, Ron E.

2017-01-01

It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients’ long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is sleeping without hectic movements nearby. PMID:29140281

Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design.

PubMed

Hall, Travis; Lie, Donald Y C; Nguyen, Tam Q; Mayeda, Jill C; Lie, Paul E; Lopez, Jerry; Banister, Ron E

2017-11-15

It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients' long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient's vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is sleeping without hectic movements nearby.

Field evaluation of roller integrated intelligent compaction monitoring

DOT National Transportation Integrated Search

2016-05-01

DOTD conducted a demonstration : project to evaluate intelligent compaction (IC). The : project developed specifications, which allo : wed and incorporated : the IC rollers on the : project. The specification went through th : e competitive bidding p...

Challenges in sensor development for the electric utility industry

NASA Astrophysics Data System (ADS)

Ward, Barry H.

1999-01-01

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

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

PubMed

Alwan, Majd

2009-01-01

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

Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.

PubMed

Labovitz, Daniel L; Shafner, Laura; Reyes Gil, Morayma; Virmani, Deepti; Hanina, Adam

2017-05-01

This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulants, while reducing the need for monitoring, have also placed pressure on patients to self-manage. Suboptimal adherence goes undetected as routine laboratory tests are not reliable indicators of adherence, placing patients at increased risk of stroke and bleeding. A randomized, parallel-group, 12-week study was conducted in adults (n=28) with recently diagnosed ischemic stroke receiving any anticoagulation. Patients were randomized to daily monitoring by the artificial intelligence platform (intervention) or to no daily monitoring (control). The artificial intelligence application visually identified the patient, the medication, and the confirmed ingestion. Adherence was measured by pill counts and plasma sampling in both groups. For all patients (n=28), mean (SD) age was 57 years (13.2 years) and 53.6% were women. Mean (SD) cumulative adherence based on the artificial intelligence platform was 90.5% (7.5%). Plasma drug concentration levels indicated that adherence was 100% (15 of 15) and 50% (6 of 12) in the intervention and control groups, respectively. Patients, some with little experience using a smartphone, successfully used the technology and demonstrated a 50% improvement in adherence based on plasma drug concentration levels. For patients receiving direct oral anticoagulants, absolute improvement increased to 67%. Real-time monitoring has the potential to increase adherence and change behavior, particularly in patients on direct oral anticoagulant therapy. URL: http://www.clinicaltrials.gov. Unique identifier: NCT02599259. © 2017 American Heart Association, Inc.

A Bridge Over Troubled Waters: The Vital Role of Intelligence Sharing in Shaping the Anglo-American Special Relationship

DTIC Science & Technology

2008-12-01

of Intelligence Sharing in Shaping the Anglo-American “Special Relationship” 6. AUTHOR( S ) LT David B. Clark 5. FUNDING NUMBERS 7. PERFORMING...ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING...MONITORING AGENCY NAME( S ) AND ADDRESS(ES) N/A 10. SPONSORING/MONITORING AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES The views expressed in

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

PubMed

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

Learning Agents for Autonomous Space Asset Management (LAASAM)

NASA Astrophysics Data System (ADS)

Scally, L.; Bonato, M.; Crowder, J.

2011-09-01

Current and future space systems will continue to grow in complexity and capabilities, creating a formidable challenge to monitor, maintain, and utilize these systems and manage their growing network of space and related ground-based assets. Integrated System Health Management (ISHM), and in particular, Condition-Based System Health Management (CBHM), is the ability to manage and maintain a system using dynamic real-time data to prioritize, optimize, maintain, and allocate resources. CBHM entails the maintenance of systems and equipment based on an assessment of current and projected conditions (situational and health related conditions). A complete, modern CBHM system comprises a number of functional capabilities: sensing and data acquisition; signal processing; conditioning and health assessment; diagnostics and prognostics; and decision reasoning. In addition, an intelligent Human System Interface (HSI) is required to provide the user/analyst with relevant context-sensitive information, the system condition, and its effect on overall situational awareness of space (and related) assets. Colorado Engineering, Inc. (CEI) and Raytheon are investigating and designing an Intelligent Information Agent Architecture that will provide a complete range of CBHM and HSI functionality from data collection through recommendations for specific actions. The research leverages CEI’s expertise with provisioning management network architectures and Raytheon’s extensive experience with learning agents to define a system to autonomously manage a complex network of current and future space-based assets to optimize their utilization.

Study on road sign recognition in LabVIEW

NASA Astrophysics Data System (ADS)

Panoiu, M.; Rat, C. L.; Panoiu, C.

2016-02-01

Road and traffic sign identification is a field of study that can be used to aid the development of in-car advisory systems. It uses computer vision and artificial intelligence to extract the road signs from outdoor images acquired by a camera in uncontrolled lighting conditions where they may be occluded by other objects, or may suffer from problems such as color fading, disorientation, variations in shape and size, etc. An automatic means of identifying traffic signs, in these conditions, can make a significant contribution to develop an Intelligent Transport Systems (ITS) that continuously monitors the driver, the vehicle, and the road. Road and traffic signs are characterized by a number of features which make them recognizable from the environment. Road signs are located in standard positions and have standard shapes, standard colors, and known pictograms. These characteristics make them suitable for image identification. Traffic sign identification covers two problems: traffic sign detection and traffic sign recognition. Traffic sign detection is meant for the accurate localization of traffic signs in the image space, while traffic sign recognition handles the labeling of such detections into specific traffic sign types or subcategories [1].

Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1990-01-01

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Wireless structural monitoring for homeland security applications

NASA Astrophysics Data System (ADS)

Kiremidjian, Garo K.; Kiremidjian, Anne S.; Lynch, Jerome P.

2004-07-01

This paper addresses the development of a robust, low-cost, low power, and high performance autonomous wireless monitoring system for civil assets such as large facilities, new construction, bridges, dams, commercial buildings, etc. The role of the system is to identify the onset, development, location and severity of structural vulnerability and damage. The proposed system represents an enabling infrastructure for addressing structural vulnerabilities specifically associated with homeland security. The system concept is based on dense networks of "intelligent" wireless sensing units. The fundamental properties of a wireless sensing unit include: (a) interfaces to multiple sensors for measuring structural and environmental data (such as acceleration, displacements, pressure, strain, material degradation, temperature, gas agents, biological agents, humidity, corrosion, etc.); (b) processing of sensor data with embedded algorithms for assessing damage and environmental conditions; (c) peer-to-peer wireless communications for information exchange among units(thus enabling joint "intelligent" processing coordination) and storage of data and processed information in servers for information fusion; (d) ultra low power operation; (e) cost-effectiveness and compact size through the use of low-cost small-size off-the-shelf components. An integral component of the overall system concept is a decision support environment for interpretation and dissemination of information to various decision makers.

The flaw-detected coating and its applications in R&M of aircrafts

NASA Astrophysics Data System (ADS)

Hu, Feng; Liu, Mabao; Lü, Zhigang

2009-07-01

A monitoring method called ICM (Intelligent Coating Monitoring), which is based mainly on the intelligent coating sensors, has the capability to monitor crack initiation and growth in fatigue test coupons has been suggested in this study. The intelligent coating sensor is normally consisted of three layers: driving layer, sensing layer and protective layer where necessary. Fatigue tests with ICM for various materials demonstrate the capability to detect cracks with l<300μm, corresponding to the increment of the sensing layer's resistance at the level of 0.05Ω. Also, ICM resistance measurements correlate with crack length, permitting crack length monitoring. Numerous applications are under evaluation for ICM in difficult-to-access locations on commercial and military aircrafts. The motivation for the permanently flaw-detected coating monitoring is either (i) to replace an existing inspection that requires substantial disassembly and surface preparation (e.g. inside the fuel tank of an aircraft), or (ii) to take advantage of early detection and apply less invasive life-extension repairs, as well as reduce interruption of service when flaws are detected. Implementation of ICM is expected to improve fleet management practices and modify damage tolerance assumptions.

Smart Multi-Level Tool for Remote Patient Monitoring Based on a Wireless Sensor Network and Mobile Augmented Reality

PubMed Central

González, Fernando Cornelio Jimènez; Villegas, Osslan Osiris Vergara; Ramírez, Dulce Esperanza Torres; Sánchez, Vianey Guadalupe Cruz; Domínguez, Humberto Ochoa

2014-01-01

Technological innovations in the field of disease prevention and maintenance of patient health have enabled the evolution of fields such as monitoring systems. One of the main advances is the development of real-time monitors that use intelligent and wireless communication technology. In this paper, a system is presented for the remote monitoring of the body temperature and heart rate of a patient by means of a wireless sensor network (WSN) and mobile augmented reality (MAR). The combination of a WSN and MAR provides a novel alternative to remotely measure body temperature and heart rate in real time during patient care. The system is composed of (1) hardware such as Arduino microcontrollers (in the patient nodes), personal computers (for the nurse server), smartphones (for the mobile nurse monitor and the virtual patient file) and sensors (to measure body temperature and heart rate), (2) a network layer using WiFly technology, and (3) software such as LabView, Android SDK, and DroidAR. The results obtained from tests show that the system can perform effectively within a range of 20 m and requires ten minutes to stabilize the temperature sensor to detect hyperthermia, hypothermia or normal body temperature conditions. Additionally, the heart rate sensor can detect conditions of tachycardia and bradycardia. PMID:25230306

Smart multi-level tool for remote patient monitoring based on a wireless sensor network and mobile augmented reality.

PubMed

González, Fernando Cornelio Jiménez; Villegas, Osslan Osiris Vergara; Ramírez, Dulce Esperanza Torres; Sánchez, Vianey Guadalupe Cruz; Domínguez, Humberto Ochoa

2014-09-16

Technological innovations in the field of disease prevention and maintenance of patient health have enabled the evolution of fields such as monitoring systems. One of the main advances is the development of real-time monitors that use intelligent and wireless communication technology. In this paper, a system is presented for the remote monitoring of the body temperature and heart rate of a patient by means of a wireless sensor network (WSN) and mobile augmented reality (MAR). The combination of a WSN and MAR provides a novel alternative to remotely measure body temperature and heart rate in real time during patient care. The system is composed of (1) hardware such as Arduino microcontrollers (in the patient nodes), personal computers (for the nurse server), smartphones (for the mobile nurse monitor and the virtual patient file) and sensors (to measure body temperature and heart rate), (2) a network layer using WiFly technology, and (3) software such as LabView, Android SDK, and DroidAR. The results obtained from tests show that the system can perform effectively within a range of 20 m and requires ten minutes to stabilize the temperature sensor to detect hyperthermia, hypothermia or normal body temperature conditions. Additionally, the heart rate sensor can detect conditions of tachycardia and bradycardia.

Physical Intelligent Sensors

NASA Technical Reports Server (NTRS)

Bandhil, Pavan; Chitikeshi, Sanjeevi; Mahajan, Ajay; Figueroa, Fernando

2005-01-01

This paper proposes the development of intelligent sensors as part of an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA s Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS). The PIS discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the collected data and if any event is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with confidence factor in the reliability of the data which leads to information on the health of the sensor at all times. All protocols are consistent with IEEE 1451.X standards. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities.

Intelligent data analysis: the best approach for chronic heart failure (CHF) follow up management.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza; Baraani, Alireza; Mohammadzadeh, Farshid

2014-08-01

Intelligent data analysis has ability to prepare and present complex relations between symptoms and diseases, medical and treatment consequences and definitely has significant role in improving follow-up management of chronic heart failure (CHF) patients, increasing speed ​​and accuracy in diagnosis and treatments; reducing costs, designing and implementation of clinical guidelines. The aim of this article is to describe intelligent data analysis methods in order to improve patient monitoring in follow and treatment of chronic heart failure patients as the best approach for CHF follow up management. Minimum data set (MDS) requirements for monitoring and follow up of CHF patient designed in checklist with six main parts. All CHF patients that discharged in 2013 from Tehran heart center have been selected. The MDS for monitoring CHF patient status were collected during 5 months in three different times of follow up. Gathered data was imported in RAPIDMINER 5 software. Modeling was based on decision trees methods such as C4.5, CHAID, ID3 and k-Nearest Neighbors algorithm (K-NN) with k=1. Final analysis was based on voting method. Decision trees and K-NN evaluate according to Cross-Validation. Creating and using standard terminologies and databases consistent with these terminologies help to meet the challenges related to data collection from various places and data application in intelligent data analysis. It should be noted that intelligent analysis of health data and intelligent system can never replace cardiologists. It can only act as a helpful tool for the cardiologist's decisions making.

Evaluation of performance of asphalt pavements constructed using intelligent compaction techniques.

DOT National Transportation Integrated Search

2014-10-01

The long-term performance of asphalt pavements depends on the quality of the subgrade and : asphalt layers. Intelligent compaction methods continuously monitor the modulus/stiffness of : subgrade and asphalt layers during compaction process and have ...

Space Communications Artificial Intelligence for Link Evaluation Terminal (SCAILET)

NASA Technical Reports Server (NTRS)

Shahidi, Anoosh

1991-01-01

A software application to assis end-users of the Link Evaluation Terminal (LET) for satellite communication is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving, 220/110 Mbps capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET and ACTS are being developed at the NASA Lewis Research Center. The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. By comparing the transmitted bit pattern with the received bit pattern, HBR LET can determine the bit error rate BER) under various atmospheric conditions. An algorithm for power augmentation is applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions. Programming scripts, defined by the design engineer, set up the HBR LET terminal by programming subsystem devices through IEEE488 interfaces. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. The combination of the learning curve and the complexities involved with editing the script files may discourage end-users from utilizing the full capabilities of the HBR LET system. An intelligent assistant component of SCAILET that addresses critical end-user needs in the programming of the HBR LET system as anticipated by its developers is described. A close look is taken at the various steps involved in writing ECM software for a C&P, computer and at how the intelligent assistant improves the HBR LET system and enhances the end-user's ability to perform the experiments.

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

NASA Technical Reports Server (NTRS)

Saeed, M.; Lieu, C.; Raber, G.; Mark, R. G.

2002-01-01

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

Anti-Runaway Prevention System with Wireless Sensors for Intelligent Track Skates at Railway Stations.

PubMed

Jiang, Chaozhe; Xu, Yibo; Wen, Chao; Chen, Dilin

2017-12-19

Anti-runaway prevention of rolling stocks at a railway station is essential in railway safety management. The traditional track skates for anti-runaway prevention of rolling stocks have some disadvantages since they are operated and monitored completely manually. This paper describes an anti-runaway prevention system (ARPS) based on intelligent track skates equipped with sensors and real-time monitoring and management system. This system, which has been updated from the traditional track skates, comprises four parts: intelligent track skates, a signal reader, a database station, and a monitoring system. This system can monitor the real-time situation of track skates without changing their workflow for anti-runaway prevention, and thus realize the integration of anti-runaway prevention information management. This system was successfully tested and practiced at Sunjia station in Harbin Railway Bureau in 2014, and the results confirmed that the system showed 100% accuracy in reflecting the usage status of the track skates. The system could meet practical demands, as it is highly reliable and supports long-distance communication.

[Intelligent watch system for health monitoring based on Bluetooth low energy technology].

PubMed

Wang, Ji; Guo, Hailiang; Ren, Xiaoli

2017-08-01

According to the development status of wearable technology and the demand of intelligent health monitoring, we studied the multi-function integrated smart watches solution and its key technology. First of all, the sensor technology with high integration density, Bluetooth low energy (BLE) and mobile communication technology were integrated and used in develop practice. Secondly, for the hardware design of the system in this paper, we chose the scheme with high integration density and cost-effective computer modules and chips. Thirdly, we used real-time operating system FreeRTOS to develop the friendly graphical interface interacting with touch screen. At last, the high-performance application software which connected with BLE hardware wirelessly and synchronized data was developed based on android system. The function of this system included real-time calendar clock, telephone message, address book management, step-counting, heart rate and sleep quality monitoring and so on. Experiments showed that the collecting data accuracy of various sensors, system data transmission capacity, the overall power consumption satisfy the production standard. Moreover, the system run stably with low power consumption, which could realize intelligent health monitoring effectively.

Anti-Runaway Prevention System with Wireless Sensors for Intelligent Track Skates at Railway Stations

PubMed Central

Jiang, Chaozhe; Xu, Yibo; Chen, Dilin

2017-01-01

Anti-runaway prevention of rolling stocks at a railway station is essential in railway safety management. The traditional track skates for anti-runaway prevention of rolling stocks have some disadvantages since they are operated and monitored completely manually. This paper describes an anti-runaway prevention system (ARPS) based on intelligent track skates equipped with sensors and real-time monitoring and management system. This system, which has been updated from the traditional track skates, comprises four parts: intelligent track skates, a signal reader, a database station, and a monitoring system. This system can monitor the real-time situation of track skates without changing their workflow for anti-runaway prevention, and thus realize the integration of anti-runaway prevention information management. This system was successfully tested and practiced at Sunjia station in Harbin Railway Bureau in 2014, and the results confirmed that the system showed 100% accuracy in reflecting the usage status of the track skates. The system could meet practical demands, as it is highly reliable and supports long-distance communication. PMID:29257108

An Integrated Modeling and Simulation Methodology for Intelligent Systems Design and Testing

DTIC Science & Technology

2002-08-01

simulation and actual execution. KEYWORDS: Model Continuity, Modeling, Simulation, Experimental Frame, Real Time Systems , Intelligent Systems...the methodology for a stand-alone real time system. Then it will scale up to distributed real time systems . For both systems, step-wise simulation...MODEL CONTINUITY Intelligent real time systems monitor, respond to, or control, an external environment. This environment is connected to the digital

Forensic intelligence framework--Part I: Induction of a transversal model by comparing illicit drugs and false identity documents monitoring.

PubMed

Morelato, Marie; Baechler, Simon; Ribaux, Olivier; Beavis, Alison; Tahtouh, Mark; Kirkbride, Paul; Roux, Claude; Margot, Pierre

2014-03-01

Forensic intelligence is a distinct dimension of forensic science. Forensic intelligence processes have mostly been developed to address either a specific type of trace or a specific problem. Even though these empirical developments have led to successes, they are trace-specific in nature and contribute to the generation of silos which hamper the establishment of a more general and transversal model. Forensic intelligence has shown some important perspectives but more general developments are required to address persistent challenges. This will ensure the progress of the discipline as well as its widespread implementation in the future. This paper demonstrates that the description of forensic intelligence processes, their architectures, and the methods for building them can, at a certain level, be abstracted from the type of traces considered. A comparative analysis is made between two forensic intelligence approaches developed independently in Australia and in Europe regarding the monitoring of apparently very different kind of problems: illicit drugs and false identity documents. An inductive effort is pursued to identify similarities and to outline a general model. Besides breaking barriers between apparently separate fields of study in forensic science and intelligence, this transversal model would assist in defining forensic intelligence, its role and place in policing, and in identifying its contributions and limitations. The model will facilitate the paradigm shift from the current case-by-case reactive attitude towards a proactive approach by serving as a guideline for the use of forensic case data in an intelligence-led perspective. A follow-up article will specifically address issues related to comparison processes, decision points and organisational issues regarding forensic intelligence (part II). Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Distributed Acoustic Sensing (DAS) Array near a Highway for Traffic Monitoring and Near-Surface Shear-Wave Velocity Profiles

NASA Astrophysics Data System (ADS)

Wang, H. F.; Fratta, D.; Lancelle, C.; Ak, E. Ms; Lord, N. E.

2017-12-01

Monitoring traffic is important for many technical reasons. It allows for better design of future roads and assessment of the state of current roads. The number, size, weight, and speed of vehicles control deterioration rate. Also, real-time information supplies data to intelligent information systems to help control traffic. Recently there have been studies looking at monitoring traffic seismically as vibrations from traffic are not sensitive to weather and poor visibility. Furthermore, traffic noise can be used to image S-wave velocity distribution in the near surface by capturing and interpreting Rayleigh and Love waves (Nakata, 2016; Zeng et al. 2016). The capability of DAS for high spatial sampling (1 m), temporal sampling (up to 10 kHz), and distributed nature (tens of kilometers) allows for a closer look at the traffic as it passes and how the speed of the vehicle may change over the length of the array. The potential and difficulties of using DAS for these objectives were studied using two DAS arrays. One at Garner Valley in Southern California (a 700-meter array adjacent to CA Highway 74) and another in Brady Hot Springs, Nevada (an 8700-meter array adjacent to Interstate 80). These studies experimentally evaluated the use of DAS data for monitoring traffic and assessing the use of traffic vibration as non-localized sources for seismic imaging. DAS arrays should also be resilient to issues with lighting conditions that are problematic for video monitoring and it may be sensitive to the weight of a vehicle. This study along a major interstate provides a basis for examining DAS' potential and limitations as a key component of intelligent highway systems.

Back Propagation Artificial Neural Network and Its Application in Fault Detection of Condenser Failure in Thermo Plant

NASA Astrophysics Data System (ADS)

Ismail, Firas B.; Thiruchelvam, Vinesh

2013-06-01

Steam condenser is one of the most important equipment in steam power plants. If the steam condenser trips it may lead to whole unit shutdown, which is economically burdensome. Early condenser trips monitoring is crucial to maintain normal and safe operational conditions. In the present work, artificial intelligent monitoring systems specialized in condenser outages has been proposed and coded within the MATLAB environment. The training and validation of the system has been performed using real operational measurements captured from the control system of selected steam power plant. An integrated plant data preparation scheme for condenser outages with related operational variables has been proposed. Condenser outages under consideration have been detected by developed system before the plant control system"

The influence of visual speech information on the intelligibility of English consonants produced by non-native speakers.

PubMed

Kawase, Saya; Hannah, Beverly; Wang, Yue

2014-09-01

This study examines how visual speech information affects native judgments of the intelligibility of speech sounds produced by non-native (L2) speakers. Native Canadian English perceivers as judges perceived three English phonemic contrasts (/b-v, θ-s, l-ɹ/) produced by native Japanese speakers as well as native Canadian English speakers as controls. These stimuli were presented under audio-visual (AV, with speaker voice and face), audio-only (AO), and visual-only (VO) conditions. The results showed that, across conditions, the overall intelligibility of Japanese productions of the native (Japanese)-like phonemes (/b, s, l/) was significantly higher than the non-Japanese phonemes (/v, θ, ɹ/). In terms of visual effects, the more visually salient non-Japanese phonemes /v, θ/ were perceived as significantly more intelligible when presented in the AV compared to the AO condition, indicating enhanced intelligibility when visual speech information is available. However, the non-Japanese phoneme /ɹ/ was perceived as less intelligible in the AV compared to the AO condition. Further analysis revealed that, unlike the native English productions, the Japanese speakers produced /ɹ/ without visible lip-rounding, indicating that non-native speakers' incorrect articulatory configurations may decrease the degree of intelligibility. These results suggest that visual speech information may either positively or negatively affect L2 speech intelligibility.

A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

NASA Technical Reports Server (NTRS)

Hancock, Thomas M., III

1994-01-01

This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

An intelligent health monitoring system using radio-frequency identification technology.

PubMed

Lai, Yeong-Lin; Chen, Chin-Ling; Chang, Ching-Hisang; Hsu, Chih-Yu; Lai, Yeong-Kang; Tseng, Kuo-Kun; Chen, Chih-Cheng; Zheng, Chun-Yi

2015-01-01

Long-term care (LTC) for the elderly has become extremely important in recent years. It is necessary for the different physiological monitoring systems to be integrated on the same interface to help oversee and manage the elderly's needs. This paper presents a novel health monitoring system for LTC services using radio-frequency identification (RFID) technology. Dual-band RFID protocols were included in the system, in which the high-frequency (HF) band of 13.56 MHz was used to identify individuals and the microwave band of 2.45 GHz was used to monitor physiological information. Distinct physiological data, including oxyhemoglobin saturation by pulse oximetry (SpO2), blood pressure, blood sugar, electrocardiogram (ECG) readings, body temperature, and respiration rate, were monitored by various biosensors. The intelligent RFID health monitoring system provided the features of the real-time acquisition of biomedical signals and the identification of personal information pertaining to the elderly and patients in nursing homes.

From intensive care monitoring to personal health monitoring to ambient intelligence.

PubMed

Rienhoff, Otto

2013-01-01

The historical roots of IT-based monitoring in health care are described. Since the 1970ies monitoring has been spreading to more and more domains of health care and public health. Today one can observe monitoring of persons in many environments and regarding widely different questions. While these monitoring applications have been introduced ethical questions have been raised to balance the possible positive and negative outcomes of the approaches. Today IT-technology is entering many parts of our life - IT eventually became what had been coined already in the last century by IBM as "electronic dust" which one can find in every part of our environment. As most of these "dust-particles" are able to observe something one can also understand this development as a development into ubiquitous monitoring of nearly everything at any time. The foreseen ambient intelligence worlds are also spaces of ambient monitoring. This article describes this historical development. It emphasizes why ethical and data protection questions are an absolute must in most IT activities today.

Design of embedded intelligent monitoring system based on face recognition

NASA Astrophysics Data System (ADS)

Liang, Weidong; Ding, Yan; Zhao, Liangjin; Li, Jia; Hu, Xuemei

2017-01-01

In this paper, a new embedded intelligent monitoring system based on face recognition is proposed. The system uses Pi Raspberry as the central processor. A sensors group has been designed with Zigbee module in order to assist the system to work better and the two alarm modes have been proposed using the Internet and 3G modem. The experimental results show that the system can work under various light intensities to recognize human face and send alarm information in real time.

Using Crowdsourced Geospatial Data to Aid in Nuclear Proliferation Monitoring

DTIC Science & Technology

2016-12-01

M. Stephens, and Ronald D. Bonnell, “DAI for Document Retrieval: The MINDS Project,” in Distributed Artificial Intelligence , ed. Michael N. Huhns...Ronald D. Bonnell. “DAI for Document Retrieval: The MINDS Project,” In Distributed Artificial Intelligence , edited by Michael N. Huhns, 249–283...was for the director of National Intelligence to explore ways that crowdsourced geospatial imagery technologies could aid existing governmental

Fusing Open Source Intelligence and Handheld Situational Awareness - Benghazi Case Study

DTIC Science & Technology

2014-10-01

of the Battlespace (IPB) • Link OSINT to mobile SA 5 DM-0001694 Background • Between September 11 and 17, 2012, diplomatic missions in the...explore what might have been possible by integrating social media information ( OSINT ) with traditional intelligence combined with improved mobile...command and control element at the CIA compound that would have been monitoring OSINT and other sources of intelligence before the attack and

Studies in Intelligence. Volume 54, Number 3, September 2010

DTIC Science & Technology

2010-09-01

ADDRESS( ES ) Center for the Study of Intelligence,Central Intelligence Agency,Washington,DC,20505 8. PERFORMING ORGANIZATION REPORT NUMBER 9...SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS( ES ) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY...The Deceivers: Allied Military Deception in the Second World War by Thaddeus Holt •Eyes In The Sky: Eisenhower, The CIA and Cold War Aerial Es

An Overview of the United States Intelligence Community

DTIC Science & Technology

2007-01-01

PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES...Office of the Director of National Intelligence,Washington,DC,20511 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S...based on budget proposals provided by IC component organizations . ü Oversee coordination of relationships with the intelligence or security services

Pathfinder. Volume 8, Number 4, July/August 2010

DTIC Science & Technology

2010-08-01

Intelligence Agency,4600 Sangamore Road, Mail Stop D-54,Bethesda,MD, 20816 -5003 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING...Intelligence Agency Office of Corporate Communications 4600 Sangamore Road, Mail Stop D-54 Bethesda, MD 20816 -5003 Telephone: (301) 227-7388

An artificial-intelligence technique for qualitatively deriving enzyme kinetic mechanisms from initial-velocity measurements and its application to hexokinase.

PubMed Central

Garfinkel, L; Cohen, D M; Soo, V W; Garfinkel, D; Kulikowski, C A

1989-01-01

We have developed a computer method based on artificial-intelligence techniques for qualitatively analysing steady-state initial-velocity enzyme kinetic data. We have applied our system to experiments on hexokinase from a variety of sources: yeast, ascites and muscle. Our system accepts qualitative stylized descriptions of experimental data, infers constraints from the observed data behaviour and then compares the experimentally inferred constraints with corresponding theoretical model-based constraints. It is desirable to have large data sets which include the results of a variety of experiments. Human intervention is needed to interpret non-kinetic information, differences in conditions, etc. Different strategies were used by the several experimenters whose data was studied to formulate mechanisms for their enzyme preparations, including different methods (product inhibitors or alternate substrates), different experimental protocols (monitoring enzyme activity differently), or different experimental conditions (temperature, pH or ionic strength). The different ordered and rapid-equilibrium mechanisms proposed by these experimenters were generally consistent with their data. On comparing the constraints derived from the several experimental data sets, they are found to be in much less disagreement than the mechanisms published, and some of the disagreement can be ascribed to different experimental conditions (especially ionic strength). PMID:2690819

Some recent advances of intelligent health monitoring systems for civil infrastructures in HIT

NASA Astrophysics Data System (ADS)

Ou, Jinping

2005-06-01

The intelligent health monitoring systems more and more become a technique for ensuring the health and safety of civil infrastructures and also an important approach for research of the damage accumulation or even disaster evolving characteristics of civil infrastructures, and attracts prodigious research interests and active development interests of scientists and engineers since a great number of civil infrastructures are planning and building each year in mainland China. In this paper, some recent advances on research, development nad implementation of intelligent health monitoring systems for civil infrastructuresin mainland China, especially in Harbin Institute of Technology (HIT), P.R.China. The main contents include smart sensors such as optical fiber Bragg grating (OFBG) and polivinyllidene fluoride (PVDF) sensors, fatigue life gauges, self-sensing mortar and carbon fiber reinforced polymer (CFRP), wireless sensor networks and their implementation in practical infrastructures such as offshore platform structures, hydraulic engineering structures, large span bridges and large space structures. Finally, the relative research projects supported by the national foundation agencies of China are briefly introduced.

Female voice communications in high level aircraft cockpit noises--part II: vocoder and automatic speech recognition systems.

PubMed

Nixon, C; Anderson, T; Morris, L; McCavitt, A; McKinley, R; Yeager, D; McDaniel, M

1998-11-01

The intelligibility of female and male speech is equivalent under most ordinary living conditions. However, due to small differences between their acoustic speech signals, called speech spectra, one can be more or less intelligible than the other in certain situations such as high levels of noise. Anecdotal information, supported by some empirical observations, suggests that some of the high intensity noise spectra of military aircraft cockpits may degrade the intelligibility of female speech more than that of male speech. In an applied research study, the intelligibility of female and male speech was measured in several high level aircraft cockpit noise conditions experienced in military aviation. In Part I, (Nixon CW, et al. Aviat Space Environ Med 1998; 69:675-83) female speech intelligibility measured in the spectra and levels of aircraft cockpit noises and with noise-canceling microphones was lower than that of the male speech in all conditions. However, the differences were small and only those at some of the highest noise levels were significant. Although speech intelligibility of both genders was acceptable during normal cruise noises, improvements are required in most of the highest levels of noise created during maximum aircraft operating conditions. These results are discussed in a Part I technical report. This Part II report examines the intelligibility in the same aircraft cockpit noises of vocoded female and male speech and the accuracy with which female and male speech in some of the cockpit noises were understood by automatic speech recognition systems. The intelligibility of vocoded female speech was generally the same as that of vocoded male speech. No significant differences were measured between the recognition accuracy of male and female speech by the automatic speech recognition systems. The intelligibility of female and male speech was equivalent for these conditions.

Guidelines for Effective Selective Listening.

ERIC Educational Resources Information Center

Schendel, Joel D.; Shields, Joyce L.

Defining selective listening as an intelligence gathering technique that depends on an individual's ability to access, monitor, and report oral messages accurately and to give processing priority to messages of possible intelligence value, this report describes one important application of the technique: overhearing the conversations of others…

The search for intelligence

NASA Astrophysics Data System (ADS)

Coffey, E. J.

1980-12-01

Implications of current understandings of the nature of human intelligence for the possibility of extraterrestrial intelligence are discussed. The perceptual theory of intelligence as the manipulation of perceptual images rather than language is introduced, and conditions leading to the ascendancy of man over other hominids with similar conceptual abilities are discussed, including the liberation of the hands from a locomotive function and the evolution of neoteny. It is argued that the specificity of the environmental, behavioral and physiological conditions which lead to the emergence of technologically oriented, and communicative intelligent creatures suggests that any SETI would most likely be fruitless.

A multi-agent approach to intelligent monitoring in smart grids

NASA Astrophysics Data System (ADS)

Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

2014-04-01

In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

An overview of the artificial intelligence and expert systems component of RICIS

NASA Technical Reports Server (NTRS)

Feagin, Terry

1987-01-01

Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

A hybrid prognostic model for multistep ahead prediction of machine condition

NASA Astrophysics Data System (ADS)

Roulias, D.; Loutas, T. H.; Kostopoulos, V.

2012-05-01

Prognostics are the future trend in condition based maintenance. In the current framework a data driven prognostic model is developed. The typical procedure of developing such a model comprises a) the selection of features which correlate well with the gradual degradation of the machine and b) the training of a mathematical tool. In this work the data are taken from a laboratory scale single stage gearbox under multi-sensor monitoring. Tests monitoring the condition of the gear pair from healthy state until total brake down following several days of continuous operation were conducted. After basic pre-processing of the derived data, an indicator that correlated well with the gearbox condition was obtained. Consecutively the time series is split in few distinguishable time regions via an intelligent data clustering scheme. Each operating region is modelled with a feed-forward artificial neural network (FFANN) scheme. The performance of the proposed model is tested by applying the system to predict the machine degradation level on unseen data. The results show the plausibility and effectiveness of the model in following the trend of the timeseries even in the case that a sudden change occurs. Moreover the model shows ability to generalise for application in similar mechanical assets.

Application of Wireless Intelligent Control System for HPS Lamps and LEDs Combined Illumination in Road Tunnel

PubMed Central

Lai, Jinxing; Qiu, Junling; Chen, Jianxun; Wang, Yaqiong; Fan, Haobo

2014-01-01

Because of the particularity of the environment in the tunnel, the rational tunnel illumination system should be developed, so as to optimize the tunnel environment. Considering the high cost of traditional tunnel illumination system with high-pressure sodium (HPS) lamps as well as the effect of a single light source on tunnel entrance, the energy-saving illumination system with HPS lamps and LEDs combined illumination in road tunnel, which could make full use of these two kinds of lamps, was proposed. The wireless intelligent control system based on HPS lamps and LEDs combined illumination and microcontrol unit (MCU) Si1000 wireless communication technology was designed. And the remote monitoring, wireless communication, and PWM dimming module of this system were designed emphatically. Intensity detector and vehicle flow detector can be configured in wireless intelligent control system, which gather the information to the master control unit, and then the information is sent to the monitoring center through the Ethernet. The control strategies are got by the monitoring center according to the calculated results, and the control unit wirelessly sends parameters to lamps, which adjust the luminance of each segment of the tunnel and realize the wireless intelligent control of combined illumination in road tunnel. PMID:25587266

Intelligent Hardware-Enabled Sensor and Software Safety and Health Management for Autonomous UAS

NASA Technical Reports Server (NTRS)

Rozier, Kristin Y.; Schumann, Johann; Ippolito, Corey

2015-01-01

Unmanned Aerial Systems (UAS) can only be deployed if they can effectively complete their mission and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. We propose to design a real-time, onboard system health management (SHM) capability to continuously monitor essential system components such as sensors, software, and hardware systems for detection and diagnosis of failures and violations of safety or performance rules during the ight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the- y temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power hardware realization using Field Programmable Gate Arrays (FPGAs) in order to avoid overburdening limited computing resources or costly re-certi cation of ight software due to instrumentation. No currently available SHM capabilities (or combinations of currently existing SHM capabilities) come anywhere close to satisfying these three criteria yet NASA will require such intelligent, hardwareenabled sensor and software safety and health management for introducing autonomous UAS into the National Airspace System (NAS). We propose a novel approach of creating modular building blocks for combining responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. Our proposed research program includes both developing this novel approach and demonstrating its capabilities using the NASA Swift UAS as a demonstration platform.

Intelligent monitoring of Aedes aegypti in a rural area of Rio de Janeiro State, Brazil

PubMed Central

Sanavria, Argemiro; da Silva, Claudia Bezerra; Electo, Érica Heleno; Nogueira, Lidiane Cristina Rocha; Thomé, Sandra Maria Gomes; Angelo, Isabele da Costa; Vita, Gilmar Ferreira; Sanavria, Talles Eduardo Cabral; Padua, Elisa Domingues; Gaiotte, Denise Glória

2017-01-01

ABSTRACT The aim of this research was to monitor the presence of females of Aedes aegypti (Linnaeus, 1762) on the Seropédica municipality, Rio de Janeiro State, from 2010 to 2013. For this purpose, the Intelligent Dengue Monitoring (IM-Dengue) and Intelligent Virus Monitoring (IM-Virus) developed by Universidade Federal de Minas Gerais (Ecovec – Minas Gerais, Brazil), were used. IM-Dengue is a tool that allows achieving a weekly overview of A. aegypti infestation, while IM-Virus is another tool that allows detecting dengue virus directly from the mosquito, by Real Time-PCR. Both tools were developed for diagnosis in a prepathogenesis period of the disease, before infection occurrence. Traps were distributed in 19 locations inside the municipality and the bugs were collected weekly during the years of the research. As a result, the presence of 163 females of A. aegypti was recorded over the period; there was no circulation of the virus in the municipality. In one of the 19 study sites, a high degree of disease transmission risk was verified. The study concluded that the municipality, as a whole, showed no risk of disease transmission throughout the field research period. PMID:28793020

Higher Social Intelligence Can Impair Source Memory

ERIC Educational Resources Information Center

Barber, Sarah J.; Franklin, Nancy; Naka, Makiko; Yoshimura, Hiroki

2010-01-01

Source monitoring is made difficult when the similarity between candidate sources increases. The current work examines how individual differences in social intelligence and perspective-taking abilities serve to increase source similarity and thus negatively impact source memory. Strangers first engaged in a cooperative storytelling task. On each…

Online Sources of Competitive Intelligence.

ERIC Educational Resources Information Center

Wagers, Robert

1986-01-01

Presents an approach to using online sources of information for competitor intelligence (i.e., monitoring industry and tracking activities of competitors); identifies principal sources; and suggests some ways of making use of online databases. Types and sources of information and sources and database charts are appended. Eight references are…

FDEMS Sensing for Automated Intelligent Processing of PMR-15

NASA Technical Reports Server (NTRS)

Kranbuehl, David E.; Hood, D. K.; Rogozinski, J.; Barksdale, R.; Loos, Alfred C.; McRae, Doug

1993-01-01

The purpose of this grant was to develop frequency dependent dielectric measurements, often called FDEMS (frequency dependent electromagnetic sensing), to monitor and intelligently control the cure process in PMR-15, a stoichiometric mixture of a nadic ester, dimethyl ester, and methylendianiline in a monomor ratio.

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

PubMed

Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

2018-02-01

Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising approaches for the prescription and monitoring of hemodialysis therapy. Current dialysis machines are continuously improving due to innovative technological developments, but patient safety is still a key challenge. Real-time monitoring systems, coupled with automatic instantaneous biofeedback, will allow changing dialysis prescriptions continuously. The integration of vital sign monitoring with dialysis parameters will produce large data sets that will require the use of data analysis techniques, possibly from the area of machine learning, in order to make better decisions and increase the safety of patients.

Intelligent flight control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1993-01-01

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.

Embedded expert system for space shuttle main engine maintenance

NASA Technical Reports Server (NTRS)

Pooley, J.; Thompson, W.; Homsley, T.; Teoh, W.; Jones, J.; Lewallen, P.

1987-01-01

The SPARTA Embedded Expert System (SEES) is an intelligent health monitoring system that directs analysis by placing confidence factors on possible engine status and then recommends a course of action to an engineer or engine controller. The technique can prevent catastropic failures or costly rocket engine down time because of false alarms. Further, the SEES has potential as an on-board flight monitor for reusable rocket engine systems. The SEES methodology synergistically integrates vibration analysis, pattern recognition and communications theory techniques with an artificial intelligence technique - the Embedded Expert System (EES).

Encephaloceles

MedlinePlus

... and seizures. Some affected children may have normal intelligence. There is a genetic component to the condition; ... and seizures. Some affected children may have normal intelligence. There is a genetic component to the condition; ...

BSN Program Admittance Criteria: Should Emotional Intelligence Be Included?

PubMed

Smith, Tanya

2017-01-01

Emotional intelligence refers to the ability to identify and monitor emotions and remain aware of how emotions affect thoughts and actions. Emotional intelligence has been discussed as a better predictor of personal and occupational success than performance on intellectual intelligence tests. Despite the importance of one's emotional intelligence, BSN (Bachelor of Science in Nursing) nursing schools routinely admit candidates based on the student's cumulative college course grade point average (GPA). Nursing is a profession that requires one's ability to empathize, care, and react in emotionally sound manners. Is the GPA enough to determine if a student will evolve into a professional nurse? This article will explore the routine admittance criteria for BSN nursing programs and propose the concept of using the emotional intelligence tool as an adjunct to the cumulative college course GPA. The emotional intelligence theory will be identified and applied to the nursing profession. © 2016 Wiley Periodicals, Inc.

Impact of clear, loud, and slow speech on scaled intelligibility and speech severity in Parkinson's disease and multiple sclerosis.

PubMed

Tjaden, Kris; Sussman, Joan E; Wilding, Gregory E

2014-06-01

The perceptual consequences of rate reduction, increased vocal intensity, and clear speech were studied in speakers with multiple sclerosis (MS), Parkinson's disease (PD), and healthy controls. Seventy-eight speakers read sentences in habitual, clear, loud, and slow conditions. Sentences were equated for peak amplitude and mixed with multitalker babble for presentation to listeners. Using a computerized visual analog scale, listeners judged intelligibility or speech severity as operationally defined in Sussman and Tjaden (2012). Loud and clear but not slow conditions improved intelligibility relative to the habitual condition. With the exception of the loud condition for the PD group, speech severity did not improve above habitual and was reduced relative to habitual in some instances. Intelligibility and speech severity were strongly related, but relationships for disordered speakers were weaker in clear and slow conditions versus habitual. Both clear and loud speech show promise for improving intelligibility and maintaining or improving speech severity in multitalker babble for speakers with mild dysarthria secondary to MS or PD, at least as these perceptual constructs were defined and measured in this study. Although scaled intelligibility and speech severity overlap, the metrics further appear to have some separate value in documenting treatment-related speech changes.

Wearable medical devices using textile and flexible technologies for ambulatory monitoring.

PubMed

Dittmar, Andre; Meffre, Richard; De Oliveira, Fabrice; Gehin, Claudine; Delhomme, Georges

2005-01-01

Health smart clothes are in contact with almost all the surface of the skin offer large possibilities for the location of sensors for non invasive measurements. Head band, collar, tee-shirt, socks, shoes, belts for chest, arm, wrist, legs ... provide localization with specific purpose taking into account their proximity of an organ or a source of biosignal, and also its ergonomic possibility (user friendly) to fix a sensor, and the associated instrumentations (batteries, amplifiers, signal processing, telecom, alarm, display ...). Progress in science and technology offers, for the first time, intelligence, speed, miniaturization, sophistication and new materials at low cost. In this new landscape, microtechnologies, information technologies and telecommunications are a key factor. Microsensors : Microtechnologies offer the possibility of small size, but also intelligent, active device, working with low energy, wireless and non invasive or mini invasive. These sensors have to be thin, flexible and compatible with textile, or made using textile technologies, new fibers with specific properties: mechanical, electrical, optical ... The field of applications is very large, e.g. continuous monitoring on elderly population, professional and military activities, athlete's performance and condition, and people with disabilities. The research are oriented toward two complementary directions: Improving the relevancy of each sensor and increasing the number of sensors for having a more global synthetic and robust information.

Cognitive processing load across a wide range of listening conditions: insights from pupillometry.

PubMed

Zekveld, Adriana A; Kramer, Sophia E

2014-03-01

The pupil response to speech masked by interfering speech was assessed across an intelligibility range from 0% to 99% correct. In total, 37 participants aged between 18 and 36 years and with normal hearing were included. Pupil dilation was largest at intermediate intelligibility levels, smaller at high intelligibility, and slightly smaller at very difficult levels. Participants who reported that they often gave up listening at low intelligibility levels had smaller pupil dilations in these conditions. Participants who were good at reading masked text had relatively large pupil dilation when intelligibility was low. We conclude that the pupil response is sensitive to processing load, and possibly reflects cognitive overload in difficult conditions. It seems affected by methodological aspects and individual abilities, but does not reflect subjective ratings. Copyright © 2014 Society for Psychophysiological Research.

Incorporation of Automated ISR Systems by the 75th Ranger Regiment

DTIC Science & Technology

2003-06-06

Intelligence, describes the intelligence challenges faced by a commander, the command estimate process, military intelligence unit capabilities...feed- capture stills INTERVIEW SUBJECT #2 Strategic Range N/S N/S N/S Voice Recognitio n for TGT/Comb at ID INTERVIEW SUBJECT #3 100- 1000+ N/S...intercept- monitor- jam freqs. Send live feed- capture stills INTERVIEW SUBJECT #2 Strategic Range N/S N/S N/S Voice Recognitio n for TGT/Comb at ID

An Assessment of Perceived Emotional Intelligence and Health Behaviors among College Students

ERIC Educational Resources Information Center

Pettit, Michele L.; Jacobs, Sue C.; Page, Kyle S.; Porras, Claudia V.

2009-01-01

The purpose of this study was to assess the relationship between perceived emotional intelligence (i.e., recognizing, expressing, monitoring, managing, and reflecting on emotions) (Presbury, Echterling, & McKee, 2007) and self-reported health behaviors among college students. A convenience sample of 418 undergraduates completed online surveys…

Making intelligent systems team players: Additional case studies

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Rhoads, Ron W.

1993-01-01

Observations from a case study of intelligent systems are reported as part of a multi-year interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. A series of studies were conducted to investigate issues in designing intelligent fault management systems in aerospace applications for effective human-computer interaction. The results of the initial study are documented in two NASA technical memoranda: TM 104738 Making Intelligent Systems Team Players: Case Studies and Design Issues, Volumes 1 and 2; and TM 104751, Making Intelligent Systems Team Players: Overview for Designers. The objective of this additional study was to broaden the investigation of human-computer interaction design issues beyond the focus on monitoring and fault detection in the initial study. The results of this second study are documented which is intended as a supplement to the original design guidance documents. These results should be of interest to designers of intelligent systems for use in real-time operations, and to researchers in the areas of human-computer interaction and artificial intelligence.

Design of intelligent composites with life-cycle health management capabilities

NASA Astrophysics Data System (ADS)

Rosania, Colleen L.; Larrosa, Cecilia C.; Chang, Fu-Kuo

2015-03-01

Use of carbon fiber reinforced polymers (CFRPs) presents challenges because of their complex manufacturing processes and different damage mechanics in relation to legacy metal materials. New monitoring methods for manufacturing, quality verification, damage estimation, and prognosis are needed to use CFRPs safely and efficiently. This work evaluates the development of intelligent composite materials using integrated piezoelectric sensors to monitor the material during cure and throughout service life. These sensors are used to propagate ultrasonic waves through the structure for health monitoring. During manufacturing, data is collected at different stages during the cure cycle, detecting the changing material properties during cure and verifying quality and degree of cure. The same sensors can then be used with previously developed techniques to perform damage detection, such as impact detection and matrix crack density estimation. Real-time damage estimation can be combined with prognostic models to predict future propagation of damage in the material. In this work experimental results will be presented from composite coupons with embedded piezoelectric sensors. Cure monitoring and damage detection results derived from analysis of the ultrasonic sensor signal will be shown. Sensitive signal parameters to the different stimuli in both the time and frequency domains will be explored for this analysis. From these results, use of the same sensor networks from manufacturing throughout the life of the composite material will demonstrate the full life-cycle monitoring capability of these intelligent materials.

A novel paradigm for telemedicine using the personal bio-monitor.

PubMed

Bhatikar, Sanjay R; Mahajan, Roop L; DeGroff, Curt

2002-01-01

The foray of solid-state technology in the medical field has yielded an arsenal of sophisticated healthcare tools. Personal, portable computing power coupled with the information superhighway open up the possibility of sophisticated healthcare management that will impact the medical field just as much. The full synergistic potential of three interwoven technologies: (1) compact electronics, (2) World Wide Web, and (3) Artificial Intelligence is yet to be realized. The system presented in this paper integrates these technologies synergistically, providing a new paradigm for healthcare. Our idea is to deploy internet-enabled, intelligent, handheld personal computers for medical diagnosis. The salient features of the 'Personal Bio-Monitor' we envisage are: (1) Utilization of the peripheral signals of the body which may be acquired non-invasively and with ease, for diagnosis of medical conditions; (2) An Artificial Neural Network (ANN) based approach for diagnosis; (3) Configuration of the diagnostic device as a handheld for personal use; (4) Internet connectivity, following the emerging bluetooth protocol, for prompt conveyance of information to a patient's health care provider via the World Wide Web. The proposal is substantiated with an intelligent handheld device developed by the investigators for pediatric cardiac auscultation. This device performed accurate diagnoses of cardiac abnormalities in pediatrics using an artificial neural network to process heart sounds acquired by a low-frequency microphone and transmitted its diagnosis to a desktop PC via infrared. The idea of the personal biomonitor presented here has the potential to streamline healthcare by optimizing two valuable resources: physicians' time and sophisticated equipment time. We show that the elements of such a system are in place, with our prototype. Our novel contribution is the synergistic integration of compact electronics' technology, artificial neural network methodology and the wireless web resulting in a revolutionary new paradigm for healthcare management.

How do working-memory-related demand, reasoning ability and aversive reinforcement modulate conflict monitoring?

PubMed Central

Leue, Anja; Weber, Bernd; Beauducel, André

2014-01-01

Conflict monitoring is a process of stimulus evaluation and a pre-requisite for subsequent recruitment of cognitive control and behavioral adaptations. This study investigated how experimentally manipulated working-memory-related cognitive demand and aversive reinforcement modulate individual differences of conflict monitoring intensity and behavioral adjustments. Individual differences were assessed by means of an anxiety-related trait dimension (trait-BIS) and by means of reasoning abilities—a core determinant of intelligence. Moreover, we investigated the special role of verbal reasoning ability and figural reasoning ability for the modulation of the conflict monitoring intensity. Ninety participants performed a go/nogo task with four conditions each comprising a combination of low vs. high working-memory-related cognitive demand and low vs. high aversive reinforcement. No effect of aversive reinforcement was observed for the N2 amplitude. The fronto-central nogo N2 amplitude was more pronounced for high demand vs. low demand suggesting that cognitive demand served as an aversive costly event. Higher total reasoning abilities were associated with more intense conflict monitoring and shorter response times with increasing aversive reinforcement (defined as verbal error-feedback vs. monetary loss). Individuals with higher trait-BIS scores demonstrated a more intense conflict monitoring even in conditions with low aversive reinforcement and also a more cautious responding (i.e., response times slowing) with increasing aversive reinforcement indicating a focus on negative feedback prevention. The findings provide evidence for the conflict monitoring theory and suggest that working-memory-related demand overrules the impact of aversive reinforcement on conflict monitoring intensity. Reasoning abilities and anxiety-related traits go along with an intensification of conflict monitoring but differences in the flexibility of behavioral adjustment. PMID:24782739

Affordable and personalized lighting using inverse modeling and virtual sensors

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Lawson, Denise L.; James, Mark L.

1989-01-01

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

PubMed

Hsu, Yu-Liang; Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

2017-07-15

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents' wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident's feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology

PubMed Central

Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

2017-01-01

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents’ wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident’s feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment. PMID:28714884

The Information Edge: Imagery Intelligence and Geospatial Information in an Evolving National Security Environment

DTIC Science & Technology

2000-12-01

8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10 . SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR...Activities................................................................................ 48 10 . NIMA and Its Suppliers...Agency (DIA), the National Reconnaissance Office (NRO), the Defense Airborne Reconnaissance Office (DARO), and the Central Intelligence Agency” ibid. 10

Storage Capacity Explains Fluid Intelligence but Executive Control Does Not

ERIC Educational Resources Information Center

Chuderski, Adam; Taraday, Maciej; Necka, Edward; Smolen, Tomasz

2012-01-01

We examined whether fluid intelligence (Gf) is better predicted by the storage capacity of active memory or by the effectiveness of executive control. In two psychometric studies, we measured storage capacity with three kinds of task which required the maintenance of a visual array, the monitoring of simple relations among perceptually available…

Artificial Intelligence Applications to Fire Management

Treesearch

Don J. Latham

1987-01-01

Artificial intelligence could be used in Forest Service fire management and land-use planning to a larger degree than is now done. Robots, for example, could be programmed to monitor for fire and insect activity, to keep track of wildlife, and to do elementary thinking about the environment. Catching up with the fast-changing technology is imperative.

The 1992 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1992-01-01

The purpose of this conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers fall into the following areas: planning and scheduling, control, fault monitoring/diagnosis and recovery, information management, tools, neural networks, and miscellaneous applications.

SCAILET - An intelligent assistant for satellite ground terminal operations

NASA Technical Reports Server (NTRS)

Shahidi, A. K.; Crapo, J. A.; Schlegelmilch, R. F.; Reinhart, R. C.; Petrik, E. J.; Walters, J. L.; Jones, R. E.

1992-01-01

Space communication artificial intelligence for the link evaluation terminal (SCAILET) is an experimenter interface to the link evaluation terminal (LET) developed by NASA through the application of artificial intelligence to an advanced ground terminal. The high-burst-rate (HBR) LET provides the required capabilities for wideband communications experiments with the advanced communications technology satellite (ACTS). The HBR-LET terminal consists of seven major subsystems and is controlled and monitored by a minicomputer through an IEEE-488 or RS-232 interface. Programming scripts configure HBR-LET and allow data acquisition but are difficult to use and therefore the full capabilities of the system are not utilized. An intelligent assistant module was developed as part of the SCAILET module and solves problems encountered during configuration of the HBR-LET system. This assistant is a graphical interface with an expert system running in the background and allows users to configure instrumentation, program sequences and reference documentation. The simplicity of use makes SCAILET a superior interface to the ASCII terminal and continuous monitoring allows nearly flawless configuration and execution of HBR-LET experiments.

An Intelligent CAI Monitor and Generative Tutor. Interim Report.

ERIC Educational Resources Information Center

Koffman, Elliot B.; And Others

Design techniques for generative computer-assisted-instructional (CAI) systems are described in this report. These are systems capable of generating problems for students and of deriving and monitoring solutions; problem difficulty, instructional pace, and depth of monitoring are all individually tailored and parts of the solution algorithms can…

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E.; Parvin, Bahram

2009-06-09

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time: quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E [Martinez, CA; Parvin, Bahram [Mill Valley, CA

2011-05-24

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time; quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E; Parvin, Bahram

2013-10-01

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time; quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Ambient Assisted Nutritional Advisor for elderly people living at home.

PubMed

Lazaro, Juan P; Fides, Alvaro; Navarro, Ana; Guillen, Sergio

2010-01-01

Nutrition is a critical aspect when getting older because bad nutrition habits can accelerate the process of degradation of the physical condition of the old person. In order to mitigate this problem, an Ambient Assisted Living service has been developed. Research with this service is focused on demonstrating that with an Ambient Intelligence systems it is possible to make the nutritional management much more effective by influencing the user, by automatically and seamlessly monitoring and by facilitating tools for nutritional management for people that want to be autonomous. In this paper both requirement acquisition and development processes are described as well.

Genetics Home Reference: 7q11.23 duplication syndrome

MedlinePlus

... with this condition have low-average to average intelligence. Intellectual disability or borderline intellectual ability occur in ... Rarely, people with this disorder have above-average intelligence. Behavioral problems associated with this condition include anxiety ...

The impact of reverberant self-masking and overlap-masking effects on speech intelligibility by cochlear implant listeners (L).

PubMed

Kokkinakis, Kostas; Loizou, Philipos C

2011-09-01

The purpose of this study is to determine the relative impact of reverberant self-masking and overlap-masking effects on speech intelligibility by cochlear implant listeners. Sentences were presented in two conditions wherein reverberant consonant segments were replaced with clean consonants, and in another condition wherein reverberant vowel segments were replaced with clean vowels. The underlying assumption is that self-masking effects would dominate in the first condition, whereas overlap-masking effects would dominate in the second condition. Results indicated that the degradation of speech intelligibility in reverberant conditions is caused primarily by self-masking effects that give rise to flattened formant transitions. © 2011 Acoustical Society of America

Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

PubMed

Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

2004-02-01

To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal hemorrhagic shock. We suggest that this technology may represent a noninvasive means of assessing the physiologic state during and immediately following hemorrhage. Point of care application of this technology may improve outcomes with earlier diagnosis and better titration of therapy of shock.

Spatial Collective Intelligence? credibility, accuracy, and Volunteered Geographic Information

PubMed Central

Spielman, Seth E.

2014-01-01

Collective intelligence is the idea that under the right circumstances collections of individuals are smarter than even the smartest individuals in the group (Suroweiki 2004), that is a group has an “intelligence” that is independent of the intelligence of its members. The ideology of collective intelligence undergirds much of the enthusiasm about the use of “volunteered” or crowdsourced geographic information. Literature from a variety of fields makes clear that not all groups possess collective intelligence, this paper identifies four pre-conditions for the emergence of collective intelligence and then examine the extent to which collectively generated mapping systems satisfy these conditions. However, the “intelligence” collectively generated maps is hard to assess because there are two difficult to reconcile perspectives on map quality- the credibility perspective and the accuracy perspective. Much of the current literature on user generated maps focuses on assessing the quality of individual contributions. However, because user generated maps are complex social systems and because the quality of a contribution is difficult to assess this strategy may not yield an “intelligent” end product. The existing literature on collective intelligence suggests that the structure of groups more important that the intelligence of group members. Applying this idea to user generated suggests that systems should be designed to foster conditions known to produce collective intelligence rather than privileging particular contributions/contributors. The paper concludes with some design recommendations and by considering the implications of collectively generated maps for both expert knowledge and traditional state sponsored mapping programs. PMID:25419184

Coordinating High-Resolution Traffic Cameras : Developing Intelligent, Collaborating Cameras for Transportation Security and Communications

DOT National Transportation Integrated Search

2015-08-01

Cameras are used prolifically to monitor transportation incidents, infrastructure, and congestion. Traditional camera systems often require human monitoring and only offer low-resolution video. Researchers for the Exploratory Advanced Research (EAR) ...

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

2011-01-01

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

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

Mohaghegh, Shahab D.

apability of underground carbon dioxide storage to confine and sustain injected CO2 for a very long time is the main concern for geologic CO2 sequestration. If a leakage from a geological CO2 sequestration site occurs, it is crucial to find the approximate amount and the location of the leak in order to implement proper remediation activity. An overwhelming majority of research and development for storage site monitoring has been concentrated on atmospheric, surface or near surface monitoring of the sequestered CO2. This study aims to monitor the integrity of CO2 storage at the reservoir level. This work proposes developing in-situmore » CO2 Monitoring and Verification technology based on the implementation of Permanent Down-hole Gauges (PDG) or “Smart Wells” along with Artificial Intelligence and Data Mining (AI&DM). The technology attempts to identify the characteristics of the CO2 leakage by de-convolving the pressure signals collected from Permanent Down-hole Gauges (PDG). Citronelle field, a saline aquifer reservoir, located in the U.S. was considered for this study. A reservoir simulation model for CO2 sequestration in the Citronelle field was developed and history matched. The presence of the PDGs were considered in the reservoir model at the injection well and an observation well. High frequency pressure data from sensors were collected based on different synthetic CO2 leakage scenarios in the model. Due to complexity of the pressure signal behaviors, a Machine Learning-based technology was introduced to build an Intelligent Leakage Detection System (ILDS). The ILDS was able to detect leakage characteristics in a short period of time (less than a day) demonstrating the capability of the system in quantifying leakage characteristics subject to complex rate behaviors. The performance of ILDS was examined under different conditions such as multiple well leakages, cap rock leakage, availability of an additional monitoring well, presence of pressure drift and noise in the pressure sensor and uncertainty in the reservoir model.« less

Distributed intrusion monitoring system with fiber link backup and on-line fault diagnosis functions

NASA Astrophysics Data System (ADS)

Xu, Jiwei; Wu, Huijuan; Xiao, Shunkun

2014-12-01

A novel multi-channel distributed optical fiber intrusion monitoring system with smart fiber link backup and on-line fault diagnosis functions was proposed. A 1× N optical switch was intelligently controlled by a peripheral interface controller (PIC) to expand the fiber link from one channel to several ones to lower the cost of the long or ultra-long distance intrusion monitoring system and also to strengthen the intelligent monitoring link backup function. At the same time, a sliding window auto-correlation method was presented to identify and locate the broken or fault point of the cable. The experimental results showed that the proposed multi-channel system performed well especially whenever any a broken cable was detected. It could locate the broken or fault point by itself accurately and switch to its backup sensing link immediately to ensure the security system to operate stably without a minute idling. And it was successfully applied in a field test for security monitoring of the 220-km-length national borderline in China.

OFMTutor: An operator function model intelligent tutoring system

NASA Technical Reports Server (NTRS)

Jones, Patricia M.

1989-01-01

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described.

Man-Robot Symbiosis: A Framework For Cooperative Intelligence And Control

NASA Astrophysics Data System (ADS)

Parker, Lynne E.; Pin, Francois G.

1988-10-01

The man-robot symbiosis concept has the fundamental objective of bridging the gap between fully human-controlled and fully autonomous systems to achieve true man-robot cooperative control and intelligence. Such a system would allow improved speed, accuracy, and efficiency of task execution, while retaining the man in the loop for innovative reasoning and decision-making. The symbiont would have capabilities for supervised and unsupervised learning, allowing an increase of expertise in a wide task domain. This paper describes a robotic system architecture facilitating the symbiotic integration of teleoperative and automated modes of task execution. The architecture reflects a unique blend of many disciplines of artificial intelligence into a working system, including job or mission planning, dynamic task allocation, man-robot communication, automated monitoring, and machine learning. These disciplines are embodied in five major components of the symbiotic framework: the Job Planner, the Dynamic Task Allocator, the Presenter/Interpreter, the Automated Monitor, and the Learning System.

A survey of fuzzy logic monitoring and control utilisation in medicine.

PubMed

Mahfouf, M; Abbod, M F; Linkens, D A

2001-01-01

Intelligent systems have appeared in many technical areas, such as consumer electronics, robotics and industrial control systems. Many of these intelligent systems are based on fuzzy control strategies which describe complex systems mathematical models in terms of linguistic rules. Since the 1980s new techniques have appeared from which fuzzy logic has been applied extensively in medical systems. The justification for such intelligent systems driven solutions is that biological systems are so complex that the development of computerised systems within such environments is not always a straightforward exercise. In practice, a precise model may not exist for biological systems or it may be too difficult to model. In most cases fuzzy logic is considered to be an ideal tool as human minds work from approximate data, extract meaningful information and produce crisp solutions. This paper surveys the utilisation of fuzzy logic control and monitoring in medical sciences with an analysis of its possible future penetration.

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

NASA Technical Reports Server (NTRS)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Real-time GMAW quality classification using an artificial neural network with airborne acoustic signals as inputs

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

Matteson, A.; Morris, R.; Tate, R.

1993-12-31

The acoustic signal produced by the gas metal arc welding (GMAW) arc contains information about the behavior of the arc column, the molten pool and droplet transfer. It is possible to detect some defect producing conditions from the acoustic signal from the GMAW arc. An intelligent sensor, called the Weld Acoustic Monitor (WAM) has been developed to take advantage of this acoustic information in order to provide real-time quality assessment information for process control. The WAM makes use of an Artificial Neural Network (ANN) to classify the characteristic arc acoustic signals of acceptable and unacceptable welds. The ANN used inmore » the Weld Acoustic Monitor developed its own set of rules for this classification problem by learning a data base of known GMAW acoustic signals.« less

Model-based reasoning for power system management using KATE and the SSM/PMAD

NASA Technical Reports Server (NTRS)

Morris, Robert A.; Gonzalez, Avelino J.; Carreira, Daniel J.; Mckenzie, F. D.; Gann, Brian

1993-01-01

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

PubMed Central

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system. PMID:25140342

Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

PubMed

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Ageing-in-place with the use of ambient intelligence technology: perspectives of older users.

PubMed

van Hoof, J; Kort, H S M; Rutten, P G S; Duijnstee, M S H

2011-05-01

Ambient intelligence technologies are a means to support ageing-in-place by monitoring clients in the home. In this study, monitoring is applied for the purpose of raising an alarm in an emergency situation, and thereby, providing an increased sense of safety and security. Apart from these technological solutions, there are numerous environmental interventions in the home environment that can support people to age-in-place. The aim of this study was to investigate the needs and motives, related to ageing-in-place, of the respondents receiving ambient intelligence technologies, and to investigate whether, and how, these technologies contributed to aspects of ageing-in-place. This paper presents the results of a qualitative study comprised of interviews and observations of technology and environmental interventions in the home environment among 18 community-dwelling older adults with a complex demand for care. These respondents had a prototype of the Unattended Autonomous Surveillance system, an example of ambient intelligence technology, installed in their homes as a means to age-in-place. The UAS-system offers a large range of functionalities, including mobility monitoring, voice response, fire detection, as well as wandering detection and prevention, which can be installed in different configurations. The respondents had various motives to use ambient intelligence technologies to support ageing-in-place. The most prominent reason was to improve the sense of safety and security, in particular, in case of fall incidents, when people were afraid not to be able to use their existing emergency response systems. The ambient intelligence technologies were initially seen as a welcome addition to strategies already adopted by the respondents, including a variety of home modifications and assistive devices. The systems tested increased the sense of safety and security and helped to postpone institutionalisation. Respondents came up with a set of specifications in terms of the operation and the design of the technology. False alarms were also regarded as a sign that the ambient intelligence technology is functioning. Moreover, a good integration of the new technologies in the provision of health care is indispensable, and installation should be done in an acceptable and unobtrusive manner. Ambient intelligence technologies can contribute to an increased safety and security at home. The technologies alone offer no all encompassing solution as home care and additional environmental interventions are still needed to support ageing-in-place. Results of the study are used to further improve the ambient intelligence technologies and their implementation. 2011 Elsevier Ireland Ltd. All rights reserved.

Empirical Investigation of Select Personality, Attitudinal, and Experience-Based Antecedents of Cultural Intelligence in Undergraduate Business Students

ERIC Educational Resources Information Center

Kurpis, Lada V.

2012-01-01

Fostering cultural intelligence development in undergraduate business students should be one of the goals of diversity education in undergraduate business programs due to the demands of the increasingly global workplace of today. A number of personality-based (e.g., self-monitoring personality trait), attitudinal (e.g., preference for jobs…

Using business intelligence to monitor clinical quality metrics.

PubMed

Resetar, Ervina; Noirot, Laura A; Reichley, Richard M; Storey, Patricia; Skiles, Ann M; Traynor, Patrick; Dunagan, W Claiborne; Bailey, Thomas C

2007-10-11

BJC HealthCare (BJC) uses a number of industry standard indicators to monitor the quality of services provided by each of its hospitals. By establishing an enterprise data warehouse as a central repository of clinical quality information, BJC is able to monitor clinical quality performance in a timely manner and improve clinical outcomes.

Design of a real-time tax-data monitoring intelligent card system

NASA Astrophysics Data System (ADS)

Gu, Yajun; Bi, Guotang; Chen, Liwei; Wang, Zhiyuan

2009-07-01

To solve the current problem of low efficiency of domestic Oil Station's information management, Oil Station's realtime tax data monitoring system has been developed to automatically access tax data of Oil pumping machines, realizing Oil-pumping machines' real-time automatic data collection, displaying and saving. The monitoring system uses the noncontact intelligent card or network to directly collect data which can not be artificially modified and so seals the loopholes and improves the tax collection's automatic level. It can perform real-time collection and management of the Oil Station information, and find the problem promptly, achieves the automatic management for the entire process covering Oil sales accounting and reporting. It can also perform remote query to the Oil Station's operation data. This system has broad application future and economic value.

Bluetooth-based sensor networks for remotely monitoring the physiological signals of a patient.

PubMed

Zhang, Ying; Xiao, Hannan

2009-11-01

Integrating intelligent medical microsensors into a wireless communication network makes it possible to remotely collect physiological signals of a patient, release the patient from being tethered to monitoring medical instrumentations, and facilitate the patient's early hospital discharge. This can further improve life quality by providing continuous observation without the need of disrupting the patient's normal life, thus reducing the risk of infection significantly, and decreasing the cost of the hospital and the patient. This paper discusses the implementation issues, and describes the overall system architecture of our developed Bluetooth sensor network for patient monitoring and the corresponding heart activity sensors. It also presents our approach to developing the intelligent physiological sensor nodes involving integration of Bluetooth radio technology, hardware and software organization, and our solutions for onboard signal processing.

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection.

PubMed

Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

2017-06-12

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan-Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities.

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection †

PubMed Central

Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

2017-01-01

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan–Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities. PMID:28604628

Challenges in building intelligent systems for space mission operations

NASA Technical Reports Server (NTRS)

Hartman, Wayne

1991-01-01

The purpose here is to provide a top-level look at the stewardship functions performed in space operations, and to identify the major issues and challenges that must be addressed to build intelligent systems that can realistically support operations functions. The focus is on decision support activities involving monitoring, state assessment, goal generation, plan generation, and plan execution. The bottom line is that problem solving in the space operations domain is a very complex process. A variety of knowledge constructs, representations, and reasoning processes are necessary to support effective human problem solving. Emulating these kinds of capabilities in intelligent systems offers major technical challenges that the artificial intelligence community is only beginning to address.

EXODUS: Integrating intelligent systems for launch operations support

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1991-01-01

Kennedy Space Center (KSC) is developing knowledge-based systems to automate critical operations functions for the space shuttle fleet. Intelligent systems will monitor vehicle and ground support subsystems for anomalies, assist in isolating and managing faults, and plan and schedule shuttle operations activities. These applications are being developed independently of one another, using different representation schemes, reasoning and control models, and hardware platforms. KSC has recently initiated the EXODUS project to integrate these stand alone applications into a unified, coordinated intelligent operations support system. EXODUS will be constructed using SOCIAL, a tool for developing distributed intelligent systems. EXODUS, SOCIAL, and initial prototyping efforts using SOCIAL to integrate and coordinate selected EXODUS applications are described.

Intelligent hypertext manual development for the Space Shuttle hazardous gas detection system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Hoyt, W. Andes

1989-01-01

This research is designed to utilize artificial intelligence (AI) technology to increase the efficiency of personnel involved with monitoring the space shuttle hazardous gas detection systems at the Marshall Space Flight Center. The objective is to create a computerized service manual in the form of a hypertext and expert system which stores experts' knowledge and experience. The resulting Intelligent Manual will assist the user in interpreting data timely, in identifying possible faults, in locating the applicable documentation efficiently, in training inexperienced personnel effectively, and updating the manual frequently as required.

Comparison of speech intelligibility in cockpit noise using SPH-4 flight helmet with and without active noise reduction

NASA Technical Reports Server (NTRS)

Chan, Jeffrey W.; Simpson, Carol A.

1990-01-01

Active Noise Reduction (ANR) is a new technology which can reduce the level of aircraft cockpit noise that reaches the pilot's ear while simultaneously improving the signal to noise ratio for voice communications and other information bearing sound signals in the cockpit. A miniature, ear-cup mounted ANR system was tested to determine whether speech intelligibility is better for helicopter pilots using ANR compared to a control condition of ANR turned off. Two signal to noise ratios (S/N), representative of actual cockpit conditions, were used for the ratio of the speech to cockpit noise sound pressure levels. Speech intelligibility was significantly better with ANR compared to no ANR for both S/N conditions. Variability of speech intelligibility among pilots was also significantly less with ANR. When the stock helmet was used with ANR turned off, the average PB Word speech intelligibility score was below the Normally Acceptable level. In comparison, it was above that level with ANR on in both S/N levels.

Motivation and intelligence drive auditory perceptual learning.

PubMed

Amitay, Sygal; Halliday, Lorna; Taylor, Jenny; Sohoglu, Ediz; Moore, David R

2010-03-23

Although feedback on performance is generally thought to promote perceptual learning, the role and necessity of feedback remain unclear. We investigated the effect of providing varying amounts of positive feedback while listeners attempted to discriminate between three identical tones on learning frequency discrimination. Using this novel procedure, the feedback was meaningless and random in relation to the listeners' responses, but the amount of feedback provided (or lack thereof) affected learning. We found that a group of listeners who received positive feedback on 10% of the trials improved their performance on the task (learned), while other groups provided either with excess (90%) or with no feedback did not learn. Superimposed on these group data, however, individual listeners showed other systematic changes of performance. In particular, those with lower non-verbal IQ who trained in the no feedback condition performed more poorly after training. This pattern of results cannot be accounted for by learning models that ascribe an external teacher role to feedback. We suggest, instead, that feedback is used to monitor performance on the task in relation to its perceived difficulty, and that listeners who learn without the benefit of feedback are adept at self-monitoring of performance, a trait that also supports better performance on non-verbal IQ tests. These results show that 'perceptual' learning is strongly influenced by top-down processes of motivation and intelligence.

Intelligent approach to prognostic enhancements of diagnostic systems

NASA Astrophysics Data System (ADS)

Vachtsevanos, George; Wang, Peng; Khiripet, Noppadon; Thakker, Ash; Galie, Thomas R.

2001-07-01

This paper introduces a novel methodology to prognostics based on a dynamic wavelet neural network construct and notions from the virtual sensor area. This research has been motivated and supported by the U.S. Navy's active interest in integrating advanced diagnostic and prognostic algorithms in existing Naval digital control and monitoring systems. A rudimentary diagnostic platform is assumed to be available providing timely information about incipient or impending failure conditions. We focus on the development of a prognostic algorithm capable of predicting accurately and reliably the remaining useful lifetime of a failing machine or component. The prognostic module consists of a virtual sensor and a dynamic wavelet neural network as the predictor. The virtual sensor employs process data to map real measurements into difficult to monitor fault quantities. The prognosticator uses a dynamic wavelet neural network as a nonlinear predictor. Means to manage uncertainty and performance metrics are suggested for comparison purposes. An interface to an available shipboard Integrated Condition Assessment System is described and applications to shipboard equipment are discussed. Typical results from pump failures are presented to illustrate the effectiveness of the methodology.

Integration of a computerized two-finger gripper for robot workstation safety

NASA Technical Reports Server (NTRS)

Sneckenberger, John E.; Yoshikata, Kazuki

1988-01-01

A microprocessor-based controller has been developed that continuously monitors and adjusts the gripping force applied by a special two-finger gripper. This computerized force sensing gripper system enables the endeffector gripping action to be independently detected and corrected. The gripping force applied to a manipulated object is real-time monitored for problem situations, situations which can occur during both planned and errant robot arm manipulation. When unspecified force conditions occur at the gripper, the gripping force controller initiates specific reactions to cause dynamic corrections to the continuously variable gripping action. The force controller for this intelligent gripper has been interfaced to the controller of an industrial robot. The gripper and robot controllers communicate to accomplish the successful completion of normal gripper operations as well as unexpected hazardous situations. An example of an unexpected gripping condition would be the sudden deformation of the object being manipulated by the robot. The capabilities of the interfaced gripper-robot system to apply workstation safety measures (e.g., stop the robot) when these unexpected gripping effects occur have been assessed.

Communications and Intelligent Systems Division Overview

NASA Technical Reports Server (NTRS)

Emerson, Dawn

2017-01-01

Provides expertise, and plans, conducts and directs research and engineering development in the competency fields of advanced communications and intelligent systems technologies for applications in current and future aeronautics and space systems.Advances communication systems engineering, development and analysis needed for Glenn Research Center's leadership in communications and intelligent systems technology. Focus areas include advanced high frequency devices, components, and antennas; optical communications, health monitoring and instrumentation; digital signal processing for communications and navigation, and cognitive radios; network architectures, protocols, standards and network-based applications; intelligent controls, dynamics and diagnostics; and smart micro- and nano-sensors and harsh environment electronics. Research and discipline engineering allow for the creation of innovative concepts and designs for aerospace communication systems with reduced size and weight, increased functionality and intelligence. Performs proof-of-concept studies and analyses to assess the impact of the new technologies.

The Intelligent Control System and Experiments for an Unmanned Wave Glider.

PubMed

Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

2016-01-01

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the "Ocean Rambler" UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified.

The Intelligent Control System and Experiments for an Unmanned Wave Glider

PubMed Central

Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

2016-01-01

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the “Ocean Rambler” UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified. PMID:28005956

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

NASA Astrophysics Data System (ADS)

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

1999-03-01

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

Priming Ability Emotional Intelligence

ERIC Educational Resources Information Center

Schutte, Nicola S.; Malouff, John M.

2012-01-01

Two studies examined whether priming self-schemas relating to successful emotional competency results in better emotional intelligence performance. In the first study participants were randomly assigned to a successful emotional competency self-schema prime condition or a control condition and then completed an ability measure of emotional…

Social intelligence and adequate self-expression in patients with orbitofrontal cortex injury and in the criminals

PubMed Central

Pąchalska, Maria; Ledwoch, Beata; Moskała, Marek; Zieniewicz, Katarzyna; Mańko, Grzegorz; Polak, Jarosław

2012-01-01

Summary Background The aim of present article is to compare patients with damage to the orbitofrontal cortex and prison inmates in terms of social intelligence and social intelligence monitoring. In addition, personal principles and emotional regulation of behavior will be assessed in both groups. Material/Methods 20 patients with orbitofrontal cortical injury, 20 prisoners and 20 controls answered questions from the Social Interactions Assessment Questionnaire. Then they evaluated their self-disclosure, reported their emotions related to self-disclosure and declared their personal principles concerning conversations with strangers. Results The patients with damage to the orbitofrontal cortex disclosed themselves to a stranger less appropriately than did other subjects, and did not assess it critically. They also violated their own declared principles, but did not feel embarrassed because of that. The prison inmates spoke out less forthrightly on many topics and felt confused during the whole examination. Conclusions Damage to the the orbital part of frontal lobes may result in a disorder of self-disclosure monitoring and impairment of social intelligence in conversations with unknown persons. Prison inmates give information about themselves unwillingly, which may result from their specific experiences during criminal and judicatory procedures and confinement. PMID:22648252

Using the Environmental Intelligence Framework to Address Arctic Issues: A Case Study of Alaskan Fisheries and Ocean Acidification

NASA Astrophysics Data System (ADS)

Mathis, J. T.; Osborne, E.; Bamzai, A. S.; Starkweather, S.

2017-12-01

Profound environmental change in the Arctic region is driving an urgent need for faster and more efficient knowledge creation and delivery for residents of the Arctic as well as stakeholders around the globe. The overarching issues at play include environmental stewardship, community health and cultural survival. To effectively address these issues, the Interagency Arctic Research Policy Committee (IAPRC) recently established the Environmental Intelligence Collaboration Team (EICT) that integrates observing capabilities, modelling efforts and data management. Since its inception, the EICT has been working to create pathways to environmental knowledge that sustains end-to-end integration of research across the linked steps of data integration, environmental observing, predictive modelling, assessing responsiveness to stakeholder needs and ultimately providing decision support. The EICT is currently focusing on the carbon-climate aspect of environmental knowledge and identifing specific decision-making needs to meet policy goals for topics such as carbon emissions from permafrost thaw, increasing wildfire frequency and ocean acidification. As a case study, we applied the Environmental Intelligence framework to understanding the effects of ocean acidification in southern Alaska where there are critical commercial and subsistence fisheries. The results of this work revealed that there is currently a 5-month window of optimal growing conditions at a hatchery facility for many juvenile shellfish although that window is expected to close by 2040. The outcome of this work relates directly to fisheries management decisions and identifies the need for continued Environmental Intelligence collection to monitor and mitigate ocean acidification in the Alaskan region.

Next generation control system for reflexive aerostructures

NASA Astrophysics Data System (ADS)

Maddux, Michael R.; Meents, Elizabeth P.; Barnell, Thomas J.; Cable, Kristin M.; Hemmelgarn, Christopher; Margraf, Thomas W.; Havens, Ernie

2010-04-01

Cornerstone Research Group Inc. (CRG) has developed and demonstrated a composite structural solution called reflexive composites for aerospace applications featuring CRG's healable shape memory polymer (SMP) matrix. In reflexive composites, an integrated structural health monitoring (SHM) system autonomously monitors the structural health of composite aerospace structures, while integrated intelligent controls monitor data from the SHM system to characterize damage and initiate healing when damage is detected. Development of next generation intelligent controls for reflexive composites were initiated for the purpose of integrating prognostic health monitoring capabilities into the reflexive composite structural solution. Initial efforts involved data generation through physical inspections and mechanical testing. Compression after impact (CAI) testing was conducted on composite-reinforced shape memory polymer samples to induce damage and investigate the effectiveness of matrix healing on mechanical performance. Non-destructive evaluation (NDE) techniques were employed to observe and characterize material damage. Restoration of mechanical performance was demonstrated through healing, while NDE data showed location and size of damage and verified mitigation of damage post-healing. Data generated was used in the development of next generation reflexive controls software. Data output from the intelligent controls could serve as input to Integrated Vehicle Health Management (IVHM) systems and Integrated Resilient Aircraft Controls (IRAC). Reflexive composite technology has the ability to reduce maintenance required on composite structures through healing, offering potential to significantly extend service life of aerospace vehicles and reduce operating and lifecycle costs.

Developing Software For Monitoring And Diagnosis

NASA Technical Reports Server (NTRS)

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

1993-01-01

Expert-system software shell produces executable code. Report discusses beginning phase of research directed toward development of artificial intelligence for real-time monitoring of, and diagnosis of faults in, complicated systems of equipment. Motivated by need for onboard monitoring and diagnosis of electronic sensing and controlling systems of advanced aircraft. Also applicable to such equipment systems as refineries, factories, and powerplants.

The DOE/NASA wind turbine data acquisition system. Part 3: Unattended power performance monitor

NASA Technical Reports Server (NTRS)

Halleyy, A.; Heidkamp, D.; Neustadter, H.; Olson, R.

1983-01-01

Software documentation, operational procedures, and diagnostic instructions for development version of an unattended wind turbine performance monitoring system is provided. Designed to be used for off line intelligent data acquisition in conjunction with the central host computer.

47 CFR 90.351 - Location and Monitoring Service.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Location and Monitoring Service. 90.351 Section 90.351 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES Intelligent Transportation Systems Radio Service § 90.351...

Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring

DTIC Science & Technology

2012-04-16

Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based...time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless

Model architecture of intelligent data mining oriented urban transportation information

NASA Astrophysics Data System (ADS)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

The Relationship between the Wechsler Intelligence Scale for Children-Revised and the Wechsler Intelligence Scale for Children-III Scales and Subtests for Gifted Children.

ERIC Educational Resources Information Center

Sabatino, David A.; And Others

1995-01-01

This study determines the comparability of the Wechsler Intelligence Scale for Children-Revised and the Wechsler Intelligence Scale for Children-III in relation to gifted children. Results indicate that both tests produce remarkably similar scale and subtest scores when administered under clinical conditions. (JPS)

Tracking signal test to monitor an intelligent time series forecasting model

NASA Astrophysics Data System (ADS)

Deng, Yan; Jaraiedi, Majid; Iskander, Wafik H.

2004-03-01

Extensive research has been conducted on the subject of Intelligent Time Series forecasting, including many variations on the use of neural networks. However, investigation of model adequacy over time, after the training processes is completed, remains to be fully explored. In this paper we demonstrate a how a smoothed error tracking signals test can be incorporated into a neuro-fuzzy model to monitor the forecasting process and as a statistical measure for keeping the forecasting model up-to-date. The proposed monitoring procedure is effective in the detection of nonrandom changes, due to model inadequacy or lack of unbiasedness in the estimation of model parameters and deviations from the existing patterns. This powerful detection device will result in improved forecast accuracy in the long run. An example data set has been used to demonstrate the application of the proposed method.

Improving traveler information on rural corridors in Wyoming through the use of intelligent transportation systems.

DOT National Transportation Integrated Search

2014-03-01

Using intelligent transportation systems to help report traveling conditions has been reserved for urban : areas. The goal of this research was to help develop a new methodology for incorporating travel times : calculated from intelligent transportat...

[Epidemiological intelligence as a model of organization in health].

PubMed

Rodrigues-Júnior, Antonio Luiz

2012-03-01

The concept of epidemiological intelligence, as a construction of information societies, goes beyond monitoring a list of diseases and the ability to elicit rapid responses. The concept should consider the complexity of the definition of epidemiology in the identification of this object of study without being limited to a set of actions in a single government sector. The activities of epidemiological intelligence include risk assessment, strategies for prevention and protection, subsystems of information, crisis management rooms, geographical analysis, etc. This concept contributes to the understanding of policies in health, in multisectorial and geopolitical dimensions, as regards the organization of services around public health emergencies, primary healthcare, as well as disasters. The activities of epidemiological intelligence should not be restricted to scientific research, but the researchers must beware of threats to public health. Lalonde's model enabled consideration of epidemiological intelligence as a way to restructure policies and share resources by creating communities of intelligence, whose purpose is primarily to deal with public health emergencies and disasters.

E-learning environment as intelligent tutoring system

NASA Astrophysics Data System (ADS)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Public Health Intelligence: Learning From the Ebola Crisis

PubMed Central

Weber, David Jay

2015-01-01

Today’s public health crises, as exemplified by the Ebola outbreak, lead to dramatic calls to action that typically include improved electronic monitoring systems to better prepare for, and respond to, similar occurrences in the future. Even a preliminary public health informatics evaluation of the current Ebola crisis exposes the need for enhanced coordination and sharing of trustworthy public health intelligence. We call for a consumer-centric model of public health intelligence and the formation of a national center to guide public health intelligence gathering and synthesis. Sharing accurate and actionable information with government agencies, health care practitioners, policymakers, and, critically, the general public, will mark a shift from doing public health surveillance on people to doing public health surveillance for people. PMID:26180978

Investigation on the use of artificial neural networks to overcome the effects of environmental and operational changes on guided waves monitoring

NASA Astrophysics Data System (ADS)

El Mountassir, M.; Yaacoubi, S.; Dahmene, F.

2015-07-01

Intelligent feature extraction and advanced signal processing techniques are necessary for a better interpretation of ultrasonic guided waves signals either in structural health monitoring (SHM) or in nondestructive testing (NDT). Such signals are characterized by at least multi-modal and dispersive components. In addition, in SHM, these signals are closely vulnerable to environmental and operational conditions (EOCs), and can be severely affected. In this paper we investigate the use of Artificial Neural Network (ANN) to overcome these effects and to provide a reliable damage detection method with a minimal of false indications. An experimental case of study (full scale pipe) is presented. Damages sizes have been increased and their shapes modified in different steps. Various parameters such as the number of inputs and the number of hidden neurons were studied to find the optimal configuration of the neural network.

Intelligent data management for real-time spacecraft monitoring

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

An Integrated Patient Information and In-Home Health Monitoring System Using Smartphones and Web Services.

PubMed

Sorwar, Golam; Ali, Mortuza; Islam, Md Kamrul; Miah, Mohammad Selim

2016-01-01

Modern healthcare systems are undergoing a paradigm shift from in-hospital care to in-home monitoring, leveraging the emerging technologies in the area of bio-sensing, wireless communication, mobile computing, and artificial intelligence. In-home monitoring promises to significantly reduce healthcare spending by preventing unnecessary hospital admissions and visits to healthcare professionals. Most of the in-home monitoring systems, proposed in the literature, focus on monitoring a set of specific vital signs. However, from the perspective of caregivers it is infeasible to maintain a collection of specialized monitoring systems. In this paper, we view the problem of in-home monitoring from the perspective of caregivers and present a framework that supports various monitoring capabilities while making the complexity transparent to the end users. The essential idea of the framework is to define a 'general purpose architecture' where the system specifies a particular protocol for communication and makes it public. Then any bio-sensing system can communicate with the system as long as it conforms to the protocol. We then argue that as the system grows in terms of number of patients and bio-sensing systems, artificial intelligence technologies need to be employed for patients' risk assessment, prioritization, and recommendation. Finally, we present an initial prototype of the system designed according to the proposed framework.

The design of an intelligent human-computer interface for the test, control and monitor system

NASA Technical Reports Server (NTRS)

Shoaff, William D.

1988-01-01

The graphical intelligence and assistance capabilities of a human-computer interface for the Test, Control, and Monitor System at Kennedy Space Center are explored. The report focuses on how a particular commercial off-the-shelf graphical software package, Data Views, can be used to produce tools that build widgets such as menus, text panels, graphs, icons, windows, and ultimately complete interfaces for monitoring data from an application; controlling an application by providing input data to it; and testing an application by both monitoring and controlling it. A complete set of tools for building interfaces is described in a manual for the TCMS toolkit. Simple tools create primitive widgets such as lines, rectangles and text strings. Intermediate level tools create pictographs from primitive widgets, and connect processes to either text strings or pictographs. Other tools create input objects; Data Views supports output objects directly, thus output objects are not considered. Finally, a set of utilities for executing, monitoring use, editing, and displaying the content of interfaces is included in the toolkit.

A bio-inspired memory model for structural health monitoring

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhu, Yong

2009-04-01

Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system.

A high-speed trapezoid image sensor design for continuous traffic monitoring at signalized intersection approaches.

DOT National Transportation Integrated Search

2014-10-01

The goal of this project is to monitor traffic flow continuously with an innovative camera system composed of a custom : designed image sensor integrated circuit (IC) containing trapezoid pixel array and camera system that is capable of : intelligent...

Optimizing Classroom Acoustics Using Computer Model Studies.

ERIC Educational Resources Information Center

Reich, Rebecca; Bradley, John

1998-01-01

Investigates conditions relating to the maximum useful-to-detrimental sound ratios present in classrooms and determining the optimum conditions for speech intelligibility. Reveals that speech intelligibility is more strongly influenced by ambient noise levels and that the optimal location for sound absorbing material is on a classroom's upper…

Construction and application of an intelligent air quality monitoring system for healthcare environment.

PubMed

Yang, Chao-Tung; Liao, Chi-Jui; Liu, Jung-Chun; Den, Walter; Chou, Ying-Chyi; Tsai, Jaw-Ji

2014-02-01

Indoor air quality monitoring in healthcare environment has become a critical part of hospital management and policy. Manual air sampling and analysis are cost-inhibitive and do not provide real-time air quality data and response measures. In this month-long study over 14 sampling locations in a public hospital in Taiwan, we observed a positive correlation between CO(2) concentration and population, total bacteria, and particulate matter concentrations, thus monitoring CO(2) concentration as a general indicator for air quality could be a viable option. Consequently, an intelligent environmental monitoring system consisting of a CO(2)/temperature/humidity sensor, a digital plug, and a ZigBee Router and Coordinator was developed and tested. The system also included a backend server that received and analyzed data, as well as activating ventilation and air purifiers when CO(2) concentration exceeded a pre-set value. Alert messages can also be delivered to offsite users through mobile devices.

Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 4. Part A. Hierarchical Region-Based Approach to Automatic Photointerpretation. Part B. Application of AI Techniques to Image Segmentation and Region Identification

DTIC Science & Technology

1988-01-01

MONITORING ORGANIZATION Northeast Artificial (If applicaole)nelincCostum(AcRome Air Development Center (COCU) Inteligence Consortium (NAIC)I 6c. ADDRESS...f, Offell RADC-TR-88-1 1, Vol IV (of eight) Interim Technical ReportS June 1988 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1986...13441-5700 EMENT NO NO NO ACCESSION NO62702F 5 8 71 " " over) I 58 27 13 " ൓ TITLE (Include Security Classification) NORTHEAST ARTIFICIAL INTELLIGENCE

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

NASA Technical Reports Server (NTRS)

Erickson, Jon D. (Editor)

1994-01-01

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications.

The need for monitoring metabolic status

NASA Astrophysics Data System (ADS)

Vanderveen, John E.

2005-05-01

Modern military operations utilize complex technologies that require high levels of readiness and sustained cognitive and physical performance of combat military combat personnel. These military operations often depend on weapon systems that use advanced computer technology coupled with an array of sensors that provide continuous information on the battlefield environment and on equipment function. However there is a lack of real-time information on status of the personnel who control these systems and who are vital to mission success. Failure of the human element renders the weapon system useless so it is important to know if an individual is physically and cognitively fit to perform his or her task. Based on the premise that status of metabolic processes provide an early indication of a change in an individuals physiological status, monitoring of selective biomarkers of metabolism and organ function can provide insight on the individual"s ability to perform mission tasks. During combat individuals may not be aware that they have reached a compromised physiological condition due to dehydration, physical exertion, stress, fatigue, sleep deprivation, exposure to toxins or other condition that may affect physical and cognitive performance and health. Systems that can provide the individual or his or her commander with information about significant changes in one or more metabolic functions could permit timely intervention to correct the condition. In the event that serious injury has already occurred to an individual, metabolic monitoring can provide valuable intelligence needed for decisions on achieving mission objectives.

Intelligent Control Approaches for Aircraft Applications

NASA Technical Reports Server (NTRS)

Gundy-Burlet, Karen; KrishnaKumar, K.; Soloway, Don; Kaneshige, John; Clancy, Daniel (Technical Monitor)

2001-01-01

This paper presents an overview of various intelligent control technologies currently being developed and studied under the Intelligent Flight Control (IFC) program at the NASA Ames Research Center. The main objective of the intelligent flight control program is to develop the next generation of flight controllers for the purpose of automatically compensating for a broad spectrum of damaged or malfunctioning aircraft components and to reduce control law development cost and time. The approaches being examined include: (a) direct adaptive dynamic inverse controller and (b) an adaptive critic-based dynamic inverse controller. These approaches can utilize, but do not require, fault detection and isolation information. Piloted simulation studies are performed to examine if the intelligent flight control techniques adequately: 1) Match flying qualities of modern fly-by-wire flight controllers under nominal conditions; 2) Improve performance under failure conditions when sufficient control authority is available; and 3) Achieve consistent handling qualities across the flight envelope and for different aircraft configurations. Results obtained so far demonstrate the potential for improving handling qualities and significantly increasing survivability rates under various simulated failure conditions.

The 1991 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1991-01-01

The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.

Standing on the Shoulders of Giants: Where Do We Go from Here to Bring the Fire Service into the Domestic Intelligence Community?

DTIC Science & Technology

2012-09-01

49 B. AREAS FOR FURTHER STUDY ...............................................................49 C. LEVERAGING CURRENT TECHNOLOGY AND THE FUTURE...Working Group also monitored network governance developments necessary to renovate existing DHS computer-based communication channels and technological ... technology ? b. What role does suspicious activity reporting play? 24 With these questions in mind, policies and plans related to intelligence

Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.

PubMed

2018-01-04

An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.

Triggers and monitoring in intelligent personal health record.

PubMed

Luo, Gang

2012-10-01

Although Web-based personal health records (PHRs) have been widely deployed, the existing ones have limited intelligence. Previously, we introduced expert system technology and Web search technology into the PHR domain and proposed the concept of an intelligent PHR (iPHR). iPHR provides personalized healthcare information to facilitate users' daily activities of living. The current iPHR is passive and follows the pull model of information distribution. This paper introduces triggers and monitoring into iPHR to make iPHR become active. Our idea is to let medical professionals pre-compile triggers and store them in iPHR's knowledge base. Each trigger corresponds to an abnormal event that may have potential medical impact. iPHR keeps collecting, processing, and analyzing the user's medical data from various sources such as wearable sensors. Whenever an abnormal event is detected from the user's medical data, the corresponding trigger fires and the related personalized healthcare information is pushed to the user using natural language generation technology, expert system technology, and Web search technology.

Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

NASA Astrophysics Data System (ADS)

Taylan, Osman

2017-02-01

High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

Influence of Activity Monitor Location and Bout Duration on Free-Living Physical Activity

ERIC Educational Resources Information Center

Heil, Daniel P.; Bennett, Gary G.; Bond, Kathleen S.; Webster, Michael D.; Wolin, Kathleen Y.

2009-01-01

The purpose of this study was to evaluate the influence of the location (ankle, hip, wrist) where an activity monitor (AM) is worn and of the minimum bout duration (BD) on physical activity (PA) variables during free-living monitoring. Study 1 participants wore AMs at three locations for 1 day while wearing the Intelligent Device for Energy…

Automation and robotics technology for intelligent mining systems

NASA Technical Reports Server (NTRS)

Welsh, Jeffrey H.

1989-01-01

The U.S. Bureau of Mines is approaching the problems of accidents and efficiency in the mining industry through the application of automation and robotics to mining systems. This technology can increase safety by removing workers from hazardous areas of the mines or from performing hazardous tasks. The short-term goal of the Automation and Robotics program is to develop technology that can be implemented in the form of an autonomous mining machine using current continuous mining machine equipment. In the longer term, the goal is to conduct research that will lead to new intelligent mining systems that capitalize on the capabilities of robotics. The Bureau of Mines Automation and Robotics program has been structured to produce the technology required for the short- and long-term goals. The short-term goal of application of automation and robotics to an existing mining machine, resulting in autonomous operation, is expected to be accomplished within five years. Key technology elements required for an autonomous continuous mining machine are well underway and include machine navigation systems, coal-rock interface detectors, machine condition monitoring, and intelligent computer systems. The Bureau of Mines program is described, including status of key technology elements for an autonomous continuous mining machine, the program schedule, and future work. Although the program is directed toward underground mining, much of the technology being developed may have applications for space systems or mining on the Moon or other planets.

Strong Genetic Overlap Between Executive Functions and Intelligence

PubMed Central

Engelhardt, Laura E.; Mann, Frank D.; Briley, Daniel A.; Church, Jessica A.; Harden, K. Paige; Tucker-Drob, Elliot M.

2016-01-01

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision-making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7-15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically-mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. PMID:27359131

Managing Sustainability with the Support of Business Intelligence Methods and Tools

NASA Astrophysics Data System (ADS)

Petrini, Maira; Pozzebon, Marlei

In this paper we explore the role of business intelligence (BI) in helping to support the management of sustainability in contemporary firms. The concepts of sustainability and corporate social responsibility (CSR) are among the most important themes to have emerged in the last decade at the global level. We suggest that BI methods and tools have an important but not yet well studied role to play in helping organizations implement and monitor sustainable and socially responsible business practices. Using grounded theory, the main contribution of our study is to propose a conceptual model that seeks to support the process of definition and monitoring of socio-environmental indicators and the relationship between their management and business strategy.

Wearable real-time and adaptive feedback device to face the stuttering: a knowledge-based telehealthcare proposal.

PubMed

Prado, Manuel; Roa, Laura M

2007-01-01

Despite first written references to permanent developmental stuttering occurred more than 2500 years ago, the mechanisms underlying this disorder are still unknown. This paper briefly reviews stuttering causal hypothesis and treatments, and presents the requirements that a new stuttering therapeutic device should verify. As a result of the analysis, an adaptive altered auditory feedback device based on a multimodal intelligent monitor, within the framework of a knowledge-based telehealthcare system, is presented. The subsequent discussion, based partly on the successful outcomes of a similar intelligent monitor, suggests that this novel device is feasible and could help to fill the gap between research and clinic.

Telemedicine and medical informatics in the multimedia super corridor: the Malaysian vision.

PubMed

Abidi, S S; Goh, A; Yusoff, Z

1998-01-01

The practice of medicine, with its wide range of environmental conditions and complex dependencies, has long been used as a test bed for various advanced technologies. Telemedicine, as conceptualised within the Multimedia Super Corridor (MSC) context, is seen as the application of several relatively mature technologiesartificial intelligence (AI), multimedia communication and information systems (IS) amongst othersso as to benefit a large cross-section of the Malaysian population. We will discuss in general terms the Malaysian vision on the comprehensive MSC telemedicine solution, its functionality and associated operational conditions. In particular, this paper focuses on the conceptualisation of one key telemedical component i.e. the Lifetime Health Plan (LHP) system, which is eventually intended to be a distributed multi-module application for the periodic monitoring and generation of health-care advisories for upwards of 20 million Malaysians.

Speech outcome in unilateral complete cleft lip and palate patients: a descriptive study.

PubMed

Rullo, R; Di Maggio, D; Addabbo, F; Rullo, F; Festa, V M; Perillo, L

2014-09-01

In this study, resonance and articulation disorders were examined in a group of patients surgically treated for cleft lip and palate, considering family social background, and children's ability of self monitoring their speech output while speaking. Fifty children (32 males and 18 females) mean age 6.5 ± 1.6 years, affected by non-syndromic complete unilateral cleft of the lip and palate underwent the same surgical protocol. The speech level was evaluated using the Accordi's speech assessment protocol that focuses on intelligibility, nasality, nasal air escape, pharyngeal friction, and glottal stop. Pearson product-moment correlation analysis was used to detect significant associations between analysed parameters. A total of 16% (8 children) of the sample had severe to moderate degree of nasality and nasal air escape, presence of pharyngeal friction and glottal stop, which obviously compromise speech intelligibility. Ten children (10%) showed a barely acceptable phonological outcome: nasality and nasal air escape were mild to moderate, but the intelligibility remained poor. Thirty-two children (64%) had normal speech. Statistical analysis revealed a significant correlation between the severity of nasal resonance and nasal air escape (p ≤ 0.05). No statistical significant correlation was found between the final intelligibility and the patient social background, neither between the final intelligibility nor the age of the patients. The differences in speech outcome could be explained with a specific, subjective, and inborn ability, different for each child, in self-monitoring their speech output.

Prior exposure to a reverberant listening environment improves speech intelligibility in adult cochlear implant listeners.

PubMed

Srinivasan, Nirmal Kumar; Tobey, Emily A; Loizou, Philipos C

2016-01-01

The goal of this study is to investigate whether prior exposure to reverberant listening environment improves speech intelligibility of adult cochlear implant (CI) users. Six adult CI users participated in this study. Speech intelligibility was measured in five different simulated reverberant listening environments with two different speech corpuses. Within each listening environment, prior exposure was varied by either having the same environment across all trials (blocked presentation) or having different environment from trial to trial (unblocked). Speech intelligibility decreased as reverberation time increased. Although substantial individual variability was observed, all CI listeners showed an increase in the blocked presentation condition as compared to the unblocked presentation condition for both speech corpuses. Prior listening exposure to a reverberant listening environment improves speech intelligibility in adult CI listeners. Further research is required to understand the underlying mechanism of adaptation to listening environment.

Reliability Prediction Approaches For Domestic Intelligent Electric Energy Meter Based on IEC62380

NASA Astrophysics Data System (ADS)

Li, Ning; Tong, Guanghua; Yang, Jincheng; Sun, Guodong; Han, Dongjun; Wang, Guixian

2018-01-01

The reliability of intelligent electric energy meter is a crucial issue considering its large calve application and safety of national intelligent grid. This paper developed a procedure of reliability prediction for domestic intelligent electric energy meter according to IEC62380, especially to identify the determination of model parameters combining domestic working conditions. A case study was provided to show the effectiveness and validation.

Intelligence and Complexity of the Averaged Evoked Potential: An Attentional Theory.

ERIC Educational Resources Information Center

Bates, Tim; And Others

1995-01-01

A study measuring average evoked potentials in 21 college students finds that intelligence test scores correlate significantly with the difference between string length in attended and nonattended conditions, a finding that suggests that previous inconsistencies in reporting string length-intelligence correlations may have resulted from confound…

Self-powered Real-time Movement Monitoring Sensor Using Triboelectric Nanogenerator Technology.

PubMed

Jin, Liangmin; Tao, Juan; Bao, Rongrong; Sun, Li; Pan, Caofeng

2017-09-05

The triboelectric nanogenerator (TENG) has great potential in the field of self-powered sensor fabrication. Recently, smart electronic devices and movement monitoring sensors have attracted the attention of scientists because of their application in the field of artificial intelligence. In this article, a TENG finger movement monitoring, self-powered sensor has been designed and analysed. Under finger movements, the TENG realizes the contact and separation to convert the mechanical energy into electrical signal. A pulse output current of 7.8 μA is generated by the bending and straightening motions of the artificial finger. The optimal output power can be realized when the external resistance is approximately 30 MΩ. The random motions of the finger are detected by the system with multiple TENG sensors in series. This type of flexible and self-powered sensor has potential applications in artificial intelligence and robot manufacturing.

Intelligent command and control systems for satellite ground operations

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1994-01-01

The Georgia Tech portion of the Intelligent Control Center project includes several complementary activities. Two major activities entail thesis level research; the other activities are either support activities or preliminary explorations (e.g., task analyses) to support the research. The first research activity is the development of principles for the design of active interfaces to support monitoring during real-time supports. It is well known that as the operator's task becomes less active, i.e., more monitoring and less active control, there is concern that the operator will be less involved and less able to rapidly identify anomalous or failure situations. The research project to design active monitoring interfaces is an attempt to remediate this undesirable side-effect of increasingly automated control systems that still depend ultimately on operator supervision. The second research activity is the exploration of the use of case-based reasoning as a way to accumulate operator experience and make it available in computational form.

Intelligent data reduction for autonomous power systems

NASA Technical Reports Server (NTRS)

Floyd, Stephen A.

1988-01-01

Since 1984 Marshall Space Flight Center was actively engaged in research and development concerning autonomous power systems. Much of the work in this domain has dealt with the development and application of knowledge-based or expert systems to perform tasks previously accomplished only through intensive human involvement. One such task is the health status monitoring of electrical power systems. Such monitoring is a manpower intensive task which is vital to mission success. The Hubble Space Telescope testbed and its associated Nickel Cadmium Battery Expert System (NICBES) were designated as the system on which the initial proof of concept for intelligent power system monitoing will be established. The key function performed by an engineer engaged in system monitoring is to analyze the raw telemetry data and identify from the whole only those elements which can be considered significant. This function requires engineering expertise on the functionality of the system, the mode of operation and the efficient and effective reading of the telemetry data. Application of this expertise to extract the significant components of the data is referred to as data reduction. Such a function possesses characteristics which make it a prime candidate for the application of knowledge-based systems' technologies. Such applications are investigated and recommendations are offered for the development of intelligent data reduction systems.

Wearable nanosensor systems and their applications in healthcare

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Improved Real-Time Monitoring Using Multiple Expert Systems

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Angelino, Robert; Quan, Alan G.; Veregge, John; Childs, Cynthia

1993-01-01

Monitor/Analyzer of Real-Time Voyager Engineering Link (MARVEL) computer program implements combination of techniques of both conventional automation and artificial intelligence to improve monitoring of complicated engineering system. Designed to support ground-based operations of Voyager spacecraft, also adapted to other systems. Enables more-accurate monitoring and analysis of telemetry, enhances productivity of monitoring personnel, reduces required number of such personnel by performing routine monitoring tasks, and helps ensure consistency in face of turnover of personnel. Programmed in C language and includes commercial expert-system software shell also written in C.

The use of artificially intelligent agents with bounded rationality in the study of economic markets

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

Rajan, V.; Slagle, J.R.

The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

Predictability in space launch vehicle anomaly detection using intelligent neuro-fuzzy systems

NASA Technical Reports Server (NTRS)

Gulati, Sandeep; Toomarian, Nikzad; Barhen, Jacob; Maccalla, Ayanna; Tawel, Raoul; Thakoor, Anil; Daud, Taher

1994-01-01

Included in this viewgraph presentation on intelligent neuroprocessors for launch vehicle health management systems (HMS) are the following: where the flight failures have been in launch vehicles; cumulative delay time; breakdown of operations hours; failure of Mars Probe; vehicle health management (VHM) cost optimizing curve; target HMS-STS auxiliary power unit location; APU monitoring and diagnosis; and integration of neural networks and fuzzy logic.

Operational Intelligence Failures of the Korean War

DTIC Science & Technology

2014-05-22

of Advanced Military Studies United States Army Command and General Staff College Fort Leavenworth, Kansas 2014-01 Approved for public...MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) U.S. Army Command and General Staff College ATTN: ATZL-SWD-GD Fort ...of the Intelligence Art, The Official Homepage of Fort Huachuca, AZ, http://huachuca- www.army.mil/files/History_MWILLOU.PDF (accessed March 23, 2014

New concepts and technologies in home care and ambulatory monitoring.

PubMed

Dittmar, A; Axisa, F; Delhomme, G; Gehin, C

2004-01-01

The world is becoming more and more health conscious. Society, health policy and patients' needs are all changing dramatically. The challenges society is currently facing are related to the increase in the aging population, changes in lifestyle, the need for healthcare cost containment and the need for improvement and monitoring of healthcare quality. The emphasis is put on prevention rather than on treatment. In addition, patients and health consumers are waiting for non-invasive or minimally-invasive diagnosis and treatment methods, for home care, short stays in hospital, enhancement of rehabilitation, information and involvement in their own treatment. Progress in science and technology offers, today, miniaturization, speed, intelligence, sophistication and new materials at lower cost. In this new landscape, microtechnologies, information technologies and telecommunications are key factors. Telemedicine has also evolved. Used initially to exchange patients' files, radiographic data and other information between health providers, today telemedicine contributes to new trends in "hospital extension" through all-day monitoring of vital signs, professional activities, entertainment and home-based activities. The new possibilities for home care and ambulatory monitoring are provided at 4 levels: a) Microsensors. Microtechnologies offer the possibility of small size, but also of intelligent, active devices, working with low energy, wireless and non-invasive or minimally-invasive; b) Wrist devices are particularly user friendly and combine sensors, circuits, supply, display and wireless transmission in a single box, very convenient for common physical activities; c) Health smart clothes make contact with 90 % of the skin and offer many possibilities for the location of sensors. These sensors have to be thin, flexible and compatible with textiles, or made using textile technologies, such as new fibers with specific (mechanical, electrical and optical) properties; d) Health smart homes. The aim of this method is to improve the patient's living conditions and to avoid the cost of long hospitalization. "Exosensors" are used for measurement of the activity and behavior of the patient. The field of applications is very large, e.g. continuous monitoring of elderly populations, professional and military activities, athletes performance and condition, and people with disabilities. This new healthcare approach has to take into account lifestyle for improving prevention. For the patient to be more and more involved in his/her own therapy, new responsibilities and ethics have to be defined. A "societal health education" has to be provided to physicians and to patients to get all the benefits of this new context.

A demonstration of an intelligent control system for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Musgrave, Jeffrey L.; Paxson, Daniel E.; Litt, Jonathan S.; Merrill, Walter C.

1992-01-01

An Intelligent Control System for reusable rocket engines is under development at NASA Lewis Research Center. The primary objective is to extend the useful life of a reusable rocket propulsion system while minimizing between flight maintenance and maximizing engine life and performance through improved control and monitoring algorithms and additional sensing and actuation. This paper describes current progress towards proof-of-concept of an Intelligent Control System for the Space Shuttle Main Engine. A subset of identifiable and accommodatable engine failure modes is selected for preliminary demonstration. Failure models are developed retaining only first order effects and included in a simplified nonlinear simulation of the rocket engine for analysis under closed loop control. The engine level coordinator acts as an interface between the diagnostic and control systems, and translates thrust and mixture ratio commands dictated by mission requirements, and engine status (health) into engine operational strategies carried out by a multivariable control. Control reconfiguration achieves fault tolerance if the nominal (healthy engine) control cannot. Each of the aforementioned functionalities is discussed in the context of an example to illustrate the operation of the system in the context of a representative failure. A graphical user interface allows the researcher to monitor the Intelligent Control System and engine performance under various failure modes selected for demonstration.

Intelligent route surveillance

NASA Astrophysics Data System (ADS)

Schoemaker, Robin; Sandbrink, Rody; van Voorthuijsen, Graeme

2009-05-01

Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent ground sensor networks use simple sensing nodes, e.g. seismic, magnetic, radar, or acoustic, or combinations of these in one housing. The nodes deliver rudimentary data at any time to be processed with software that filters out the required information. At TNO (Netherlands Organisation for Applied Scientific Research) research has started on how to equip a sensor network with data analysis software to determine whether behaviour is suspicious or not. Furthermore, the nodes should be expendable, if necessary, and be small in size such that they are hard to detect by adversaries. The network should be self-configuring and self-sustaining and should be reliable, efficient, and effective during operational tasks - especially route surveillance - as well as robust in time and space. If data from these networks are combined with data from other remote sensing devices (e.g. UAVs (Unmanned Aerial Vehicles)/aerostats), an even more accurate assessment of the tactical situation is possible. This paper shall focus on the concepts of operation towards a working intelligent route surveillance (IRS) research demonstrator network for monitoring suspicious behaviour in IED sensitive domains.

Portable Intelligent Tritium in Air Monitor

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

Purghel, L.; Calin, M.R.; Bartos, D.

2005-07-15

The tritium detection method used for this monitor is original, patented in Romania. The detection unit consists of a single ionization chamber, a special fast preamplifier and a dedicated software associated to the detection unit, for signals processing. Some results concerning the tritium in relative strong gamma-ray fields are presented.

Continued Development of Compact Multi-gas Monitor for Life Support Systems Control in Space

NASA Technical Reports Server (NTRS)

Delgado-Alonso, Jesús; Phillips, Straun; Chullen, Cinda; Quinn, Gregory

2016-01-01

Miniature optic gas sensors (MOGS) based on luminescent materials have shown great potential as alternatives to Near-Infrared-based gas sensor systems for the advanced space suit portable life support system (PLSS). The unique capability of MOGS for carbon dioxide and oxygen monitoring under wet conditions has been reported, as has the fast recovery of MOGS humidity sensors after long periods of being wet. Lower volume and power requirements are also potential advantages of MOGS over both traditional and advanced Non-Dispersive Infrared (NDIR) gas sensors, which have shown so far longer life than luminescent sensors. This paper presents the most recent results in the development and analytical validation of a compact multi-gas sensor unit based on luminescent sensors for the PLSS. Results of extensive testing are presented, including studies conducted at Intelligent Optical Systems laboratories, a United Technology Corporation Aerospace Systems (UTAS) laboratory, and a Johnson Space Center laboratory. The potential of this sensor technology for gas monitoring in PLSSs and other life support systems and the advantages and limitations found through detailed sensor validation are discussed.

Test and assessment method of Automotive Safety Systems (SSB) particularly to monitor traffic incidents

NASA Astrophysics Data System (ADS)

Pijanowski, B.; Łukjanow, S.; Burliński, R.

2016-09-01

The rapid development of telematics, particularly mobile telephony (GSM), wireless data transmission (GPRS) and satellite positioning (GPS) noticeable in the last decade, resulted in an almost unlimited growth of the possibilities for monitoring of mobile objects. These solutions are already widely used in the so-called “Intelligent Transport Systems” - ITS and affect a significant increase for road safety. The article describes a method of testing and evaluation of Car Safety Systems (Polish abbreviation - SSB) especially for monitoring traffic incidents, such as collisions and accidents. The algorithm of SSB testing process is also presented. Tests are performed on the dynamic test bench, part of which is movable platform with car security system mounted on it. Crash tests with a rigid obstacle are carried out instead of destructive attempts to crash test of the entire vehicle which is expensive. The tested system, depending on the simulated traffic conditions, is mounted in such a position and with the use of components, indicated by the manufacturer for the automotive safety system installation in a vehicle, for which it is intended. Then, the tests and assessments are carried out.

Continued Development of Compact Multi-Gas Monitor for Life Support Systems Control in Space

NASA Technical Reports Server (NTRS)

Delgado, Jesus; Phillips, Straun; Chullen, Cinda

2015-01-01

Miniature optic gas sensors (MOGS) based on luminescent materials have shown great potential as alternatives to NIR-based gas sensor systems for the Portable Life Support System (PLSS). The unique capability of MOGS for carbon dioxide and oxygen monitoring under wet conditions has been reported, as has the fast recovery of MOGS humidity sensors after long periods of being wet. Lower volume and power requirements are also potential advantages of MOGS over both traditional and advanced Non-Dispersive Infrared (NDIR) gas sensors, which have shown so far longer life than luminescent sensors. In this paper we present the most recent results in the development and analytical validation of a compact multi-gas sensor unit based on luminescent sensors for the PLSS. Results of extensive testing are presented, including studies conducted at Intelligent Optical Systems laboratories, a United Technology Corporation Aerospace Systems (UTAS) laboratory, and a Johnson Space Center laboratory. The potential of this sensor technology for gas monitoring in PLSSs and other life support systems and the advantages and limitations found through detailed sensor validation are discussed.

Continued Development of Compact Multi-Gas Monitor for Life Support Systems Control in Space

NASA Technical Reports Server (NTRS)

Delgado-Alonso, Jesus; Phillips, Straun; Berry, David; DiCarmine, Paul; Chullen, Cinda; Quinn, Gregory

2016-01-01

Miniature optical gas sensors based on luminescent materials have shown great potential as alternatives to NIR-based gas sensor systems for the Portable Life Support System (PLSS). The unique capability of luminescent sensors for carbon dioxide and oxygen monitoring under wet conditions has been reported, as has the fast recovery of humidity sensors after long periods of being wet. Lower volume and power requirements are also potential advantages over both traditional and advanced non-dispersive infrared (NDIR) gas sensors, which have so far shown longer life than luminescent sensors. In this paper we present the most recent results in the development and analytical validation of a compact multi-gas sensor unit based on luminescent sensors for the PLSS. Results of extensive testing are presented, including studies conducted in Intelligent Optical Systems laboratories, a United Technologies Corporation Aerospace Systems (UTC) laboratory, and a Johnson Space Center laboratory. The potential of this sensor technology for gas monitoring in PLSSs and other life support systems, and the advantages and limitations found through detailed sensor validation are discussed.

Development of a Tool Condition Monitoring System for Impregnated Diamond Bits in Rock Drilling Applications

NASA Astrophysics Data System (ADS)

Perez, Santiago; Karakus, Murat; Pellet, Frederic

2017-05-01

The great success and widespread use of impregnated diamond (ID) bits are due to their self-sharpening mechanism, which consists of a constant renewal of diamonds acting at the cutting face as the bit wears out. It is therefore important to keep this mechanism acting throughout the lifespan of the bit. Nonetheless, such a mechanism can be altered by the blunting of the bit that ultimately leads to a less than optimal drilling performance. For this reason, this paper aims at investigating the applicability of artificial intelligence-based techniques in order to monitor tool condition of ID bits, i.e. sharp or blunt, under laboratory conditions. Accordingly, topologically invariant tests are carried out with sharp and blunt bits conditions while recording acoustic emissions (AE) and measuring-while-drilling variables. The combined output of acoustic emission root-mean-square value (AErms), depth of cut ( d), torque (tob) and weight-on-bit (wob) is then utilized to create two approaches in order to predict the wear state condition of the bits. One approach is based on the combination of the aforementioned variables and another on the specific energy of drilling. The two different approaches are assessed for classification performance with various pattern recognition algorithms, such as simple trees, support vector machines, k-nearest neighbour, boosted trees and artificial neural networks. In general, Acceptable pattern recognition rates were obtained, although the subset composed by AErms and tob excels due to the high classification performances rates and fewer input variables.

Innovative Technologies for Efficient Pharmacotherapeutic Management in Space

NASA Technical Reports Server (NTRS)

Putcha, Lakshmi; Daniels, Vernie

2014-01-01

Current and future Space exploration missions and extended human presence in space aboard the ISS will expose crew to risks that differ both quantitatively and qualitatively from those encountered before by space travelers and will impose an unknown risk of safety and crew health. The technology development challenges for optimizing therapeutics in space must include the development of pharmaceuticals with extended stability, optimal efficacy and bioavailability with minimal toxicity and side effects. Innovative technology development goals may include sustained/chronic delivery preventive health care products and vaccines, low-cost high-efficiency noninvasive, non-oral dosage forms with radio-protective formulation matrices and dispensing technologies coupled with self-reliant tracking technologies for quality assurance and quality control assessment. These revolutionary advances in pharmaceutical technology will assure human presence in space and healthy living on Earth. Additionally, the Joint Commission on Accreditation of Healthcare Organizations advocates the use of health information technologies to effectively execute all aspects of medication management (prescribing, dispensing, and administration). The advent of personalized medicine and highly streamlined treatment regimens stimulated interest in new technologies for medication management. Intelligent monitoring devices enhance medication accountability compliance, enable effective drug use, and offer appropriate storage and security conditions for dangerous drug and controlled substance medications in remote sites where traditional pharmacies are unavailable. These features are ideal for Exploration Medical Capabilities. This presentation will highlight current novel commercial off-the-shelf (COTS) intelligent medication management devices for the unique dispensing, therapeutic drug monitoring, medication tracking, and drug delivery demands of exploration space medical operations.

Impaired conditional reasoning in alcoholics: a negative impact on social interactions and risky behaviors?

PubMed

Kornreich, Charles; Delle-Vigne, Dyna; Knittel, Julian; Nerincx, Aurore; Campanella, Salvatore; Noel, Xavier; Hanak, Catherine; Verbanck, Paul; Ermer, Elsa

2011-05-01

To study the 'social brain' in alcoholics by investigating social contract reasoning, theory of mind and emotional intelligence. A behavioral study comparing recently detoxified alcoholics with normal, healthy controls. Emotional intelligence and decoding of emotional non-verbal cues have been shown to be impaired in alcoholics. This study explores whether these deficits extend to conditional reasoning about social contracts. Twenty-five recently detoxified alcoholics (17 men and eight women) were compared with 25 normal controls (17 men and eight women) matched for sex, age and education level. Wason selection task investigating conditional reasoning on three different rule types (social contract, precautionary and descriptive), revised Reading the Mind in the Eyes Test, Trait Emotional Intelligence Questionnaire (modified version) and additional control measures. Conditional reasoning was impaired in alcoholics. Performance on descriptive rules was not above chance. Reasoning performance was markedly better on social contract and precautionary rules, but this performance was still significantly lower than in controls. Several emotional intelligence measures were lower in alcoholics compared to controls, but these were not correlated with reasoning performance. Conditional reasoning, including reasoning about social contracts and emotional intelligence appear to be impaired in alcoholics. Impairment seems to be particularly severe on descriptive rules. Impairment in social contract reasoning might lead to misunderstandings and frustration in social interactions, and reasoning difficulties about precautionary rules might contribute to risky behaviors in this population. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

Options for reducing food waste by quality-controlled logistics using intelligent packaging along the supply chain.

PubMed

Heising, Jenneke K; Claassen, G D H; Dekker, Matthijs

2017-10-01

Optimising supply chain management can help to reduce food waste. This paper describes how intelligent packaging can be used to reduce food waste when used in supply chain management based on quality-controlled logistics (QCL). Intelligent packaging senses compounds in the package that correlate with the critical quality attribute of a food product. The information on the quality of each individual packaged food item that is provided by the intelligent packaging can be used for QCL. In a conceptual approach it is explained that monitoring food quality by intelligent packaging sensors makes it possible to obtain information about the variation in the quality of foods and to use a dynamic expiration date (IP-DED) on a food package. The conceptual approach is supported by quantitative data from simulations on the effect of using the information of intelligent packaging in supply chain management with the goal to reduce food waste. This simulation shows that by using the information on the quality of products that is provided by intelligent packaging, QCL can substantially reduce food waste. When QCL is combined with dynamic pricing based on the predicted expiry dates, a further waste reduction is envisaged.

Hydrological Monitoring System Design and Implementation Based on IOT

NASA Astrophysics Data System (ADS)

Han, Kun; Zhang, Dacheng; Bo, Jingyi; Zhang, Zhiguang

In this article, an embedded system development platform based on GSM communication is proposed. Through its application in hydrology monitoring management, the author makes discussion about communication reliability and lightning protection, suggests detail solutions, and also analyzes design and realization of upper computer software. Finally, communication program is given. Hydrology monitoring system from wireless communication network is a typical practical application of embedded system, which has realized intelligence, modernization, high-efficiency and networking of hydrology monitoring management.

Systematic Development of Intelligent Systems for Public Road Transport.

PubMed

García, Carmelo R; Quesada-Arencibia, Alexis; Cristóbal, Teresa; Padrón, Gabino; Alayón, Francisco

2016-07-16

This paper presents an architecture model for the development of intelligent systems for public passenger transport by road. The main objective of our proposal is to provide a framework for the systematic development and deployment of telematics systems to improve various aspects of this type of transport, such as efficiency, accessibility and safety. The architecture model presented herein is based on international standards on intelligent transport system architectures, ubiquitous computing and service-oriented architecture for distributed systems. To illustrate the utility of the model, we also present a use case of a monitoring system for stops on a public passenger road transport network.

Systematic Development of Intelligent Systems for Public Road Transport

PubMed Central

García, Carmelo R.; Quesada-Arencibia, Alexis; Cristóbal, Teresa; Padrón, Gabino; Alayón, Francisco

2016-01-01

This paper presents an architecture model for the development of intelligent systems for public passenger transport by road. The main objective of our proposal is to provide a framework for the systematic development and deployment of telematics systems to improve various aspects of this type of transport, such as efficiency, accessibility and safety. The architecture model presented herein is based on international standards on intelligent transport system architectures, ubiquitous computing and service-oriented architecture for distributed systems. To illustrate the utility of the model, we also present a use case of a monitoring system for stops on a public passenger road transport network. PMID:27438836

36 CFR 25.2 - License.

Code of Federal Regulations, 2011 CFR

2011-07-01

... condition, honest, intelligent, tactful, and of good repute. They must be thoroughly familiar with the... of the character, reputation, intelligence, and ability of the applicants, and of questions designed...

36 CFR 25.2 - License.

Code of Federal Regulations, 2014 CFR

2014-07-01

... condition, honest, intelligent, tactful, and of good repute. They must be thoroughly familiar with the... of the character, reputation, intelligence, and ability of the applicants, and of questions designed...

36 CFR 25.2 - License.

Code of Federal Regulations, 2012 CFR

2012-07-01

... condition, honest, intelligent, tactful, and of good repute. They must be thoroughly familiar with the... of the character, reputation, intelligence, and ability of the applicants, and of questions designed...

36 CFR 25.2 - License.

Code of Federal Regulations, 2013 CFR

2013-07-01

... condition, honest, intelligent, tactful, and of good repute. They must be thoroughly familiar with the... of the character, reputation, intelligence, and ability of the applicants, and of questions designed...

The effect of audiovisual and binaural listening on the acceptable noise level (ANL): establishing an ANL conceptual model.

PubMed

Wu, Yu-Hsiang; Stangl, Elizabeth; Pang, Carol; Zhang, Xuyang

2014-02-01

Little is known regarding the acoustic features of a stimulus used by listeners to determine the acceptable noise level (ANL). Features suggested by previous research include speech intelligibility (noise is unacceptable when it degrades speech intelligibility to a certain degree; the intelligibility hypothesis) and loudness (noise is unacceptable when the speech-to-noise loudness ratio is poorer than a certain level; the loudness hypothesis). The purpose of the study was to investigate if speech intelligibility or loudness is the criterion feature that determines ANL. To achieve this, test conditions were chosen so that the intelligibility and loudness hypotheses would predict different results. In Experiment 1, the effect of audiovisual (AV) and binaural listening on ANL was investigated; in Experiment 2, the effect of interaural correlation (ρ) on ANL was examined. A single-blinded, repeated-measures design was used. Thirty-two and twenty-five younger adults with normal hearing participated in Experiments 1 and 2, respectively. In Experiment 1, both ANL and speech recognition performance were measured using the AV version of the Connected Speech Test (CST) in three conditions: AV-binaural, auditory only (AO)-binaural, and AO-monaural. Lipreading skill was assessed using the Utley lipreading test. In Experiment 2, ANL and speech recognition performance were measured using the Hearing in Noise Test (HINT) in three binaural conditions, wherein the interaural correlation of noise was varied: ρ = 1 (N(o)S(o) [a listening condition wherein both speech and noise signals are identical across two ears]), -1 (NπS(o) [a listening condition wherein speech signals are identical across two ears whereas the noise signals of two ears are 180 degrees out of phase]), and 0 (N(u)S(o) [a listening condition wherein speech signals are identical across two ears whereas noise signals are uncorrelated across ears]). The results were compared to the predictions made based on the intelligibility and loudness hypotheses. The results of the AV and AO conditions appeared to support the intelligibility hypothesis due to the significant correlation between visual benefit in ANL (AV re: AO ANL) and (1) visual benefit in CST performance (AV re: AO CST) and (2) lipreading skill. The results of the N(o)S(o), NπS(o), and N(u)S(o) conditions negated the intelligibility hypothesis because binaural processing benefit (NπS(o) re: N(o)S(o), and N(u)S(o) re: N(o)S(o)) in ANL was not correlated to that in HINT performance. Instead, the results somewhat supported the loudness hypothesis because the pattern of ANL results across the three conditions (N(o)S(o) ≈ NπS(o) ≈ N(u)S(o) ANL) was more consistent with what was predicted by the loudness hypothesis (N(o)S(o) ≈ NπS(o) < N(u)S(o) ANL) than by the intelligibility hypothesis (NπS(o) < N(u)S(o) < N(o)S(o) ANL). The results of the binaural and monaural conditions supported neither hypothesis because (1) binaural benefit (binaural re: monaural) in ANL was not correlated to that in speech recognition performance, and (2) the pattern of ANL results across conditions (binaural < monaural ANL) was not consistent with the prediction made based on previous binaural loudness summation research (binaural ≥ monaural ANL). The study suggests that listeners may use multiple acoustic features to make ANL judgments. The binaural/monaural results showing that neither hypothesis was supported further indicate that factors other than speech intelligibility and loudness, such as psychological factors, may affect ANL. The weightings of different acoustic features in ANL judgments may vary widely across individuals and listening conditions. American Academy of Audiology.

Strong genetic overlap between executive functions and intelligence.

PubMed

Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M

2016-09-01

Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Yasar, Murat; Tolani, Devendra; Ray, Asok; Shah, Neerav; Litt, Jonathan S.

2004-01-01

This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.

Building a robust vehicle detection and classification module

NASA Astrophysics Data System (ADS)

Grigoryev, Anton; Khanipov, Timur; Koptelov, Ivan; Bocharov, Dmitry; Postnikov, Vassily; Nikolaev, Dmitry

2015-12-01

The growing adoption of intelligent transportation systems (ITS) and autonomous driving requires robust real-time solutions for various event and object detection problems. Most of real-world systems still cannot rely on computer vision algorithms and employ a wide range of costly additional hardware like LIDARs. In this paper we explore engineering challenges encountered in building a highly robust visual vehicle detection and classification module that works under broad range of environmental and road conditions. The resulting technology is competitive to traditional non-visual means of traffic monitoring. The main focus of the paper is on software and hardware architecture, algorithm selection and domain-specific heuristics that help the computer vision system avoid implausible answers.

The design of liquid drip speed monitoring device system based on MCU

NASA Astrophysics Data System (ADS)

Zheng, Shiyong; Li, Zhao; Li, Biqing

2017-08-01

This page proposed an intelligent transfusion control and monitoring system which designed by using AT89S52 micro controller as the core, using the keyboard and photoelectric sensor as the input module, digital tube and motor as the output module. The keyboard is independent and photoelectric sensor can offer reliable detection for liquid drop speed and the transfusion bottle page. When the liquid amount is less than the warning value, the system sounded the alarm, you can remove the alert by hand movement. With the advantages of speed controllable and input pulse power can be maintained of the motor, the system can control the bottle through the upper and lower slow-moving liquid drip to control the speed of intelligent purpose.

Development of an Intelligent Monitoring System for Geological Carbon Sequestration (GCS) Systems

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Jeong, H.; Xu, W.; Hovorka, S. D.; Zhu, T.; Templeton, T.; Arctur, D. K.

2016-12-01

To provide stakeholders timely evidence that GCS repositories are operating safely and efficiently requires integrated monitoring to assess the performance of the storage reservoir as the CO2 plume moves within it. As a result, GCS projects can be data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, and accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. How to correlate anomaly detected by a certain sensor to events observed by other devices to verify leakage incidents? How to optimally allocate resources for task-oriented monitoring if reservoir integrity is in question? These are issues that warrant further investigation before real integration can take place. In this work, we are building a web-based, data integration, assimilation, and learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS will be an intelligent monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in high-throughput database, complex event processing, data assimilation, and machine learning technologies. Results will be demonstrated using realistic data and model derived from a GCS site.

The knowledge-based framework for a nuclear power plant operator advisor

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

Miller, D.W.; Hajek, B.K.

1989-01-01

An important facet in the design, development, and evaluation of aids for complex systems is the identification of the tasks performed by the operator. Operator aids utilizing artificial intelligence, or more specifically knowledge-based systems, require identification of these tasks in the context of a knowledge-based framework. In this context, the operator responses to the plant behavior are to monitor and comprehend the state of the plant, identify normal and abnormal plant conditions, diagnose abnormal plant conditions, predict plant response to specific control actions, and select the best available control action, implement a feasible control action, monitor system response to themore » control action, and correct for any inappropriate responses. These tasks have been identified to formulate a knowledge-based framework for an operator advisor under development at Ohio State University that utilizes the generic task methodology proposed by Chandrasekaran. The paper lays the foundation to identify the responses as a knowledge-based set of tasks in accordance with the expected human operator responses during an event. Initial evaluation of the expert system indicates the potential for an operator aid that will improve the operator's ability to respond to both anticipated and unanticipated events.« less

Classification of Partial Discharge Signals by Combining Adaptive Local Iterative Filtering and Entropy Features

PubMed Central

Morison, Gordon; Boreham, Philip

2018-01-01

Electromagnetic Interference (EMI) is a technique for capturing Partial Discharge (PD) signals in High-Voltage (HV) power plant apparatus. EMI signals can be non-stationary which makes their analysis difficult, particularly for pattern recognition applications. This paper elaborates upon a previously developed software condition-monitoring model for improved EMI events classification based on time-frequency signal decomposition and entropy features. The idea of the proposed method is to map multiple discharge source signals captured by EMI and labelled by experts, including PD, from the time domain to a feature space, which aids in the interpretation of subsequent fault information. Here, instead of using only one permutation entropy measure, a more robust measure, called Dispersion Entropy (DE), is added to the feature vector. Multi-Class Support Vector Machine (MCSVM) methods are utilized for classification of the different discharge sources. Results show an improved classification accuracy compared to previously proposed methods. This yields to a successful development of an expert’s knowledge-based intelligent system. Since this method is demonstrated to be successful with real field data, it brings the benefit of possible real-world application for EMI condition monitoring. PMID:29385030

Is Variability in Mate Choice Similar for Intelligence and Personality Traits? Testing a Hypothesis about the Evolutionary Genetics of Personality

ERIC Educational Resources Information Center

Stone, Emily A.; Shackelford, Todd K.; Buss, David M.

2012-01-01

This study tests the hypothesis presented by Penke, Denissen, and Miller (2007a) that condition-dependent traits, including intelligence, attractiveness, and health, are universally and uniformly preferred as characteristics in a mate relative to traits that are less indicative of condition, including personality traits. We analyzed…

Studies in Intelligence. Volume 58, Number 3 (Unclassified Articles from September 2014)

DTIC Science & Technology

2014-09-01

tics offi cer, presumably responsible for maintaining the quality of the technical data on Japanese radars and radios the unit collected. 11 ...NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11 . SPONSOR/MONITOR’S REPORT NUMBER(S) 12...Intelligence welcomes articles, book reviews, and other communications . Hardcopy material or data discs (preferably in .doc or .rtf formats) may be mailed to

Proceedings of the Air Force Forum for Intelligent Tutoring Systems

DTIC Science & Technology

1989-04-01

interface help the students find facts? I recently developed an expert system that is used at the JFK Airport to help workers assign incoming planes to...of their errors and to make comparisons with optimal solution paths. Chapters 2, and 5 BIP, BIP II: Basic Instructional Program BIP applied knowledge...OFFICE SYMBOL 7a NAME OF MONITORING ORGANIZATION Center for Applied Artificial (If applicable) Training Systems Division Intelligence 1 6. ADDRESS (City

Study of the Military Intelligence Support to Domestic Law Enforcement in Counterdrug and Counterterrorism Operations

DTIC Science & Technology

2012-06-08

havens–Southwest Asia, the Horn of Africa, Southeast Asia, and Latin America . This data is collected in military intelligence databases and accessible to...National Security Agency ONDCP Office of National Drug Control Policy ORA Organization Risk Analyzer REMBASS Remotely Monitored Battlefield...The Crime Drop in America .”4 Law enforcement officials the author talked with stated this is a limitation in that police officers remain reactive to

Military Intelligence Fusion for Complex Operations: A New Paradigm

DTIC Science & Technology

2012-01-01

TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) RAND Corporation,National Defense Research Institute,1776 Main...Street, P.O. Box 2138,Santa Monica,CA,90407-2138 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10...Community under Contract W74V8H-06-C-0002. iii Preface This occasional paper examines how military intelligence organizations and, more broadly, the

FOREWORD: Structural Health Monitoring and Intelligent Infrastructure

NASA Astrophysics Data System (ADS)

Wu, Zhishen; Fujino, Yozo

2005-06-01

This special issue collects together 19 papers that were originally presented at the First International Conference on Structural Health Monitoring and Intelligent Infrastructure (SHMII-1'2003), held in Tokyo, Japan, on 13-15 November 2003. This conference was organized by the Japan Society of Civil Engineers (JSCE) with partial financial support from the Japan Society for the Promotion of Science (JSPS) and the Ministry of Education, Culture, Sport, Science and Technology, Japan. Many related organizations supported the conference. A total of 16 keynote papers including six state-of-the-art reports from different counties, six invited papers and 154 contributed papers were presented at the conference. The conference was attended by a diverse group of about 300 people from a variety of disciplines in academia, industry and government from all over the world. Structural health monitoring (SHM) and intelligent materials, structures and systems have been the subject of intense research and development in the last two decades and, in recent years, an increasing range of applications in infrastructure have been discovered both for existing structures and for new constructions. SHMII-1'2003 addressed progress in the development of building, transportation, marine, underground and energy-generating structures, and other civilian infrastructures that are periodically, continuously and/or actively monitored where there is a need to optimize their performance. In order to focus the current needs on SHM and intelligent technologies, the conference theme was set as 'Structures/Infrastructures Sustainability'. We are pleased to have the privilege to edit this special issue on SHM and intelligent infrastructure based on SHMII-1'2003. We invited some of the presenters to submit a revised/extended version of their paper that was included in the SHMII-1'2003 proceedings for possible publication in the special issue. Each paper included in this special issue was edited with the same quality standards as for any paper in a regular issue. The papers cover a wide spectrum of topics including smart and effective sensing technologies, reliable approaches to signal processing, rational data gathering and interpretation methods, advanced damage characterization, modeling feature selection and diagnosis methods, and system integration technologies, etc. This special issue contains the most up-to-date achievements in SHM and intelligent technologies and provides information pertaining to their current and potential applications in infrastructure. It is our hope that this special issue makes a significant contribution in advancing awareness and acceptance of SHM and intelligent technologies for the maintenance and construction of different kinds of infrastructure. We would like to express our sincere thanks to Professor Varadan (Editor-in-Chief), Professor Matsuzaki (Regional Editor), the Editorial Assistants and the staff at Institute of Physics Publishing for their great support and advice in publishing this special issue. Special thanks are due to all the reviewers for their willingness to share their time and expertise. Final but important thanks go to Ms Suzhen Li (Doctorate Candidate at Ibaraki University) for her assistance in editing this special issue.

High-efficient Unmanned Aircraft System Operations for Ecosystem Assessment

NASA Astrophysics Data System (ADS)

Xu, H.; Zhang, H.

2016-02-01

Diverse national and international agencies support the idea that incorporating Unmanned Aircraft Systems (UAS) into ecosystem assessment will improve the operations efficiency and accuracy. In this paper, a UAS will be designed to monitor the Gulf of Mexico's coastal area ecosystems intelligently and routinely. UAS onboard sensors will capture information that can be utilized to detect and geo-locate areas affected by invasive grasses. Moreover, practical ecosystem will be better assessed by analyzing the collected information. Compared with human-based/satellite-based surveillance, the proposed strategy is more efficient and accurate, and eliminates limitations and risks associated with human factors. State of the art UAS onboard sensors (e.g. high-resolution electro optical camera, night vision camera, thermal sensor etc.) will be used for monitoring coastal ecosystems. Once detected the potential risk in ecosystem, the onboard GPS data will be used to geo-locate and to store the exact coordinates of the affected area. Moreover, the UAS sensors will be used to observe and to record the daily evolution of coastal ecosystems. Further, benefitting from the data collected by the UAS, an intelligent big data processing scheme will be created to assess the ecosystem evolution effectively. Meanwhile, a cost-efficient intelligent autonomous navigation strategy will be implemented into the UAS, in order to guarantee that the UAS can fly over designated areas, and collect significant data in a safe and effective way. Furthermore, the proposed UAS-based ecosystem surveillance and assessment methodologies can be utilized for natural resources conservation. Flying UAS with multiple state of the art sensors will monitor and report the actual state of high importance natural resources frequently. Using the collected data, the ecosystem conservation strategy can be performed effectively and intelligently.

Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

PubMed

Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

2018-08-01

An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in augmenting clinical decision making.

Automation for deep space vehicle monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1991-01-01

Information on automation for deep space vehicle monitoring is given in viewgraph form. Information is given on automation goals and strategy; the Monitor Analyzer of Real-time Voyager Engineering Link (MARVEL); intelligent input data management; decision theory for making tradeoffs; dynamic tradeoff evaluation; evaluation of anomaly detection results; evaluation of data management methods; system level analysis with cooperating expert systems; the distributed architecture of multiple expert systems; and event driven response.

Evolving Intelligence, Surveillance & Reconnaissance (ISR) for Air Force Cyber Defense

DTIC Science & Technology

2013-02-14

Telecommunications and Assessment Program ( TMAP ) notes in Air Force Instruction (AFI) 10-712 that “adversaries can easily monitor (unclassified) systems to...Instruction (AFI) 10-712, Telecommunications Monitoring And Assessment Program ( TMAP ), 2011, 4. 23. Lt Col Hugh M. Ragland., interview with author...Monitoring And Assessment Program ( TMAP ), 8 June 2011. Brenner, Carl N. Col, USAF. NASIC Air & Cyber Analysis Group/CC. Interview by the author. 29

Artificial intelligence in a mission operations and satellite test environment

NASA Technical Reports Server (NTRS)

Busse, Carl

1988-01-01

A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

Real-time prediction of acute cardiovascular events using hardware-implemented Bayesian networks.

PubMed

Tylman, Wojciech; Waszyrowski, Tomasz; Napieralski, Andrzej; Kamiński, Marek; Trafidło, Tamara; Kulesza, Zbigniew; Kotas, Rafał; Marciniak, Paweł; Tomala, Radosław; Wenerski, Maciej

2016-02-01

This paper presents a decision support system that aims to estimate a patient׳s general condition and detect situations which pose an immediate danger to the patient׳s health or life. The use of this system might be especially important in places such as accident and emergency departments or admission wards, where a small medical team has to take care of many patients in various general conditions. Particular stress is laid on cardiovascular and pulmonary conditions, including those leading to sudden cardiac arrest. The proposed system is a stand-alone microprocessor-based device that works in conjunction with a standard vital signs monitor, which provides input signals such as temperature, blood pressure, pulseoxymetry, ECG, and ICG. The signals are preprocessed and analysed by a set of artificial intelligence algorithms, the core of which is based on Bayesian networks. The paper focuses on the construction and evaluation of the Bayesian network, both its structure and numerical specification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intelligent Structured Intermittent Auscultation (ISIA): evaluation of a decision-making framework for fetal heart monitoring of low-risk women

PubMed Central

2014-01-01

Background Research-informed fetal monitoring guidelines recommend intermittent auscultation (IA) for fetal heart monitoring for low-risk women. However, the use of cardiotocography (CTG) continues to dominate many institutional maternity settings. Methods A mixed methods intervention study with before and after measurement was undertaken in one secondary level health service to facilitate the implementation of an initiative to encourage the use of IA. The intervention initiative was a decision-making framework called Intelligent Structured Intermittent Auscultation (ISIA) introduced through an education session. Results Following the intervention, medical records review revealed an increase in the use of IA during labour represented by a relative change of 12%, with improved documentation of clinical findings from assessments, and a significant reduction in the risk of receiving an admission CTG (RR 0.75, 95% CI, 0.60 – 0.95, p = 0.016). Conclusion The ISIA informed decision-making framework transformed the practice of IA and provided a mechanism for knowledge translation that enabled midwives to implement evidence-based fetal heart monitoring for low risk women. PMID:24884597

Chemical-Sensing Cables Detect Potential Threats

NASA Technical Reports Server (NTRS)

2007-01-01

Intelligent Optical Systems Inc. (IOS) completed Phase I and II Small Business Innovation Research (SBIR) contracts with NASA's Langley Research Center to develop moisture- and pH-sensitive sensors to detect corrosion or pre-corrosive conditions, warning of potentially dangerous conditions before significant structural damage occurs. This new type of sensor uses a specially manufactured optical fiber whose entire length is chemically sensitive, changing color in response to contact with its target, and demonstrated to detect potentially corrosive moisture incursions to within 2 cm. After completing the work with NASA, the company received a Defense Advanced Research Projects Agency (DARPA) Phase III SBIR to develop the sensors further for detecting chemical warfare agents, for which they proved just as successful. The company then worked with the U.S. Department of Defense (DoD) to fine tune the sensors for detecting potential threats, such as toxic industrial compounds and nerve agents. In addition to the work with government agencies, Intelligent Optical Systems has sold the chemically sensitive fiber optic cables to major automotive and aerospace companies, who are finding a variety of uses for the devices. Marketed under the brand name Distributed Intrinsic Chemical Agent Sensing and Transmission (DICAST), these unique continuous-cable fiber optic chemical sensors can serve in a variety of applications: Corrosive-condition monitoring, aiding experimentation with nontraditional power sources, as an economical means of detecting chemical release in large facilities, as an inexpensive "alarm" systems to alert the user to a change in the chemical environment anywhere along the cable, or in distance-resolved optical time domain reflectometry systems to provide detailed profiles of chemical concentration versus length.

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

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

El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

Intelligent poly (vinyl alcohol)-chitosan nanoparticles-mulberry extracts films capable of monitoring pH variations.

PubMed

Ma, Qianyun; Liang, Tieqiang; Cao, Lele; Wang, Lijuan

2018-03-01

The aim of this study was to prepare a visually responsive intelligent film based on poly (vinyl alcohol) (PVA), chitosan nanoparticles (CHNPs) and mulberry extracts (MBE). CHNPs were first prepared by using ionotropic gelation method to enhance the mechanical properties of PVA based films. The morphology, particle size, zeta potential and crystallinity of CHNPs were measured. The resultant CHNPs were spherical with a diameter of 381.2nm, with high stability and a zeta potential of 49.1±1.33mV. The film with 6% CHNPs (P-C6) had the highest tensile strength (∼73.43MPa). MBE was incorporated into the P-C6 film. The film containing 20% MBE had the highest tensile strength and showed visible color responses to variations across pH 1-13. The film was tested by monitoring the spoilage of fish. The color of the film changed from red to green as the fish spoiled. Therefore, the pH responsive intelligent film developed here can be used as a package label to detect food spoilage. Copyright © 2017 Elsevier B.V. All rights reserved.

Intelligent instrumentation applied in environment management

NASA Astrophysics Data System (ADS)

Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

2005-06-01

The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

New methods for the condition monitoring of level crossings

NASA Astrophysics Data System (ADS)

García Márquez, Fausto Pedro; Pedregal, Diego J.; Roberts, Clive

2015-04-01

Level crossings represent a high risk for railway systems. This paper demonstrates the potential to improve maintenance management through the use of intelligent condition monitoring coupled with reliability centred maintenance (RCM). RCM combines advanced electronics, control, computing and communication technologies to address the multiple objectives of cost effectiveness, improved quality, reliability and services. RCM collects digital and analogue signals utilising distributed transducers connected to either point-to-point or digital bus communication links. Assets in many industries use data logging capable of providing post-failure diagnostic support, but to date little use has been made of combined qualitative and quantitative fault detection techniques. The research takes the hydraulic railway level crossing barrier (LCB) system as a case study and develops a generic strategy for failure analysis, data acquisition and incipient fault detection. For each barrier the hydraulic characteristics, the motor's current and voltage, hydraulic pressure and the barrier's position are acquired. In order to acquire the data at a central point efficiently, without errors, a distributed single-cable Fieldbus is utilised. This allows the connection of all sensors through the project's proprietary communication nodes to a high-speed bus. The system developed in this paper for the condition monitoring described above detects faults by means of comparing what can be considered a 'normal' or 'expected' shape of a signal with respect to the actual shape observed as new data become available. ARIMA (autoregressive integrated moving average) models were employed for detecting faults. The statistical tests known as Jarque-Bera and Ljung-Box have been considered for testing the model.

Health monitoring and rehabilitation of a concrete structure using intelligent materials

NASA Astrophysics Data System (ADS)

Song, G.; Mo, Y. L.; Otero, K.; Gu, H.

2006-04-01

This paper presents the concept of an intelligent reinforced concrete structure (IRCS) and its application in structural health monitoring and rehabilitation. The IRCS has multiple functions which include self-rehabilitation, self-vibration damping, and self-structural health monitoring. These functions are enabled by two types of intelligent (smart) materials: shape memory alloys (SMAs) and piezoceramics. In this research, Nitinol type SMA and PZT (lead zirconate titanate) type piezoceramics are used. The proposed concrete structure is reinforced by martensite Nitinol cables using the method of post-tensioning. The martensite SMA significantly increases the concrete's damping property and its ability to handle large impact. In the presence of cracks due to explosions or earthquakes, by electrically heating the SMA cables, the SMA cables contract and close up the cracks. In this research, PZT patches are embedded in the concrete structure to detect possible cracks inside the concrete structure. The wavelet packet analysis method is then applied as a signal-processing tool to analyze the sensor signals. A damage index is defined to describe the damage severity for health monitoring purposes. In addition, by monitoring the electric resistance change of the SMA cables, the crack width can be estimated. To demonstrate this concept, a concrete beam specimen with reinforced SMA cables and with embedded PZT patches is fabricated. Experiments demonstrate that the IRC has the ability of self-sensing and self-rehabilitation. Three-point bending tests were conducted. During the loading process, a crack opens up to 0.47 inches. Upon removal of the load and heating the SMA cables, the crack closes up. The damage index formed by wavelet packet analysis of the PZT sensor data predicts and confirms the onset and severity of the crack during the loading. Also during the loading, the electrical resistance value of the SMA cable changes by up to 27% and this phenomenon is used to monitor the crack width.

Impaired conditional reasoning in alcoholics: A negative impact on social interactions and risky behaviors?

PubMed Central

Kornreich, C; Delle-Vigne, D; Knittel, J; Nerincx, A; Campanella, S; Noel, X; Hanak, C; Verbanck, P; Ermer, E

2011-01-01

Aims To study the “social brain” in alcoholics by investigating social contract reasoning, theory of mind, and emotional intelligence. Design A behavioral study comparing recently detoxified alcoholics with normal, healthy controls. Setting Emotional intelligence and decoding of emotional non-verbal cues have been shown to be impaired in alcoholics. This study explores whether these deficits extend to conditional reasoning about social contracts. Participants 25 recently detoxified alcoholics (17 men and 8 women) were compared with 25 normal controls (17 men and 8 women) matched for sex, age, and education level. Measurements Wason Selection Task investigating conditional reasoning on three different rule types (social contract, precautionary, and descriptive), Revised Reading the Mind in the Eyes Test, Trait Emotional Intelligence Questionnaire (modified version), and additional control measures. Findings Conditional reasoning was impaired in alcoholics. Performance on descriptive rules was not above chance. Reasoning performance was markedly better on social contract and precautionary rules, but this performance was still significantly lower than in controls. Several emotional intelligence measures were lower in alcoholics compared to controls, but these were not correlated with reasoning performance. Conclusions Conditional reasoning and emotional intelligence appear impaired in alcoholics. Impairment was particularly severe on descriptive rules. Though alcoholics' performance was better on social contract and precautionary rules, overall reasoning performance was still low. Differential performance is consistent with distinct neurocognitive reasoning mechanisms and partial resilience of evolutionarily-relevant functions. Impairment in social contract reasoning might lead to misunderstandings and frustration in social interactions, and reasoning difficulties about precautionary rules might contribute to risky behaviors in this population. PMID:21205056

What Are Neural Tube Defects?

MedlinePlus

... are born with spina bifida will have normal intelligence, but some will have learning or intellectual disabilities . ... effects, some children with this condition have normal intelligence. 6 Iniencephaly Iniencephaly(pronounced in-ee-ehn-SEF- ...

Relation between spiritual intelligence and clinical competency of nurses in Iran

PubMed Central

Karimi-Moonaghi, Hossein; Gazerani, Akram; Vaghee, Saeed; Gholami, Hassan; Salehmoghaddam, Amir Reza; Gharibnavaz, Raheleh

2015-01-01

Background: Clinical competency is one of the most important requirements in nursing profession, based on which nurses are assessed. To obtain an effective and improved form of clinical competency, several factors are observed and monitored by the health educational systems. Among these observed factors, spiritual intelligence is considered as one of the most significant factors in nurses’ success and efficacy. In this study, it is aimed to determine the spiritual intelligence status and its relationship with clinical competency. Materials and Methods: The descriptive–correlational research was carried out on 250 nurses in Mashhad educational hospitals, selected by multi-stage sampling. Demographic, clinical competency, and spiritual intelligence questionnaires were used for data collection and 212 questionnaires were analyzed. Results: About 53.3% of nurses obtained above average scores in spiritual intelligence. Clinical competency was evaluated by both self-evaluation and head nurse evaluation methods. Most nurses (53.8%) were having good level of clinical competency based on self-evaluation, 48.2% were at average level based on head nurse evaluation, and 53.3% were at average level based on overall score. A significant correlation was found between spiritual intelligence and clinical competency. Conclusions: In this study, the positive significant correlation between nurses’ spiritual intelligence and their clinical competency is investigated. Because of the positive effects of spiritual intelligence on nurses’ clinical competency and quality of care, it is recommended to develop nurses’ spiritual intelligence during their education and by way of continuous medical education. PMID:26793250

Utilization of artificial intelligence techniques for the Space Station power system

NASA Technical Reports Server (NTRS)

Evatt, Thomas C.; Gholdston, Edward W.

1988-01-01

Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

Propulsion health monitoring of a turbine engine disk using spin test data

NASA Astrophysics Data System (ADS)

Abdul-Aziz, Ali; Woike, Mark; Oza, Nikunj; Matthews, Bryan; Baakilini, George

2010-03-01

On line detection techniques to monitor the health of rotating engine components are becoming increasingly attractive options to aircraft engine companies in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenging feature to easily implement, especially, in the presence of scattered loading conditions, crack size, component geometry and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini cracks before any catastrophic event occurs. These techniques go further to evaluate materials' discontinuities and other anomalies that have grown to the level of critical defects which can lead to failure. Generally, health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications. These efforts are focused on developing high temperature, wireless, low cost and durable products. Therefore, in an effort to address the technical issues concerning health monitoring of a rotor disk, this paper considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating engine-like-disk-to predict the disk faults and assess its structural integrity. The experimental results collected at a range of rotational speeds from tests conducted at the NASA Glenn Research Center's Rotordynamics Laboratory will be evaluated using multiple data-driven anomaly detection techniques to identify anomalies in the disk. This study is expected to present a select evaluation of online health monitoring of a rotating disk using these high caliber sensors and test the capability of the in-house spin system.

Brigade Intelligence Operations. Implications for the Nonlinear Battlefield

DTIC Science & Technology

1990-11-21

Intellingence School of Advanced Military Studies United States Army Command and General Staff College Fort Leavenworth2 Kansas~~First Term 90-91 / Approved...has few equipment needs. The section has an M577 staff track and a wheeled vehicle for transportion and communications. It acts as the net control... vehicle for operating on the move or for monitoring the brigade command net. There is no intelligence specific equipment assigned to the S2 section

Exodus - Distributed artificial intelligence for Shuttle firing rooms

NASA Technical Reports Server (NTRS)

Heard, Astrid E.

1990-01-01

This paper describes the Expert System for Operations Distributed Users (EXODUS), a knowledge-based artificial intelligence system developed for the four Firing Rooms at the Kennedy Space Center. EXODUS is used by the Shuttle engineers and test conductors to monitor and control the sequence of tasks required for processing and launching Shuttle vehicles. In this paper, attention is given to the goals and the design of EXODUS, the operational requirements, and the extensibility of the technology.

The Quest for Contact: NASA's Search for Extraterrestrial Intelligence

NASA Technical Reports Server (NTRS)

1992-01-01

This video details the history and current efforts of NASA's Search for Extraterrestrial Intelligence program. The video explains the use of radiotelescopes to monitor electromagnetic frequencies reaching the Earth, and the analysis of this data for patterns or signals that have no natural origin. The video presents an overview of Frank Drake's 1960 'Ozma' experiment, the current META experiment, and planned efforts incorporating an international Deep Space Network of radiotelescopes that will be trained on over 800 stars.

Goal neglect, fluid intelligence and processing speed: Manipulating instruction load and inter-stimulus interval.

PubMed

Iveson, Matthew H; Della Sala, Sergio; Anderson, Mike; MacPherson, Sarah E

2017-05-01

Goal maintenance is the process where task rules and instructions are kept active to exert their control on behavior. When this process fails, an individual may ignore a rule while performing the task, despite being able to describe it after task completion. Previous research has suggested that the goal maintenance system is limited by the number of concurrent rules which can be maintained during a task, and that this limit is dependent on an individual's level of fluid intelligence. However, the speed at which an individual can process information may also limit their ability to use task rules when the task demands them. In the present study, four experiments manipulated the number of instructions to be maintained by younger and older adults and examined whether performance on a rapid letter-monitoring task was predicted by individual differences in fluid intelligence or processing speed. Fluid intelligence played little role in determining how frequently rules were ignored during the task, regardless of the number of rules to be maintained. In contrast, processing speed predicted the rate of goal neglect in older adults, where increasing the presentation rate of the letter-monitoring task increased goal neglect. These findings suggest that goal maintenance may be limited by the speed at which it can operate. Copyright © 2017. Published by Elsevier B.V.

Optimizing acoustical conditions for speech intelligibility in classrooms

NASA Astrophysics Data System (ADS)

Yang, Wonyoung

High speech intelligibility is imperative in classrooms where verbal communication is critical. However, the optimal acoustical conditions to achieve a high degree of speech intelligibility have previously been investigated with inconsistent results, and practical room-acoustical solutions to optimize the acoustical conditions for speech intelligibility have not been developed. This experimental study validated auralization for speech-intelligibility testing, investigated the optimal reverberation for speech intelligibility for both normal and hearing-impaired listeners using more realistic room-acoustical models, and proposed an optimal sound-control design for speech intelligibility based on the findings. The auralization technique was used to perform subjective speech-intelligibility tests. The validation study, comparing auralization results with those of real classroom speech-intelligibility tests, found that if the room to be auralized is not very absorptive or noisy, speech-intelligibility tests using auralization are valid. The speech-intelligibility tests were done in two different auralized sound fields---approximately diffuse and non-diffuse---using the Modified Rhyme Test and both normal and hearing-impaired listeners. A hybrid room-acoustical prediction program was used throughout the work, and it and a 1/8 scale-model classroom were used to evaluate the effects of ceiling barriers and reflectors. For both subject groups, in approximately diffuse sound fields, when the speech source was closer to the listener than the noise source, the optimal reverberation time was zero. When the noise source was closer to the listener than the speech source, the optimal reverberation time was 0.4 s (with another peak at 0.0 s) with relative output power levels of the speech and noise sources SNS = 5 dB, and 0.8 s with SNS = 0 dB. In non-diffuse sound fields, when the noise source was between the speaker and the listener, the optimal reverberation time was 0.6 s with SNS = 4 dB and increased to 0.8 and 1.2 s with decreased SNS = 0 dB, for both normal and hearing-impaired listeners. Hearing-impaired listeners required more early energy than normal-hearing listeners. Reflective ceiling barriers and ceiling reflectors---in particular, parallel front-back rows of semi-circular reflectors---achieved the goal of decreasing reverberation with the least speech-level reduction.

What Are Intellectual and Developmental Disabilities (IDDs)?

MedlinePlus

... characterized by problems with both: Intellectual functioning or intelligence, which include the ability to learn, reason, problem ... cord, and nervous system function, which can affect intelligence and learning. These conditions can also cause other ...

The Impact of Emotional Intelligence on Conditions of Trust among Leaders at the Kentucky Department for Public Health

PubMed Central

Knight, Jennifer Redmond; Bush, Heather M.; Mase, William A.; Riddell, Martha Cornwell; Liu, Meng; Holsinger, James W.

2015-01-01

There has been limited leadership research on emotional intelligence and trust in governmental public health settings. The purpose of this study was to identify and seek to understand the relationship between trust and elements of emotional intelligence, including stress management, at the Kentucky Department for Public Health (KDPH). The KDPH serves as Kentucky’s state governmental health department. KDPH is led by a Commissioner and composed of seven primary divisions and 25 branches within those divisions. The study was a non-randomized cross-sectional study utilizing electronic surveys that evaluated conditions of trust among staff members and emotional intelligence among supervisors. Pearson correlation coefficients and corresponding p-values are presented to provide the association between emotional intelligence scales and the conditions of trust. Significant positive correlations were observed between supervisors’ stress management and the staff members’ trust or perception of supervisors’ loyalty (r = 0.6, p = 0.01), integrity (r = 0.5, p = 0.03), receptivity (r = 0.6, p = 0.02), promise fulfillment (r = 0.6, p = 0.02), and availability (r = 0.5, p = 0.07). This research lays the foundation for emotional intelligence and trust research and leadership training in other governmental public health settings, such as local, other state, national, or international organizations. This original research provides metrics to assess the public health workforce with attention to organizational management and leadership constructs. The survey tools could be used in other governmental public health settings in order to develop tailored training opportunities related to emotional intelligence and trust organizations. PMID:25821778

USDA Foreign Agricultural Service overview for operational monitoring of current crop conditions and production forecasts.

NASA Astrophysics Data System (ADS)

Crutchfield, J.

2016-12-01

The presentation will discuss the current status of the International Production Assessment Division of the USDA ForeignAgricultural Service for operational monitoring and forecasting of current crop conditions, and anticipated productionchanges to produce monthly, multi-source consensus reports on global crop conditions including the use of Earthobservations (EO) from satellite and in situ sources.United States Department of Agriculture (USDA) Foreign Agricultural Service (FAS) International Production AssessmentDivision (IPAD) deals exclusively with global crop production forecasting and agricultural analysis in support of the USDAWorld Agricultural Outlook Board (WAOB) lockup process and contributions to the World Agricultural Supply DemandEstimates (WASE) report. Analysts are responsible for discrete regions or countries and conduct in-depth long-termresearch into national agricultural statistics, farming systems, climatic, environmental, and economic factors affectingcrop production. IPAD analysts become highly valued cross-commodity specialists over time, and are routinely soughtout for specialized analyses to support governmental studies. IPAD is responsible for grain, oilseed, and cotton analysison a global basis. IPAD is unique in the tools it uses to analyze crop conditions around the world, including customweather analysis software and databases, satellite imagery and value-added image interpretation products. It alsoincorporates all traditional agricultural intelligence resources into its forecasting program, to make the fullest use ofavailable information in its operational commodity forecasts and analysis. International travel and training play animportant role in learning about foreign agricultural production systems and in developing analyst knowledge andcapabilities.

Monitoring the health of power transformers

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

Kirtley, J.L. Jr.; Hagman, W.H.; Lesieutre, B.C.

This article reviews MIT`s model-based system which offers adaptive, intelligent surveillance of transformers, and summons attention to anomalous operation through paging devices. Failures of large power transformers are problematic for four reasons. Generally, large transformers are situated so that failures present operational problems to the system. In addition, large power transformers are encased in tanks of flammable and environmentally hazardous fluid. Failures are often accompanied by fire and/or spillage of this fluid. This presents hazards to people, other equipment and property, and the local environment. Finally, large power transformers are costly devices. There is a clear incentive for utilities tomore » keep track of the health of their power transformers. Massachusetts Institute of Technology (MIT) has developed an adaptive, intelligent, monitoring system for large power transformers. Four large transformers on the Boston Edison system are under continuous surveillance by this system, which can summon attention to anomalous operation through paging devices. The monitoring system offers two advantages over more traditional (not adaptive) methods of tracking transformer operation.« less

The smart house for older persons and persons with physical disabilities: structure, technology arrangements, and perspectives.

PubMed

Stefanov, Dimitar H; Bien, Zeungnam; Bang, Won-Chul

2004-06-01

Smart houses are considered a good alternative for the independent life of older persons and persons with disabilities. Numerous intelligent devices, embedded into the home environment, can provide the resident with both movement assistance and 24-h health monitoring. Modern home-installed systems tend to be not only physically versatile in functionality but also emotionally human-friendly, i.e., they may be able to perform their functions without disturbing the user and without causing him/her any pain, inconvenience, or movement restriction, instead possibly providing him/her with comfort and pleasure. Through an extensive survey, this paper analyzes the building blocks of smart houses, with particular attention paid to the health monitoring subsystem as an important component, by addressing the basic requirements of various sensors implemented from both research and clinical perspectives. The paper will then discuss some important issues of the future development of an intelligent residential space with a human-friendly health monitoring functional system.

A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures

PubMed Central

Jeon, Joonryong

2017-01-01

In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size. PMID:28704945

A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures.

PubMed

Heo, Gwanghee; Jeon, Joonryong

2017-07-12

In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size.

Development of intelligent monitoring purifier for indoor PM 2.5

NASA Astrophysics Data System (ADS)

Lou, Guanting; Zhu, Rong; Guo, Jiangwei; Wei, Yongqing

2018-03-01

The particulate matter 2.5 (PM2.5) refers to tiny particles or droplets in the air that are two and one half microns or less in width. PM2.5 is an air pollutant that is a concern for people’s health when levels in air are high. The intelligent monitoring purifier was developed to detect indoor PM2.5 concentration before and after purification and the monitoring data could be displayed on the LCD screen, displaying different color patterns according to the concentrations. Through the Bluetooth transport module, real-time values could also display on the mobile phone and voice broadcast PM2.5 concentration level in the air. When PM2.5 concentration is higher than the setting threshold, the convection fan rotation and the speed can be remote controlled with mobile phone through the Bluetooth transport. Therefore, the efficiency and scope of the purification could be enhanced and further better air quality could be achieved.

An evaluation of an intelligent home monitoring system.

PubMed

Sixsmith, A J

2000-01-01

A trial was performed of an intelligent monitoring system which used sensors in the home to identify emergencies by detecting deviations from normal activity patterns. The field trial lasted three months. Twenty-two elderly people agreed to participate. Their ages ranged from early 60s to over 85, with two-thirds in the age range 75-84 years. They lived in four different localities within the UK--Ipswich, Northumberland, Merseyside and Nottingham. A total of 61 alerts was recorded, at a mean frequency about one alert per month per client. Of the 61 alerts generated, 46 were classified as false alerts and the other 15 as genuine, although no real emergencies occurred during the study. Many people in the field trial reported enhanced feelings of safety and security, which could help to stimulate independence and help them to remain living in their own homes. The monitoring system increased the care choices available to elderly people and supported and enhanced the carer's role.

"SmartMonitor"--an intelligent security system for the protection of individuals and small properties with the possibility of home automation.

PubMed

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-06-05

"SmartMonitor" is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the "SmartMonitor" system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons.

Symbolic Constraint Maintenance Grid

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

Version 3.1 of Symbolic Constraint Maintenance Grid (SCMG) is a software system that provides a general conceptual framework for utilizing pre-existing programming techniques to perform symbolic transformations of data. SCMG also provides a language (and an associated communication method and protocol) for representing constraints on the original non-symbolic data. SCMG provides a facility for exchanging information between numeric and symbolic components without knowing the details of the components themselves. In essence, it integrates symbolic software tools (for diagnosis, prognosis, and planning) with non-artificial-intelligence software. SCMG executes a process of symbolic summarization and monitoring of continuous time series data that are being abstractly represented as symbolic templates of information exchange. This summarization process enables such symbolic- reasoning computing systems as artificial- intelligence planning systems to evaluate the significance and effects of channels of data more efficiently than would otherwise be possible. As a result of the increased efficiency in representation, reasoning software can monitor more channels and is thus able to perform monitoring and control functions more effectively.

Intelligence Community Forum

DTIC Science & Technology

2008-11-05

Description Operationally Feasible? EEG ms ms cm Measures electrical activity in the brain. Practical tool for applications - real time monitoring or...Cognitive Systems Device Development & Processing Methods Brain activity can be monitored in real-time in operational environments with EEG Brain...biological and cognitive findings about the user to customize the learning environment Neurofeedback • Present the user with real-time feedback

Epilepsy monitoring - The patients' views: A qualitative study based on Kolcaba's Comfort Theory.

PubMed

Egger-Rainer, Andrea; Trinka, Eugen; Höfler, Julia; Dieplinger, Anna Maria

2017-03-01

The aim of this qualitative study was to determine which perception of personal comfort patients name in the context of their hospitalization in an Austrian Epilepsy Monitoring Unit (EMU). Problem-centred interviews with twelve inpatients were conducted. Data analyses were done according to Mayring's qualitative content analyses following the technique of structuring-deductive category assignment. Patients experienced different kinds of comfort along with their hospitalization in the EMU. Comfort-decreasing factors were bed rest, boredom, and waiting for possible seizures. As comfort-increasing factors, hope for enhanced seizure control, support by family and staff, and intelligible information about the necessity of restrictive conditions were identified. The study results should assist health care professionals, enabling them to design comfort enhancing interventions for patients undergoing video-electroencephalography (EEG) investigations in an EMU. Some of these seem to be simple and obtainable without high financial or technical effort. Others are more complex and have to be further assessed for their feasibility. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Addressing Control Research Issues Leading to Piloted Simulations in Support of the IFCS F-15

NASA Technical Reports Server (NTRS)

Napolitano, Marcello; Perhinschi, Mario; Campa, Giampiero; Seanor, Brad

2004-01-01

This report summarizes the research effort by a team of researchers at West Virginia University in support of the NASA Intelligent Flight Control System (IFCS) F-15 program. In particular, WVU researchers assisted NASA Dryden researchers in the following technical tasks leading to piloted simulation of the 'Gen_2' IFCS control laws. Task #1- Performance comparison of different neural network (NN) augmentation for the Dynamic Inversion (DI) -based VCAS 'Gen_2' control laws. Task #2- Development of safety monitor criteria for transition to research control laws with and without failure during flight test. Task #3- Fine-tuning of the 'Gen_2' control laws for cross-coupling reduction at post-failure conditions. Matlab/Simulink-based simulation codes were provided to the technical monitor on a regular basis throughout the duration of the project. Additional deliverables for the project were Power Point-based slides prepared for different project meetings. This document provides a description of the methodology and discusses the general conclusions from the simulation results.

Residential area streetlight intelligent monitoring management system based on ZigBee and GPRS

NASA Astrophysics Data System (ADS)

Liang, Guozhuang; Xu, Xiaoyu

2017-05-01

According to current situation of green environmental protection lighting policy and traditional residential lighting system automation degree, low energy efficiency, difficult to management and other problems, the residential area streetlight monitoring management system based on ZigBee and GPRS is proposed. This design is put forward by using sensor technology, ZigBee and GPRS wireless communication technology network. To realize intelligent lighting parameters adjustment, coordination control method of various kinds of sensors is used. The system through multiple ZigBee nodes topology network to collect street light's information, each subnet through the ZigBee coordinator and GPRS network to transmit data. The street lamps can be put on or off, or be adjusted the brightness automatic ally according to the surrounding environmental illumination.

Tuberculosis control, and the where and why of artificial intelligence

PubMed Central

Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

2017-01-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

Tuberculosis control, and the where and why of artificial intelligence.

PubMed

Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

2017-04-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

Pavlovian, Skinner, and Other Behaviourists' Contributions to AI. Chapter 9

NASA Technical Reports Server (NTRS)

Kosinski, Withold; Zaczek-Chrzanowska, Dominika

2007-01-01

A version of the definition of intelligent behaviour will be supplied in the context of real and artificial systems. Short presentation of principles of learning, starting with Pavlovian s classical conditioning through reinforced response and operant conditioning of Thorndike and Skinner and finishing with cognitive learning of Tolman and Bandura will be given. The most important figures within behaviourism, especially those with contribution to AI, will be described. Some tools of artificial intelligence that act according to those principles will be presented. An attempt will be made to show when some simple rules for behaviour modifications can lead to a complex intelligent behaviour.

Performance in noise: Impact of reduced speech intelligibility on Sailor performance in a Navy command and control environment.

PubMed

Keller, M David; Ziriax, John M; Barns, William; Sheffield, Benjamin; Brungart, Douglas; Thomas, Tony; Jaeger, Bobby; Yankaskas, Kurt

2017-06-01

Noise, hearing loss, and electronic signal distortion, which are common problems in military environments, can impair speech intelligibility and thereby jeopardize mission success. The current study investigated the impact that impaired communication has on operational performance in a command and control environment by parametrically degrading speech intelligibility in a simulated shipborne Combat Information Center. Experienced U.S. Navy personnel served as the study participants and were required to monitor information from multiple sources and respond appropriately to communications initiated by investigators playing the roles of other personnel involved in a realistic Naval scenario. In each block of the scenario, an adaptive intelligibility modification system employing automatic gain control was used to adjust the signal-to-noise ratio to achieve one of four speech intelligibility levels on a Modified Rhyme Test: No Loss, 80%, 60%, or 40%. Objective and subjective measures of operational performance suggested that performance systematically degraded with decreasing speech intelligibility, with the largest drop occurring between 80% and 60%. These results confirm the importance of noise reduction, good communication design, and effective hearing conservation programs to maximize the operational effectiveness of military personnel. Published by Elsevier B.V.

The simulation of emergent dispatch of cars for intelligent driving autos

NASA Astrophysics Data System (ADS)

Zheng, Ziao

2018-03-01

It is widely acknowledged that it is important for the development of intelligent cars to be widely accepted by the majority of car users. While most of the intelligent cars have the system of monitoring itself whether it is on the good situation to drive, it is also clear that studies should be performed on the way of cars for the emergent rescue of the intelligent vehicles. In this study, writer focus mainly on how to derive a separate system for the car caring teams to arrive as soon as they get the signal sent out by the intelligent driving autos. This simulation measure the time for the rescuing team to arrive, the cost it spent on arriving on the site of car problem happens, also how long the queue is when the rescuing auto is waiting to cross a road. This can be definitely in great use when there are a team of intelligent cars with one car immediately having problems causing it's not moving and can be helpful in other situations. Through this way, the interconnection of cars can be a safety net for the drivers encountering difficulties in any time.

The comparing analysis of simulation of emergent dispatch of cars for intelligent driving autos in crossroads

NASA Astrophysics Data System (ADS)

Zheng, Ziao

2018-03-01

It is widely acknowledged that it is important for the development of intelligent cars to be widely accepted by the majority of car users. While most of the intelligent cars have the system of monitoring itself whether it is on the good situation to drive, it is also clear that studies should be performed on the way of cars for the emergent rescue of the intelligent vehicles. In this study, writer focus mainly on how to derive a separate system for the car caring teams to arrive as soon as they get the signal sent out by the intelligent driving autos. This simulation measure the time for the rescuing team to arrive, the cost it spent on arriving on the site of car problem happens, also how long the queue is when the rescuing auto is waiting to cross a road. This can be definitely in great use when there are a team of intelligent cars with one car immediately having problems causing its not moving and can be helpful in other situations. Through this way, the interconnection of cars can be a safety net for the drivers encountering difficulties in any time.

Information and redundancy: key concepts in understanding the genetic control of health and intelligence.

PubMed

Morris, J A

1999-08-01

A model is proposed in which information from the environment is analysed by complex biological decision-making systems which are highly redundant. A correct response is intelligent behaviour which preserves health; incorrect responses lead to disease. Mutations in genes which code for the redundant systems will accumulate in the genome and impair decision-making. The number of mutant genes will depend upon a balance between the new mutation rate per generation and systems of elimination based on synergistic interaction in redundant systems. This leads to a polygenic pattern of inheritance for intelligence and the common diseases. The model also gives a simple explanation for some of the hitherto puzzling aspects of work on the genetic basis of intelligence including the recorded rise in IQ this century. There is a prediction that health, intelligence and socio-economic position will be correlated generating a health differential in the social hierarchy. Furthermore, highly competitive societies will place those least able to cope in the harshest environment and this will impair health overall. The model points to a need for population monitoring of somatic mutation in order to preserve the health and intelligence of future generations.

Artificial intelligence applications in the intensive care unit.

PubMed

Hanson, C W; Marshall, B E

2001-02-01

To review the history and current applications of artificial intelligence in the intensive care unit. The MEDLINE database, bibliographies of selected articles, and current texts on the subject. The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. All literature relevant to the topic was reviewed. Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

Chinese speech intelligibility and its relationship with the speech transmission index for children in elementary school classrooms.

PubMed

Peng, Jianxin; Yan, Nanjie; Wang, Dan

2015-01-01

The present study investigated Chinese speech intelligibility in 28 classrooms from nine different elementary schools in Guangzhou, China. The subjective Chinese speech intelligibility in the classrooms was evaluated with children in grades 2, 4, and 6 (7 to 12 years old). Acoustical measurements were also performed in these classrooms. Subjective Chinese speech intelligibility scores and objective speech intelligibility parameters, such as speech transmission index (STI), were obtained at each listening position for all tests. The relationship between subjective Chinese speech intelligibility scores and STI was revealed and analyzed. The effects of age on Chinese speech intelligibility scores were compared. Results indicate high correlations between subjective Chinese speech intelligibility scores and STI for grades 2, 4, and 6 children. Chinese speech intelligibility scores increase with increase of age under the same STI condition. The differences in scores among different age groups decrease as STI increases. To achieve 95% Chinese speech intelligibility scores, the STIs required for grades 2, 4, and 6 children are 0.75, 0.69, and 0.63, respectively.

Design and development of an IoT-based web application for an intelligent remote SCADA system

NASA Astrophysics Data System (ADS)

Kao, Kuang-Chi; Chieng, Wei-Hua; Jeng, Shyr-Long

2018-03-01

This paper presents a design of an intelligent remote electrical power supervisory control and data acquisition (SCADA) system based on the Internet of Things (IoT), with Internet Information Services (IIS) for setting up web servers, an ASP.NET model-view- controller (MVC) for establishing a remote electrical power monitoring and control system by using responsive web design (RWD), and a Microsoft SQL Server as the database. With the web browser connected to the Internet, the sensing data is sent to the client by using the TCP/IP protocol, which supports mobile devices with different screen sizes. The users can provide instructions immediately without being present to check the conditions, which considerably reduces labor and time costs. The developed system incorporates a remote measuring function by using a wireless sensor network and utilizes a visual interface to make the human-machine interface (HMI) more instinctive. Moreover, it contains an analog input/output and a basic digital input/output that can be applied to a motor driver and an inverter for integration with a remote SCADA system based on IoT, and thus achieve efficient power management.

An Expert System For Tuning Particle-Beam Accelerators

NASA Astrophysics Data System (ADS)

Lager, Darrel L.; Brand, Hal R.; Maurer, William J.; Searfus, Robert M.; Hernandez, Jose E.

1989-03-01

We have developed a proof-of-concept prototype of an expert system for tuning particle beam accelerators. It is designed to function as an intelligent assistant for an operator. In its present form it implements the strategies and reasoning followed by the operator for steering through the beam transport section of the Advanced Test Accelerator at Lawrence Livermore Laboratory's Site 300. The system is implemented in the language LISP using the Artificial Intelligence concepts of frames, daemons, and a representation we developed called a Monitored Decision Script.

Multispectral Image Processing for Plants

NASA Technical Reports Server (NTRS)

Miles, Gaines E.

1991-01-01

The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 2, Part B. Discussing, Using, and Recognizing Plans

DTIC Science & Technology

1989-03-01

1978. Williams. B.C. Qualitative Analysis of MOS Circuits. Artificial Inteligence . 1984. 24.. Wilson. K. From Association to Structure. Amsterdam:North...D-A208 378 RADC-TR-88-324, Vol II (of nine), Part B Interim Report March 1969 4. NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1987...II (of nine), Part B 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (ff ’aolicbl

U.S. Intelligence: Compliance with the Intelligence Reform and Terrorism Prevention Act of 2004 and the 9/11 Commission Report Recommendations

DTIC Science & Technology

2006-05-26

pertinent documents. In a Congressional Research Service (CRS) report to Congress dated April 11, 2005 Richard Best, Alfred Cummings and Todd Masse...Members of the 9/11 Commission16 Thomas H. Kean, Chair Lee H. Hamilton, Vice Chair Richard Ben-Veniste Fred F. Fielding Jamie S. Gorelick Slade Gorton Bob...closely monitor worksites. 109 51 Richard L. Skinner, Inspector General of the Department of Homeland Security, provided Congress a comprehensive and

Are We Tracking the Dragon? Ensuring the Intelligence Community is Properly Postured to Monitor an Emerging China

DTIC Science & Technology

2008-03-01

franchise conferred by secrets is at the root of why U.S. intelligence made puzzle solving its principal Cold War business….For the mysteries…information...Enterprises (SOEs). As a corollary, local entrepreneurship has been emphasized. There has also been a growing application of market forces, and the...decentralize the economy and encourage entrepreneurship on the part of local leaders has robbed the center of much of its ability to force environmental

Mobile Monitoring and Embedded Control System for Factory Environment

PubMed Central

Lian, Kuang-Yow; Hsiao, Sung-Jung; Sung, Wen-Tsai

2013-01-01

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones. PMID:24351642

Mobile monitoring and embedded control system for factory environment.

PubMed

Lian, Kuang-Yow; Hsiao, Sung-Jung; Sung, Wen-Tsai

2013-12-17

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.

Distributed intelligent urban environment monitoring system

NASA Astrophysics Data System (ADS)

Du, Jinsong; Wang, Wei; Gao, Jie; Cong, Rigang

2018-02-01

The current environmental pollution and destruction have developed into a world-wide major social problem that threatens human survival and development. Environmental monitoring is the prerequisite and basis of environmental governance, but overall, the current environmental monitoring system is facing a series of problems. Based on the electrochemical sensor, this paper designs a small, low-cost, easy to layout urban environmental quality monitoring terminal, and multi-terminal constitutes a distributed network. The system has been small-scale demonstration applications and has confirmed that the system is suitable for large-scale promotion

State of the Art and Challenges of Radio Spectrum Monitoring in China

NASA Astrophysics Data System (ADS)

Lu, Q. N.; Yang, J. J.; Jin, Z. Y.; Chen, D. Z.; Huang, M.

2017-10-01

This paper provides an overview of radio spectrum monitoring in China. First, research background, the motivation is described and then train of thought, the prototype system, and the accomplishments are presented. Current radio spectrum monitoring systems are man-machine communication systems, which are unable to detect and process the radio interference automatically. In order to realize intelligent radio monitoring and spectrum management, we proposed an Internet of Things-based spectrum sensing approach using information system architecture and implemented a pilot program; then some very interesting results were obtained.

Development of real-time voltage stability monitoring tool for power system transmission network using Synchrophasor data

NASA Astrophysics Data System (ADS)

Pulok, Md Kamrul Hasan

Intelligent and effective monitoring of power system stability in control centers is one of the key issues in smart grid technology to prevent unwanted power system blackouts. Voltage stability analysis is one of the most important requirements for control center operation in smart grid era. With the advent of Phasor Measurement Unit (PMU) or Synchrophasor technology, real time monitoring of voltage stability of power system is now a reality. This work utilizes real-time PMU data to derive a voltage stability index to monitor the voltage stability related contingency situation in power systems. The developed tool uses PMU data to calculate voltage stability index that indicates relative closeness of the instability by producing numerical indices. The IEEE 39 bus, New England power system was modeled and run on a Real-time Digital Simulator that stream PMU data over the Internet using IEEE C37.118 protocol. A Phasor data concentrator (PDC) is setup that receives streaming PMU data and stores them in Microsoft SQL database server. Then the developed voltage stability monitoring (VSM) tool retrieves phasor measurement data from SQL server, performs real-time state estimation of the whole network, calculate voltage stability index, perform real-time ranking of most vulnerable transmission lines, and finally shows all the results in a graphical user interface. All these actions are done in near real-time. Control centers can easily monitor the systems condition by using this tool and can take precautionary actions if needed.

A Personalized Risk Stratification Platform for Population Lifetime Healthcare.

PubMed

Daowd, Ali; Abidi, Samina Raza; Abusharekh, Ashraf; Abidi, Syed Sibte Raza

2018-01-01

Chronic diseases are the leading cause of death worldwide. It is well understood that if modifiable risk factors are targeted, most chronic diseases can be prevented. Lifetime health is an emerging health paradigm that aims to assist individuals to achieve desired health targets, and avoid harmful lifecycle choices to mitigate the risk of chronic diseases. Early risk identification is central to lifetime health. In this paper, we present a digital health-based platform (PRISM) that leverages artificial intelligence, data visualization and mobile health technologies to empower citizens to self-assess, self-monitor and self-manage their overall risk of major chronic diseases and pursue personalized chronic disease prevention programs. PRISM offers risk assessment tools for 5 chronic conditions, 2 psychiatric disorders and 8 different cancers.

Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

NASA Astrophysics Data System (ADS)

Nalamwar, H. S.; Ivanov, M. A.; Baidali, S. A.

2017-01-01

The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the system especially for renewable energy source application such as solar photovoltaic (PV), data-acquisition systems had been used to collect all the data regarding the installed system. In this paper the development of a smart automated monitoring & controlling system for the solar panel is described, the core idea is based on IoT (the Internet of Things). The measurements of data are made using sensors, block management data acquisition modules, and a software system. Then, all the real-time data collection of the electrical output parameters of the PV plant such as voltage, current and generated electricity is displayed and stored in the block management. The proposed system is smart enough to make suggestions if the panel is not working properly, to display errors, to remind about maintenance of the system through email or SMS, and to rotate panels according to a sun position using the Ephemeral table that stored in the system. The advantages of the system are the performance of the solar panel system which can be monitored and analyzed.

Ambient Intelligence Research Landscapes: Introduction and Overview

NASA Astrophysics Data System (ADS)

Streitz, Norbert

This paper starts out by introducing the "Landscapes" category at the Joint International Conference on Ambient Intelligence (AmI-2010) and provides an overview over the two sessions. The main part of the paper presents a framework for the role of Ambient Intelligence in the development of the cities of the future. This includes the integration of real and virtual worlds resulting in Hybrid Cities and their transformation into Smart Cities. In the context, it is argued that the technological development has to be monitored by guidelines and goals for maintaining and improving the quality of life leading to what is called Humane Cities, addressing, e.g., social awareness and privacy, trust and identity. The paper closes with proposals for a future research agenda.

Design for perception management system on offshore reef based on integrated management

NASA Astrophysics Data System (ADS)

Peng, Li; Qiankun, Wang

2017-06-01

According to an analysis of actual monitoring demands using integrated management and information technology, a quad monitoring system is proposed to provide intelligent perception of offshore reefs, including indoor building environments, architectural structures, and facilities and perimeter integrity. This will strengthen the ability to analyse and evaluate offshore reef operation and health, promoting efficiency in decision making.

Organizational Social Effectiveness: An Annotated Bibliography

DTIC Science & Technology

2014-01-01

Results for two new tests . British Journal of Psychology , 101(3), 563-578. Emotional intelligence (EI) has received increasing attention as a...influence. Self-Monitoring Self-monitoring is a concept, related to impression management, that is largely discussed in the social psychology ...was further demonstrated by Phelps , Ramsden Zbylut, and Brunner (2009) in research which examined how the interpersonal skills exhibited by advisors

Multilevel semantic analysis and problem-solving in the flight-domain

NASA Technical Reports Server (NTRS)

Chien, R. T.

1982-01-01

The use of knowledge-base architecture and planning control; mechanisms to perform an intelligent monitoring task in the flight domain is addressed. The route level, the trajectory level, and parts of the aerodynamics level are demonstrated. Hierarchical planning and monitoring conceptual levels, functional-directed mechanism rationalization, and using deep-level mechanism models for diagnoses of dependent failures are discussed.

Transit transparency.

DOT National Transportation Integrated Search

2012-07-01

Public transit agencies have employed intelligent systems for determining : schedules and routes and for monitoring the real-time location and status of their : vehicle fleets for nearly two decades. But until recently, the data generated by : daily ...

Traffic management simulation development : summary.

DOT National Transportation Integrated Search

2011-01-01

Increasingly, Florida traffic is monitored electronically by components of the Intelligent Traffic System (ITS), which send data to regional traffic management centers and assist management of traffic flows and incident response using software called...

Machine intelligence and robotics: Report of the NASA study group. Executive summary

NASA Technical Reports Server (NTRS)

1979-01-01

A brief overview of applications of machine intelligence and robotics in the space program is given. These space exploration robots, global service robots to collect data for public service use on soil conditions, sea states, global crop conditions, weather, geology, disasters, etc., from Earth orbit, space industrialization and processing technologies, and construction of large structures in space. Program options for research, advanced development, and implementation of machine intelligence and robot technology for use in program planning are discussed. A vigorous and long-range program to incorporate and keep pace with state of the art developments in computer technology, both in spaceborne and ground-based computer systems is recommended.

Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing.

PubMed

Jørgensen, Søren; Dau, Torsten

2011-09-01

A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The model estimates the speech-to-noise envelope power ratio, SNR(env), at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech-shaped noise. The model was further tested in conditions with noisy speech subjected to reverberation and spectral subtraction. Good agreement between predictions and data was found in all cases. For spectral subtraction, an analysis of the model's internal representation of the stimuli revealed that the predicted decrease of intelligibility was caused by the estimated noise envelope power exceeding that of the speech. The classical concept of the speech transmission index fails in this condition. The results strongly suggest that the signal-to-noise ratio at the output of a modulation frequency selective process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America

The interaction of acoustic and linguistic grouping cues in auditory object formation

NASA Astrophysics Data System (ADS)

Shapley, Kathy; Carrell, Thomas

2005-09-01

One of the earliest explanations for good speech intelligibility in poor listening situations was context [Miller et al., J. Exp. Psychol. 41 (1951)]. Context presumably allows listeners to group and predict speech appropriately and is known as a top-down listening strategy. Amplitude comodulation is another mechanism that has been shown to improve sentence intelligibility. Amplitude comodulation provides acoustic grouping information without changing the linguistic content of the desired signal [Carrell and Opie, Percept. Psychophys. 52 (1992); Hu and Wang, Proceedings of ICASSP-02 (2002)] and is considered a bottom-up process. The present experiment investigated how amplitude comodulation and semantic information combined to improve speech intelligibility. Sentences with high- and low-predictability word sequences [Boothroyd and Nittrouer, J. Acoust. Soc. Am. 84 (1988)] were constructed in two different formats: time-varying sinusoidal sentences (TVS) and reduced-channel sentences (RC). The stimuli were chosen because they minimally represent the traditionally defined speech cues and therefore emphasized the importance of the high-level context effects and low-level acoustic grouping cues. Results indicated that semantic information did not influence intelligibility levels of TVS and RC sentences. In addition amplitude modulation aided listeners' intelligibility scores in the TVS condition but hindered listeners' intelligibility scores in the RC condition.

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

NASA Astrophysics Data System (ADS)

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

2017-12-01

Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

New hydrologic instrumentation in the U.S. Geological Survey

USGS Publications Warehouse

Latkovich, V.J.; Shope, W.G.; ,

1991-01-01

New water-level sensing and recording instrumentation is being used by the U.S. Geological Survey for monitoring water levels, stream velocities, and water-quality characteristics. Several of these instruments are briefly described. The Basic Data Recorder (BDR) is an electronic data logger, that interfaces to sensor systems through a serial-digital interface standard (SDI-12), which was proposed by the data-logger industry; the Incremental Shaft Encoder is an intelligent water-level sensor, which interfaces to the BDR through the SDI-12; the Pressure Sensor is an intelligent, nonsubmersible pressure sensor, which interfaces to the BDR through the SDI-12 and monitors water levels from 0 to 50 feet; the Ultrasonic Velocity Meter is an intelligent, water-velocity sensor, which interfaces to the BDR through the SDI-12 and measures the velocity across a stream up to 500 feet in width; the Collapsible Hand Sampler can be collapsed for insertion through holes in the ice and opened under the ice to collect a water sample; the Lighweight Ice Auger, weighing only 32 pounds, can auger 6- and 8-inch holes through approximately 3.5 feet of ice; and the Ice Chisel has a specially hardened steel blade and 6-foot long, hickory D-handle.

Evaluation of an artificial intelligence program for estimating occupational exposures.

PubMed

Johnston, Karen L; Phillips, Margaret L; Esmen, Nurtan A; Hall, Thomas A

2005-03-01

Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals--a common solvent (toluene) and a specialty monomer (chloroprene)--present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary exposure assessment if it is recognized that the actual interquartile range could be much wider and/or offset by a factor of 10 or more.

Improving Information Exchange and Coordination amongst Homeland Security Organizations (Briefing Charts)

DTIC Science & Technology

2005-06-01

need for user-defined dashboard • automated monitoring of web data sources • task driven data aggregation and display Working toward automated processing of task, resource, and intelligence updates

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

NASA Technical Reports Server (NTRS)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

Monitor for detecting and assessing exposure to airborne nanoparticles

NASA Astrophysics Data System (ADS)

Marra, Johan; Voetz, Matthias; Kiesling, Heinz-Jürgen

2010-01-01

An important safety aspect of the workplace environment concerns the severity of its air pollution with nanoparticles (NP; <100 nm) and ultrafine particles (UFP; <300 nm). Depending on their size and chemical nature, exposure to these particles through inhalation can be hazardous because of their intrinsic ability to deposit in the deep lung regions and the possibility to subsequently pass into the blood stream. Recommended safety measures in the nanomaterials industry are pragmatic, aiming at exposure minimization in general, and advocating continuous control by monitoring both the workplace air pollution level and the personal exposure to airborne NPs. This article describes the design and operation of the Aerasense NP monitor that enables intelligence gathering in particular with respect to airborne particles in the 10-300 nm size range. The NP monitor provides real time information about their number concentration, average size, and surface areas per unit volume of inhaled air that deposit in the various compartments of the respiratory tract. The monitor's functionality relies on electrical charging of airborne particles and subsequent measurements of the total particle charge concentration under various conditions. Information obtained with the NP monitor in a typical workplace environment has been compared with simultaneously recorded data from a Scanning Mobility Particle Sizer (SMPS) capable of measuring the particle size distribution in the 11-1086 nm size range. When the toxicological properties of the engineered and/or released particles in the workplace are known, personal exposure monitoring allows a risk assessment to be made for a worker during each workday, when the workplace-produced particles can be distinguished from other (ambient) particles.

Ambient Intelligence in a Smart Home for Energy Efficiency and Eldercare

NASA Astrophysics Data System (ADS)

de Silva, Liyanage C.; Petra, M. Iskandar; Punchihewa, G. Amal

In this paper we present our research results related to smart monitoring, control and communication with the main objective of energy efficiency and eldercare in mind. One of the main objectives of this research work is to use multitude of different sensors to monitor activities in a smart home and use the results to control the home environment to meet the objectives of energy efficiency and eldercare. Here we present the application of the smart monitoring to a prototype system.

Combining real-time monitoring and knowledge-based analysis in MARVEL

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Quan, A. G.; Angelino, R.; Veregge, J. R.

1993-01-01

Real-time artificial intelligence is gaining increasing attention for applications in which conventional software methods are unable to meet technology needs. One such application area is the monitoring and analysis of complex systems. MARVEL, a distributed monitoring and analysis tool with multiple expert systems, was developed and successfully applied to the automation of interplanetary spacecraft operations at NASA's Jet Propulsion Laboratory. MARVEL implementation and verification approaches, the MARVEL architecture, and the specific benefits that were realized by using MARVEL in operations are described.

Overview of condition monitoring and operation control of electric power conversion systems in direct-drive wind turbines under faults

NASA Astrophysics Data System (ADS)

Huang, Shoudao; Wu, Xuan; Liu, Xiao; Gao, Jian; He, Yunze

2017-09-01

Electric power conversion system (EPCS), which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine (DD-WT). However, this component accounts for the most failures (approximately 60% of the total number) in the entire DD-WT system according to statistical data. To improve the reliability of EPCSs and reduce the operation and maintenance cost of DD-WTs, numerous researchers have studied condition monitoring (CM) and fault diagnostics (FD). Numerous CM and FD techniques, which have respective advantages and disadvantages, have emerged. This paper provides an overview of the CM, FD, and operation control of EPCSs in DD-WTs under faults. After introducing the functional principle and structure of EPCS, this survey discusses the common failures in wind generators and power converters; briefly reviewed CM and FD methods and operation control of these generators and power converters under faults; and discussed the grid voltage faults related to EPCSs in DD-WTs. These theories and their related technical concepts are systematically discussed. Finally, predicted development trends are presented. The paper provides a valuable reference for developing service quality evaluation methods and fault operation control systems to achieve high-performance and high-intelligence DD-WTs.

Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

2013-03-01

The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

Intelligibility of Clear Speech: Effect of Instruction

ERIC Educational Resources Information Center

Lam, Jennifer; Tjaden, Kris

2013-01-01

Purpose: The authors investigated how clear speech instructions influence sentence intelligibility. Method: Twelve speakers produced sentences in habitual, clear, hearing impaired, and overenunciate conditions. Stimuli were amplitude normalized and mixed with multitalker babble for orthographic transcription by 40 listeners. The main analysis…

Intelligence in youth and health at age 50

PubMed Central

Wraw, Christina; Deary, Ian J.; Gale, Catharine R.; Der, Geoff

2015-01-01

Background The link between intelligence in youth and all-cause mortality in later-life is well established. To better understand this relationship, the current study examines the links between pre-morbid intelligence and a number of specific health outcomes at age 50 using the NLSY-1979 cohort. Methods Participants were the 5793 participants in the NLSY-79 who responded to questions about health outcomes at age 50. Sixteen health outcomes were examined: two were summary measures (physical health and functional limitation), 9 were diagnosed illness conditions, 4 were self-reported conditions, and one was a measure of general health status. Linear and logistic regressions were used, as appropriate, to examine the relationship between intelligence in youth and the health outcomes. Age, sex and both childhood and adult SES, and its sub-components – income, education, & occupational prestige – are all adjusted for separately. Results & conclusion Higher pre-morbid intelligence is linked with better physical health at age 50, and a lower risk for a number of chronic health conditions. For example, a 1 SD higher score in IQ was significantly associated with increased odds of having good, very good, or excellent health, with an odds ratio of 1.70 (C.I. 1.55–1.86). Thirteen of the illness outcomes were significantly and negatively associated with IQ in youth; the odds ratios ranged from 0.85 for diabetes/high blood sugar to 0.65 for stroke, per one standard deviation higher score in IQ. Adjustment for childhood SES led to little attenuation but adult SES partially mediated the relationship for a number of conditions. Mediation by adult SES was not consistently explained by any one of its components—income, education, and occupation status. The current findings contribute to our understanding of lower intelligence as a risk factor for poor health and how this may contribute to health inequalities. PMID:26766880

SCAILET: An intelligent assistant for satellite ground terminal operations

NASA Technical Reports Server (NTRS)

Shahidi, A. K.; Crapo, J. A.; Schlegelmilch, R. F.; Reinhart, R. C.; Petrik, E. J.; Walters, J. L.; Jones, R. E.

1993-01-01

NASA Lewis Research Center has applied artificial intelligence to an advanced ground terminal. This software application is being deployed as an experimenter interface to the link evaluation terminal (LET) and was named Space Communication Artificial Intelligence for the Link Evaluation Terminal (SCAILET). The high-burst-rate (HBR) LET provides 30-GHz-transmitting and 20-GHz-receiving, 220-Mbps capability for wide band communications technology experiments with the Advanced Communication Technology Satellite (ACTS). The HBR-LET terminal consists of seven major subsystems. A minicomputer controls and monitors these subsystems through an IEEE-488 or RS-232 protocol interface. Programming scripts (test procedures defined by design engineers) configure the HBR-LET and permit data acquisition. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. This discourages experimenters from utilizing the full capabilities of the HBR-LET system. An intelligent assistant module was developed as part of the SCAILET software. The intelligent assistant addresses critical experimenter needs by solving and resolving problems that are encountered during the configuring of the HBR-LET system. The intelligent assistant is a graphical user interface with an expert system running in the background. In order to further assist and familiarize an experimenter, an on-line hypertext documentation module was developed and included in the SCAILET software.

Appearance-based multimodal human tracking and identification for healthcare in the digital home.

PubMed

Yang, Mau-Tsuen; Huang, Shen-Yen

2014-08-05

There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare.

Audiomotor Perceptual Training Enhances Speech Intelligibility in Background Noise.

PubMed

Whitton, Jonathon P; Hancock, Kenneth E; Shannon, Jeffrey M; Polley, Daniel B

2017-11-06

Sensory and motor skills can be improved with training, but learning is often restricted to practice stimuli. As an exception, training on closed-loop (CL) sensorimotor interfaces, such as action video games and musical instruments, can impart a broad spectrum of perceptual benefits. Here we ask whether computerized CL auditory training can enhance speech understanding in levels of background noise that approximate a crowded restaurant. Elderly hearing-impaired subjects trained for 8 weeks on a CL game that, like a musical instrument, challenged them to monitor subtle deviations between predicted and actual auditory feedback as they moved their fingertip through a virtual soundscape. We performed our study as a randomized, double-blind, placebo-controlled trial by training other subjects in an auditory working-memory (WM) task. Subjects in both groups improved at their respective auditory tasks and reported comparable expectations for improved speech processing, thereby controlling for placebo effects. Whereas speech intelligibility was unchanged after WM training, subjects in the CL training group could correctly identify 25% more words in spoken sentences or digit sequences presented in high levels of background noise. Numerically, CL audiomotor training provided more than three times the benefit of our subjects' hearing aids for speech processing in noisy listening conditions. Gains in speech intelligibility could be predicted from gameplay accuracy and baseline inhibitory control. However, benefits did not persist in the absence of continuing practice. These studies employ stringent clinical standards to demonstrate that perceptual learning on a computerized audio game can transfer to "real-world" communication challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home

PubMed Central

Yang, Mau-Tsuen; Huang, Shen-Yen

2014-01-01

There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare. PMID:25098207

In-Situ MVA of CO 2 Sequestration Using Smart Field Technology

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

Mohaghegh, Shahab D.

2014-09-01

Capability of underground carbon dioxide storage to confine and sustain injected CO 2 for a long period of time is the main concern for geologic CO 2 sequestration. If a leakage from a geological CO 2 sequestration site occurs, it is crucial to find the approximate amount and the location of the leak, in a timely manner, in order to implement proper remediation activities. An overwhelming majority of research and development for storage site monitoring has been concentrated on atmospheric, surface or near surface monitoring of the sequestered CO 2 . This study aims to monitor themore » integrity of CO 2 storage at the reservoir level. This work proposes developing in-situ CO 2 Monitoring and Verification technology based on the implementation of Permanent Down-hole Gauges (PDG) or “Smart Wells” along with Artificial Intelligence and Data Mining (AI&DM). The technology attempts to identify the characteristics of the CO 2 leakage by de-convolving the pressure signals collected from Permanent Down-hole Gauges (PDG). Citronelle field, a saline aquifer reservoir, located in the U.S. was considered as the basis for this study. A reservoir simulation model for CO 2 sequestration in the Citronelle field was developed and history matched. PDGs were installed, and therefore were considered in the numerical model, at the injection well and an observation well. Upon completion of the history matching process, high frequency pressure data from PDGs were generated using the history matched numerical model using different CO 2 leakage scenarios. Since pressure signal behaviors were too complicated to de-convolute using any existing mathematical formulations, a Machine Learning-based technology was introduced for this purpose. An Intelligent Leakage Detection System (ILDS) was developed as the result of this effort using the machine learning and pattern recognition technologies. The ILDS is able to detect leakage characteristics in a short period of time (less than a day from its occurrence) demonstrating the capability of the system in quantifying leakage characteristics subject to complex rate behaviors. The performance of ILDS is examined under different conditions such as multiple well leakages, cap rock leakage, availability of an additional monitoring well, presence of pressure drift and noise in the pressure sensor and uncertainty in the reservoir model.« less

Information Assurance Technology Analysis Center Information Assurance Tools Report Intrusion Detection

DTIC Science & Technology

1998-01-01

such as central processing unit (CPU) usage, disk input/output (I/O), memory usage, user activity, and number of logins attempted. The statistics... EMERALD Commercial anomaly detection, system monitoring SRI porras@csl.sri.com www.csl.sri.com/ emerald /index. html Gabriel Commercial system...sensors, it starts to protect the network with minimal configuration and maximum intelligence. T 11 EMERALD TITLE EMERALD (Event Monitoring

A Deep Denoising Autoencoder Approach to Improving the Intelligibility of Vocoded Speech in Cochlear Implant Simulation.

PubMed

Lai, Ying-Hui; Chen, Fei; Wang, Syu-Siang; Lu, Xugang; Tsao, Yu; Lee, Chin-Hui

2017-07-01

In a cochlear implant (CI) speech processor, noise reduction (NR) is a critical component for enabling CI users to attain improved speech perception under noisy conditions. Identifying an effective NR approach has long been a key topic in CI research. Recently, a deep denoising autoencoder (DDAE) based NR approach was proposed and shown to be effective in restoring clean speech from noisy observations. It was also shown that DDAE could provide better performance than several existing NR methods in standardized objective evaluations. Following this success with normal speech, this paper further investigated the performance of DDAE-based NR to improve the intelligibility of envelope-based vocoded speech, which simulates speech signal processing in existing CI devices. We compared the performance of speech intelligibility between DDAE-based NR and conventional single-microphone NR approaches using the noise vocoder simulation. The results of both objective evaluations and listening test showed that, under the conditions of nonstationary noise distortion, DDAE-based NR yielded higher intelligibility scores than conventional NR approaches. This study confirmed that DDAE-based NR could potentially be integrated into a CI processor to provide more benefits to CI users under noisy conditions.

Accent, intelligibility, and comprehensibility in the perception of foreign-accented Lombard speech

NASA Astrophysics Data System (ADS)

Li, Chi-Nin

2003-10-01

Speech produced in noise (Lombard speech) has been reported to be more intelligible than speech produced in quiet (normal speech). This study examined the perception of non-native Lombard speech in terms of intelligibility, comprehensibility, and degree of foreign accent. Twelve Cantonese speakers and a comparison group of English speakers read simple true and false English statements in quiet and in 70 dB of masking noise. Lombard and normal utterances were mixed with noise at a constant signal-to-noise ratio, and presented along with noise-free stimuli to eight new English listeners who provided transcription scores, comprehensibility ratings, and accent ratings. Analyses showed that, as expected, utterances presented in noise were less well perceived than were noise-free sentences, and that the Cantonese speakers' productions were more accented, but less intelligible and less comprehensible than those of the English speakers. For both groups of speakers, the Lombard sentences were correctly transcribed more often than their normal utterances in noisy conditions. However, the Cantonese-accented Lombard sentences were not rated as easier to understand than was the normal speech in all conditions. The assigned accent ratings were similar throughout all listening conditions. Implications of these findings will be discussed.

Intelligibility of foreign-accented speech: Effects of listening condition, listener age, and listener hearing status

NASA Astrophysics Data System (ADS)

Ferguson, Sarah Hargus

2005-09-01

It is well known that, for listeners with normal hearing, speech produced by non-native speakers of the listener's first language is less intelligible than speech produced by native speakers. Intelligibility is well correlated with listener's ratings of talker comprehensibility and accentedness, which have been shown to be related to several talker factors, including age of second language acquisition and level of similarity between the talker's native and second language phoneme inventories. Relatively few studies have focused on factors extrinsic to the talker. The current project explored the effects of listener and environmental factors on the intelligibility of foreign-accented speech. Specifically, monosyllabic English words previously recorded from two talkers, one a native speaker of American English and the other a native speaker of Spanish, were presented to three groups of listeners (young listeners with normal hearing, elderly listeners with normal hearing, and elderly listeners with hearing impairment; n=20 each) in three different listening conditions (undistorted words in quiet, undistorted words in 12-talker babble, and filtered words in quiet). Data analysis will focus on interactions between talker accent, listener age, listener hearing status, and listening condition. [Project supported by American Speech-Language-Hearing Association AARC Award.

ITS data quality : assessment procedure for freeway point detectors.

DOT National Transportation Integrated Search

2003-01-01

The Virginia Department of Transportation (VDOT) has made significant investments in the traffic-monitoring infrastructure that supports intelligent transportation systems (ITS). The purpose of this infrastructure is to provide accurate, real-time in...

Artificial intelligence: a new approach for prescription and monitoring of hemodialysis therapy.

PubMed

Akl, A I; Sobh, M A; Enab, Y M; Tattersall, J

2001-12-01

The effect of dialysis on patients is conventionally predicted using a formal mathematical model. This approach requires many assumptions of the processes involved, and validation of these may be difficult. The validity of dialysis urea modeling using a formal mathematical model has been challenged. Artificial intelligence using neural networks (NNs) has been used to solve complex problems without needing a mathematical model or an understanding of the mechanisms involved. In this study, we applied an NN model to study and predict concentrations of urea during a hemodialysis session. We measured blood concentrations of urea, patient weight, and total urea removal by direct dialysate quantification (DDQ) at 30-minute intervals during the session (in 15 chronic hemodialysis patients). The NN model was trained to recognize the evolution of measured urea concentrations and was subsequently able to predict hemodialysis session time needed to reach a target solute removal index (SRI) in patients not previously studied by the NN model (in another 15 chronic hemodialysis patients). Comparing results of the NN model with the DDQ model, the prediction error was 10.9%, with a not significant difference between predicted total urea nitrogen (UN) removal and measured UN removal by DDQ. NN model predictions of time showed a not significant difference with actual intervals needed to reach the same SRI level at the same patient conditions, except for the prediction of SRI at the first 30-minute interval, which showed a significant difference (P = 0.001). This indicates the sensitivity of the NN model to what is called patient clearance time; the prediction error was 8.3%. From our results, we conclude that artificial intelligence applications in urea kinetics can give an idea of intradialysis profiling according to individual clinical needs. In theory, this approach can be extended easily to other solutes, making the NN model a step forward to achieving artificial-intelligent dialysis control.

Using Multiple Intelligences to Bridge the Educational Poverty Gap

ERIC Educational Resources Information Center

Goebel, Kym

2009-01-01

Students living in poverty have needs that are not being addressed in traditional classrooms. Students from "generational poverty" process information differently (Payne 1996). Information is processed based on their living conditions and upbringing. Differentiating instruction using Howard Gardener's Multiple Intelligence theory…

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

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

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

A wireless fatigue monitoring system utilizing a bio-inspired tree ring data tracking technique.

PubMed

Bai, Shi; Li, Xuan; Xie, Zhaohui; Zhou, Zhi; Ou, Jinping

2014-03-05

Fatigue, a hot scientific research topic for centuries, can trigger sudden failure of critical structures such as aircraft and railway systems, resulting in enormous casualties as well as economic losses. The fatigue life of certain structures is intrinsically random and few monitoring techniques are capable of tracking the full life-cycle fatigue damage. In this paper, a novel in-situ wireless real-time fatigue monitoring system using a bio-inspired tree ring data tracking technique is proposed. The general framework, methodology, and verification of this intelligent system are discussed in details. The rain-flow counting (RFC) method is adopted as the core algorithm which quantifies fatigue damages, and Digital Signal Processing (DSP) is introduced as the core module for data collection and analysis. Laboratory test results based on strain gauges and polyvinylidene fluoride (PVDF) sensors have shown that the developed intelligent system can provide a reliable quick feedback and early warning of fatigue failure. With the merits of low cost, high accuracy and great reliability, the developed wireless fatigue sensing system can be further applied to mechanical engineering, civil infrastructures, transportation systems, aerospace engineering, etc.

An intelligent monitoring and management system for cross-enterprise biomedical data sharing platform

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Jianguo

2013-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai by using grid-based or cloud-based distributed architecture and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. However, when the platform integrates more and more nodes over different networks, the first challenge is that how to monitor and maintain all the hosts and services operating cross multiple academic institutions and hospitals in the e-Science platform, such as DICOM and Web based image communication services, messaging services and XDS ITI transaction services. In this presentation, we presented a system design and implementation of intelligent monitoring and management which can collect system resource status of every node in real time, alert when node or service failure occurs, and can finally improve the robustness, reliability and service continuity of this e-Science platform.

SHARP: A multi-mission AI system for spacecraft telemetry monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Lawson, Denise L.; James, Mark L.

1989-01-01

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

[Chinese medicine industry 4.0：advancing digital pharmaceutical manufacture toward intelligent pharmaceutical manufacture].

PubMed

Cheng, Yi-Yu; Qu, Hai-Bin; Zhang, Bo-Li

2016-01-01

A perspective analysis on the technological innovation in pharmaceutical engineering of Chinese medicine unveils a vision on "Future Factory" of Chinese medicine industry in mind. The strategy as well as the technical roadmap of "Chinese medicine industry 4.0" is proposed, with the projection of related core technology system. It is clarified that the technical development path of Chinese medicine industry from digital manufacture to intelligent manufacture. On the basis of precisely defining technical terms such as process control, on-line detection and process quality monitoring for Chinese medicine manufacture, the technical concepts and characteristics of intelligent pharmaceutical manufacture as well as digital pharmaceutical manufacture are elaborated. Promoting wide applications of digital manufacturing technology of Chinese medicine is strongly recommended. Through completely informationized manufacturing processes and multi-discipline cluster innovation, intelligent manufacturing technology of Chinese medicine should be developed, which would provide a new driving force for Chinese medicine industry in technology upgrade, product quality enhancement and efficiency improvement. Copyright© by the Chinese Pharmaceutical Association.

A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard.

PubMed

Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

2015-08-01

management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process.

Proceedings from the ETS and ARI Emotional Intelligence Workshop held in Princeton, New Jersey on November 13-15, 2003. Volume 1. Sessions 1 and 2

DTIC Science & Technology

2003-11-01

cultural influences” describes its subject or informants as students at a particular university, or nationals of a particular country, this is the...companion. This is an NSF project in my lab where the companion would be not so much an intelligent tutor, but at the peer level of the student ...assisting the student by helping to monitor their affect, watching especially for states such as boredom or interest, and for signs of enjoyment. You might

Intelligent Traffic Quantification System

NASA Astrophysics Data System (ADS)

Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta

2017-08-01

Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.

Low cost composite manufacturing utilizing intelligent pultrusion and resin transfer molding (IPRTM)

NASA Astrophysics Data System (ADS)

Bradley, James E.; Wysocki, Tadeusz S., Jr.

1993-02-01

This article describes an innovative method for the economical manufacturing of large, intricately-shaped tubular composite parts. Proprietary intelligent process control techniques are combined with standard pultrusion and RTM methodologies to provide high part throughput, performance, and quality while substantially reducing scrap, rework costs, and labor requirements. On-line process monitoring and control is achieved through a smart tooling interface consisting of modular zone tiles installed on part-specific die assemblies. Real-time archiving of process run parameters provides enhanced SPC and SQC capabilities.

Application of semi-active RFID power meter in automatic verification pipeline and intelligent storage system

NASA Astrophysics Data System (ADS)

Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng

2018-03-01

In this paper, the semi-active RFID watt-hour meter is applied to automatic test lines and intelligent warehouse management, from the transmission system, test system and auxiliary system, monitoring system, realize the scheduling of watt-hour meter, binding, control and data exchange, and other functions, make its more accurate positioning, high efficiency of management, update the data quickly, all the information at a glance. Effectively improve the quality, efficiency and automation of verification, and realize more efficient data management and warehouse management.

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.

Intelligent approach for analysis of respiratory signals and oxygen saturation in the sleep apnea/hypopnea syndrome.

PubMed

Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

2014-01-01

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints.

An intelligent tutoring system for space shuttle diagnosis

NASA Technical Reports Server (NTRS)

Johnson, William B.; Norton, Jeffrey E.; Duncan, Phillip C.

1988-01-01

An Intelligent Tutoring System (ITS) transcends conventional computer-based instruction. An ITS is capable of monitoring and understanding student performance thereby providing feedback, explanation, and remediation. This is accomplished by including models of the student, the instructor, and the expert technician or operator in the domain of interest. The space shuttle fuel cell is the technical domain for the project described below. One system, Microcomputer Intelligence for Technical Training (MITT), demonstrates that ITS's can be developed and delivered, with a reasonable amount of effort and in a short period of time, on a microcomputer. The MITT system capitalizes on the diagnostic training approach called Framework for Aiding the Understanding of Logical Troubleshooting (FAULT) (Johnson, 1987). The system's embedded procedural expert was developed with NASA's C-Language Integrated Production (CLIP) expert system shell (Cubert, 1987).

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

Innovative applications of artificial intelligence

NASA Astrophysics Data System (ADS)

Schorr, Herbert; Rappaport, Alain

Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

Intelligent Approach for Analysis of Respiratory Signals and Oxygen Saturation in the Sleep Apnea/Hypopnea Syndrome

PubMed Central

Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

2014-01-01

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712

The Benefits of Bimodal Aiding on Extended Dimensions of Speech Perception: Intelligibility, Listening Effort, and Sound Quality

PubMed Central

Chalupper, Josef

2017-01-01

The benefits of combining a cochlear implant (CI) and a hearing aid (HA) in opposite ears on speech perception were examined in 15 adult unilateral CI recipients who regularly use a contralateral HA. A within-subjects design was carried out to assess speech intelligibility testing, listening effort ratings, and a sound quality questionnaire for the conditions CI alone, CIHA together, and HA alone when applicable. The primary outcome of bimodal benefit, defined as the difference between CIHA and CI, was statistically significant for speech intelligibility in quiet as well as for intelligibility in noise across tested spatial conditions. A reduction in effort on top of intelligibility at the highest tested signal-to-noise ratio was found. Moreover, the bimodal listening situation was rated to sound more voluminous, less tinny, and less unpleasant than CI alone. Listening effort and sound quality emerged as feasible and relevant measures to demonstrate bimodal benefit across a clinically representative range of bimodal users. These extended dimensions of speech perception can shed more light on the array of benefits provided by complementing a CI with a contralateral HA. PMID:28874096

Development of Wireless Subsurface Microsensors for Health Monitoring of Thermal Protection Systems

NASA Technical Reports Server (NTRS)

Pallix, Joan; Milos, Frank; Arnold, James O. (Technical Monitor)

2000-01-01

Low cost access to space is a primary goal for both NASA and the U.S. aerospace industry. Integrated subsystem health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles (RLVS) in order to reduce life cycle costs, increase safety margins and improve mission reliability. A number of efforts are underway to use existing and emerging technologies to establish new methods for vehicle health monitoring on operational vehicles as well as X-vehicles. This paper summarizes a joint effort between several NASA centers and industry partners to develop rapid wireless diagnostic tools for failure management and long-term TPS performance monitoring of thermal protection systems (TPS) on future RLVS. An embedded wireless microsensor suite is being designed to allow rapid subsurface TPS health monitoring and damage assessment. This sensor suite will consist of both passive overlimit sensors and sensors for continuous parameter monitoring in flight. The on-board diagnostic system can be used to radio in maintenance requirements before landing and the data could also be used to assist in design validation for X-vehicles. For a 3rd generation vehicle, wireless diagnostics should be at a stage of technical development that will allow use for intelligent feedback systems for guidance and navigation control applications and can also serve as feedback for TPS that can intelligently adapt to its environment.

Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

PubMed

Ashrafian, Hutan

2017-04-01

The potential for artificial intelligences and robotics in achieving the capacity of consciousness, sentience and rationality offers the prospect that these agents have minds. If so, then there may be a potential for these minds to become dysfunctional, or for artificial intelligences and robots to suffer from mental illness. The existence of artificially intelligent psychopathology can be interpreted through the philosophical perspectives of mental illness. This offers new insights into what it means to have either robot or human mental disorders, but may also offer a platform on which to examine the mechanisms of biological or artificially intelligent psychiatric disease. The possibility of mental illnesses occurring in artificially intelligent individuals necessitates the consideration that at some level, they may have achieved a mental capability of consciousness, sentience and rationality such that they can subsequently become dysfunctional. The deeper philosophical understanding of these conditions in mankind and artificial intelligences might therefore offer reciprocal insights into mental health and mechanisms that may lead to the prevention of mental dysfunction.

Relationship Between Speech Intelligibility and Speech Comprehension in Babble Noise.

PubMed

Fontan, Lionel; Tardieu, Julien; Gaillard, Pascal; Woisard, Virginie; Ruiz, Robert

2015-06-01

The authors investigated the relationship between the intelligibility and comprehension of speech presented in babble noise. Forty participants listened to French imperative sentences (commands for moving objects) in a multitalker babble background for which intensity was experimentally controlled. Participants were instructed to transcribe what they heard and obey the commands in an interactive environment set up for this purpose. The former test provided intelligibility scores and the latter provided comprehension scores. Collected data revealed a globally weak correlation between intelligibility and comprehension scores (r = .35, p < .001). The discrepancy tended to grow as noise level increased. An analysis of standard deviations showed that variability in comprehension scores increased linearly with noise level, whereas higher variability in intelligibility scores was found for moderate noise level conditions. These results support the hypothesis that intelligibility scores are poor predictors of listeners' comprehension in real communication situations. Intelligibility and comprehension scores appear to provide different insights, the first measure being centered on speech signal transfer and the second on communicative performance. Both theoretical and practical implications for the use of speech intelligibility tests as indicators of speakers' performances are discussed.

Comparing Binaural Pre-processing Strategies II: Speech Intelligibility of Bilateral Cochlear Implant Users.

PubMed

Baumgärtel, Regina M; Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-12-30

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. © The Author(s) 2015.

Finding Creativity in an Artificial Artist

ERIC Educational Resources Information Center

Norton, David; Heath, Derrall; Ventura, Dan

2013-01-01

Creativity is an important component of human intelligence, and imbuing artificially intelligent systems with creativity is an interesting challenge. In particular, it is difficult to quantify (or even qualify) creativity. Recently, it has been suggested that conditions for attributing creativity to a system include: appreciation, imagination, and…

Examining explanations for fundamental frequency's contribution to speech intelligibility in noise

NASA Astrophysics Data System (ADS)

Schlauch, Robert S.; Miller, Sharon E.; Watson, Peter J.

2005-09-01

Laures and Weismer [JSLHR, 42, 1148 (1999)] reported that speech with natural variation in fundamental frequency (F0) is more intelligible in noise than speech with a flattened F0 contour. Cognitive-linguistic based explanations have been offered to account for this drop in intelligibility for the flattened condition, but a lower-level mechanism related to auditory streaming may be responsible. Numerous psychoacoustic studies have demonstrated that modulating a tone enables a listener to segregate it from background sounds. To test these rival hypotheses, speech recognition in noise was measured for sentences with six different F0 contours: unmodified, flattened at the mean, natural but exaggerated, reversed, and frequency modulated (rates of 2.5 and 5.0 Hz). The 180 stimulus sentences were produced by five talkers (30 sentences per condition). Speech recognition for fifteen listeners replicate earlier findings showing that flattening the F0 contour results in a roughly 10% reduction in recognition of key words compared with the natural condition. Although the exaggerated condition produced results comparable to those of the flattened condition, the other conditions with unnatural F0 contours all yielded significantly poorer performance than the flattened condition. These results support the cognitive, linguistic-based explanations for the reduction in performance.

Cortical characterization of the perception of intelligible and unintelligible speech measured via high-density electroencephalography.

PubMed

Utianski, Rene L; Caviness, John N; Liss, Julie M

2015-01-01

High-density electroencephalography was used to evaluate cortical activity during speech comprehension via a sentence verification task. Twenty-four participants assigned true or false to sentences produced with 3 noise-vocoded channel levels (1--unintelligible, 6--decipherable, 16--intelligible), during simultaneous EEG recording. Participant data were sorted into higher- (HP) and lower-performing (LP) groups. The identification of a late-event related potential for LP listeners in the intelligible condition and in all listeners when challenged with a 6-Ch signal supports the notion that this induced potential may be related to either processing degraded speech, or degraded processing of intelligible speech. Different cortical locations are identified as neural generators responsible for this activity; HP listeners are engaging motor aspects of their language system, utilizing an acoustic-phonetic based strategy to help resolve the sentence, while LP listeners do not. This study presents evidence for neurophysiological indices associated with more or less successful speech comprehension performance across listening conditions. Copyright © 2014 Elsevier Inc. All rights reserved.

Intelligent Life-Extending Controls for Aircraft Engines Studied

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

2005-01-01

Current aircraft engine controllers are designed and operated to provide desired performance and stability margins. Except for the hard limits for extreme conditions, engine controllers do not usually take engine component life into consideration during the controller design and operation. The end result is that aircraft pilots regularly operate engines under unnecessarily harsh conditions to strive for optimum performance. The NASA Glenn Research Center and its industrial and academic partners have been working together toward an intelligent control concept that will include engine life as part of the controller design criteria. This research includes the study of the relationship between control action and engine component life as well as the design of an intelligent control algorithm to provide proper tradeoffs between performance and engine life. This approach is expected to maintain operating safety while minimizing overall operating costs. In this study, the thermomechanical fatigue (TMF) of a critical component was selected to demonstrate how an intelligent engine control algorithm can significantly extend engine life with only a very small sacrifice in performance. An intelligent engine control scheme based on modifying the high-pressure spool speed (NH) was proposed to reduce TMF damage from ground idle to takeoff. The NH acceleration schedule was optimized to minimize the TMF damage for a given rise-time constraint, which represents the performance requirement. The intelligent engine control scheme was used to simulate a commercial short-haul aircraft engine.

Fault detection and analysis in nuclear research facility using artificial intelligence methods

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

Ghazali, Abu Bakar, E-mail: Abakar@uniten.edu.my; Ibrahim, Maslina Mohd

In this article, an online detection of transducer and actuator condition is discussed. A case study is on the reading of area radiation monitor (ARM) installed at the chimney of PUSPATI TRIGA nuclear reactor building, located at Bangi, Malaysia. There are at least five categories of abnormal ARM reading that could happen during the transducer failure, namely either the reading becomes very high, or very low/ zero, or with high fluctuation and noise. Moreover, the reading may be significantly higher or significantly lower as compared to the normal reading. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS)more » are good methods for modeling this plant dynamics. The failure of equipment is based on ARM reading so it is then to compare with the estimated ARM data from ANN/ ANFIS function. The failure categories in either ‘yes’ or ‘no’ state are obtained from a comparison between the actual online data and the estimated output from ANN/ ANFIS function. It is found that this system design can correctly report the condition of ARM equipment in a simulated environment and later be implemented for online monitoring. This approach can also be extended to other transducers, such as the temperature profile of reactor core and also to include other critical actuator conditions such as the valves and pumps in the reactor facility provided that the failure symptoms are clearly defined.« less

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

PubMed

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

The Influence of Noise Reduction on Speech Intelligibility, Response Times to Speech, and Perceived Listening Effort in Normal-Hearing Listeners.

PubMed

van den Tillaart-Haverkate, Maj; de Ronde-Brons, Inge; Dreschler, Wouter A; Houben, Rolph

2017-01-01

Single-microphone noise reduction leads to subjective benefit, but not to objective improvements in speech intelligibility. We investigated whether response times (RTs) provide an objective measure of the benefit of noise reduction and whether the effect of noise reduction is reflected in rated listening effort. Twelve normal-hearing participants listened to digit triplets that were either unprocessed or processed with one of two noise-reduction algorithms: an ideal binary mask (IBM) and a more realistic minimum mean square error estimator (MMSE). For each of these three processing conditions, we measured (a) speech intelligibility, (b) RTs on two different tasks (identification of the last digit and arithmetic summation of the first and last digit), and (c) subjective listening effort ratings. All measurements were performed at four signal-to-noise ratios (SNRs): -5, 0, +5, and +∞ dB. Speech intelligibility was high (>97% correct) for all conditions. A significant decrease in response time, relative to the unprocessed condition, was found for both IBM and MMSE for the arithmetic but not the identification task. Listening effort ratings were significantly lower for IBM than for MMSE and unprocessed speech in noise. We conclude that RT for an arithmetic task can provide an objective measure of the benefit of noise reduction. For young normal-hearing listeners, both ideal and realistic noise reduction can reduce RTs at SNRs where speech intelligibility is close to 100%. Ideal noise reduction can also reduce perceived listening effort.

A MICROPROCESSOR ASCII CHARACTER BUFFERING SYSTEM

EPA Science Inventory

A microprocessor buffering system (MBS) was developed at the Environmental Monitoring and Support Laboratory -Cincinnati (EMSL-CI) to provide an efficient transfer for serial ASCII information between intelligent instrument systema and a Data General NOVA laboratory automation co...

National Intelligent Transportation Infrastructure Initiative

DOT National Transportation Integrated Search

1992-10-01

This report presents data which can be used in the evaluation of the highway safety performance of the States. The data were submitted by the States through the Highway Performance Monitoring System operated by the Federal Highway Administration. The...

Demand based signal retiming phase 2 - real world implementation : [summary].

DOT National Transportation Integrated Search

2016-01-01

Monitoring and managing the operation of arterial operations represents a significant : challenge for many public agencies. While there are more arterial streets which cover a : larger road network, arterials generally have less Intelligent Transport...

3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

NASA Astrophysics Data System (ADS)

Saeed, R. A.; Galybin, A. N.; Popov, V.

2013-01-01

This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

Conditional standard errors of measurement for composite scores on the Wechsler Preschool and Primary Scale of Intelligence-Third Edition.

PubMed

Price, Larry R; Raju, Nambury; Lurie, Anna; Wilkins, Charles; Zhu, Jianjun

2006-02-01

A specific recommendation of the 1999 Standards for Educational and Psychological Testing by the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education is that test publishers report estimates of the conditional standard error of measurement (SEM). Procedures for calculating the conditional (score-level) SEM based on raw scores are well documented; however, few procedures have been developed for estimating the conditional SEM of subtest or composite scale scores resulting from a nonlinear transformation. Item response theory provided the psychometric foundation to derive the conditional standard errors of measurement and confidence intervals for composite scores on the Wechsler Preschool and Primary Scale of Intelligence-Third Edition.

An open and reconfigurable wireless sensor network for pervasive health monitoring.

PubMed

Triantafyllidis, A; Koutkias, V; Chouvarda, I; Maglaveras, N

2008-01-01

Sensor networks constitute the backbone for the construction of personalized monitoring systems. Up to now, several sensor networks have been proposed for diverse pervasive healthcare applications, which are however characterized by a significant lack of open architectures, resulting in closed, non-interoperable and difficult to extend solutions. In this context, we propose an open and reconfigurable wireless sensor network (WSN) for pervasive health monitoring, with particular emphasis in its easy extension with additional sensors and functionality by incorporating embedded intelligence mechanisms. We consider a generic WSN architecture comprised of diverse sensor nodes (with communication and processing capabilities) and a mobile base unit (MBU) operating as the gateway between the sensors and the medical personnel, formulating this way a body area network (BAN). The primary focus of this work is on the intra-BAN data communication issues, adopting SensorML as the data representation mean, including the encoding of the monitoring patterns and the functionality of the sensor network. In our prototype implementation two sensor nodes are emulated; one for heart rate monitoring and the other for blood glucose observations, while the MBU corresponds to a personal digital assistant (PDA) device. Java 2 Micro Edition (J2ME) is used to implement both the sensor nodes and the MBU components. Intra-BAN wireless communication relies on the Blue-tooth protocol. Via an adaptive user interface in the MBU, health professionals may specify the monitoring parameters of the WSN and define the monitoring patterns of interest in terms of rules. This work constitutes an essential step towards the construction of open, extensible, inter-operable and intelligent WSNs for pervasive health monitoring.

Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

1986-01-01

Describes possible applications of new technologies to special education. Discusses results of a study designed to explore the use of robotics, artificial intelligence, and computer simulations to aid people with handicapping conditions. Presents several scenarios in which specific technological advances may contribute to special education…

Trend Monitoring System (TMS) graphics software

NASA Technical Reports Server (NTRS)

Brown, J. S.

1979-01-01

A prototype bus communications systems, which is being used to support the Trend Monitoring System (TMS) and to evaluate the bus concept is considered. A set of FORTRAN-callable graphics subroutines for the host MODCOMP comuter, and an approach to splitting graphics work between the host and the system's intelligent graphics terminals are described. The graphics software in the MODCOMP and the operating software package written for the graphics terminals are included.

Tunable thin film filters for intelligent WDM networks

NASA Astrophysics Data System (ADS)

Cahill, Michael; Bartolini, Glenn; Lourie, Mark; Domash, Lawrence

2006-08-01

Optical transmission systems have evolved rapidly in recent years with the emergence of new technologies for gain management, wavelength multiplexing, tunability, and switching. WDM networks are increasingly expected to be agile, flexible, and reconfigurable which in turn has led to a need for monitoring to be more widely distributed within the network. Automation of many actions performed on these networks, such as channel provisioning and power balancing, can only be realized by the addition of optical channel monitors (OCMs). These devices provide information about the optical transmission system including the number of optical channels, channel identification, wavelength, power, and in some cases optical signal-to-noise ratio (OSNR). Until recently OCMs were costly and bulky and thus the number of OCMs used in optical networks was often kept to a minimum. We describe a family of tunable thin film filters which have greatly reduced the cost and physical footprint of channel monitors, making possible 'monitoring everywhere' for intelligent optical networks which can serve long haul, metro and access requirements from a single technology platform. As examples of specific applications we discuss network issues such as auto provisioning, wavelength collision avoidance, power balancing, OSNR balancing, gain equalization, alien wavelength recognition, interoperability, and other requirements assigned to the emerging concept of an Optical Control Plane.

Improving the speech intelligibility in classrooms

NASA Astrophysics Data System (ADS)

Lam, Choi Ling Coriolanus

One of the major acoustical concerns in classrooms is the establishment of effective verbal communication between teachers and students. Non-optimal acoustical conditions, resulting in reduced verbal communication, can cause two main problems. First, they can lead to reduce learning efficiency. Second, they can also cause fatigue, stress, vocal strain and health problems, such as headaches and sore throats, among teachers who are forced to compensate for poor acoustical conditions by raising their voices. Besides, inadequate acoustical conditions can induce the usage of public address system. Improper usage of such amplifiers or loudspeakers can lead to impairment of students' hearing systems. The social costs of poor classroom acoustics will be large to impair the learning of children. This invisible problem has far reaching implications for learning, but is easily solved. Many researches have been carried out that they have accurately and concisely summarized the research findings on classrooms acoustics. Though, there is still a number of challenging questions remaining unanswered. Most objective indices for speech intelligibility are essentially based on studies of western languages. Even several studies of tonal languages as Mandarin have been conducted, there is much less on Cantonese. In this research, measurements have been done in unoccupied rooms to investigate the acoustical parameters and characteristics of the classrooms. The speech intelligibility tests, which based on English, Mandarin and Cantonese, and the survey were carried out on students aged from 5 years old to 22 years old. It aims to investigate the differences in intelligibility between English, Mandarin and Cantonese of the classrooms in Hong Kong. The significance on speech transmission index (STI) related to Phonetically Balanced (PB) word scores will further be developed. Together with developed empirical relationship between the speech intelligibility in classrooms with the variations of the reverberation time, the indoor ambient noise (or background noise level), the signal-to-noise ratio, and the speech transmission index, it aims to establish a guideline for improving the speech intelligibility in classrooms for any countries and any environmental conditions. The study showed that the acoustical conditions of most of the measured classrooms in Hong Kong are unsatisfactory. The selection of materials inside a classroom is important for improving speech intelligibility at design stage, especially the acoustics ceiling, to shorten the reverberation time inside the classroom. The signal-to-noise should be higher than 11dB(A) for over 70% of speech perception, either tonal or non-tonal languages, without the usage of address system. The unexpected results bring out a call to revise the standard design and to devise acceptable standards for classrooms in Hong Kong. It is also demonstrated a method for assessment on the classroom in other cities with similar environmental conditions.

Neuroanatomical correlates of intelligence in healthy young adults: the role of basal ganglia volume.

PubMed

Rhein, Cosima; Mühle, Christiane; Richter-Schmidinger, Tanja; Alexopoulos, Panagiotis; Doerfler, Arnd; Kornhuber, Johannes

2014-01-01

In neuropsychiatric diseases with basal ganglia involvement, higher cognitive functions are often impaired. In this exploratory study, we examined healthy young adults to gain detailed insight into the relationship between basal ganglia volume and cognitive abilities under non-pathological conditions. We investigated 137 healthy adults that were between the ages of 21 and 35 years with similar educational backgrounds. Magnetic resonance imaging (MRI) was performed, and volumes of basal ganglia nuclei in both hemispheres were calculated using FreeSurfer software. The cognitive assessment consisted of verbal, numeric and figural aspects of intelligence for either the fluid or the crystallised intelligence factor using the intelligence test Intelligenz-Struktur-Test (I-S-T 2000 R). Our data revealed significant correlations of the caudate nucleus and pallidum volumes with figural and numeric aspects of intelligence, but not with verbal intelligence. Interestingly, figural intelligence associations were dependent on sex and intelligence factor; in females, the pallidum volumes were correlated with crystallised figural intelligence (r = 0.372, p = 0.01), whereas in males, the caudate volumes were correlated with fluid figural intelligence (r = 0.507, p = 0.01). Numeric intelligence was correlated with right-lateralised caudate nucleus volumes for both females and males, but only for crystallised intelligence (r = 0.306, p = 0.04 and r = 0.459, p = 0.04, respectively). The associations were not mediated by prefrontal cortical subfield volumes when controlling with partial correlation analyses. The findings of our exploratory analysis indicate that figural and numeric intelligence aspects, but not verbal aspects, are strongly associated with basal ganglia volumes. Unlike numeric intelligence, the type of figural intelligence appears to be related to distinct basal ganglia nuclei in a sex-specific manner. Subcortical brain structures thus may contribute substantially to cognitive performance.

Real time charge efficiency monitoring for nickel electrodes in NICD and NIH2 cells

NASA Astrophysics Data System (ADS)

Zimmerman, A. H.

1987-09-01

The charge efficiency of nickel-cadmium and nickel-hydrogen battery cells is critical in spacecraft applications for determining the amount of time required for a battery to reach a full state of charge. As the nickel-cadmium or nickel-hydrogen batteries approach about 90 percent state of charge, the charge efficiency begins to drop towards zero, making estimation of the total amount of stored charge uncertain. Charge efficiency estimates are typically based on prior history of available capacity following standardized conditions for charge and discharge. These methods work well as long as performance does not change significantly. A relatively simple method for determining charge efficiencies during real time operation for these battery cells would be a tremendous advantage. Such a method was explored and appears to be quite well suited for application to nickel-cadmium and nickel-hydrogen battery cells. The charge efficiency is monitored in real time, using only voltage measurements as inputs. With further evaluation such a method may provide a means to better manage charge control of batteries, particularly in systems where a high degree of autonomy or system intelligence is required.

airborne data analysis/monitor system

NASA Technical Reports Server (NTRS)

Stephison, D. B.

1981-01-01

An Airborne Data Analysis/Monitor System (ADAMS), a ROLM 1666 computer based system installed onboard test airplanes used during experimental testing is evaluated. In addition to the 1666 computer, the ADAMS hardware includes a DDC System 90 fixed head disk and a Miltape DD400 floppy disk. Boeing designed a DMA interface to the data acquisition system and an intelligent terminal to reduce system overhead and simplify operator commands. The ADAMS software includes RMX/RTOS and both ROLM FORTRAN and assembly language are used. The ADAMS provides real time displays that enable onboard test engineers to make rapid decisions about test conduct thus reducing the cost and time required to certify new model airplanes, and improved the quality of data derived from the test, leading to more rapid development of improvements resulting in quieter, safer, and more efficient airplanes. The availability of airborne data processing removes most of the weather and geographical restrictions imposed by telemetered flight test data systems. A data base is maintained to describe the airplane, the data acquisition system, the type of testing, and the conditions under which the test is performed.

Real time charge efficiency monitoring for nickel electrodes in NICD and NIH2 cells

NASA Technical Reports Server (NTRS)

Zimmerman, A. H.

1987-01-01

The charge efficiency of nickel-cadmium and nickel-hydrogen battery cells is critical in spacecraft applications for determining the amount of time required for a battery to reach a full state of charge. As the nickel-cadmium or nickel-hydrogen batteries approach about 90 percent state of charge, the charge efficiency begins to drop towards zero, making estimation of the total amount of stored charge uncertain. Charge efficiency estimates are typically based on prior history of available capacity following standardized conditions for charge and discharge. These methods work well as long as performance does not change significantly. A relatively simple method for determining charge efficiencies during real time operation for these battery cells would be a tremendous advantage. Such a method was explored and appears to be quite well suited for application to nickel-cadmium and nickel-hydrogen battery cells. The charge efficiency is monitored in real time, using only voltage measurements as inputs. With further evaluation such a method may provide a means to better manage charge control of batteries, particularly in systems where a high degree of autonomy or system intelligence is required.

CHRONIOUS: an open, ubiquitous and adaptive chronic disease management platform for chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD) and renal insufficiency.

PubMed

Rosso, R; Munaro, G; Salvetti, O; Colantonio, S; Ciancitto, F

2010-01-01

CHRONIOUS is an highly innovative Information and Communication Technologies (ICT) research Initiative that aspires to implement its vision for ubiquitous health and lifestyle monitoring. The 17 European project partners are strictly working together since February 2008 to realize and open platform to manage and monitor elderly patients with chronic diseases and many difficulties to reach hospital centers for routine controls. The testing activities will be done in Italy and Spain involving COPD (Chronic Obstructive Pulmonary Disease) and CKD (Chronic Kidney Disease) patients, these being widespread and highly expensive in terms of social and economic costs. Patients, equipped by wearable technologies and sensors and interacting with lifestyle interfaces, will be assisted by healthcare personnel able to check the health record and critical conditions through the Chronious platform data analysis and decision support system. Additionally, the new ontology based literature search engine will help the clinicians in the standardization of care delivery process. This paper is to present the main project objectives and its principal components from the intelligent system point of view.

Towards Smart Grid Dynamic Ratings

NASA Astrophysics Data System (ADS)

Cheema, Jamal; Clark, Adrian; Kilimnik, Justin; Pavlovski, Chris; Redman, David; Vu, Maria

2011-08-01

The energy distribution industry is giving greater attention to smart grid solutions as a means for increasing the capabilities, efficiency and reliability of the electrical power network. The smart grid makes use of intelligent monitoring and control devices throughout the distribution network to report on electrical properties such as voltage, current and power, as well as raising network alarms and events. A further aspect of the smart grid embodies the dynamic rating of electrical assets of the network. This fundamentally involves a rating of the load current capacity of electrical assets including feeders, transformers and switches. The mainstream approach to rate assets is to apply the vendor plate rating, which often under utilizes assets, or in some cases over utilizes when environmental conditions reduce the effective rated capacity, potentially reducing lifetime. Using active intelligence we have developed a rating system that rates assets in real time based upon several events. This allows for a far more efficient and reliable electrical grid that is able to extend further the life and reliability of the electrical network. In this paper we describe our architecture, the observations made during development and live deployment of the solution into operation. We also illustrate how this solution blends with the smart grid by proposing a dynamic rating system for the smart grid.

STATISTICS AND INTELLIGENCE IN DEVELOPING COUNTRIES: A NOTE.

PubMed

Kodila-Tedika, Oasis; Asongu, Simplice A; Azia-Dimbu, Florentin

2017-05-01

The purpose of this study is to assess the relationship between intelligence (or human capital) and the statistical capacity of developing countries. The line of inquiry is motivated essentially by the scarce literature on poor statistics in developing countries and an evolving stream of literature on the knowledge economy. A positive association is established between intelligence quotient (IQ) and statistical capacity. The relationship is robust to alternative specifications with varying conditioning information sets and control for outliers. Policy implications are discussed.

Monitoring and Identifying in Real time Critical Patients Events.

PubMed

Chavez Mora, Emma

2014-01-01

Nowadays pervasive health care monitoring environments, as well as business activity monitoring environments, gather information from a variety of data sources. However it includes new challenges because of the use of body and wireless sensors, nontraditional operational and transactional sources. This makes the health data more difficult to monitor. Decision making in this environment is typically complex and unstructured as clinical work is essentially interpretative, multitasking, collaborative, distributed and reactive. Thus, the health care arena requires real time data management in areas such as patient monitoring, detection of adverse events and adaptive responses to operational failures. This research presents a new architecture that enables real time patient data management through the use of intelligent data sources.

Idea Project Final Report, Passive Optical Lane Position Monitor

DOT National Transportation Integrated Search

1996-01-01

INTELLIGENT VEHICLE INITIATIVE OR IVI : THIS INVESTIGATION WAS COMPLETED AS PART OF THE ITS-IDEA PROGRAM, WHICH IS ONE OF THREE IDEA PROGRAMS MANAGED BY THE TRANSPORTATION RESEARCH BOARD (TRB) TO FOSTER INNOVATIONS IN SURFACE TRANSPORTATION. IT FOCUS...

iTRAC : intelligent video compression for automated traffic surveillance systems.

DOT National Transportation Integrated Search

2010-08-01

Non-intrusive video imaging sensors are commonly used in traffic monitoring : and surveillance. For some applications it is necessary to transmit the video : data over communication links. However, due to increased requirements of : bitrate this mean...

Logic-centered architecture for ubiquitous health monitoring.

PubMed

Lewandowski, Jacek; Arochena, Hisbel E; Naguib, Raouf N G; Chao, Kuo-Ming; Garcia-Perez, Alexeis

2014-09-01

One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework with customizable wireless interfaces and plug'n'play capability to easily interconnect third party sensor devices. It caters to wireless body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual development and remote deployment model. The complementary visual Inference Engine Editor that comes with the package enables artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications.

Ambient intelligence systems for personalized sport training.

PubMed

Vales-Alonso, Javier; López-Matencio, Pablo; Gonzalez-Castaño, Francisco J; Navarro-Hellín, Honorio; Baños-Guirao, Pedro J; Pérez-Martínez, Francisco J; Martínez-Álvarez, Rafael P; González-Jiménez, Daniel; Gil-Castiñeira, Felipe; Duro-Fernández, Richard

2010-01-01

Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project "Ambient Intelligence Systems Support for Athletes with Specific Profiles", which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes' mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes' training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m, s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably.

Ambient Intelligence Systems for Personalized Sport Training

PubMed Central

Vales-Alonso, Javier; López-Matencio, Pablo; Gonzalez-Castaño, Francisco J.; Navarro-Hellín, Honorio; Baños-Guirao, Pedro J.; Pérez-Martínez, Francisco J.; Martínez-Álvarez, Rafael P.; González-Jiménez, Daniel; Gil-Castiñeira, Felipe; Duro-Fernández, Richard

2010-01-01

Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m, s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably. PMID:22294931

Association between Sleep Duration and Intelligence Scores in Healthy Children

ERIC Educational Resources Information Center

Geiger, Anja; Achermann, Peter; Jenni, Oskar G.

2010-01-01

We examined the association between sleep behavior and cognitive functioning in 60 healthy children between 7 and 11 years of age under nonexperimental conditions. Intellectual abilities were assessed by the Wechsler Intelligence Scale for Children (4th edition) and sleep variables by questionnaires, actigraphy, and sleep diaries. Correlation…

Invited Reaction: Developing Emotional Intelligence (EI) Abilities through Team-Based Learning

ERIC Educational Resources Information Center

Leimbach, Michael P.; Maringka, Jane

2010-01-01

The preceding article (Clarke, 2010) examines an important and interesting question; that is, under what conditions can learning contribute to the development of emotional intelligence (EI)? Despite the controversy surrounding the definition and construct of EI, its prevalence for the human resources development (HRD) field and its implications…

F-15 IFCS: Intelligent Flight Control System

NASA Technical Reports Server (NTRS)

Bosworth, John

2007-01-01

This viewgraph presentation describes the F-15 Intelligent Flight Control System (IFCS). The goals of this project include: 1) Demonstrate revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions; and 2) Demonstrate advance neural network-based flight control technology for new aerospace systems designs.

Enhancing Speech Intelligibility: Interactions among Context, Modality, Speech Style, and Masker

ERIC Educational Resources Information Center

Van Engen, Kristin J.; Phelps, Jasmine E. B.; Smiljanic, Rajka; Chandrasekaran, Bharath

2014-01-01

Purpose: The authors sought to investigate interactions among intelligibility-enhancing speech cues (i.e., semantic context, clearly produced speech, and visual information) across a range of masking conditions. Method: Sentence recognition in noise was assessed for 29 normal-hearing listeners. Testing included semantically normal and anomalous…

The Effect of Translators' Emotional Intelligence on Their Translation Quality

ERIC Educational Resources Information Center

Varzande, Mohsen; Jadidi, Esmaeil

2015-01-01

Translators differ from each other in many ways in terms of their knowledge, professional and psychological conditions that may directly influence their translation. The present study aimed at investigating the impact of translators' Emotional Intelligence on their translation quality. Following a "causal-comparative study," a sample of…

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

PubMed

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

A music perception disorder (congenital amusia) influences speech comprehension.

PubMed

Liu, Fang; Jiang, Cunmei; Wang, Bei; Xu, Yi; Patel, Aniruddh D

2015-01-01

This study investigated the underlying link between speech and music by examining whether and to what extent congenital amusia, a musical disorder characterized by degraded pitch processing, would impact spoken sentence comprehension for speakers of Mandarin, a tone language. Sixteen Mandarin-speaking amusics and 16 matched controls were tested on the intelligibility of news-like Mandarin sentences with natural and flat fundamental frequency (F0) contours (created via speech resynthesis) under four signal-to-noise (SNR) conditions (no noise, +5, 0, and -5dB SNR). While speech intelligibility in quiet and extremely noisy conditions (SNR=-5dB) was not significantly compromised by flattened F0, both amusic and control groups achieved better performance with natural-F0 sentences than flat-F0 sentences under moderately noisy conditions (SNR=+5 and 0dB). Relative to normal listeners, amusics demonstrated reduced speech intelligibility in both quiet and noise, regardless of whether the F0 contours of the sentences were natural or flattened. This deficit in speech intelligibility was not associated with impaired pitch perception in amusia. These findings provide evidence for impaired speech comprehension in congenital amusia, suggesting that the deficit of amusics extends beyond pitch processing and includes segmental processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cerebellar neurocontroller project, for aerospace applications, in a civilian neurocomputing initiative in the 'decade of the brain'

NASA Technical Reports Server (NTRS)

Pellionisz, Andras J.; Jorgensen, Charles C.; Werbos, Paul J.

1992-01-01

A key question is how to utilize civilian government agencies along with an industrial consortium to successfully complement the so far primarily defense-oriented neural network research. Civilian artificial neural system projects, such as artificial cerebellar neurocontrollers aimed at duplicating nature's existing neural network solutions for adaptive sensorimotor coordination, are proposed by such a synthesis. The cerebellum provides an intelligent interface between higher possibly symbolic levels of human intelligence and repetitious demands of real world conventional controllers. The generation of such intelligent interfaces could be crucial to the economic feasibility of the human settlement of space and an improvement in telerobotics techniques to permit the cost-effective exploitation of nonterrestrial materials and planetary exploration and monitoring. The authors propose a scientific framework within which such interagency activities could effectively cooperate.

A mobile device system for early warning of ECG anomalies.

PubMed

Szczepański, Adam; Saeed, Khalid

2014-06-20

With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors' work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device-a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient's surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns.

Flight Test Implementation of a Second Generation Intelligent Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2005-01-01

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team was to develop and flight-test control systems that use neural network technology, to optimize the performance of the aircraft under nominal conditions, and to stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. The Intelligent Flight Control System team is currently in the process of implementing a second generation control scheme, collectively known as Generation 2 or Gen 2, for flight testing on the NASA F-15 aircraft. This report describes the Gen 2 system as implemented by the team for flight test evaluation. Simulation results are shown which describe the experiment to be performed in flight and highlight the ways in which the Gen 2 system meets the defined objectives.

A survey of acoustic conditions in semi-open plan classrooms in the United Kingdom.

PubMed

Greenland, Emma E; Shield, Bridget M

2011-09-01

This paper reports the results of a large scale, detailed acoustic survey of 42 open plan classrooms of varying design in the UK each of which contained between 2 and 14 teaching areas or classbases. The objective survey procedure, which was designed specifically for use in open plan classrooms, is described. The acoustic measurements relating to speech intelligibility within a classbase, including ambient noise level, intrusive noise level, speech to noise ratio, speech transmission index, and reverberation time, are presented. The effects on speech intelligibility of critical physical design variables, such as the number of classbases within an open plan unit and the selection of acoustic finishes for control of reverberation, are examined. This analysis enables limitations of open plan classrooms to be discussed and acoustic design guidelines to be developed to ensure good listening conditions. The types of teaching activity to provide adequate acoustic conditions, plus the speech intelligibility requirements of younger children, are also discussed. © 2011 Acoustical Society of America

Development of ship structure health monitoring system based on IOT technology

NASA Astrophysics Data System (ADS)

Yang, Sujun; Shi, Lei; Chen, Demin; Dong, Yuqing; Hu, Zhenyi

2017-06-01

It is very important to monitor the ship structure, because ships are affected by all kinds of wind wave and current environment factor. At the same time, internet of things (IOT) technology plays more and more important role of in the development of industrial process. In the paper, real-time online monitoring of the ship can be realized by means of IOT technology. Ship stress, vibration and dynamic parameters are measured. Meanwhile, data is transmitted to remote monitoring system through intelligent data gateway. Timely remote support can be realized for dangerous stage of ship. Safe navigation of ships is guaranteed through application of the system.

Plan execution monitoring with distributed intelligent agents for battle command

NASA Astrophysics Data System (ADS)

Allen, James P.; Barry, Kevin P.; McCormick, John M.; Paul, Ross A.

2004-07-01

As military tactics evolve toward execution centric operations the ability to analyze vast amounts of mission relevant data is essential to command and control decision making. To maintain operational tempo and achieve information superiority we have developed Vigilant Advisor, a mobile agent-based distributed Plan Execution Monitoring system. It provides military commanders with continuous contingency monitoring tailored to their preferences while overcoming the network bandwidth problem often associated with traditional remote data querying. This paper presents an overview of Plan Execution Monitoring as well as a detailed view of the Vigilant Advisor system including key features and statistical analysis of resource savings provided by its mobile agent-based approach.

Health-related quality of life and cognitive functioning at on- and off-treatment periods in children aged between 6-13 years old with brain tumors: a prospective longitudinal study.

PubMed

An, Kyung Jin; Joung, Yoo Sook; Sung, Ki Woong; Kim, Ji-Hae

2013-03-01

Our study aimed to examine the relationship between intelligence and health-related quality of life (HRQOL) in children (6-13 years old) diagnosed as having a brain tumor. We administered a Korean version of the Wechsler Intelligence Scale for Children-III, the Pediatric Quality of Life Inventory, version 4.0 (PedsQL), the Korean version of the Parenting Stress Index-Short Form, and the Korean Version of the Parenting Sense of Competence (K-PSOC) scale before or after initial radiotherapy (T1) and after treatment termination (T2). In total, 13 patients completed both the T1 and T2 interviews. Scores significantly declined between T1 and T2 on the full-scale intelligence quotients (FIQ), verbal intelligence quotients (VIQ), performance intelligence quotients (PIQ), similarity and coding tests, as well as the K-PSOC, which measures parental anxiety. FIQ scores at T1 were correlated with the self-reported PedsQL total scores (r=0.739) and the parent proxy-report PedsQL scores for school functioning (r=0.706) at T2. Also, the FIQ scores at T2 were correlated with the self-reported PedsQL total scores (r=0.748) and scores for physical health (r=0.728) at T2. The cognitive ability and intelligence level of the patients significantly declined between on and off treatment periods, and higher intelligence functioning at both on and off treatment was correlated with long-term higher HRQOL. Further investigations that monitor intelligence, HRQOL and parenting stress over a longer period, using a greater number of participants, are needed.

Person centered prediction of survival in population based screening program by an intelligent clinical decision support system.

PubMed

Safdari, Reza; Maserat, Elham; Asadzadeh Aghdaei, Hamid; Javan Amoli, Amir Hossein; Mohaghegh Shalmani, Hamid

2017-01-01

To survey person centered survival rate in population based screening program by an intelligent clinical decision support system. Colorectal cancer is the most common malignancy and major cause of morbidity and mortality throughout the world. Colorectal cancer is the sixth leading cause of cancer death in Iran. In this survey, we used cosine similarity as data mining technique and intelligent system for estimating survival of at risk groups in the screening plan. In the first step, we determined minimum data set (MDS). MDS was approved by experts and reviewing literatures. In the second step, MDS were coded by python language and matched with cosine similarity formula. Finally, survival rate by percent was illustrated in the user interface of national intelligent system. The national intelligent system was designed in PyCharm environment. Main data elements of intelligent system consist demographic information, age, referral type, risk group, recommendation and survival rate. Minimum data set related to survival comprise of clinical status, past medical history and socio-demographic information. Information of the covered population as a comprehensive database was connected to intelligent system and survival rate estimated for each patient. Mean range of survival of HNPCC patients and FAP patients were respectively 77.7% and 75.1%. Also, the mean range of the survival rate and other calculations have changed with the entry of new patients in the CRC registry by real-time. National intelligent system monitors the entire of risk group and reports survival rates by electronic guidelines and data mining technique and also operates according to the clinical process. This web base software has a critical role in the estimation survival rate in order to health care planning.

Rhythm Perception and Its Role in Perception and Learning of Dysrhythmic Speech.

PubMed

Borrie, Stephanie A; Lansford, Kaitlin L; Barrett, Tyson S

2017-03-01

The perception of rhythm cues plays an important role in recognizing spoken language, especially in adverse listening conditions. Indeed, this has been shown to hold true even when the rhythm cues themselves are dysrhythmic. This study investigates whether expertise in rhythm perception provides a processing advantage for perception (initial intelligibility) and learning (intelligibility improvement) of naturally dysrhythmic speech, dysarthria. Fifty young adults with typical hearing participated in 3 key tests, including a rhythm perception test, a receptive vocabulary test, and a speech perception and learning test, with standard pretest, familiarization, and posttest phases. Initial intelligibility scores were calculated as the proportion of correct pretest words, while intelligibility improvement scores were calculated by subtracting this proportion from the proportion of correct posttest words. Rhythm perception scores predicted intelligibility improvement scores but not initial intelligibility. On the other hand, receptive vocabulary scores predicted initial intelligibility scores but not intelligibility improvement. Expertise in rhythm perception appears to provide an advantage for processing dysrhythmic speech, but a familiarization experience is required for the advantage to be realized. Findings are discussed in relation to the role of rhythm in speech processing and shed light on processing models that consider the consequence of rhythm abnormalities in dysarthria.