Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

NASA Astrophysics Data System (ADS)

Chang, Ya-Ting; Chang, Li-Chiu; Chang, Fi-John

2005-04-01

To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input-output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Woods, David D.; Potter, Scott S.; Johannesen, Leila; Holloway, Matthew; Forbus, Kenneth D.

1991-01-01

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design.

Associative memory for online learning in noisy environments using self-organizing incremental neural network.

PubMed

Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

2009-06-01

Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

A Kinect based intelligent e-rehabilitation system in physical therapy.

PubMed

Gal, Norbert; Andrei, Diana; Nemeş, Dan Ion; Nădăşan, Emanuela; Stoicu-Tivadar, Vasile

2015-01-01

This paper presents an intelligent Kinect and fuzzy inference system based e-rehabilitation system. The Kinect can detect the posture and motion of the patients while the fuzzy inference system can interpret the acquired data on the cognitive level. The system is capable to assess the initial posture and motion ranges of 20 joints. Using angles to describe the motion of the joints, exercise patterns can be developed for each patient. Using the exercise descriptors the fuzzy inference system can track the patient and deliver real-time feedback to maximize the efficiency of the rehabilitation. The first laboratory tests confirm the utility of this system for the initial posture detection, motion range and exercise tracking.

Real-Time Control of an Articulatory-Based Speech Synthesizer for Brain Computer Interfaces

PubMed Central

Bocquelet, Florent; Hueber, Thomas; Girin, Laurent; Savariaux, Christophe; Yvert, Blaise

2016-01-01

Restoring natural speech in paralyzed and aphasic people could be achieved using a Brain-Computer Interface (BCI) controlling a speech synthesizer in real-time. To reach this goal, a prerequisite is to develop a speech synthesizer producing intelligible speech in real-time with a reasonable number of control parameters. We present here an articulatory-based speech synthesizer that can be controlled in real-time for future BCI applications. This synthesizer converts movements of the main speech articulators (tongue, jaw, velum, and lips) into intelligible speech. The articulatory-to-acoustic mapping is performed using a deep neural network (DNN) trained on electromagnetic articulography (EMA) data recorded on a reference speaker synchronously with the produced speech signal. This DNN is then used in both offline and online modes to map the position of sensors glued on different speech articulators into acoustic parameters that are further converted into an audio signal using a vocoder. In offline mode, highly intelligible speech could be obtained as assessed by perceptual evaluation performed by 12 listeners. Then, to anticipate future BCI applications, we further assessed the real-time control of the synthesizer by both the reference speaker and new speakers, in a closed-loop paradigm using EMA data recorded in real time. A short calibration period was used to compensate for differences in sensor positions and articulatory differences between new speakers and the reference speaker. We found that real-time synthesis of vowels and consonants was possible with good intelligibility. In conclusion, these results open to future speech BCI applications using such articulatory-based speech synthesizer. PMID:27880768

A Measure of Real-Time Intelligence

NASA Astrophysics Data System (ADS)

Gavane, Vaibhav

2013-03-01

We propose a new measure of intelligence for general reinforcement learning agents, based on the notion that an agent's environment can change at any step of execution of the agent. That is, an agent is considered to be interacting with its environment in real-time. In this sense, the resulting intelligence measure is more general than the universal intelligence measure (Legg and Hutter, 2007) and the anytime universal intelligence test (Hernández-Orallo and Dowe, 2010). A major advantage of the measure is that an agent's computational complexity is factored into the measure in a natural manner. We show that there exist agents with intelligence arbitrarily close to the theoretical maximum, and that the intelligence of agents depends on their parallel processing capability. We thus believe that the measure can provide a better evaluation of agents and guidance for building practical agents with high intelligence.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

An intelligent processing environment for real-time simulation

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Wells, Buren Earl, Jr.

1988-01-01

The development of a highly efficient and thus truly intelligent processing environment for real-time general purpose simulation of continuous systems is described. Such an environment can be created by mapping the simulation process directly onto the University of Alamba's OPERA architecture. To facilitate this effort, the field of continuous simulation is explored, highlighting areas in which efficiency can be improved. Areas in which parallel processing can be applied are also identified, and several general OPERA type hardware configurations that support improved simulation are investigated. Three direct execution parallel processing environments are introduced, each of which greatly improves efficiency by exploiting distinct areas of the simulation process. These suggested environments are candidate architectures around which a highly intelligent real-time simulation configuration can be developed.

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.

Integrated human-machine intelligence in space systems

NASA Technical Reports Server (NTRS)

Boy, Guy A.

1992-01-01

The integration of human and machine intelligence in space systems is outlined with respect to the contributions of artificial intelligence. The current state-of-the-art in intelligent assistant systems (IASs) is reviewed, and the requirements of some real-world applications of the technologies are discussed. A concept of integrated human-machine intelligence is examined in the contexts of: (1) interactive systems that tolerate human errors; (2) systems for the relief of workloads; and (3) interactive systems for solving problems in abnormal situations. Key issues in the development of IASs include the compatibility of the systems with astronauts in terms of inputs/outputs, processing, real-time AI, and knowledge-based system validation. Real-world applications are suggested such as the diagnosis, planning, and control of enginnered systems.

Variability and Intelligibility of Clarified Speech to Different Listener Groups

NASA Astrophysics Data System (ADS)

Silber, Ronnie F.

Two studies examined the modifications that adult speakers make in speech to disadvantaged listeners. Previous research that has focused on speech to the deaf individuals and to young children has shown that adults clarify speech when addressing these two populations. Acoustic measurements suggest that the signal undergoes similar changes for both populations. Perceptual tests corroborate these results for the deaf population, but are nonsystematic in developmental studies. The differences in the findings for these populations and the nonsystematic results in the developmental literature may be due to methodological factors. The present experiments addressed these methodological questions. Studies of speech to hearing impaired listeners have used read, nonsense, sentences, for which speakers received explicit clarification instructions and feedback, while in the child literature, excerpts of real-time conversations were used. Therefore, linguistic samples were not precisely matched. In this study, experiments used various linguistic materials. Experiment 1 used a children's story; experiment 2, nonsense sentences. Four mothers read both types of material in four ways: (1) in "normal" adult speech, (2) in "babytalk," (3) under the clarification instructions used in the "hearing impaired studies" (instructed clear speech) and (4) in (spontaneous) clear speech without instruction. No extra practice or feedback was given. Sentences were presented to 40 normal hearing college students with and without simultaneous masking noise. Results were separately tabulated for content and function words, and analyzed using standard statistical tests. The major finding in the study was individual variation in speaker intelligibility. "Real world" speakers vary in their baseline intelligibility. The four speakers also showed unique patterns of intelligibility as a function of each independent variable. Results were as follows. Nonsense sentences were less intelligible than story sentences. Function words were equal to, or more intelligible than, content words. Babytalk functioned as a clear speech style in story sentences but not nonsense sentences. One of the two clear speech styles was clearer than normal speech in adult-directed clarification. However, which style was clearer depended on interactions among the variables. The individual patterns seemed to result from interactions among demand characteristics, baseline intelligibility, materials, and differences in articulatory flexibility.

Development of an intelligent diagnostic system for reusable rocket engine control

NASA Technical Reports Server (NTRS)

Anex, R. P.; Russell, J. R.; Guo, T.-H.

1991-01-01

A description of an intelligent diagnostic system for the Space Shuttle Main Engines (SSME) is presented. This system is suitable for incorporation in an intelligent controller which implements accommodating closed-loop control to extend engine life and maximize available performance. The diagnostic system architecture is a modular, hierarchical, blackboard system which is particularly well suited for real-time implementation of a system which must be repeatedly updated and extended. The diagnostic problem is formulated as a hierarchical classification problem in which the failure hypotheses are represented in terms of predefined data patterns. The diagnostic expert system incorporates techniques for priority-based diagnostics, the combination of analytical and heuristic knowledge for diagnosis, integration of different AI systems, and the implementation of hierarchical distributed systems. A prototype reusable rocket engine diagnostic system (ReREDS) has been implemented. The prototype user interface and diagnostic performance using SSME test data are described.

Intelligent system of coordination and control for manufacturing

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2016-08-01

This paper wants shaping an intelligent system monitoring and control, which leads to optimizing material and information flows of the company. The paper presents a model for tracking and control system using intelligent real. Production system proposed for simulation analysis provides the ability to track and control the process in real time. Using simulation models be understood: the influence of changes in system structure, commands influence on the general condition of the manufacturing process conditions influence the behavior of some system parameters. Practical character consists of tracking and real-time control of the technological process. It is based on modular systems analyzed using mathematical models, graphic-analytical sizing, configuration, optimization and simulation.

An intelligent space for mobile robot localization using a multi-camera system.

PubMed

Rampinelli, Mariana; Covre, Vitor Buback; de Queiroz, Felippe Mendonça; Vassallo, Raquel Frizera; Bastos-Filho, Teodiano Freire; Mazo, Manuel

2014-08-15

This paper describes an intelligent space, whose objective is to localize and control robots or robotic wheelchairs to help people. Such an intelligent space has 11 cameras distributed in two laboratories and a corridor. The cameras are fixed in the environment, and image capturing is done synchronously. The system was programmed as a client/server with TCP/IP connections, and a communication protocol was defined. The client coordinates the activities inside the intelligent space, and the servers provide the information needed for that. Once the cameras are used for localization, they have to be properly calibrated. Therefore, a calibration method for a multi-camera network is also proposed in this paper. A robot is used to move a calibration pattern throughout the field of view of the cameras. Then, the captured images and the robot odometry are used for calibration. As a result, the proposed algorithm provides a solution for multi-camera calibration and robot localization at the same time. The intelligent space and the calibration method were evaluated under different scenarios using computer simulations and real experiments. The results demonstrate the proper functioning of the intelligent space and validate the multi-camera calibration method, which also improves robot localization.

An Intelligent Space for Mobile Robot Localization Using a Multi-Camera System

PubMed Central

Rampinelli, Mariana.; Covre, Vitor Buback.; de Queiroz, Felippe Mendonça.; Vassallo, Raquel Frizera.; Bastos-Filho, Teodiano Freire.; Mazo, Manuel.

2014-01-01

This paper describes an intelligent space, whose objective is to localize and control robots or robotic wheelchairs to help people. Such an intelligent space has 11 cameras distributed in two laboratories and a corridor. The cameras are fixed in the environment, and image capturing is done synchronously. The system was programmed as a client/server with TCP/IP connections, and a communication protocol was defined. The client coordinates the activities inside the intelligent space, and the servers provide the information needed for that. Once the cameras are used for localization, they have to be properly calibrated. Therefore, a calibration method for a multi-camera network is also proposed in this paper. A robot is used to move a calibration pattern throughout the field of view of the cameras. Then, the captured images and the robot odometry are used for calibration. As a result, the proposed algorithm provides a solution for multi-camera calibration and robot localization at the same time. The intelligent space and the calibration method were evaluated under different scenarios using computer simulations and real experiments. The results demonstrate the proper functioning of the intelligent space and validate the multi-camera calibration method, which also improves robot localization. PMID:25196009

Freight information real-time system for transport : evaluation final report

DOT National Transportation Integrated Search

2003-10-01

This report presents the findings of an independent evaluation of the Freight Information Real-time System for Transport (FIRST) intermodal freight Intelligent Transportation System (ITS) prototype system. FIRST is an Internet-based, real-time networ...

Launch vehicle operations cost reduction through artificial intelligence techniques

NASA Technical Reports Server (NTRS)

Davis, Tom C., Jr.

1988-01-01

NASA's Kennedy Space Center has attempted to develop AI methods in order to reduce the cost of launch vehicle ground operations as well as to improve the reliability and safety of such operations. Attention is presently given to cost savings estimates for systems involving launch vehicle firing-room software and hardware real-time diagnostics, as well as the nature of configuration control and the real-time autonomous diagnostics of launch-processing systems by these means. Intelligent launch decisions and intelligent weather forecasting are additional applications of AI being considered.

Thickening the Fog: The Truncation of Air Intelligence Since World War II

DTIC Science & Technology

2010-06-01

the US Government with global situational awareness, real - time engagement support, SIGINT and near real time IMINT, agile systems , and access to...The scarcity of reliable and detailed intelligence on the USSR precludes the determination at this time of specific target systems for air... time consuming task. This system is in no way haphazard, and in no way could the term ‘indiscriminate’ be applied to it.”38 One of the largest

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.

Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information preview and neural networks for plug-in hybrid electric vehicles fuel economy

NASA Astrophysics Data System (ADS)

Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.

2015-06-01

The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.

Intelligent Paging Based Mobile User Tracking Using Fuzzy Logic

NASA Astrophysics Data System (ADS)

Saha, Sajal; Dutta, Raju; Debnath, Soumen; Mukhopadhyay, Asish K.

2010-11-01

In general, a mobile user travels in a predefined path that depends mostly on the user's characteristics. Thus, tracking the locations of a mobile user is one of the challenges for location management. In this paper, we introduce a movement pattern learning strategy system to track the user's movements using adaptive fuzzy logic. Our fuzzy inference system extracts patterns from the historical data record of the cell numbers along with the date and time stamp of the users occupying the cell. Implementation of this strategy has been evaluated with the real time user data which proves the efficiency and accuracy of the model. This mechanism not only reduces user location tracking costs, but also significantly decreases the call-loss rates and average paging delays.

Intelligent systems technology infrastructure for integrated systems

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.

1991-01-01

Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.

A Strategic Design of an Opto-Chemical Security Device with Resettable and Reconfigurable Password Based Upon Dual Channel Two-in-One Chemosensor Molecule.

PubMed

Majumdar, Tapas; Haldar, Basudeb; Mallick, Arabinda

2017-02-20

A simple strategy is proposed to design and develop an intelligent device based on dual channel ion responsive spectral properties of a commercially available molecule, harmine (HM). The system can process different sets of opto-chemical inputs generating different patterns as fluorescence outputs at specific wavelengths which can provide an additional level of protection exploiting both password and pattern recognitions. The proposed system could have the potential to come up with highly secured combinatorial locks at the molecular level that could pose valuable real time and on-site applications for user authentication.

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

A Strategic Design of an Opto-Chemical Security Device with Resettable and Reconfigurable Password Based Upon Dual Channel Two-in-One Chemosensor Molecule

NASA Astrophysics Data System (ADS)

Majumdar, Tapas; Haldar, Basudeb; Mallick, Arabinda

2017-02-01

A simple strategy is proposed to design and develop an intelligent device based on dual channel ion responsive spectral properties of a commercially available molecule, harmine (HM). The system can process different sets of opto-chemical inputs generating different patterns as fluorescence outputs at specific wavelengths which can provide an additional level of protection exploiting both password and pattern recognitions. The proposed system could have the potential to come up with highly secured combinatorial locks at the molecular level that could pose valuable real time and on-site applications for user authentication.

Page Oriented Holographic Memories And Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Caulfield, H. J.

1987-08-01

In the twenty-two years since VanderLugt's introduction of holographic matched filtering, the intensive research carried out throughout the world has led to no applications in complex environment. This leads one to the suspicion that the VanderLugt filter technique is insufficiently complex to handle truly complex problems. Therefore, it is of great interest to increase the complexity of the VanderLugt filtering operation. We introduce here an approach to the real time filter assembly: use of page oriented holographic memories and optically addressed SLMs to achieve intelligent and fast reprogramming of the filters using a 10 4 to 10 6 stored pattern base.

Next Generation Real-Time Systems: Investigating the Potential of Partial-Solution Tasks.

DTIC Science & Technology

1994-12-01

insufficient for dealing with the complexities of next-generation real - time systems . New methods of intelligent control must be developed for guaranteeing...on-time task completion for real - time systems that are faced with unpredictable and dynamically changing requirements. Implementing real-time...tasks by experimentally measuring the change in performance of 11 simulated real - time systems when converted from all-or-nothing tasks to partial

A conceptual framework for intelligent real-time information processing

NASA Technical Reports Server (NTRS)

Schudy, Robert

1987-01-01

By combining artificial intelligence concepts with the human information processing model of Rasmussen, a conceptual framework was developed for real time artificial intelligence systems which provides a foundation for system organization, control and validation. The approach is based on the description of system processing terms of an abstraction hierarchy of states of knowledge. The states of knowledge are organized along one dimension which corresponds to the extent to which the concepts are expressed in terms of the system inouts or in terms of the system response. Thus organized, the useful states form a generally triangular shape with the sensors and effectors forming the lower two vertices and the full evaluated set of courses of action the apex. Within the triangle boundaries are numerous processing paths which shortcut the detailed processing, by connecting incomplete levels of analysis to partially defined responses. Shortcuts at different levels of abstraction include reflexes, sensory motor control, rule based behavior, and satisficing. This approach was used in the design of a real time tactical decision aiding system, and in defining an intelligent aiding system for transport pilots.

Real time testing of intelligent relays for synchronous distributed generation islanding detection

NASA Astrophysics Data System (ADS)

Zhuang, Davy

As electric power systems continue to grow to meet ever-increasing energy demand, their security, reliability, and sustainability requirements also become more stringent. The deployment of distributed energy resources (DER), including generation and storage, in conventional passive distribution feeders, gives rise to integration problems involving protection and unintentional islanding. Distributed generators need to be islanded for safety reasons when disconnected or isolated from the main feeder as distributed generator islanding may create hazards to utility and third-party personnel, and possibly damage the distribution system infrastructure, including the distributed generators. This thesis compares several key performance indicators of a newly developed intelligent islanding detection relay, against islanding detection devices currently used by the industry. The intelligent relay employs multivariable analysis and data mining methods to arrive at decision trees that contain both the protection handles and the settings. A test methodology is developed to assess the performance of these intelligent relays on a real time simulation environment using a generic model based on a real-life distribution feeder. The methodology demonstrates the applicability and potential advantages of the intelligent relay, by running a large number of tests, reflecting a multitude of system operating conditions. The testing indicates that the intelligent relay often outperforms frequency, voltage and rate of change of frequency relays currently used for islanding detection, while respecting the islanding detection time constraints imposed by standing distributed generator interconnection guidelines.

Flightspeed Integral Image Analysis Toolkit

NASA Technical Reports Server (NTRS)

Thompson, David R.

2009-01-01

The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

Panel Discussion: Near Real Time Imagery Intelligence How Will We Do It?

NASA Astrophysics Data System (ADS)

Andraitis, Arthur A.; Crane, Alfred C.; Daniels, George; Graham, Johnny; LaGesse, Francis R.

1987-02-01

This afternoon's panel discussion will address near real time imagery and intelligence--how will we do it? Our moderator is Arthur Andraitis, a consultant in intelligence reconnaissance systems and international marketing. He was commissioned in the United States Air Force out of the University of Idaho, and entered the Air Force in 1955 where he became an Image Intelligence Officer serving in a variety of intelligence and reconnaisance related assignments, including two tours each in Asia and Europe supporting tactical theater and national level operations. He also suffered through two Pentagon tours--one as Branch Chief of the Imagery Branch for the Assistant Chief of Staff for Intelligence. He was the U. S. National Coordinator for two NATO intelligence and reconnaissance panels, and served several assignments in support of special operations, which included a year with the special forces in Viet Nam where he flew many missions in L-19s, 01 and assault helicopters. He has been an advisor on intelligence and reconnaissance matters to several foreign countries. In 1978 he retired from the United States Air Force, went to work for Itek, and then became an independent consultant in intelligence and reconaissance systems. I would like to introduce Art Andraitis.

Educational Assessment via a Web-Based Intelligent System

ERIC Educational Resources Information Center

Huang, Jingshan; He, Lei; Davidson-Shivers, Gayle V.

2011-01-01

Effective assessment is vital in educational activities. We propose IWAS (intelligent Web-based assessment system), an intelligent, generalized and real-time system to assess both learning and teaching. IWAS provides a foundation for more efficiency in instructional activities and, ultimately, students' performances. Our contributions are…

The application of connectionism to query planning/scheduling in intelligent user interfaces

NASA Technical Reports Server (NTRS)

Short, Nicholas, Jr.; Shastri, Lokendra

1990-01-01

In the mid nineties, the Earth Observing System (EOS) will generate an estimated 10 terabytes of data per day. This enormous amount of data will require the use of sophisticated technologies from real time distributed Artificial Intelligence (AI) and data management. Without regard to the overall problems in distributed AI, efficient models were developed for doing query planning and/or scheduling in intelligent user interfaces that reside in a network environment. Before intelligent query/planning can be done, a model for real time AI planning and/or scheduling must be developed. As Connectionist Models (CM) have shown promise in increasing run times, a connectionist approach to AI planning and/or scheduling is proposed. The solution involves merging a CM rule based system to a general spreading activation model for the generation and selection of plans. The system was implemented in the Rochester Connectionist Simulator and runs on a Sun 3/260.

PlanetSense: A Real-time Streaming and Spatio-temporal Analytics Platform for Gathering Geo-spatial Intelligence from Open Source Data

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

Thakur, Gautam S; Bhaduri, Budhendra L; Piburn, Jesse O

Geospatial intelligence has traditionally relied on the use of archived and unvarying data for planning and exploration purposes. In consequence, the tools and methods that are architected to provide insight and generate projections only rely on such datasets. Albeit, if this approach has proven effective in several cases, such as land use identification and route mapping, it has severely restricted the ability of researchers to inculcate current information in their work. This approach is inadequate in scenarios requiring real-time information to act and to adjust in ever changing dynamic environments, such as evacuation and rescue missions. In this work, wemore » propose PlanetSense, a platform for geospatial intelligence that is built to harness the existing power of archived data and add to that, the dynamics of real-time streams, seamlessly integrated with sophisticated data mining algorithms and analytics tools for generating operational intelligence on the fly. The platform has four main components i) GeoData Cloud a data architecture for storing and managing disparate datasets; ii) Mechanism to harvest real-time streaming data; iii) Data analytics framework; iv) Presentation and visualization through web interface and RESTful services. Using two case studies, we underpin the necessity of our platform in modeling ambient population and building occupancy at scale.« less

Socioscape: Real-Time Analysis of Dynamic Heterogeneous Networks In Complex Socio-Cultural Systems

DTIC Science & Technology

2015-10-22

Cluster Mixed-Membership Blockmodel for Time-Evolving Networks, Proceedings of the 14th International Conference on Artifical Intelligence and...Learning With Simultaneous Orthogonal Matching Pursuit, Proceedings of the 13th International Conference on Artifical Intelligence and Statistics

Novel wavelength diversity technique for high-speed atmospheric turbulence compensation

NASA Astrophysics Data System (ADS)

Arrasmith, William W.; Sullivan, Sean F.

2010-04-01

The defense, intelligence, and homeland security communities are driving a need for software dominant, real-time or near-real time atmospheric turbulence compensated imagery. The development of parallel processing capabilities are finding application in diverse areas including image processing, target tracking, pattern recognition, and image fusion to name a few. A novel approach to the computationally intensive case of software dominant optical and near infrared imaging through atmospheric turbulence is addressed in this paper. Previously, the somewhat conventional wavelength diversity method has been used to compensate for atmospheric turbulence with great success. We apply a new correlation based approach to the wavelength diversity methodology using a parallel processing architecture enabling high speed atmospheric turbulence compensation. Methods for optical imaging through distributed turbulence are discussed, simulation results are presented, and computational and performance assessments are provided.

TDAS: The Thermal Expert System (TEXSYS) data acquisition system

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Healey, Kathleen J.

1987-01-01

As part of the NASA Systems Autonomy Demonstration Project, a thermal expert system (TEXSYS) is being developed. TEXSYS combines a fast real time control system, a sophisticated human interface for the user and several distinct artificial intelligence techniques in one system. TEXSYS is to provide real time control, operations advice and fault detection, isolation and recovery capabilities for the space station Thermal Test Bed (TTB). TEXSYS will be integrated with the TTB and act as an intelligent assistant to thermal engineers conducting TTB tests and experiments. The results are presented from connecting the real time controller to the knowledge based system thereby creating an integrated system. Special attention will be paid to the problem of filtering and interpreting the raw, real time data and placing the important values into the knowledge base of the expert system.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

The implementation of CMOS sensors within a real time digital mammography intelligent imaging system: The I-ImaS System

NASA Astrophysics Data System (ADS)

Esbrand, C.; Royle, G.; Griffiths, J.; Speller, R.

2009-07-01

The integration of technology with healthcare has undoubtedly propelled the medical imaging sector well into the twenty first century. The concept of digital imaging introduced during the 1970s has since paved the way for established imaging techniques where digital mammography, phase contrast imaging and CT imaging are just a few examples. This paper presents a prototype intelligent digital mammography system designed and developed by a European consortium. The final system, the I-ImaS system, utilises CMOS monolithic active pixel sensor (MAPS) technology promoting on-chip data processing, enabling the acts of data processing and image acquisition to be achieved simultaneously; consequently, statistical analysis of tissue is achievable in real-time for the purpose of x-ray beam modulation via a feedback mechanism during the image acquisition procedure. The imager implements a dual array of twenty 520 pixel × 40 pixel CMOS MAPS sensing devices with a 32μm pixel size, each individually coupled to a 100μm thick thallium doped structured CsI scintillator. This paper presents the first intelligent images of real breast tissue obtained from the prototype system of real excised breast tissue where the x-ray exposure was modulated via the statistical information extracted from the breast tissue itself. Conventional images were experimentally acquired where the statistical analysis of the data was done off-line, resulting in the production of simulated real-time intelligently optimised images. The results obtained indicate real-time image optimisation using the statistical information extracted from the breast as a means of a feedback mechanisms is beneficial and foreseeable in the near future.

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.

A force vector and surface orientation sensor for intelligent grasping

NASA Technical Reports Server (NTRS)

Mcglasson, W. D.; Lorenz, R. D.; Duffie, N. A.; Gale, K. L.

1991-01-01

The paper discusses a force vector and surface orientation sensor suitable for intelligent grasping. The use of a novel four degree-of-freedom force vector robotic fingertip sensor allows efficient, real time intelligent grasping operations. The basis of sensing for intelligent grasping operations is presented and experimental results demonstrate the accuracy and ease of implementation of this approach.

Systems autonomy

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.

1988-01-01

Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.

Interfacing An Intelligent Decision-Maker To A Real-Time Control System

NASA Astrophysics Data System (ADS)

Evers, D. C.; Smith, D. M.; Staros, C. J.

1984-06-01

This paper discusses some of the practical aspects of implementing expert systems in a real-time environment. There is a conflict between the needs of a process control system and the computational load imposed by intelligent decision-making software. The computation required to manage a real-time control problem is primarily concerned with routine calculations which must be executed in real time. On most current hardware, non-trivial AI software should not be forced to operate under real-time constraints. In order for the system to work efficiently, the two processes must be separated by a well-defined interface. Although the precise nature of the task separation will vary with the application, the definition of the interface will need to follow certain fundamental principles in order to provide functional separation. This interface was successfully implemented in the expert scheduling software currently running the automated chemical processing facility at Lockheed-Georgia. Potential applications of this concept in the areas of airborne avionics and robotics will be discussed.

Designing and implementing transparency for real time inspection of autonomous robots

NASA Astrophysics Data System (ADS)

Theodorou, Andreas; Wortham, Robert H.; Bryson, Joanna J.

2017-07-01

The EPSRC's Principles of Robotics advises the implementation of transparency in robotic systems, however research related to AI transparency is in its infancy. This paper introduces the reader of the importance of having transparent inspection of intelligent agents and provides guidance for good practice when developing such agents. By considering and expanding upon other prominent definitions found in literature, we provide a robust definition of transparency as a mechanism to expose the decision-making of a robot. The paper continues by addressing potential design decisions developers need to consider when designing and developing transparent systems. Finally, we describe our new interactive intelligence editor, designed to visualise, develop and debug real-time intelligence.

Moving Smart in Rhode Island

DOT National Transportation Integrated Search

2004-06-01

Real-time transportation system information is a critical element in the development of Intelligent Transportation Systems (ITS). The Rhode Island Department of Transportation (RIDOT) is in the process of developing a fully integrated intelligent tra...

A software architecture for hard real-time execution of automatically synthesized plans or control laws

NASA Technical Reports Server (NTRS)

Schoppers, Marcel

1994-01-01

The design of a flexible, real-time software architecture for trajectory planning and automatic control of redundant manipulators is described. Emphasis is placed on a technique of designing control systems that are both flexible and robust yet have good real-time performance. The solution presented involves an artificial intelligence algorithm that dynamically reprograms the real-time control system while planning system behavior.

Expert system decision support for low-cost launch vehicle operations

NASA Technical Reports Server (NTRS)

Szatkowski, G. P.; Levin, Barry E.

1991-01-01

Progress in assessing the feasibility, benefits, and risks associated with AI expert systems applied to low cost expendable launch vehicle systems is described. Part one identified potential application areas in vehicle operations and on-board functions, assessed measures of cost benefit, and identified key technologies to aid in the implementation of decision support systems in this environment. Part two of the program began the development of prototypes to demonstrate real-time vehicle checkout with controller and diagnostic/analysis intelligent systems and to gather true measures of cost savings vs. conventional software, verification and validation requirements, and maintainability improvement. The main objective of the expert advanced development projects was to provide a robust intelligent system for control/analysis that must be performed within a specified real-time window in order to meet the demands of the given application. The efforts to develop the two prototypes are described. Prime emphasis was on a controller expert system to show real-time performance in a cryogenic propellant loading application and safety validation implementation of this system experimentally, using commercial-off-the-shelf software tools and object oriented programming techniques. This smart ground support equipment prototype is based in C with imbedded expert system rules written in the CLIPS protocol. The relational database, ORACLE, provides non-real-time data support. The second demonstration develops the vehicle/ground intelligent automation concept, from phase one, to show cooperation between multiple expert systems. This automated test conductor (ATC) prototype utilizes a knowledge-bus approach for intelligent information processing by use of virtual sensors and blackboards to solve complex problems. It incorporates distributed processing of real-time data and object-oriented techniques for command, configuration control, and auto-code generation.

Extensions to the Parallel Real-Time Artificial Intelligence System (PRAIS) for fault-tolerant heterogeneous cycle-stealing reasoning

NASA Technical Reports Server (NTRS)

Goldstein, David

1991-01-01

Extensions to an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS) are discussed. PRAIS strives for transparently parallelizing production (rule-based) systems, even under real-time constraints. PRAIS accomplished these goals (presented at the first annual C Language Integrated Production System (CLIPS) conference) by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors. Results using the original PRAIS architecture over a network of Sun 3's, Sun 4's and VAX's are presented. Mechanisms using the producer-consumer model to extend the architecture for fault-tolerance and distributed truth maintenance initiation are also discussed.

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

Acoustic Analyses and Intelligibility Assessments of Timing Patterns among Chinese English Learners with Different Dialect Backgrounds

ERIC Educational Resources Information Center

Chen, Hsueh Chu

2015-01-01

This paper includes two interrelated studies. The first production study investigates the timing patterns of English as spoken by Chinese learners with different dialect backgrounds. The second comprehension study explores native and non-native speakers' assessments of the intelligibility of Chinese-accented English, and examines the effects of…

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

PubMed Central

Leone, Giuseppe Riccardo; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea

2017-01-01

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities. PMID:29125535

An Intelligent Cooperative Visual Sensor Network for Urban Mobility.

PubMed

Leone, Giuseppe Riccardo; Moroni, Davide; Pieri, Gabriele; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea; Marino, Francesco

2017-11-10

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

Real-time continuous visual biofeedback in the treatment of speech breathing disorders following childhood traumatic brain injury: report of one case.

PubMed

Murdoch, B E; Pitt, G; Theodoros, D G; Ward, E C

1999-01-01

The efficacy of traditional and physiological biofeedback methods for modifying abnormal speech breathing patterns was investigated in a child with persistent dysarthria following severe traumatic brain injury (TBI). An A-B-A-B single-subject experimental research design was utilized to provide the subject with two exclusive periods of therapy for speech breathing, based on traditional therapy techniques and physiological biofeedback methods, respectively. Traditional therapy techniques included establishing optimal posture for speech breathing, explanation of the movement of the respiratory muscles, and a hierarchy of non-speech and speech tasks focusing on establishing an appropriate level of sub-glottal air pressure, and improving the subject's control of inhalation and exhalation. The biofeedback phase of therapy utilized variable inductance plethysmography (or Respitrace) to provide real-time, continuous visual biofeedback of ribcage circumference during breathing. As in traditional therapy, a hierarchy of non-speech and speech tasks were devised to improve the subject's control of his respiratory pattern. Throughout the project, the subject's respiratory support for speech was assessed both instrumentally and perceptually. Instrumental assessment included kinematic and spirometric measures, and perceptual assessment included the Frenchay Dysarthria Assessment, Assessment of Intelligibility of Dysarthric Speech, and analysis of a speech sample. The results of the study demonstrated that real-time continuous visual biofeedback techniques for modifying speech breathing patterns were not only effective, but superior to the traditional therapy techniques for modifying abnormal speech breathing patterns in a child with persistent dysarthria following severe TBI. These results show that physiological biofeedback techniques are potentially useful clinical tools for the remediation of speech breathing impairment in the paediatric dysarthric population.

Sleep stages identification in patients with sleep disorder using k-means clustering

NASA Astrophysics Data System (ADS)

Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

2018-05-01

Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

How feasible is the rapid development of artificial superintelligence?

NASA Astrophysics Data System (ADS)

Sotala, Kaj

2017-11-01

What kinds of fundamental limits are there in how capable artificial intelligence (AI) systems might become? Two questions in particular are of interest: (1) How much more capable could AI become relative to humans, and (2) how easily could superhuman capability be acquired? To answer these questions, we will consider the literature on human expertise and intelligence, discuss its relevance for AI, and consider how AI could improve on humans in two major aspects of thought and expertise, namely simulation and pattern recognition. We find that although there are very real limits to prediction, it seems like AI could still substantially improve on human intelligence.

Effectiveness of work zone intelligent transportation systems.

DOT National Transportation Integrated Search

2013-12-01

In the last decade, Intelligent Transportation Systems (ITS) have increasingly been deployed in work zones by state departments of transportation. Also known as smart work zone systems they improve traffic operations and safety by providing real-time...

Third Conference on Artificial Intelligence for Space Applications, part 2

NASA Technical Reports Server (NTRS)

Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

1988-01-01

Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed.

Intellectual interchanges in the history of the massive online open-editing encyclopedia, Wikipedia

NASA Astrophysics Data System (ADS)

Yun, Jinhyuk; Lee, Sang Hoon; Jeong, Hawoong

2016-01-01

Wikipedia is a free Internet encyclopedia with an enormous amount of content. This encyclopedia is written by volunteers with various backgrounds in a collective fashion; anyone can access and edit most of the articles. This open-editing nature may give us prejudice that Wikipedia is an unstable and unreliable source; yet many studies suggest that Wikipedia is even more accurate and self-consistent than traditional encyclopedias. Scholars have attempted to understand such extraordinary credibility, but usually used the number of edits as the unit of time, without consideration of real time. In this work, we probe the formation of such collective intelligence through a systematic analysis using the entire history of 34 534 110 English Wikipedia articles, between 2001 and 2014. From this massive data set, we observe the universality of both timewise and lengthwise editing scales, which suggests that it is essential to consider the real-time dynamics. By considering real time, we find the existence of distinct growth patterns that are unobserved by utilizing the number of edits as the unit of time. To account for these results, we present a mechanistic model that adopts the article editing dynamics based on both editor-editor and editor-article interactions. The model successfully generates the key properties of real Wikipedia articles such as distinct types of articles for the editing patterns characterized by the interrelationship between the numbers of edits and editors, and the article size. In addition, the model indicates that infrequently referred articles tend to grow faster than frequently referred ones, and articles attracting a high motivation to edit counterintuitively reduce the number of participants. We suggest that this decay of participants eventually brings inequality among the editors, which will become more severe with time.

Intellectual interchanges in the history of the massive online open-editing encyclopedia, Wikipedia.

PubMed

Yun, Jinhyuk; Lee, Sang Hoon; Jeong, Hawoong

2016-01-01

Wikipedia is a free Internet encyclopedia with an enormous amount of content. This encyclopedia is written by volunteers with various backgrounds in a collective fashion; anyone can access and edit most of the articles. This open-editing nature may give us prejudice that Wikipedia is an unstable and unreliable source; yet many studies suggest that Wikipedia is even more accurate and self-consistent than traditional encyclopedias. Scholars have attempted to understand such extraordinary credibility, but usually used the number of edits as the unit of time, without consideration of real time. In this work, we probe the formation of such collective intelligence through a systematic analysis using the entire history of 34534110 English Wikipedia articles, between 2001 and 2014. From this massive data set, we observe the universality of both timewise and lengthwise editing scales, which suggests that it is essential to consider the real-time dynamics. By considering real time, we find the existence of distinct growth patterns that are unobserved by utilizing the number of edits as the unit of time. To account for these results, we present a mechanistic model that adopts the article editing dynamics based on both editor-editor and editor-article interactions. The model successfully generates the key properties of real Wikipedia articles such as distinct types of articles for the editing patterns characterized by the interrelationship between the numbers of edits and editors, and the article size. In addition, the model indicates that infrequently referred articles tend to grow faster than frequently referred ones, and articles attracting a high motivation to edit counterintuitively reduce the number of participants. We suggest that this decay of participants eventually brings inequality among the editors, which will become more severe with time.

Execution environment for intelligent real-time control systems

NASA Technical Reports Server (NTRS)

Sztipanovits, Janos

1987-01-01

Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment.

Commanding and Controlling Satellite Clusters (IEEE Intelligent Systems, November/December 2000)

DTIC Science & Technology

2000-01-01

real - time operating system , a message-passing OS well suited for distributed...ground Flight processors ObjectAgent RTOS SCL RTOS RDMS Space command language Real - time operating system Rational database management system TS-21 RDMS...engineer with Princeton Satellite Systems. She is working with others to develop ObjectAgent software to run on the OSE Real Time Operating System .

Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

ERIC Educational Resources Information Center

Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

2010-01-01

Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

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.

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.

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

PubMed

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

MobileASL: intelligibility of sign language video over mobile phones.

PubMed

Cavender, Anna; Vanam, Rahul; Barney, Dane K; Ladner, Richard E; Riskin, Eve A

2008-01-01

For Deaf people, access to the mobile telephone network in the United States is currently limited to text messaging, forcing communication in English as opposed to American Sign Language (ASL), the preferred language. Because ASL is a visual language, mobile video phones have the potential to give Deaf people access to real-time mobile communication in their preferred language. However, even today's best video compression techniques can not yield intelligible ASL at limited cell phone network bandwidths. Motivated by this constraint, we conducted one focus group and two user studies with members of the Deaf Community to determine the intelligibility effects of video compression techniques that exploit the visual nature of sign language. Inspired by eye tracking results that show high resolution foveal vision is maintained around the face, we studied region-of-interest encodings (where the face is encoded at higher quality) as well as reduced frame rates (where fewer, better quality, frames are displayed every second). At all bit rates studied here, participants preferred moderate quality increases in the face region, sacrificing quality in other regions. They also preferred slightly lower frame rates because they yield better quality frames for a fixed bit rate. The limited processing power of cell phones is a serious concern because a real-time video encoder and decoder will be needed. Choosing less complex settings for the encoder can reduce encoding time, but will affect video quality. We studied the intelligibility effects of this tradeoff and found that we can significantly speed up encoding time without severely affecting intelligibility. These results show promise for real-time access to the current low-bandwidth cell phone network through sign-language-specific encoding techniques.

Dynamic Restructuring Of Problems In Artificial Intelligence

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1992-01-01

"Dynamic tradeoff evaluation" (DTE) denotes proposed method and procedure for restructuring problem-solving strategies in artificial intelligence to satisfy need for timely responses to changing conditions. Detects situations in which optimal problem-solving strategies cannot be pursued because of real-time constraints, and effects tradeoffs among nonoptimal strategies in such way to minimize adverse effects upon performance of system.

Implementation of an Intelligent Control System

DTIC Science & Technology

1992-05-01

there- fore implemented in a portable equipment rack. The controls computer consists of a microcomputer running a real time operating system , interface...circuit boards are mounted in an industry standard Multibus I chassis. The microcomputer runs the iRMX real time operating system . This operating system

Secure, Autonomous, Intelligent Controller for Integrating Distributed Sensor Webs

NASA Technical Reports Server (NTRS)

Ivancic, William D.

2007-01-01

This paper describes the infrastructure and protocols necessary to enable near-real-time commanding, access to space-based assets, and the secure interoperation between sensor webs owned and controlled by various entities. Select terrestrial and aeronautics-base sensor webs will be used to demonstrate time-critical interoperability between integrated, intelligent sensor webs both terrestrial and between terrestrial and space-based assets. For this work, a Secure, Autonomous, Intelligent Controller and knowledge generation unit is implemented using Virtual Mission Operation Center technology.

Airborne wildfire intelligence system: a decision support tool for wildland fire managers in Alberta

NASA Astrophysics Data System (ADS)

Campbell, Doug; Born, Wally G.; Beck, Judi; Bereska, Bill; Frederick, Kurt; Hua, Sun

2002-03-01

The Airborne Wildfire Intelligence System (AWIS) defines the state-of-the-art in remotely sensed wildfire intelligence. AWIS is a commercial, automated, intelligence service, delivering GIS integrated fire intelligence, classified interpretive and analysis layers, and higher level decision support products for wildfires in near real time via the Internet. The AWIS effort illustrates flexible and dynamic cooperation between industry and government to combine technology with field knowledge and experience into an effective, optimized end-user tool. In Alberta the Forest Protection Division of the department of Sustainable Resource Development uses AWIS for several applications: holdover and wildfire hotspot detection, fire front and burned area perimeter mapping, strategic and tactical support through 3D visualization, research into the effects of fire and its severity and to document burn patterns across the landscape. A discussion of all of the scientific themes behind the AWIS is outside the scope of this paper, however, the science of sub-element detection will be reviewed. An independent study has been conducted by the Forest Engineering Research Institute of Canada (FERIC) to investigate the capability of a variety of thermal infrared remote sensing systems to detect small and subtle hotspots in an effort to identify the strengths and weaknesses thereof. As a result of this work, method suitability guidelines have been established to match appropriate infrared technology with a given wildfire management objective.

ISTAR: Intelligent System for Telemetry Analysis in Real-time

NASA Technical Reports Server (NTRS)

Simmons, Charles

1994-01-01

The intelligent system for telemetry analysis in real-time (ISTAR) is an advanced vehicle monitoring environment incorporating expert systems, analysis tools, and on-line hypermedia documentation. The system was developed for the Air Force Space and Missile Systems Center (SMC) in Los Angeles, California, in support of the inertial upper stage (IUS) booster vehicle. Over a five year period the system progressed from rapid prototype to operational system. ISTAR has been used to support five IUS missions and countless mission simulations. There were a significant number of lessons learned with respect to integrating an expert system capability into an existing ground system.

Robust intelligent flight control for hypersonic vehicles. Ph.D. Thesis - Massachusetts Inst. of Technology

NASA Technical Reports Server (NTRS)

Chamitoff, Gregory Errol

1992-01-01

Intelligent optimization methods are applied to the problem of real-time flight control for a class of airbreathing hypersonic vehicles (AHSV). The extreme flight conditions that will be encountered by single-stage-to-orbit vehicles, such as the National Aerospace Plane, present a tremendous challenge to the entire spectrum of aerospace technologies. Flight control for these vehicles is particularly difficult due to the combination of nonlinear dynamics, complex constraints, and parametric uncertainty. An approach that utilizes all available a priori and in-flight information to perform robust, real time, short-term trajectory planning is presented.

Artificial Intelligence in Autonomous Telescopes

NASA Astrophysics Data System (ADS)

Mahoney, William; Thanjavur, Karun

2011-03-01

Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

Evaluation report for ITS for voluntary emission reduction : an ITS operational test for real-time vehicle emissions detection

DOT National Transportation Integrated Search

1997-05-01

The Intelligent Transport Systems (ITS) Operation Test Project was designed to assess the potential of ITS to support cleaner air by providing real-time vehicle tailpipe emissions information (carbon monoxide levels) to the driving public. It made...

Variable Generation Power Forecasting as a Big Data Problem

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

Haupt, Sue Ellen; Kosovic, Branko

To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model andmore » observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.« less

Variable Generation Power Forecasting as a Big Data Problem

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko

2016-10-10

To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model andmore » observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.« less

Development of a New Intelligent Joystick for People with Reduced Mobility.

PubMed

Mrabet, Makrem; Rabhi, Yassine; Fnaiech, Farhat

2018-01-01

Despite the diversity of electric wheelchairs, many people with physical limitations and seniors have difficulty using their standard joystick. As a result, they cannot meet their needs or ensure safe travel. Recent assistive technologies can help to give them autonomy and independence. This work deals with the real-time implementation of an artificial intelligence device to overcome these problems. Following a review of the literature from previous work, we present the methodology and process for implementing our intelligent control system on an electric wheelchair. The system is based on a neural algorithm that overcomes problems with standard joystick maneuvers such as the inability to move correctly in one direction. However, this implies the need for an appropriate methodology to map the position of the joystick handle. Experiments on a real wheelchair are carried out with real patients of the Mohamed Kassab National Institute Orthopedic, Physical and Functional Rehabilitation Hospital of Tunis. The proposed intelligent system gives good results compared to the use of a standard joystick.

Development of a New Intelligent Joystick for People with Reduced Mobility

PubMed Central

Mrabet, Makrem; Fnaiech, Farhat

2018-01-01

Despite the diversity of electric wheelchairs, many people with physical limitations and seniors have difficulty using their standard joystick. As a result, they cannot meet their needs or ensure safe travel. Recent assistive technologies can help to give them autonomy and independence. This work deals with the real-time implementation of an artificial intelligence device to overcome these problems. Following a review of the literature from previous work, we present the methodology and process for implementing our intelligent control system on an electric wheelchair. The system is based on a neural algorithm that overcomes problems with standard joystick maneuvers such as the inability to move correctly in one direction. However, this implies the need for an appropriate methodology to map the position of the joystick handle. Experiments on a real wheelchair are carried out with real patients of the Mohamed Kassab National Institute Orthopedic, Physical and Functional Rehabilitation Hospital of Tunis. The proposed intelligent system gives good results compared to the use of a standard joystick. PMID:29765462

Fault Diagnosis of Power Systems Using Intelligent Systems

NASA Technical Reports Server (NTRS)

Momoh, James A.; Oliver, Walter E. , Jr.

1996-01-01

The power system operator's need for a reliable power delivery system calls for a real-time or near-real-time Al-based fault diagnosis tool. Such a tool will allow NASA ground controllers to re-establish a normal or near-normal degraded operating state of the EPS (a DC power system) for Space Station Alpha by isolating the faulted branches and loads of the system. And after isolation, re-energizing those branches and loads that have been found not to have any faults in them. A proposed solution involves using the Fault Diagnosis Intelligent System (FDIS) to perform near-real time fault diagnosis of Alpha's EPS by downloading power transient telemetry at fault-time from onboard data loggers. The FDIS uses an ANN clustering algorithm augmented with a wavelet transform feature extractor. This combination enables this system to perform pattern recognition of the power transient signatures to diagnose the fault type and its location down to the orbital replaceable unit. FDIS has been tested using a simulation of the LeRC Testbed Space Station Freedom configuration including the topology from the DDCU's to the electrical loads attached to the TPDU's. FDIS will work in conjunction with the Power Management Load Scheduler to determine what the state of the system was at the time of the fault condition. This information is used to activate the appropriate diagnostic section, and to refine if necessary the solution obtained. In the latter case, if the FDIS reports back that it is equally likely that the faulty device as 'start tracker #1' and 'time generation unit,' then based on a priori knowledge of the system's state, the refined solution would be 'star tracker #1' located in cabinet ITAS2. It is concluded from the present studies that artificial intelligence diagnostic abilities are improved with the addition of the wavelet transform, and that when such a system such as FDIS is coupled to the Power Management Load Scheduler, a faulty device can be located and isolated from the rest of the system. The benefit of these studies provides NASA with the ability to quickly restore the operating status of a space station from a critical state to a safe degraded mode, thereby saving costs in experimentation rescheduling, fault diagnostics, and prevention of loss-of-life.

Simulation of intelligent object behavior in a virtual reality system

NASA Astrophysics Data System (ADS)

Mironov, Sergey F.

1998-01-01

This article presents a technique for computer control of a power boat movement in real-time marine trainers or arcade games. The author developed and successfully implemented a general technique allowing intellectual navigation of computer controlled moving objects that proved to be appropriate for real-time applications. This technique covers significant part of necessary behavioral tasks that appear in such titles. At the same time the technique forms a part of a more general system that involves control of less complicated characters of another nature. The system being an open one can be easily used by an action or arcade programming to improve the overall quality of characters artificial intelligence style.

PERTS: A Prototyping Environment for Real-Time Systems

NASA Technical Reports Server (NTRS)

Liu, Jane W. S.; Lin, Kwei-Jay; Liu, C. L.

1991-01-01

We discuss an ongoing project to build a Prototyping Environment for Real-Time Systems, called PERTS. PERTS is a unique prototyping environment in that it has (1) tools and performance models for the analysis and evaluation of real-time prototype systems, (2) building blocks for flexible real-time programs and the support system software, (3) basic building blocks of distributed and intelligent real time applications, and (4) an execution environment. PERTS will make the recent and future theoretical advances in real-time system design and engineering readily usable to practitioners. In particular, it will provide an environment for the use and evaluation of new design approaches, for experimentation with alternative system building blocks and for the analysis and performance profiling of prototype real-time systems.

PRAIS: Distributed, real-time knowledge-based systems made easy

NASA Technical Reports Server (NTRS)

Goldstein, David G.

1990-01-01

This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

An intelligent system for real time automatic defect inspection on specular coated surfaces

NASA Astrophysics Data System (ADS)

Li, Jinhua; Parker, Johné M.; Hou, Zhen

2005-07-01

Product visual inspection is still performed manually or semi automatically in most industries from simple ceramic tile grading to complex automotive body panel paint defect and surface quality inspection. Moreover, specular surfaces present additional challenge to conventional vision systems due to specular reflections, which may mask the true location of objects and lead to incorrect measurements. There are some sophisticated visual inspection methods developed in recent years. Unfortunately, most of them are highly computational. Systems built on those methods are either inapplicable or very costly to achieve real time inspection. In this paper, we describe an integrated low-cost intelligent system developed to automatically capture, extract, and segment defects on specular surfaces with uniform color coatings. The system inspects and locates regular surface defects with lateral dimensions as small as a millimeter. The proposed system is implemented on a group of smart cameras using its on-board processing ability to achieve real time inspection. The experimental results on real test panels demonstrate the effectiveness and robustness of proposed system.

Automated planning for intelligent machines in energy-related applications

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

Weisbin, C.R.; de Saussure, G.; Barhen, J.

1984-01-01

This paper discusses the current activities of the Center for Engineering Systems Advanced Research (CESAR) program related to plan generation and execution by an intelligent machine. The system architecture for the CESAR mobile robot (named HERMIES-1) is described. The minimal cut-set approach is developed to reduce the tree search time of conventional backward chaining planning techniques. Finally, a real-time concept of an Intelligent Machine Operating System is presented in which planning and reasoning is embedded in a system for resource allocation and process management.

Sandia National Laboratories: Pathfinder Radar ISR and Synthetic Aperture

Science.gov Websites

Eyes for the Warfighter Actionable Intelligence for the Decision Maker Actionable Intelligence for the Decision Maker All Weather, Persistent, Optical Like All Weather, Persistent, Optical Like Real-time, High radar systems encompass the entire end-to-end connectivity needed for decision superiority to ensure

[Temperature Measurement with Bluetooth under Android Platform].

PubMed

Wang, Shuai; Shen, Hao; Luo, Changze

2015-03-01

To realize the real-time transmission of temperature data and display using the platform of intelligent mobile phone and bluetooth. Application of Arduino Uno R3 in temperature data acquisition of digital temperature sensor DS18B20 acquisition, through the HC-05 bluetooth transmits the data to the intelligent smart phone Android system, realizes transmission of temperature data. Using Java language to write applications program under Android development environment, can achieve real-time temperature data display, storage and drawing temperature fluctuations drawn graphics. Temperature sensor is experimentally tested to meet the body temperature measurement precision and accuracy. This paper can provide a reference for other smart phone mobile medical product development.

Features: Real-Time Adaptive Feature and Document Learning for Web Search.

ERIC Educational Resources Information Center

Chen, Zhixiang; Meng, Xiannong; Fowler, Richard H.; Zhu, Binhai

2001-01-01

Describes Features, an intelligent Web search engine that is able to perform real-time adaptive feature (i.e., keyword) and document learning. Explains how Features learns from users' document relevance feedback and automatically extracts and suggests indexing keywords relevant to a search query, and learns from users' keyword relevance feedback…

Flight elements: Fault detection and fault management

NASA Technical Reports Server (NTRS)

Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

1990-01-01

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

Demonstrating artificial intelligence for space systems - Integration and project management issues

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Difilippo, Denise M.

1990-01-01

As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

Applying predictive analytics to develop an intelligent risk detection application for healthcare contexts.

PubMed

Moghimi, Fatemeh Hoda; Cheung, Michael; Wickramasinghe, Nilmini

2013-01-01

Healthcare is an information rich industry where successful outcomes require the processing of multi-spectral data and sound decision making. The exponential growth of data and big data issues coupled with a rapid increase of service demands in healthcare contexts today, requires a robust framework enabled by IT (information technology) solutions as well as real-time service handling in order to ensure superior decision making and successful healthcare outcomes. Such a context is appropriate for the application of real time intelligent risk detection decision support systems using predictive analytic techniques such as data mining. To illustrate the power and potential of data science technologies in healthcare decision making scenarios, the use of an intelligent risk detection (IRD) model is proffered for the context of Congenital Heart Disease (CHD) in children, an area which requires complex high risk decisions that need to be made expeditiously and accurately in order to ensure successful healthcare outcomes.

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.

Intelligent detection of cracks in metallic surfaces using a waveguide sensor loaded with metamaterial elements.

PubMed

Ali, Abdulbaset; Hu, Bing; Ramahi, Omar

2015-05-15

This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classification accuracy rates.

Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements

PubMed Central

Ali, Abdulbaset; Hu, Bing; Ramahi, Omar M.

2015-01-01

This work presents a real-life experiment implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impacts in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing the data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks, and the experimental results showed good crack classification accuracy rates. PMID:25988871

Explaining How to Play Real-Time Strategy Games

NASA Astrophysics Data System (ADS)

Metoyer, Ronald; Stumpf, Simone; Neumann, Christoph; Dodge, Jonathan; Cao, Jill; Schnabel, Aaron

Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.

A novel fiber-optical vibration defending system with on-line intelligent identification function

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Xie, Xin; Li, Hanyu; Li, Xiaoyu; Wu, Yu; Gong, Yuan; Rao, Yunjiang

2013-09-01

Capacity of the sensor network is always a bottleneck problem for the novel FBG-based quasi-distributed fiberoptical defending system. In this paper, a highly sensitive sensing network with FBG vibration sensors is presented to relieve stress of the capacity and the system cost. However, higher sensitivity may cause higher Nuisance Alarm Rates (NARs) in practical uses. It is necessary to further classify the intrusion pattern or threat level and determine the validity of an unexpected event. Then an intelligent identification method is proposed by extracting the statistical features of the vibration signals in the time domain, and inputting them into a 3-layer Back-Propagation(BP) Artificial Neural Network to classify the events of interest. Experiments of both simulation and field tests are carried out to validate its effectiveness. The results show the recognition rate can be achieved up to 100% for the simulation signals and as high as 96.03% in the real tests.

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.

Cloud based intelligent system for delivering health care as a service.

PubMed

Kaur, Pankaj Deep; Chana, Inderveer

2014-01-01

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Airborne net-centric multi-INT sensor control, display, fusion, and exploitation systems

NASA Astrophysics Data System (ADS)

Linne von Berg, Dale C.; Lee, John N.; Kruer, Melvin R.; Duncan, Michael D.; Olchowski, Fred M.; Allman, Eric; Howard, Grant

2004-08-01

The NRL Optical Sciences Division has initiated a multi-year effort to develop and demonstrate an airborne net-centric suite of multi-intelligence (multi-INT) sensors and exploitation systems for real-time target detection and targeting product dissemination. The goal of this Net-centric Multi-Intelligence Fusion Targeting Initiative (NCMIFTI) is to develop an airborne real-time intelligence gathering and targeting system that can be used to detect concealed, camouflaged, and mobile targets. The multi-INT sensor suite will include high-resolution visible/infrared (EO/IR) dual-band cameras, hyperspectral imaging (HSI) sensors in the visible-to-near infrared, short-wave and long-wave infrared (VNIR/SWIR/LWIR) bands, Synthetic Aperture Radar (SAR), electronics intelligence sensors (ELINT), and off-board networked sensors. Other sensors are also being considered for inclusion in the suite to address unique target detection needs. Integrating a suite of multi-INT sensors on a single platform should optimize real-time fusion of the on-board sensor streams, thereby improving the detection probability and reducing the false alarms that occur in reconnaissance systems that use single-sensor types on separate platforms, or that use independent target detection algorithms on multiple sensors. In addition to the integration and fusion of the multi-INT sensors, the effort is establishing an open-systems net-centric architecture that will provide a modular "plug and play" capability for additional sensors and system components and provide distributed connectivity to multiple sites for remote system control and exploitation.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

An intelligent anti-jamming network system of data link

NASA Astrophysics Data System (ADS)

Fan, Xiangrui; Lin, Jingyong; Liu, Jiarun; Zhou, Chunmei

2017-10-01

Data link is the key information system for the cooperation of weapons, single physical layer anti-jamming technology has been unable to meet its requirements. High dynamic precision-guided weapon nodes like missiles, anti-jamming design of data link system need to have stronger pertinence and effectiveness: the best anti-jamming communication mode can be selected intelligently in combat environment, in real time, guarantee the continuity of communication. We discuss an anti-jamming intelligent networking technology of data link based on interference awareness, put forward a model of intelligent anti-jamming system, and introduces the cognitive node protocol stack model and intelligent anti-jamming method, in order to improve the data chain of intelligent anti-jamming ability.

Real Time Conference 2014 Overview

NASA Astrophysics Data System (ADS)

Nomachi, Masaharu

2015-06-01

This article presents an overview of the 19th Real Time Conference held last May 26-30, 2014, at the Nara Prefectural New Public Hall, Nara, Japan, organized by the Research Center for Nuclear Physics of the Osaka University. The program included many invited talks and oral sessions offering an extensive overview on the following topics: real-time system architectures, intelligent signal processing, fast data transfer links and networks, trigger systems, data acquisition, processing-farms, control, monitoring and test systems, emerging real-time technologies, new standards, real-time safety and security, and some feedback on experiences. In parallel to the oral and poster presentations, industrial exhibits by companies, workshops and short courses also ran through the week.

Scientific & Intelligence Exascale Visualization Analysis System

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

Money, James H.

SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.

Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Duong, Vu A.

2012-01-01

A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.

Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

NASA Astrophysics Data System (ADS)

Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

2017-09-01

Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

NASA Astrophysics Data System (ADS)

Dieckman, Eric Allen

In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

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.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

SETI meets a social intelligence: Dolphins as a model for real-time interaction and communication with a sentient species

NASA Astrophysics Data System (ADS)

Herzing, Denise L.

2010-12-01

In the past SETI has focused on the reception and deciphering of radio signals from potential remote civilizations. It is conceivable that real-time contact and interaction with a social intelligence may occur in the future. A serious look at the development of relationship, and deciphering of communication signals within and between a non-terrestrial, non-primate sentient species is relevant. Since 1985 a resident community of free-ranging Atlantic spotted dolphins has been observed regularly in the Bahamas. Life history, relationships, regular interspecific interactions with bottlenose dolphins, and multi-modal underwater communication signals have been documented. Dolphins display social communication signals modified for water, their body types, and sensory systems. Like anthropologists, human researchers engage in benign observation in the water and interact with these dolphins to develop rapport and trust. Many individual dolphins have been known for over 20 years. Learning the culturally appropriate etiquette has been important in the relationship with this alien society. To engage humans in interaction the dolphins often initiate spontaneous displays, mimicry, imitation, and synchrony. These elements may be emergent/universal features of one intelligent species contacting another for the intention of initiating interaction. This should be a consideration for real-time contact and interaction for future SETI work.

Convergence in full motion video processing, exploitation, and dissemination and activity based intelligence

NASA Astrophysics Data System (ADS)

Phipps, Marja; Lewis, Gina

2012-06-01

Over the last decade, intelligence capabilities within the Department of Defense/Intelligence Community (DoD/IC) have evolved from ad hoc, single source, just-in-time, analog processing; to multi source, digitally integrated, real-time analytics; to multi-INT, predictive Processing, Exploitation and Dissemination (PED). Full Motion Video (FMV) technology and motion imagery tradecraft advancements have greatly contributed to Intelligence, Surveillance and Reconnaissance (ISR) capabilities during this timeframe. Imagery analysts have exploited events, missions and high value targets, generating and disseminating critical intelligence reports within seconds of occurrence across operationally significant PED cells. Now, we go beyond FMV, enabling All-Source Analysts to effectively deliver ISR information in a multi-INT sensor rich environment. In this paper, we explore the operational benefits and technical challenges of an Activity Based Intelligence (ABI) approach to FMV PED. Existing and emerging ABI features within FMV PED frameworks are discussed, to include refined motion imagery tools, additional intelligence sources, activity relevant content management techniques and automated analytics.

Perspective on intelligent avionics

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

Jones, H.L.

1987-01-01

Technical issues which could potentially limit the capability and acceptibility of expert systems decision-making for avionics applications are addressed. These issues are: real-time AI, mission-critical software, conventional algorithms, pilot interface, knowledge acquisition, and distributed expert systems. Examples from on-going expert system development programs are presented to illustrate likely architectures and applications of future intelligent avionic systems. 13 references.

A situation-response model for intelligent pilot aiding

NASA Technical Reports Server (NTRS)

Schudy, Robert; Corker, Kevin

1987-01-01

An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations.

Data Partitioning and Load Balancing in Parallel Disk Systems

NASA Technical Reports Server (NTRS)

Scheuermann, Peter; Weikum, Gerhard; Zabback, Peter

1997-01-01

Parallel disk systems provide opportunities for exploiting I/O parallelism in two possible waves, namely via inter-request and intra-request parallelism. In this paper we discuss the main issues in performance tuning of such systems, namely striping and load balancing, and show their relationship to response time and throughput. We outline the main components of an intelligent, self-reliant file system that aims to optimize striping by taking into account the requirements of the applications and performs load balancing by judicious file allocation and dynamic redistributions of the data when access patterns change. Our system uses simple but effective heuristics that incur only little overhead. We present performance experiments based on synthetic workloads and real-life traces.

Firearm microstamping technology: counterinsurgency intelligence gathering tool

NASA Astrophysics Data System (ADS)

Lizotte, Todd E.; Ohar, Orest P.

2009-05-01

Warfare relies on effective, accurate and timely intelligence an especially critical task when conducting a counterinsurgency operation [1]. Simply stated counterinsurgency is an intelligence war. Both insurgents and counterinsurgents need effective intelligence capabilities to be successful. Insurgents and counterinsurgents therefore attempt to create and maintain intelligence networks and fight continuously to neutralize each other's intelligence capabilities [1][2]. In such an environment it is obviously an advantage to target or proactively create opportunities to track and map an insurgent movement. Quickly identifying insurgency intelligence assets (Infiltrators) within a host government's infrastructure is the goal. Infiltrators can occupy various areas of government such as security personnel, national police force, government offices or military units. Intentional Firearm Microstamping offers such opportunities when implemented into firearms. Outfitted within firearms purchased and distributed to the host nation's security forces (civilian and military), Intentional Firearm Microstamping (IFM) marks bullet cartridge casings with codes as they are fired from the firearm. IFM is incorporated onto optimum surfaces with the firearm mechanism. The intentional microstamp tooling marks can take the form of alphanumeric codes or encoded geometric codes that identify the firearm. As the firearm is discharged the intentional tooling marks transfer a code to the cartridge casing which is ejected out of the firearm. When recovered at the scene of a firefight or engagement, the technology will provide forensic intelligence allowing the mapping and tracking of small arms traffic patterns within the host nation or identify insurgency force strength and pinpoint firearm sources, such as corrupt/rogue military units or police force. Intentional Firearm Microstamping is a passive mechanical trace technology that can be outfitted or retrofitted to semiautomatic handguns and military rifles to assist in developing real time intelligence providing a greater level of situational awareness. Proactively Microstamping firearms that are introduced and distributed to the host nation's security forces, it will become easier to track the firearms if they go missing or end up on the black market in the hands of an insurgency. This paper will explain the technology and key attributes of microstamping technology, test data showing its ability to identifying a specific firearm, examples of implementation strategies and to what extent data could be utilized in war zone security and counterinsurgency intelligence operations.

Laser formed intentional firearm microstamping technology: counterinsurgency intelligence gathering tool

NASA Astrophysics Data System (ADS)

Lizotte, Todd E.; Ohar, Orest P.

2009-09-01

Warfare relies on effective, accurate and timely intelligence an especially critical task when conducting a counterinsurgency operation [1]. Simply stated counterinsurgency is an intelligence war. Both insurgents and counterinsurgents need effective intelligence capabilities to be successful. Insurgents and counterinsurgents therefore attempt to create and maintain intelligence networks and fight continuously to neutralize each other's intelligence capabilities [1][2]. In such an environment it is obviously an advantage to target or proactively create opportunities to track and map an insurgent movement. Quickly identifying insurgency intelligence assets (Infiltrators) within a host government's infrastructure is the goal. Infiltrators can occupy various areas of government such as security personnel, national police force, government offices or military units. Intentional Firearm Microstamping offers such opportunities when implemented into firearms. Outfitted within firearms purchased and distributed to the host nation's security forces (civilian and military), Intentional Firearm Microstamping (IFM) marks bullet cartridge casings with codes as they are fired from the firearm. IFM is incorporated onto optimum surfaces with the firearm mechanism. The intentional microstamp tooling marks can take the form of alphanumeric codes or encoded geometric codes that identify the firearm. As the firearm is discharged the intentional tooling marks transfer a code to the cartridge casing which is ejected out of the firearm. When recovered at the scene of a firefight or engagement, the technology will provide forensic intelligence allowing the mapping and tracking of small arms traffic patterns within the host nation or identify insurgency force strength and pinpoint firearm sources, such as corrupt/rogue military units or police force. Intentional Firearm Microstamping is a passive mechanical trace technology that can be outfitted or retrofitted to semiautomatic handguns and military rifles to assist in developing real time intelligence providing a greater level of situational awareness. Proactively Microstamping firearms that are introduced and distributed to the host nation's security forces, it will become easier to track the firearms if they go missing or end up on the black market in the hands of an insurgency. This paper will explain the technology and key attributes of microstamping technology, test data showing its ability to identifying a specific firearm, examples of implementation strategies and to what extent data could be utilized in war zone security and counterinsurgency intelligence operations.

IVHM Framework for Intelligent Integration for Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre; Trevino, Luis C.; Watson, Michael D.

2005-01-01

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Real-Time Aggressive Image Data Compression

DTIC Science & Technology

1990-03-31

implemented with higher degrees of modularity, concurrency, and higher levels of machine intelligence , thereby providing higher data -throughput rates...Project Summary Project Title: Real-Time Aggressive Image Data Compression Principal Investigators: Dr. Yih-Fang Huang and Dr. Ruey-wen Liu Institution...Summary The objective of the proposed research is to develop reliable algorithms !.hat can achieve aggressive image data compression (with a compression

Software Analyzes Complex Systems in Real Time

NASA Technical Reports Server (NTRS)

2008-01-01

Expert system software programs, also known as knowledge-based systems, are computer programs that emulate the knowledge and analytical skills of one or more human experts, related to a specific subject. SHINE (Spacecraft Health Inference Engine) is one such program, a software inference engine (expert system) designed by NASA for the purpose of monitoring, analyzing, and diagnosing both real-time and non-real-time systems. It was developed to meet many of the Agency s demanding and rigorous artificial intelligence goals for current and future needs. NASA developed the sophisticated and reusable software based on the experience and requirements of its Jet Propulsion Laboratory s (JPL) Artificial Intelligence Research Group in developing expert systems for space flight operations specifically, the diagnosis of spacecraft health. It was designed to be efficient enough to operate in demanding real time and in limited hardware environments, and to be utilized by non-expert systems applications written in conventional programming languages. The technology is currently used in several ongoing NASA applications, including the Mars Exploration Rovers and the Spacecraft Health Automatic Reasoning Pilot (SHARP) program for the diagnosis of telecommunication anomalies during the Neptune Voyager Encounter. It is also finding applications outside of the Space Agency.

An Object-Oriented Graphical User Interface for a Reusable Rocket Engine Intelligent Control System

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Musgrave, Jeffrey L.; Guo, Ten-Huei; Paxson, Daniel E.; Wong, Edmond; Saus, Joseph R.; Merrill, Walter C.

1994-01-01

An intelligent control system for reusable rocket engines under development at NASA Lewis Research Center requires a graphical user interface to allow observation of the closed-loop system in operation. The simulation testbed consists of a real-time engine simulation computer, a controls computer, and several auxiliary computers for diagnostics and coordination. The system is set up so that the simulation computer could be replaced by the real engine and the change would be transparent to the control system. Because of the hard real-time requirement of the control computer, putting a graphical user interface on it was not an option. Thus, a separate computer used strictly for the graphical user interface was warranted. An object-oriented LISP-based graphical user interface has been developed on a Texas Instruments Explorer 2+ to indicate the condition of the engine to the observer through plots, animation, interactive graphics, and text.

Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

NASA Technical Reports Server (NTRS)

Gilmore, John F. (Editor)

1987-01-01

The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

Distributed intelligence for supervisory control

NASA Technical Reports Server (NTRS)

Wolfe, W. J.; Raney, S. D.

1987-01-01

Supervisory control systems must deal with various types of intelligence distributed throughout the layers of control. Typical layers are real-time servo control, off-line planning and reasoning subsystems and finally, the human operator. Design methodologies must account for the fact that the majority of the intelligence will reside with the human operator. Hierarchical decompositions and feedback loops as conceptual building blocks that provide a common ground for man-machine interaction are discussed. Examples of types of parallelism and parallel implementation on several classes of computer architecture are also discussed.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

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

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

Modeling human behaviors and reactions under dangerous environment.

PubMed

Kang, J; Wright, D K; Qin, S F; Zhao, Y

2005-01-01

This paper describes the framework of a real-time simulation system to model human behavior and reactions in dangerous environments. The system utilizes the latest 3D computer animation techniques, combined with artificial intelligence, robotics and psychology, to model human behavior, reactions and decision making under expected/unexpected dangers in real-time in virtual environments. The development of the system includes: classification on the conscious/subconscious behaviors and reactions of different people; capturing different motion postures by the Eagle Digital System; establishing 3D character animation models; establishing 3D models for the scene; planning the scenario and the contents; and programming within Virtools Dev. Programming within Virtools Dev is subdivided into modeling dangerous events, modeling character's perceptions, modeling character's decision making, modeling character's movements, modeling character's interaction with environment and setting up the virtual cameras. The real-time simulation of human reactions in hazardous environments is invaluable in military defense, fire escape, rescue operation planning, traffic safety studies, and safety planning in chemical factories, the design of buildings, airplanes, ships and trains. Currently, human motion modeling can be realized through established technology, whereas to integrate perception and intelligence into virtual human's motion is still a huge undertaking. The challenges here are the synchronization of motion and intelligence, the accurate modeling of human's vision, smell, touch and hearing, the diversity and effects of emotion and personality in decision making. There are three types of software platforms which could be employed to realize the motion and intelligence within one system, and their advantages and disadvantages are discussed.

Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques.

PubMed

Ferreira, F J O; Crispim, V R; Silva, A X

2010-06-01

In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials. Copyright 2010 Elsevier Ltd. All rights reserved.

An Intelligent Cloud Storage Gateway for Medical Imaging.

PubMed

Viana-Ferreira, Carlos; Guerra, António; Silva, João F; Matos, Sérgio; Costa, Carlos

2017-09-01

Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the storage volume, data redundancy and availability. Cloud platforms are focused on delivering hardware and software services over the Internet, becoming an appealing solution for repository outsourcing. Although this option may bring financial and technological benefits, it also presents new challenges. In medical imaging scenarios, communication latency is a critical issue that still hinders the adoption of this paradigm. This paper proposes an intelligent Cloud storage gateway that optimizes data access times. This is achieved through a new cache architecture that combines static rules and pattern recognition for eviction and prefetching. The evaluation results, obtained from experiments over a real-world dataset, show that cache hit ratios can reach around 80%, leading to reductions of image retrieval times by over 60%. The combined use of eviction and prefetching policies proposed can significantly reduce communication latency, even when using a small cache in comparison to the total size of the repository. Apart from the performance gains, the proposed system is capable of adjusting to specific workflows of different institutions.

Automated expert modeling for automated student evaluation.

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

Abbott, Robert G.

The 8th International Conference on Intelligent Tutoring Systems provides a leading international forum for the dissemination of original results in the design, implementation, and evaluation of intelligent tutoring systems and related areas. The conference draws researchers from a broad spectrum of disciplines ranging from artificial intelligence and cognitive science to pedagogy and educational psychology. The conference explores intelligent tutoring systems increasing real world impact on an increasingly global scale. Improved authoring tools and learning object standards enable fielding systems and curricula in real world settings on an unprecedented scale. Researchers deploy ITS's in ever larger studies and increasingly use datamore » from real students, tasks, and settings to guide new research. With high volumes of student interaction data, data mining, and machine learning, tutoring systems can learn from experience and improve their teaching performance. The increasing number of realistic evaluation studies also broaden researchers knowledge about the educational contexts for which ITS's are best suited. At the same time, researchers explore how to expand and improve ITS/student communications, for example, how to achieve more flexible and responsive discourse with students, help students integrate Web resources into learning, use mobile technologies and games to enhance student motivation and learning, and address multicultural perspectives.« less

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Real-time estimation of incident delay in dynamic and stochastic networks

DOT National Transportation Integrated Search

1997-01-01

The ability to predict the link travel times is a necessary requirement for most intelligent transportation systems (ITS) applications such as route guidance systems. In an urban traffic environment, these travel times are dynamic and stochastic and ...

First CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

1990-01-01

The first Conference of C Language Production Systems (CLIPS) hosted by the NASA-Lyndon B. Johnson Space Center in August 1990 is presented. Articles included engineering applications, intelligent tutors and training, intelligent software engineering, automated knowledge acquisition, network applications, verification and validation, enhancements to CLIPS, space shuttle quality control/diagnosis applications, space shuttle and real-time applications, and medical, biological, and agricultural applications.

Help Helps, but Only so Much: Research on Help Seeking with Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R.

2016-01-01

Help seeking is an important process in self-regulated learning (SRL). It may influence learning with intelligent tutoring systems (ITSs), because many ITSs provide help, often at the student's request. The Help Tutor was a tutor agent that gave in-context, real-time feedback on students' help-seeking behavior, as they were learning with an ITS.…

The Intelligent e-Therapy System: A New Paradigm for Telepsychology and Cybertherapy

ERIC Educational Resources Information Center

Alcaniz, M.; Botella, C.; Banos, R. M.; Zaragoza, I.; Guixeres, J.

2009-01-01

One of the main drawbacks of computer-assisted psychology tools developed up to now is related to the real time customisation and adaptation of the content to each patient depending on his/her activity. In this paper we propose a new approach for mental e-health treatments named Intelligent e-Therapy (eIT) with capabilities for ambient…

Design for interaction between humans and intelligent systems during real-time fault management

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.; Thronesbery, Carroll G.

1992-01-01

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

PubMed

Kuo, R J; Wu, P; Wang, C P

2002-09-01

Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

PC graphics generation and management tool for real-time applications

NASA Technical Reports Server (NTRS)

Truong, Long V.

1992-01-01

A graphics tool was designed and developed for easy generation and management of personal computer graphics. It also provides methods and 'run-time' software for many common artificial intelligence (AI) or expert system (ES) applications.

Development of a real time multiple target, multi camera tracker for civil security applications

NASA Astrophysics Data System (ADS)

Åkerlund, Hans

2009-09-01

A surveillance system has been developed that can use multiple TV-cameras to detect and track personnel and objects in real time in public areas. The document describes the development and the system setup. The system is called NIVS Networked Intelligent Video Surveillance. Persons in the images are tracked and displayed on a 3D map of the surveyed area.

An evaluation plan of bus architectures and protocols using the NASA Ames intelligent redundant actuation system

NASA Technical Reports Server (NTRS)

Defeo, P.; Chen, M.

1987-01-01

Means for evaluating data bus architectures and protocols for highly integrated flight control system applications are needed. Described are the criteria and plans to do this by using the NASA/Ames Intelligent Redundant Actuation System (IRAS) experimental set-up. Candidate bus architectures differ from one another in terms of: topology, access control, message transfer schemes, message characteristics, initialization. data flow control, transmission rates, fault tolerance, and time synchronization. The evaluation criteria are developed relative to these features. A preliminary, analytical evaluation of four candidate busses (MIL-STD-1553B, DATAC, Ethernet, and HSIS) is described. A bus must be exercised in a real-time environment to evaluate its dynamic characteristics. A plan for real-time evaluation of these four busses using a combination of hardware and simulation techniques is presented.

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.

Proceedings: IEEE Workshop on Real-Time Operating Systems and Software (11th) Held in Seattle, Washington on 18-19 May 1994

DTIC Science & Technology

1994-05-19

time artificial intelligence , algorithms [5, 6], in this paper we report on new ex- to develop a test platform for flezible manufacturing, tensions...flexible, adaptive and able to exhibit intelligence . This is * assignment of spare capacity to requesting processes. contrary to the relatively inflexible...Frenc Belina, D. Hogref, and A. Sarma, "SDL with We think the method using SDL with the compan - Applications from Protocol Specification", Print- ion

Real-time Medical Emergency Response System: Exploiting IoT and Big Data for Public Health.

PubMed

Rathore, M Mazhar; Ahmad, Awais; Paul, Anand; Wan, Jiafu; Zhang, Daqiang

2016-12-01

Healthy people are important for any nation's development. Use of the Internet of Things (IoT)-based body area networks (BANs) is increasing for continuous monitoring and medical healthcare in order to perform real-time actions in case of emergencies. However, in the case of monitoring the health of all citizens or people in a country, the millions of sensors attached to human bodies generate massive volume of heterogeneous data, called "Big Data." Processing Big Data and performing real-time actions in critical situations is a challenging task. Therefore, in order to address such issues, we propose a Real-time Medical Emergency Response System that involves IoT-based medical sensors deployed on the human body. Moreover, the proposed system consists of the data analysis building, called "Intelligent Building," depicted by the proposed layered architecture and implementation model, and it is responsible for analysis and decision-making. The data collected from millions of body-attached sensors is forwarded to Intelligent Building for processing and for performing necessary actions using various units such as collection, Hadoop Processing (HPU), and analysis and decision. The feasibility and efficiency of the proposed system are evaluated by implementing the system on Hadoop using an UBUNTU 14.04 LTS coreTMi5 machine. Various medical sensory datasets and real-time network traffic are considered for evaluating the efficiency of the system. The results show that the proposed system has the capability of efficiently processing WBAN sensory data from millions of users in order to perform real-time responses in case of emergencies.

Intelligent video storage of visual evidences on site in fast deployment

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Bastide, Arnaud; Delaigle, Jean-Francois

2004-07-01

In this article we present a generic, flexible, scalable and robust approach for an intelligent real-time forensic visual system. The proposed implementation could be rapidly deployable and integrates minimum logistic support as it embeds low complexity devices (PCs and cameras) that communicate through wireless network. The goal of these advanced tools is to provide intelligent video storage of potential video evidences for fast intervention during deployment around a hazardous sector after a terrorism attack, a disaster, an air crash or before attempt of it. Advanced video analysis tools, such as segmentation and tracking are provided to support intelligent storage and annotation.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Adaptive Modeling and Real-Time Simulation

DTIC Science & Technology

1984-01-01

34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

Defense Logistics Standard Systems Functional Requirements.

DTIC Science & Technology

1987-03-01

Artificial Intelligence - the development of a machine capability to perform functions normally concerned with human intelligence, such as learning , adapting...Basic Data Base Machine Configurations .... ......... D- 18 xx ~ ?f~~~vX PART I: MODELS - DEFENSE LOGISTICS STANDARD SYSTEMS FUNCTIONAL REQUIREMENTS...On-line, Interactive Access. Integrating user input and machine output in a dynamic, real-time, give-and- take process is considered the optimum mode

Intelligent control of PV system on the basis of the fuzzy recurrent neuronet*

NASA Astrophysics Data System (ADS)

Engel, E. A.; Kovalev, I. V.; Engel, N. E.

2016-04-01

This paper presents the fuzzy recurrent neuronet for PV system’s control. Based on the PV system’s state, the fuzzy recurrent neural net tracks the maximum power point under random perturbations. The validity and advantages of the proposed intelligent control of PV system are demonstrated by numerical simulations. The simulation results show that the proposed intelligent control of PV system achieves real-time control speed and competitive performance, as compared to a classical control scheme on the basis of the perturbation & observation algorithm.

A computer architecture for intelligent machines

NASA Technical Reports Server (NTRS)

Lefebvre, D. R.; Saridis, G. N.

1992-01-01

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Intelligent Agent Architectures: Reactive Planning Testbed

NASA Technical Reports Server (NTRS)

Rosenschein, Stanley J.; Kahn, Philip

1993-01-01

An Integrated Agent Architecture (IAA) is a framework or paradigm for constructing intelligent agents. Intelligent agents are collections of sensors, computers, and effectors that interact with their environments in real time in goal-directed ways. Because of the complexity involved in designing intelligent agents, it has been found useful to approach the construction of agents with some organizing principle, theory, or paradigm that gives shape to the agent's components and structures their relationships. Given the wide variety of approaches being taken in the field, the question naturally arises: Is there a way to compare and evaluate these approaches? The purpose of the present work is to develop common benchmark tasks and evaluation metrics to which intelligent agents, including complex robotic agents, constructed using various architectural approaches can be subjected.

Real coded genetic algorithm for fuzzy time series prediction

NASA Astrophysics Data System (ADS)

Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.

2017-10-01

Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.

A Novel Artificial Intelligence System for Endotracheal Intubation.

PubMed

Carlson, Jestin N; Das, Samarjit; De la Torre, Fernando; Frisch, Adam; Guyette, Francis X; Hodgins, Jessica K; Yealy, Donald M

2016-01-01

Adequate visualization of the glottic opening is a key factor to successful endotracheal intubation (ETI); however, few objective tools exist to help guide providers' ETI attempts toward the glottic opening in real-time. Machine learning/artificial intelligence has helped to automate the detection of other visual structures but its utility with ETI is unknown. We sought to test the accuracy of various computer algorithms in identifying the glottic opening, creating a tool that could aid successful intubation. We collected a convenience sample of providers who each performed ETI 10 times on a mannequin using a video laryngoscope (C-MAC, Karl Storz Corp, Tuttlingen, Germany). We recorded each attempt and reviewed one-second time intervals for the presence or absence of the glottic opening. Four different machine learning/artificial intelligence algorithms analyzed each attempt and time point: k-nearest neighbor (KNN), support vector machine (SVM), decision trees, and neural networks (NN). We used half of the videos to train the algorithms and the second half to test the accuracy, sensitivity, and specificity of each algorithm. We enrolled seven providers, three Emergency Medicine attendings, and four paramedic students. From the 70 total recorded laryngoscopic video attempts, we created 2,465 time intervals. The algorithms had the following sensitivity and specificity for detecting the glottic opening: KNN (70%, 90%), SVM (70%, 90%), decision trees (68%, 80%), and NN (72%, 78%). Initial efforts at computer algorithms using artificial intelligence are able to identify the glottic opening with over 80% accuracy. With further refinements, video laryngoscopy has the potential to provide real-time, direction feedback to the provider to help guide successful ETI.

Artificial intelligence for multi-mission planetary operations

NASA Technical Reports Server (NTRS)

Atkinson, David J.; Lawson, Denise L.; James, Mark L.

1990-01-01

A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems 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. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.

Constant-Time Pattern Matching For Real-Time Production Systems

NASA Astrophysics Data System (ADS)

Parson, Dale E.; Blank, Glenn D.

1989-03-01

Many intelligent systems must respond to sensory data or critical environmental conditions in fixed, predictable time. Rule-based systems, including those based on the efficient Rete matching algorithm, cannot guarantee this result. Improvement in execution-time efficiency is not all that is needed here; it is important to ensure constant, 0(1) time limits for portions of the matching process. Our approach is inspired by two observations about human performance. First, cognitive psychologists distinguish between automatic and controlled processing. Analogously, we partition the matching process across two networks. The first is the automatic partition; it is characterized by predictable 0(1) time and space complexity, lack of persistent memory, and is reactive in nature. The second is the controlled partition; it includes the search-based goal-driven and data-driven processing typical of most production system programming. The former is responsible for recognition and response to critical environmental conditions. The latter is responsible for the more flexible problem-solving behaviors consistent with the notion of intelligence. Support for learning and refining the automatic partition can be placed in the controlled partition. Our second observation is that people are able to attend to more critical stimuli or requirements selectively. Our match algorithm uses priorities to focus matching. It compares priority of information during matching, rather than deferring this comparison until conflict resolution. Messages from the automatic partition are able to interrupt the controlled partition, enhancing system responsiveness. Our algorithm has numerous applications for systems that must exhibit time-constrained behavior.

Space communications scheduler: A rule-based approach to adaptive deadline scheduling

NASA Technical Reports Server (NTRS)

Straguzzi, Nicholas

1990-01-01

Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

Real-Time, General-Purpose, High-Speed Signal Processing Systems for Underwater Research. Proceedings of a Working Level Conference held at Supreme Allied Commander, Atlantic, Anti-Submarine Warfare Research Center (SACLANTCEN) on 18-21 September 1979. Part 1. Sessions I to III.

DTIC Science & Technology

1979-12-01

intelligent graphics terminals in real-tim processing S (e) 5-1 to 5-9 MIel ita|ger The application of high-speed processors to propagation e.piriamnts...interface SACLANTCEN CP-25 5-2 M IM M STEIGER: Intelligent graphics terminals The less desirable features of the terminal are listed below. reiatively small...hours. Dismantling of the equipment is normally performed in less than one-half hour and often while waiting to clear customs. Transportation of the

OR.NET RT: how service-oriented medical device architecture meets real-time communication.

PubMed

Pfeiffer, Jonas H; Kasparick, Martin; Strathen, Benjamin; Dietz, Christian; Dingler, Max E; Lueth, Tim C; Timmermann, Dirk; Radermacher, Klaus; Golatowski, Frank

2018-02-23

Today's landscape of medical devices is dominated by stand-alone systems and proprietary interfaces lacking cross-vendor interoperability. This complicates or even impedes the innovation of novel, intelligent assistance systems relying on the collaboration of medical devices. Emerging approaches use the service-oriented architecture (SOA) paradigm based on Internet protocol (IP) to enable communication between medical devices. While this works well for scenarios with no or only soft timing constraints, the underlying best-effort communication scheme is insufficient for time critical data. Real-time (RT) networks are able to reliably guarantee fixed latency boundaries, for example, by using time division multiple access (TDMA) communication patterns. However, deterministic RT networks come with their own limitations such as tedious, inflexible configuration and a more restricted bandwidth allocation. In this contribution we overcome the drawbacks of both approaches by describing and implementing mechanisms that allow the two networks to interact. We introduce the first implementation of a medical device network that offers hard RT guarantees for control and sensor data and integrates into SOA networks. Based on two application examples we show how the flexibility of SOA networks and the reliability of RT networks can be combined to achieve an open network infrastructure for medical devices in the operating room (OR).

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.

Integrated Portfolio Analysis: Return on Investment and Real Options Analysis of Intelligence Information Systems (Cryptologic Carry On Program)

DTIC Science & Technology

2006-09-30

unlimited. Prepared for: Naval Postgraduate School, Monterey, California 93943 Integrated Portfolio Analysis : Return on Investment and Real Options... Analysis of Intelligence Information Systems (Cryptologic Carry On Program) 30 September 2006 by LCDR Cesar G. Rios, Jr., Naval Postgraduate...October 2005 – 30 September 2006 4. TITLE AND SUBTITLE Integrated Portfolio Analysis : Return on Investment and Real Options Analysis of Intelligence

Information for the user in design of intelligent systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.

1993-01-01

Recommendations are made for improving intelligent system reliability and usability based on the use of information requirements in system development. Information requirements define the task-relevant messages exchanged between the intelligent system and the user by means of the user interface medium. Thus, these requirements affect the design of both the intelligent system and its user interface. Many difficulties that users have in interacting with intelligent systems are caused by information problems. These information problems result from the following: (1) not providing the right information to support domain tasks; and (2) not recognizing that using an intelligent system introduces new user supervisory tasks that require new types of information. These problems are especially prevalent in intelligent systems used for real-time space operations, where data problems and unexpected situations are common. Information problems can be solved by deriving information requirements from a description of user tasks. Using information requirements embeds human-computer interaction design into intelligent system prototyping, resulting in intelligent systems that are more robust and easier to use.

Identification of COPD patients' health status using an intelligent system in the CHRONIOUS wearable platform.

PubMed

Bellos, Christos C; Papadopoulos, Athanasios; Rosso, Roberto; Fotiadis, Dimitrios I

2014-05-01

The CHRONIOUS system offers an integrated platform aiming at the effective management and real-time assessment of the health status of the patient suffering from chronic obstructive pulmonary disease (COPD). An intelligent system is developed for the analysis and the real-time evaluation of patient's condition. A hybrid classifier has been implemented on a personal digital assistant, combining a support vector machine, a random forest, and a rule-based system to provide a more advanced categorization scheme for the early and in real-time characterization of a COPD episode. This is followed by a severity estimation algorithm which classifies the identified pathological situation in different levels and triggers an alerting mechanism to provide an informative and instructive message/advice to the patient and the clinical supervisor. The system has been validated using data collected from 30 patients that have been annotated by experts indicating 1) the severity level of the current patient's health status, and 2) the COPD disease level of the recruited patients according to the GOLD guidelines. The achieved characterization accuracy has been found 94%.

Decision support system for outage management and automated crew dispatch

DOEpatents

Kang, Ning; Mousavi, Mirrasoul

2018-01-23

A decision support system is provided for utility operations to assist with crew dispatch and restoration activities following the occurrence of a disturbance in a multiphase power distribution network, by providing a real-time visualization of possible location(s). The system covers faults that occur on fuse-protected laterals. The system uses real-time data from intelligent electronics devices coupled with other data sources such as static feeder maps to provide a complete picture of the disturbance event, guiding the utility crew to the most probable location(s). This information is provided in real-time, reducing restoration time and avoiding more costly and laborious fault location finding practices.

V-Man Generation for 3-D Real Time Animation. Chapter 5

NASA Technical Reports Server (NTRS)

Nebel, Jean-Christophe; Sibiryakov, Alexander; Ju, Xiangyang

2007-01-01

The V-Man project has developed an intuitive authoring and intelligent system to create, animate, control and interact in real-time with a new generation of 3D virtual characters: The V-Men. It combines several innovative algorithms coming from Virtual Reality, Physical Simulation, Computer Vision, Robotics and Artificial Intelligence. Given a high-level task like "walk to that spot" or "get that object", a V-Man generates the complete animation required to accomplish the task. V-Men synthesise motion at runtime according to their environment, their task and their physical parameters, drawing upon its unique set of skills manufactured during the character creation. The key to the system is the automated creation of realistic V-Men, not requiring the expertise of an animator. It is based on real human data captured by 3D static and dynamic body scanners, which is then processed to generate firstly animatable body meshes, secondly 3D garments and finally skinned body meshes.

Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

PubMed

Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

2007-01-01

Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.

PubMed

Naso, David; Turchiano, Biagio

2005-04-01

In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.

Laser Fluence Recognition Using Computationally Intelligent Pulsed Photoacoustics Within the Trace Gases Analysis

NASA Astrophysics Data System (ADS)

Lukić, M.; Ćojbašić, Ž.; Rabasović, M. D.; Markushev, D. D.; Todorović, D. M.

2017-11-01

In this paper, the possibilities of computational intelligence applications for trace gas monitoring are discussed. For this, pulsed infrared photoacoustics is used to investigate SF6-Ar mixtures in a multiphoton regime, assisted by artificial neural networks. Feedforward multilayer perceptron networks are applied in order to recognize both the spatial characteristics of the laser beam and the values of laser fluence Φ from the given photoacoustic signal and prevent changes. Neural networks are trained in an offline batch training regime to simultaneously estimate four parameters from theoretical or experimental photoacoustic signals: the laser beam spatial profile R(r), vibrational-to-translational relaxation time τ _{V-T} , distance from the laser beam to the absorption molecules in the photoacoustic cell r* and laser fluence Φ . The results presented in this paper show that neural networks can estimate an unknown laser beam spatial profile and the parameters of photoacoustic signals in real time and with high precision. Real-time operation, high accuracy and the possibility of application for higher intensities of radiation for a wide range of laser fluencies are factors that classify the computational intelligence approach as efficient and powerful for the in situ measurement of atmospheric pollutants.

Detecting method of subjects' 3D positions and experimental advanced camera control system

NASA Astrophysics Data System (ADS)

Kato, Daiichiro; Abe, Kazuo; Ishikawa, Akio; Yamada, Mitsuho; Suzuki, Takahito; Kuwashima, Shigesumi

1997-04-01

Steady progress is being made in the development of an intelligent robot camera capable of automatically shooting pictures with a powerful sense of reality or tracking objects whose shooting requires advanced techniques. Currently, only experienced broadcasting cameramen can provide these pictures.TO develop an intelligent robot camera with these abilities, we need to clearly understand how a broadcasting cameraman assesses his shooting situation and how his camera is moved during shooting. We use a real- time analyzer to study a cameraman's work and his gaze movements at studios and during sports broadcasts. This time, we have developed a detecting method of subjects' 3D positions and an experimental camera control system to help us further understand the movements required for an intelligent robot camera. The features are as follows: (1) Two sensor cameras shoot a moving subject and detect colors, producing its 3D coordinates. (2) Capable of driving a camera based on camera movement data obtained by a real-time analyzer. 'Moving shoot' is the name we have given to the object position detection technology on which this system is based. We used it in a soccer game, producing computer graphics showing how players moved. These results will also be reported.

An intelligent robot for helping astronauts

NASA Technical Reports Server (NTRS)

Erickson, J. D.; Grimm, K. A.; Pendleton, T. W.

1994-01-01

This paper describes the development status of a prototype supervised intelligent robot for space application for purposes of (1) helping the crew of a spacecraft such as the Space Station with various tasks, such as holding objects and retrieving/replacing tools and other objects from/into storage, and (2) for purposes of retrieving detached objects, such as equipment or crew, that have become separated from their spacecraft. In addition to this set of tasks in this low-Earth-orbiting spacecraft environment, it is argued that certain aspects of the technology can be viewed as generic in approach, thereby offering insight into intelligent robots for other tasks and environments. Candidate software architectures and their key technical issues which enable real work in real environments to be accomplished safely and robustly are addressed. Results of computer simulations of grasping floating objects are presented. Also described are characterization results on the usable reduced gravity environment in an aircraft flying parabola (to simulate weightlessness) and results on hardware performance there. These results show it is feasible to use that environment for evaluative testing of dexterous grasping based on real-time vision of freely rotating and translating objects.

Intelligent Control Wheelchair Using a New Visual Joystick.

PubMed

Rabhi, Yassine; Mrabet, Makrem; Fnaiech, Farhat

2018-01-01

A new control system of a hand gesture-controlled wheelchair (EWC) is proposed. This smart control device is suitable for a large number of patients who cannot manipulate a standard joystick wheelchair. The movement control system uses a camera fixed on the wheelchair. The patient's hand movements are recognized using a visual recognition algorithm and artificial intelligence software; the derived corresponding signals are thus used to control the EWC in real time. One of the main features of this control technique is that it allows the patient to drive the wheelchair with a variable speed similar to that of a standard joystick. The designed device "hand gesture-controlled wheelchair" is performed at low cost and has been tested on real patients and exhibits good results. Before testing the proposed control device, we have created a three-dimensional environment simulator to test its performances with extreme security. These tests were performed on real patients with diverse hand pathologies in Mohamed Kassab National Institute of Orthopedics, Physical and Functional Rehabilitation Hospital of Tunis, and the validity of this intelligent control system had been proved.

Intelligent Control Wheelchair Using a New Visual Joystick

PubMed Central

Mrabet, Makrem; Fnaiech, Farhat

2018-01-01

A new control system of a hand gesture-controlled wheelchair (EWC) is proposed. This smart control device is suitable for a large number of patients who cannot manipulate a standard joystick wheelchair. The movement control system uses a camera fixed on the wheelchair. The patient's hand movements are recognized using a visual recognition algorithm and artificial intelligence software; the derived corresponding signals are thus used to control the EWC in real time. One of the main features of this control technique is that it allows the patient to drive the wheelchair with a variable speed similar to that of a standard joystick. The designed device “hand gesture-controlled wheelchair” is performed at low cost and has been tested on real patients and exhibits good results. Before testing the proposed control device, we have created a three-dimensional environment simulator to test its performances with extreme security. These tests were performed on real patients with diverse hand pathologies in Mohamed Kassab National Institute of Orthopedics, Physical and Functional Rehabilitation Hospital of Tunis, and the validity of this intelligent control system had been proved. PMID:29599953

Knowledge representation by connection matrices: A method for the on-board implementation of large expert systems

NASA Technical Reports Server (NTRS)

Kellner, A.

1987-01-01

Extremely large knowledge sources and efficient knowledge access characterizing future real-life artificial intelligence applications represent crucial requirements for on-board artificial intelligence systems due to obvious computer time and storage constraints on spacecraft. A type of knowledge representation and corresponding reasoning mechanism is proposed which is particularly suited for the efficient processing of such large knowledge bases in expert systems.

Event detection for car park entries by video-surveillance

NASA Astrophysics Data System (ADS)

Coquin, Didier; Tailland, Johan; Cintract, Michel

2007-10-01

Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting car park entries, using an adaptive background learning algorithm and two indicators representing activity and identity to overcome the difficulty of tracking objects.

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

An intelligent IoT emergency vehicle warning system using RFID and Wi-Fi technologies for emergency medical services.

PubMed

Lai, Yeong-Lin; Chou, Yung-Hua; Chang, Li-Chih

2018-01-01

Collisions between emergency vehicles for emergency medical services (EMS) and public road users have been a serious problem, impacting on the safety of road users, emergency medical technicians (EMTs), and the patients on board. The aim of this study is to develop a novel intelligent emergency vehicle warning system for EMS applications. The intelligent emergency vehicle warning system is developed by Internet of Things (IoT), radio-frequency identification (RFID), and Wi-Fi technologies. The system consists of three major parts: a system trigger tag, an RFID system in an emergency vehicle, and an RFID system at an intersection. The RFID system either in an emergency vehicle or at an intersection contains a controller, an ultrahigh-frequency (UHF) RFID reader module, a Wi-Fi module, and a 2.4-GHz antenna. In addition, a UHF ID antenna is especially designed for the RFID system in an emergency vehicle. The IoT system provides real-time visual warning at an intersection and siren warning from an emergency vehicle in order to effectively inform road users about an emergency vehicle approaching. The developed intelligent IoT emergency vehicle warning system demonstrates the capabilities of real-time visual and siren warnings for EMS safety.

Simulation of California's Major Reservoirs Outflow Using Data Mining Technique

NASA Astrophysics Data System (ADS)

Yang, T.; Gao, X.; Sorooshian, S.

2014-12-01

The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.

Living Color Frame System: PC graphics tool for data visualization

NASA Technical Reports Server (NTRS)

Truong, Long V.

1993-01-01

Living Color Frame System (LCFS) is a personal computer software tool for generating real-time graphics applications. It is highly applicable for a wide range of data visualization in virtual environment applications. Engineers often use computer graphics to enhance the interpretation of data under observation. These graphics become more complicated when 'run time' animations are required, such as found in many typical modern artificial intelligence and expert systems. Living Color Frame System solves many of these real-time graphics problems.

Intelligent Traffic Light Based on PLC Control

NASA Astrophysics Data System (ADS)

Mei, Lin; Zhang, Lijian; Wang, Lingling

2017-11-01

The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

Cost-effective implementation of intelligent systems

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.; Heer, Ewald

1990-01-01

Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which addresses technology evolution and implementation are also discussed.

Large Efficient Intelligent Heating Relay Station System

NASA Astrophysics Data System (ADS)

Wu, C. Z.; Wei, X. G.; Wu, M. Q.

2017-12-01

The design of large efficient intelligent heating relay station system aims at the improvement of the existing heating system in our country, such as low heating efficiency, waste of energy and serious pollution, and the control still depends on the artificial problem. In this design, we first improve the existing plate heat exchanger. Secondly, the ATM89C51 is used to control the whole system and realize the intelligent control. The detection part is using the PT100 temperature sensor, pressure sensor, turbine flowmeter, heating temperature, detection of user end liquid flow, hydraulic, and real-time feedback, feedback signal to the microcontroller through the heating for users to adjust, realize the whole system more efficient, intelligent and energy-saving.

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.

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.

[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.

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.

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

The Intelligibility of Non-Vocoded and Vocoded Semantically Anomalous Sentences.

DTIC Science & Technology

1985-07-26

then vocoded with a real-time channel vocoder (see Gold and Tierney 5 for program description). The Lincoln Digital Signal Processors (LDSPs) - simple...programmable computers of a Harvard architecture - were used to imple- ment the real-time channel vocoder program . Noise was generated within the...ratio at the input was approximately 0 dB. The impor- tant fact to emphasize is that identical vocoding programs were used to generate the Gold and

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 ...

Tracking children's mental states while solving algebra equations.

PubMed

Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

2012-11-01

Behavioral and function magnetic resonance imagery (fMRI) data were combined to infer the mental states of students as they interacted with an intelligent tutoring system. Sixteen children interacted with a computer tutor for solving linear equations over a six-day period (days 0-5), with days 1 and 5 occurring in an fMRI scanner. Hidden Markov model algorithms combined a model of student behavior with multi-voxel imaging pattern data to predict the mental states of students. We separately assessed the algorithms' ability to predict which step in a problem-solving sequence was performed and whether the step was performed correctly. For day 1, the data patterns of other students were used to predict the mental states of a target student. These predictions were improved on day 5 by adding information about the target student's behavioral and imaging data from day 1. Successful tracking of mental states depended on using the combination of a behavioral model and multi-voxel pattern analysis, illustrating the effectiveness of an integrated approach to tracking the cognition of individuals in real time as they perform complex tasks. Copyright © 2011 Wiley Periodicals, Inc.

Is it worth changing pattern recognition methods for structural health monitoring?

NASA Astrophysics Data System (ADS)

Bull, L. A.; Worden, K.; Cross, E. J.; Dervilis, N.

2017-05-01

The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data.

Parallel dispatch: a new paradigm of electrical power system dispatch

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

Zhang, Jun Jason; Wang, Fei-Yue; Wang, Qiang

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus, the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm, namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complexmore » power grids, extend system operators U+02BC capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.« less

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.

Dynamic traffic assignment : genetic algorithms approach

DOT National Transportation Integrated Search

1997-01-01

Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

Intelligent fault diagnosis and failure management of flight control actuation systems

NASA Technical Reports Server (NTRS)

Bonnice, William F.; Baker, Walter

1988-01-01

The real-time fault diagnosis and failure management (FDFM) of current operational and experimental dual tandem aircraft flight control system actuators was investigated. Dual tandem actuators were studied because of the active FDFM capability required to manage the redundancy of these actuators. The FDFM methods used on current dual tandem actuators were determined by examining six specific actuators. The FDFM capability on these six actuators was also evaluated. One approach for improving the FDFM capability on dual tandem actuators may be through the application of artificial intelligence (AI) technology. Existing AI approaches and applications of FDFM were examined and evaluated. Based on the general survey of AI FDFM approaches, the potential role of AI technology for real-time actuator FDFM was determined. Finally, FDFM and maintainability improvements for dual tandem actuators were recommended.

Vehicle-based vision sensors for intelligent highway systems

NASA Astrophysics Data System (ADS)

Masaki, Ichiro

1989-09-01

This paper describes a vision system, based on ASIC (Application Specific Integrated Circuit) approach, for vehicle guidance on highways. After reviewing related work in the fields of intelligent vehicles, stereo vision, and ASIC-based approaches, the paper focuses on a stereo vision system for intelligent cruise control. The system measures the distance to the vehicle in front using trinocular triangulation. An application specific processor architecture was developed to offer low mass-production cost, real-time operation, low power consumption, and small physical size. The system was installed in the trunk of a car and evaluated successfully on highways.

Application Research of Quality Control Technology of Asphalt Pavement based on GPS Intelligent

NASA Astrophysics Data System (ADS)

Wang, Min; Gao, Bo; Shang, Fei; Wang, Tao

2017-10-01

Due to the difficulty of steel deck pavement asphalt layer compaction caused by the effect of the flexible supporting system (orthotropic steel deck plate), it is usually hard and difficult to control for the site compactness to reach the design goal. The intelligent compaction technology is based on GPS control technology and real-time acquisition of actual compaction tracks, and then forms a cloud maps of compaction times, which guide the roller operator to do the compaction in accordance with the design requirement to ensure the deck compaction technology and compaction quality. From the actual construction situation of actual bridge and checked data, the intelligent compaction technology is significant in guaranteeing the steel deck asphalt pavement compactness and quality stability.

A Reasoning Hardware Platform for Real-Time Common-Sense Inference

PubMed Central

Barba, Jesús; Santofimia, Maria J.; Dondo, Julio; Rincón, Fernando; Sánchez, Francisco; López, Juan Carlos

2012-01-01

Enabling Ambient Intelligence systems to understand the activities that are taking place in a supervised context is a rather complicated task. Moreover, this task cannot be successfully addressed while overlooking the mechanisms (common-sense knowledge and reasoning) that entitle us, as humans beings, to successfully undertake it. This work is based on the premise that Ambient Intelligence systems will be able to understand and react to context events if common-sense capabilities are embodied in them. However, there are some difficulties that need to be resolved before common-sense capabilities can be fully deployed to Ambient Intelligence. This work presents a hardware accelerated implementation of a common-sense knowledge-base system intended to improve response time and efficiency. PMID:23012540

Adaptive user displays for intelligent tutoring software.

PubMed

Beal, Carole R

2004-12-01

Intelligent tutoring software (ITS) holds great promise for K-12 instruction. Yet it is difficult to obtain rich information about users that can be used in realistic educational delivery settings--public school classrooms--in which eye tracking and other user sensing technologies are not suitable. We are pursuing three "cheap and cheerful" strategies to meet this challenge in the context of an ITS for high school math instruction. First, we use detailed representations of student cognitive skills, including tasks to assess individual users' proficiency with abstract reasoning, proficiency with simple math facts and computational skill, and spatial ability. Second, we are using data mining and machine learning algorithms to identify instructional sequences that have been effective with previous students, and to use these patterns to make decisions about current students. Third, we are integrating a simple focus-of-attention tracking system into the software, using inexpensive, web cameras. This coarse-grained information can be used to time the display of multimedia hints, explanations, and examples when the user is actually looking at the screen, and to diagnose causes of problem-solving errors. The ultimate goal is to create non-intrusive software that can adapt the display of instructional information in real time to the user's cognitive strengths, motivation, and attention.

Multi Modality Brain Mapping System (MBMS) Using Artificial Intelligence and Pattern Recognition

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Kateb, Babak (Inventor)

2017-01-01

A Multimodality Brain Mapping System (MBMS), comprising one or more scopes (e.g., microscopes or endoscopes) coupled to one or more processors, wherein the one or more processors obtain training data from one or more first images and/or first data, wherein one or more abnormal regions and one or more normal regions are identified; receive a second image captured by one or more of the scopes at a later time than the one or more first images and/or first data and/or captured using a different imaging technique; and generate, using machine learning trained using the training data, one or more viewable indicators identifying one or abnormalities in the second image, wherein the one or more viewable indicators are generated in real time as the second image is formed. One or more of the scopes display the one or more viewable indicators on the second image.

Artificial intelligence and the space station software support environment

NASA Technical Reports Server (NTRS)

Marlowe, Gilbert

1986-01-01

In a software system the size of the Space Station Software Support Environment (SSE), no one software development or implementation methodology is presently powerful enough to provide safe, reliable, maintainable, cost effective real time or near real time software. In an environment that must survive one of the most harsh and long life times, software must be produced that will perform as predicted, from the first time it is executed to the last. Many of the software challenges that will be faced will require strategies borrowed from Artificial Intelligence (AI). AI is the only development area mentioned as an example of a legitimate reason for a waiver from the overall requirement to use the Ada programming language for software development. The limits are defined of the applicability of the Ada language Ada Programming Support Environment (of which the SSE is a special case), and software engineering to AI solutions by describing a scenario that involves many facets of AI methodologies.

EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery.

PubMed

Orzechowski, Patryk; Sipper, Moshe; Huang, Xiuzhen; Moore, Jason H

2018-05-22

Biclustering algorithms are commonly used for gene expression data analysis. However, accurate identification of meaningful structures is very challenging and state-of-the-art methods are incapable of discovering with high accuracy different patterns of high biological relevance. In this paper a novel biclustering algorithm based on evolutionary computation, a subfield of artificial intelligence (AI), is introduced. The method called EBIC aims to detect order-preserving patterns in complex data. EBIC is capable of discovering multiple complex patterns with unprecedented accuracy in real gene expression datasets. It is also one of the very few biclustering methods designed for parallel environments with multiple graphics processing units (GPUs). We demonstrate that EBIC greatly outperforms state-of-the-art biclustering methods, in terms of recovery and relevance, on both synthetic and genetic datasets. EBIC also yields results over 12 times faster than the most accurate reference algorithms. EBIC source code is available on GitHub at https://github.com/EpistasisLab/ebic. Correspondence and requests for materials should be addressed to P.O. (email: patryk.orzechowski@gmail.com) and J.H.M. (email: jhmoore@upenn.edu). Supplementary Data with results of analyses and additional information on the method is available at Bioinformatics online.

A multilevel investigation of motivational cultural intelligence, organizational diversity climate, and cultural sales: evidence from U.S. real estate firms.

PubMed

Chen, Xiao-Ping; Liu, Dong; Portnoy, Rebecca

2012-01-01

Adopting a multilevel theoretical framework, the authors examined how motivational cultural intelligence influences individual cultural sales--the number of housing transactions occurring between people of different cultural origins. Data from 305 real estate agents employed at 26 real estate firms in the United States demonstrated that an individual's motivational cultural intelligence is positively related to his or her cultural sales. This positive relationship is enhanced by the firm's motivational cultural intelligence and diversity climate. The authors discuss the theoretical and practical implications of their findings in a workplace context that involves cross-cultural interpersonal interactions.

Adapting Collaboration Dialogue in Response to Intelligent Tutoring System Feedback

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

2015-01-01

To be able to provide better support for collaborative learning in Intelligent Tutoring Systems, it is important to understand how collaboration patterns change. Prior work has looked at the interdependencies between utterances and the change of dialogue over time, but it has not addressed how dialogue changes during a lesson, an analysis that…

Fuzzy-based decision strategy in real-time strategic games

NASA Astrophysics Data System (ADS)

Volna, Eva

2017-11-01

The aim of this article is to describe our own gaming artificial intelligence for OpenTTD, which is a real-time building strategy game. A multi-agent system with fuzzy decision-making was used for the proposal itself. The multiagent system was chosen because real-time strategy games achieve great complexity and require decomposition of the problem into individual problems, which are then solved by individual cooperating agents. The system becomes then more stable and easily expandable. The fuzzy approach makes the decision-making process of strategies easier thanks to the use of uncertainty. In the conclusion, own experimental results were compared with other approaches.

Programmable Automated Welding System (PAWS)

NASA Technical Reports Server (NTRS)

Kline, Martin D.

1994-01-01

An ambitious project to develop an advanced, automated welding system is being funded as part of the Navy Joining Center with Babcock & Wilcox as the prime integrator. This program, the Programmable Automated Welding System (PAWS), involves the integration of both planning and real-time control activities. Planning functions include the development of a graphical decision support system within a standard, portable environment. Real-time control functions include the development of a modular, intelligent, real-time control system and the integration of a number of welding process sensors. This paper presents each of these components of the PAWS and discusses how they can be utilized to automate the welding operation.

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.

Thunderstorm Hypothesis Reasoner

NASA Technical Reports Server (NTRS)

Mulvehill, Alice M.

1994-01-01

THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.

Intelligent Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Michael D.

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

Real-Time Mapping: Contemporary Challenges and the Internet of Things as the Way Forward

NASA Astrophysics Data System (ADS)

Bęcek, Kazimierz

2016-12-01

The Internet of Things (IoT) is an emerging technology that was conceived in 1999. The key components of the IoT are intelligent sensors, which represent objects of interest. The adjective `intelligent' is used here in the information gathering sense, not the psychological sense. Some 30 billion sensors that `know' the current status of objects they represent are already connected to the Internet. Various studies indicate that the number of installed sensors will reach 212 billion by 2020. Various scenarios of IoT projects show sensors being able to exchange data with the network as well as between themselves. In this contribution, we discuss the possibility of deploying the IoT in cartography for real-time mapping. A real-time map is prepared using data harvested through querying sensors representing geographical objects, and the concept of a virtual sensor for abstract objects, such as a land parcel, is presented. A virtual sensor may exist as a data record in the cloud. Sensors are identified by an Internet Protocol address (IP address), which implies that geographical objects through their sensors would also have an IP address. This contribution is an updated version of a conference paper presented by the author during the International Federation of Surveyors 2014 Congress in Kuala Lumpur. The author hopes that the use of the IoT for real-time mapping will be considered by the mapmaking community.

A Comparison of Priority-based and Incremental Real-Time Garbage Collectors in the Implementation of the Shadow Design Pattern

DTIC Science & Technology

2008-08-15

running the real-time application we used in our previous study on IBM WebSphere Real Time. IBM WebSphere Real Time automatically sets Metronome , its...the experiment show that the modified code for the Shadow Design Pattern runs well under Metronome . 15. NUMBER OF PAGES 25 14. SUBJECT TERMS...includes the real-time garbage collector called the Metronome . Unlike the Sun RTGC, we cannot change the priority of the Metronome RTGC. Metronome is

Investigating the effect of emotional intelligence education on baccalaureate nursing students' emotional intelligence scores.

PubMed

Orak, Roohangiz Jamshidi; Farahani, Mansoureh Ashghali; Kelishami, Fatemeh Ghofrani; Seyedfatemi, Naima; Banihashemi, Sara; Havaei, Farinaz

2016-09-01

Nursing students, particularly at the time of entering clinical education, experience a great deal of stress and emotion typically related to their educational and clinical competence. Emotional intelligence is known to be one of the required skills to effectively cope with such feelings. The aim of this study was to investigate the effect of training on first-year nursing students' levels of emotional intelligence. This was a quasi-experiment study in which 69 first-year nursing students affiliated with Tehran University of Medical Sciences were assigned to either the control or the experimental groups. The study intervention included of an emotional intelligence educational program offered in eight two-hour sessions for eight subsequent weeks. In total, 66 students completed the study. The study groups did not differ significantly in terms of emotional intelligence scores before and after educational program. Although the educational program did not have an effect on students' emotional intelligence scores, this study finding can be explained. Limited time for exercising the acquired knowledge and skills may explain the non-significant findings. Moreover, our participants were exclusively first-year students who had no clinical experience and hence, might have felt no real need to learn emotional intelligence skills. Copyright © 2016 Elsevier Ltd. All rights reserved.

Traveling With Success, How Local Governments Use Intelligent Transportation Systems

DOT National Transportation Integrated Search

1995-01-01

ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT OR ETC/ETTM, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS, ADVANCED TRAVELER INFORMATION SYSTEMS OR ATIS, ELECTRONIC PAYMENTS SYSTEMS, TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, TRANSIT MANAGEM...

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...

Problem-Based Learning Pedagogies: Psychological Processes and Enhancement of Intelligences

ERIC Educational Resources Information Center

Tan, Oon-Seng

2007-01-01

Education in this 21st century is concerned with developing intelligences. Problem solving in real-world contexts involves multiple ways of knowing and learning. Intelligence in the real world involves not only learning how to do things effectively but also more importantly the ability to deal with novelty and growing our capacity to adapt, select…

Advanced obstacle avoidance for a laser based wheelchair using optimised Bayesian neural networks.

PubMed

Trieu, Hoang T; Nguyen, Hung T; Willey, Keith

2008-01-01

In this paper we present an advanced method of obstacle avoidance for a laser based intelligent wheelchair using optimized Bayesian neural networks. Three neural networks are designed for three separate sub-tasks: passing through a door way, corridor and wall following and general obstacle avoidance. The accurate usable accessible space is determined by including the actual wheelchair dimensions in a real-time map used as inputs to each networks. Data acquisitions are performed separately to collect the patterns required for specified sub-tasks. Bayesian frame work is used to determine the optimal neural network structure in each case. Then these networks are trained under the supervision of Bayesian rule. Experiment results showed that compare to the VFH algorithm our neural networks navigated a smoother path following a near optimum trajectory.

Making intelligent systems team players: Overview for designers

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.

1992-01-01

This report is a guide and companion to the NASA Technical Memorandum 104738, 'Making Intelligent Systems Team Players,' Volumes 1 and 2. The first two volumes of this Technical Memorandum provide comprehensive guidance to designers of intelligent systems for real-time fault management of space systems, with the objective of achieving more effective human interaction. This report provides an analysis of the material discussed in the Technical Memorandum. It clarifies what it means for an intelligent system to be a team player, and how such systems are designed. It identifies significant intelligent system design problems and their impacts on reliability and usability. Where common design practice is not effective in solving these problems, we make recommendations for these situations. In this report, we summarize the main points in the Technical Memorandum and identify where to look for further information.

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

An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

PubMed

Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

2018-04-01

Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the clinical utility of the proposed sepsis prediction model.

Telerobotic Surgery: An Intelligent Systems Approach to Mitigate the Adverse Effects of Communication Delay. Chapter 4

NASA Technical Reports Server (NTRS)

Cardullo, Frank M.; Lewis, Harold W., III; Panfilov, Peter B.

2007-01-01

An extremely innovative approach has been presented, which is to have the surgeon operate through a simulator running in real-time enhanced with an intelligent controller component to enhance the safety and efficiency of a remotely conducted operation. The use of a simulator enables the surgeon to operate in a virtual environment free from the impediments of telecommunication delay. The simulator functions as a predictor and periodically the simulator state is corrected with truth data. Three major research areas must be explored in order to ensure achieving the objectives. They are: simulator as predictor, image processing, and intelligent control. Each is equally necessary for success of the project and each of these involves a significant intelligent component in it. These are diverse, interdisciplinary areas of investigation, thereby requiring a highly coordinated effort by all the members of our team, to ensure an integrated system. The following is a brief discussion of those areas. Simulator as a predictor: The delays encountered in remote robotic surgery will be greater than any encountered in human-machine systems analysis, with the possible exception of remote operations in space. Therefore, novel compensation techniques will be developed. Included will be the development of the real-time simulator, which is at the heart of our approach. The simulator will present real-time, stereoscopic images and artificial haptic stimuli to the surgeon. Image processing: Because of the delay and the possibility of insufficient bandwidth a high level of novel image processing is necessary. This image processing will include several innovative aspects, including image interpretation, video to graphical conversion, texture extraction, geometric processing, image compression and image generation at the surgeon station. Intelligent control: Since the approach we propose is in a sense predictor based, albeit a very sophisticated predictor, a controller, which not only optimizes end effector trajectory but also avoids error, is essential. We propose to investigate two different approaches to the controller design. One approach employs an optimal controller based on modern control theory; the other one involves soft computing techniques, i.e. fuzzy logic, neural networks, genetic algorithms and hybrids of these.

Auditory “bubbles”: Efficient classification of the spectrotemporal modulations essential for speech intelligibility

PubMed Central

Venezia, Jonathan H.; Hickok, Gregory; Richards, Virginia M.

2016-01-01

Speech intelligibility depends on the integrity of spectrotemporal patterns in the signal. The current study is concerned with the speech modulation power spectrum (MPS), which is a two-dimensional representation of energy at different combinations of temporal and spectral (i.e., spectrotemporal) modulation rates. A psychophysical procedure was developed to identify the regions of the MPS that contribute to successful reception of auditory sentences. The procedure, based on the two-dimensional image classification technique known as “bubbles” (Gosselin and Schyns (2001). Vision Res. 41, 2261–2271), involves filtering (i.e., degrading) the speech signal by removing parts of the MPS at random, and relating filter patterns to observer performance (keywords identified) over a number of trials. The result is a classification image (CImg) or “perceptual map” that emphasizes regions of the MPS essential for speech intelligibility. This procedure was tested using normal-rate and 2×-time-compressed sentences. The results indicated: (a) CImgs could be reliably estimated in individual listeners in relatively few trials, (b) CImgs tracked changes in spectrotemporal modulation energy induced by time compression, though not completely, indicating that “perceptual maps” deviated from physical stimulus energy, and (c) the bubbles method captured variance in intelligibility not reflected in a common modulation-based intelligibility metric (spectrotemporal modulation index or STMI). PMID:27586738

Integrated corridor management initiative : demonstration phase evaluation, San Diego traveler response analysis test plan.

DOT National Transportation Integrated Search

1995-10-01

REAL-TIME TRAFFIC INFORMATION, ROUTE GUIDANCE, ROUTE PLANNING, INTELLIGENT VEHICLE INITIATIVE OR IVI ">">KEYWORDS: OPERATIONAL TESTS, TRAVTEK, ADVANCED TRAVELER INFORMATION SYSTEMS OR ATIS, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS, INTELLI...

An investigation into incident duration forecasting for FleetForward

DOT National Transportation Integrated Search

2000-08-01

Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...

Real-time communication architecture for connected-vehicle eco-traffic signal system applications.

DOT National Transportation Integrated Search

2014-02-01

Transportation Systems, and thus Intelligent Transportation Systems (ITS), are considered one of the most critical : infrastructures. For wireless communication ITS use communication links based on Dedicated Short Range Communication : (DSRC) in Wire...

Visualization of multi-INT fusion data using Java Viewer (JVIEW)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Aved, Alex; Nagy, James; Scott, Stephen

2014-05-01

Visualization is important for multi-intelligence fusion and we demonstrate issues for presenting physics-derived (i.e., hard) and human-derived (i.e., soft) fusion results. Physics-derived solutions (e.g., imagery) typically involve sensor measurements that are objective, while human-derived (e.g., text) typically involve language processing. Both results can be geographically displayed for user-machine fusion. Attributes of an effective and efficient display are not well understood, so we demonstrate issues and results for filtering, correlation, and association of data for users - be they operators or analysts. Operators require near-real time solutions while analysts have the opportunities of non-real time solutions for forensic analysis. In a use case, we demonstrate examples using the JVIEW concept that has been applied to piloting, space situation awareness, and cyber analysis. Using the open-source JVIEW software, we showcase a big data solution for multi-intelligence fusion application for context-enhanced information fusion.

GT-CATS: Tracking Operator Activities in Complex Systems

NASA Technical Reports Server (NTRS)

Callantine, Todd J.; Mitchell, Christine M.; Palmer, Everett A.

1999-01-01

Human operators of complex dynamic systems can experience difficulties supervising advanced control automation. One remedy is to develop intelligent aiding systems that can provide operators with context-sensitive advice and reminders. The research reported herein proposes, implements, and evaluates a methodology for activity tracking, a form of intent inferencing that can supply the knowledge required for an intelligent aid by constructing and maintaining a representation of operator activities in real time. The methodology was implemented in the Georgia Tech Crew Activity Tracking System (GT-CATS), which predicts and interprets the actions performed by Boeing 757/767 pilots navigating using autopilot flight modes. This report first describes research on intent inferencing and complex modes of automation. It then provides a detailed description of the GT-CATS methodology, knowledge structures, and processing scheme. The results of an experimental evaluation using airline pilots are given. The results show that GT-CATS was effective in predicting and interpreting pilot actions in real time.

Methods of Improving Speech Intelligibility for Listeners with Hearing Resolution Deficit

PubMed Central

2012-01-01

Abstract Methods developed for real-time time scale modification (TSM) of speech signal are presented. They are based on the non-uniform, speech rate depended SOLA algorithm (Synchronous Overlap and Add). Influence of the proposed method on the intelligibility of speech was investigated for two separate groups of listeners, i.e. hearing impaired children and elderly listeners. It was shown that for the speech with average rate equal to or higher than 6.48 vowels/s, all of the proposed methods have statistically significant impact on the improvement of speech intelligibility for hearing impaired children with reduced hearing resolution and one of the proposed methods significantly improves comprehension of speech in the group of elderly listeners with reduced hearing resolution. Virtual slides http://www.diagnosticpathology.diagnomx.eu/vs/2065486371761991 PMID:23009662

A structure for maturing intelligent tutoring system student models

NASA Technical Reports Server (NTRS)

Holmes, Willard M.

1990-01-01

A special structure is examined for evolving a detached model of the user of an intelligent tutoring system. Tutoring is used in the context of education and training devices. A detached approach to populating the student model data structure is examined in the context of the need for time dependent reasoning about what the student knows about a particular concept in the domain of interest. This approach, to generating a data structure for the student model, allows an inference engine separate from the tutoring strategy determination to be used. This methodology has advantages in environments requiring real-time operation.

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.

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

Optimization and Control of Cyber-Physical Vehicle Systems

PubMed Central

Bradley, Justin M.; Atkins, Ella M.

2015-01-01

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541

Optimization and Control of Cyber-Physical Vehicle Systems.

PubMed

Bradley, Justin M; Atkins, Ella M

2015-09-11

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

Development of SPIES (Space Intelligent Eyeing System) for smart vehicle tracing and tracking

NASA Astrophysics Data System (ADS)

Abdullah, Suzanah; Ariffin Osoman, Muhammad; Guan Liyong, Chua; Zulfadhli Mohd Noor, Mohd; Mohamed, Ikhwan

2016-06-01

SPIES or Space-based Intelligent Eyeing System is an intelligent technology which can be utilized for various applications such as gathering spatial information of features on Earth, tracking system for the movement of an object, tracing system to trace the history information, monitoring driving behavior, security and alarm system as an observer in real time and many more. SPIES as will be developed and supplied modularly will encourage the usage based on needs and affordability of users. SPIES are a complete system with camera, GSM, GPS/GNSS and G-Sensor modules with intelligent function and capabilities. Mainly the camera is used to capture pictures and video and sometimes with audio of an event. Its usage is not limited to normal use for nostalgic purpose but can be used as a reference for security and material of evidence when an undesirable event such as crime occurs. When integrated with space based technology of the Global Navigational Satellite System (GNSS), photos and videos can be recorded together with positioning information. A product of the integration of these technologies when integrated with Information, Communication and Technology (ICT) and Geographic Information System (GIS) will produce innovation in the form of information gathering methods in still picture or video with positioning information that can be conveyed in real time via the web to display location on the map hence creating an intelligent eyeing system based on space technology. The importance of providing global positioning information is a challenge but overcome by SPIES even in areas without GNSS signal reception for the purpose of continuous tracking and tracing capability

Integrating GPS, GYRO, vehicle speed sensor, and digital map to provide accurate and real-time position in an intelligent navigation system

NASA Astrophysics Data System (ADS)

Li, Qingquan; Fang, Zhixiang; Li, Hanwu; Xiao, Hui

2005-10-01

The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. The applications of Global Positioning System (GPS) positioning is more and more popular, especially the intelligent navigation system which relies on GPS and Dead Reckoning technology is developing quickly for future huge market in China. In this paper a practical combined positioning model of GPS/DR/MM is put forward, which integrates GPS, Gyro, Vehicle Speed Sensor (VSS) and digital navigation maps to provide accurate and real-time position for intelligent navigation system. This model is designed for automotive navigation system making use of Kalman filter to improve position and map matching veracity by means of filtering raw GPS and DR signals, and then map-matching technology is used to provide map coordinates for map displaying. In practical examples, for illustrating the validity of the model, several experiments and their results of integrated GPS/DR positioning in intelligent navigation system will be shown for the conclusion that Kalman Filter based GPS/DR integrating position approach is necessary, feasible and efficient for intelligent navigation application. Certainly, this combined positioning model, similar to other model, can not resolve all situation issues. Finally, some suggestions are given for further improving integrated GPS/DR/MM application.

Intelligent robots for planetary exploration and construction

NASA Technical Reports Server (NTRS)

Albus, James S.

1992-01-01

Robots capable of practical applications in planetary exploration and construction will require realtime sensory-interactive goal-directed control systems. A reference model architecture based on the NIST Real-time Control System (RCS) for real-time intelligent control systems is suggested. RCS partitions the control problem into four basic elements: behavior generation (or task decomposition), world modeling, sensory processing, and value judgment. It clusters these elements into computational nodes that have responsibility for specific subsystems, and arranges these nodes in hierarchical layers such that each layer has characteristic functionality and timing. Planetary exploration robots should have mobility systems that can safely maneuver over rough surfaces at high speeds. Walking machines and wheeled vehicles with dynamic suspensions are candidates. The technology of sensing and sensory processing has progressed to the point where real-time autonomous path planning and obstacle avoidance behavior is feasible. Map-based navigation systems will support long-range mobility goals and plans. Planetary construction robots must have high strength-to-weight ratios for lifting and positioning tools and materials in six degrees-of-freedom over large working volumes. A new generation of cable-suspended Stewart platform devices and inflatable structures are suggested for lifting and positioning materials and structures, as well as for excavation, grading, and manipulating a variety of tools and construction machinery.

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

FRIEDA: Flexible Robust Intelligent Elastic Data Management Framework

DOE PAGES

Ghoshal, Devarshi; Hendrix, Valerie; Fox, William; ...

2017-02-01

Scientific applications are increasingly using cloud resources for their data analysis workflows. However, managing data effectively and efficiently over these cloud resources is challenging due to the myriad storage choices with different performance, cost trade-offs, complex application choices and complexity associated with elasticity, failure rates in these environments. The different data access patterns for data-intensive scientific applications require a more flexible and robust data management solution than the ones currently in existence. FRIEDA is a Flexible Robust Intelligent Elastic Data Management framework that employs a range of data management strategies in cloud environments. FRIEDA can manage storage and data lifecyclemore » of applications in cloud environments. There are four different stages in the data management lifecycle of FRIEDA – (i) storage planning, (ii) provisioning and preparation, (iii) data placement, and (iv) execution. FRIEDA defines a data control plane and an execution plane. The data control plane defines the data partition and distribution strategy, whereas the execution plane manages the execution of the application using a master-worker paradigm. FRIEDA also provides different data management strategies, either to partition the data in real-time, or predetermine the data partitions prior to application execution.« less

FRIEDA: Flexible Robust Intelligent Elastic Data Management Framework

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

Ghoshal, Devarshi; Hendrix, Valerie; Fox, William

Scientific applications are increasingly using cloud resources for their data analysis workflows. However, managing data effectively and efficiently over these cloud resources is challenging due to the myriad storage choices with different performance, cost trade-offs, complex application choices and complexity associated with elasticity, failure rates in these environments. The different data access patterns for data-intensive scientific applications require a more flexible and robust data management solution than the ones currently in existence. FRIEDA is a Flexible Robust Intelligent Elastic Data Management framework that employs a range of data management strategies in cloud environments. FRIEDA can manage storage and data lifecyclemore » of applications in cloud environments. There are four different stages in the data management lifecycle of FRIEDA – (i) storage planning, (ii) provisioning and preparation, (iii) data placement, and (iv) execution. FRIEDA defines a data control plane and an execution plane. The data control plane defines the data partition and distribution strategy, whereas the execution plane manages the execution of the application using a master-worker paradigm. FRIEDA also provides different data management strategies, either to partition the data in real-time, or predetermine the data partitions prior to application execution.« less

PILOT: An intelligent distributed operations support system

NASA Technical Reports Server (NTRS)

Rasmussen, Arthur N.

1993-01-01

The Real-Time Data System (RTDS) project is exploring the application of advanced technologies to the real-time flight operations environment of the Mission Control Centers at NASA's Johnson Space Center. The system, based on a network of engineering workstations, provides services such as delivery of real time telemetry data to flight control applications. To automate the operation of this complex distributed environment, a facility called PILOT (Process Integrity Level and Operation Tracker) is being developed. PILOT comprises a set of distributed agents cooperating with a rule-based expert system; together they monitor process operation and data flows throughout the RTDS network. The goal of PILOT is to provide unattended management and automated operation under user control.

[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.

Real time UNIX in embedded control-a case study within the context of LynxOS

NASA Astrophysics Data System (ADS)

Kleines, H.; Zwoll, K.

1996-02-01

Intelligent communication controllers for a layered protocol profile are a typical example of an embedded control application, where the classical approach for the software development is based on a proprietary real-time operating system kernel under which the individual layers are implemented as tasks. Based on the exemplary implementation of a derivative of MAP 3.0, an unusual and innovative approach is presented, where the protocol software is implemented under the UNIX-compatible real-time operating system LynxOS. The overall design of the embedded control application is presented under a more general view and economical implications as well as aspects of the development environment and performance 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.

From Wheatstone to Cameron and beyond: overview in 3-D and 4-D imaging technology

NASA Astrophysics Data System (ADS)

Gilbreath, G. Charmaine

2012-02-01

This paper reviews three-dimensional (3-D) and four-dimensional (4-D) imaging technology, from Wheatstone through today, with some prognostications for near future applications. This field is rich in variety, subject specialty, and applications. A major trend, multi-view stereoscopy, is moving the field forward to real-time wide-angle 3-D reconstruction as breakthroughs in parallel processing and multi-processor computers enable very fast processing. Real-time holography meets 4-D imaging reconstruction at the goal of achieving real-time, interactive, 3-D imaging. Applications to telesurgery and telemedicine as well as to the needs of the defense and intelligence communities are also discussed.

An intelligent FFR with a self-adjustable ventilation fan.

PubMed

Zhou, Song; Li, Hui; Shen, Shengnan; Li, Siyu; Wang, Wei; Zhang, Xiaotie; Yang, James

2017-11-01

This article presents an intelligent Filtering Facepiece Respirator (FFR) with a self-adjustable ventilation fan for improved comfort. The ventilation fan with an intelligent control aims to reduce temperature, relative humidity, and CO 2 concentrations inside the facepiece. Compared with a previous version of the FFR, the advantage of this new FFR is the intelligent control of the fan's rotation speed based on the change in temperature and relative humidity in the FFR dead space. The design of the control system utilizes an 8-bit, ultra-low power STC15W404AS microcontroller (HongJin technology, Shenzhen, China), and adopts a high-precision AM2320 device (AoSong electronic, Guangzhou, China) as temperature and relative humidity sensor so that control of temperature and relative humidity is realized in real time within the FFR dead space. The ventilation fan is intelligently driven and runs on a rechargeable lithium battery with a power-save mode that provides a correspondingly longer operational time. Meanwhile, the design is simplistic. Two experiments were performed to determine the best location to place the fan.

Continuous real time measurement of pavement quality during construction.

DOT National Transportation Integrated Search

2010-12-01

Intelligent Compaction has been investigated as a means of improving the quality of asphalt pavements during their : construction. The long term performance of an asphalt pavement is directly related to its load bearing capability and : is determined...

Real-time traffic management to maximize throughput of automated vehicles.

DOT National Transportation Integrated Search

2015-03-01

In intelligent transportation systems, most of the research work has focused on lane change assistant : systems. No existing work considers minimizing the disruption of traffic flow by maximizing the number : of lane changes while eliminating the col...

Developing inexpensive crash countermeasures for Louisiana local roads : request for proposals

DOT National Transportation Integrated Search

2010-09-17

The intelligent transportation system (ITS) includes detectors that capture data from Floridas transportation network and computer hardware and software that process these data. Data processed in real-time can, for example, be used to develop mess...

Multiagent pursuit-evasion games: Algorithms and experiments

NASA Astrophysics Data System (ADS)

Kim, Hyounjin

Deployment of intelligent agents has been made possible through advances in control software, microprocessors, sensor/actuator technology, communication technology, and artificial intelligence. Intelligent agents now play important roles in many applications where human operation is too dangerous or inefficient. There is little doubt that the world of the future will be filled with intelligent robotic agents employed to autonomously perform tasks, or embedded in systems all around us, extending our capabilities to perceive, reason and act, and replacing human efforts. There are numerous real-world applications in which a single autonomous agent is not suitable and multiple agents are required. However, after years of active research in multi-agent systems, current technology is still far from achieving many of these real-world applications. Here, we consider the problem of deploying a team of unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV) to pursue a second team of UGV evaders while concurrently building a map in an unknown environment. This pursuit-evasion game encompasses many of the challenging issues that arise in operations using intelligent multi-agent systems. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible pursuit policies: greedy and global-max. We also formulate this probabilistic pursuit-evasion game as a partially observable Markov decision process and employ a policy search algorithm to obtain a good pursuit policy from a restricted class of policies. The estimated value of this policy is guaranteed to be uniformly close to the optimal value in the given policy class under mild conditions. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We then describe our implementation on a fleet of UGVs and UAVs, detailing components such as high level pursuit policy computation, inter-agent communication, navigation, sensing, and regulation. We present both simulation and experimental results on real pursuit-evasion games between our fleet of UAVs and UGVs and evaluate the pursuit policies, relating expected capture times to the speed and intelligence of the evaders and the sensing capabilities of the pursuers. The architecture and algorithmsis described in this dissertation are general enough to be applied to many real-world applications.

Delivery performance of conventional aircraft by terminal-area, time-based air traffic control: A real-time simulation evaluation

NASA Technical Reports Server (NTRS)

Credeur, Leonard; Houck, Jacob A.; Capron, William R.; Lohr, Gary W.

1990-01-01

A description and results are presented of a study to measure the performance and reaction of airline flight crews, in a full workload DC-9 cockpit, flying in a real-time simulation of an air traffic control (ATC) concept called Traffic Intelligence for the Management of Efficient Runway-scheduling (TIMER). Experimental objectives were to verify earlier fast-time TIMER time-delivery precision results and obtain data for the validation or refinement of existing computer models of pilot/airborne performance. Experimental data indicated a runway threshold, interarrival-time-error standard deviation in the range of 10.4 to 14.1 seconds. Other real-time system performance parameters measured include approach speeds, response time to controller turn instructions, bank angles employed, and ATC controller message delivery-time errors.

AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming

NASA Astrophysics Data System (ADS)

Kaur, Jagreet; Singh Mann, Kulwinder, Dr.

2018-01-01

AI in Healthcare needed to bring real, actionable insights and Individualized insights in real time for patients and Doctors to support treatment decisions., We need a Patient Centred Platform for integrating EHR Data, Patient Data, Prescriptions, Monitoring, Clinical research and Data. This paper proposes a generic architecture for enabling AI based healthcare analytics Platform by using open sources Technologies Apache beam, Apache Flink Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, NoSQL- Elasticsearch, Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

Distance correction system for localization based on linear regression and smoothing in ambient intelligence display.

PubMed

Kim, Dae-Hee; Choi, Jae-Hun; Lim, Myung-Eun; Park, Soo-Jun

2008-01-01

This paper suggests the method of correcting distance between an ambient intelligence display and a user based on linear regression and smoothing method, by which distance information of a user who approaches to the display can he accurately output even in an unanticipated condition using a passive infrared VIR) sensor and an ultrasonic device. The developed system consists of an ambient intelligence display and an ultrasonic transmitter, and a sensor gateway. Each module communicates with each other through RF (Radio frequency) communication. The ambient intelligence display includes an ultrasonic receiver and a PIR sensor for motion detection. In particular, this system selects and processes algorithms such as smoothing or linear regression for current input data processing dynamically through judgment process that is determined using the previous reliable data stored in a queue. In addition, we implemented GUI software with JAVA for real time location tracking and an ambient intelligence display.

A computer architecture for intelligent machines

NASA Technical Reports Server (NTRS)

Lefebvre, D. R.; Saridis, G. N.

1991-01-01

The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Intelligent optical fiber sensor system for measurement of gas concentration

NASA Astrophysics Data System (ADS)

Pan, Jingming; Yin, Zongmin

1991-08-01

A measuring, controlling, and alarming system for the concentration of a gas or transparent liquid is described. In this system, a Fabry-Perot etalon with an optical fiber is used as the sensor, a charge-coupled device (CCD) is used as the photoelectric converter, and a single- chip microcomputer 8031 along with an interface circuit is used to measure the interference ring signal. The system has such features as real-time and on-line operation, continuous dynamic handling, and intelligent control.

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.

Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Kobezhicov, V.

2015-10-01

This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

Compressed multi-block local binary pattern for object tracking

NASA Astrophysics Data System (ADS)

Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

2018-04-01

Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

Low-cost, efficient wireless intelligent sensors (LEWIS) measuring real-time reference-free dynamic displacements

NASA Astrophysics Data System (ADS)

Ozdagli, A. I.; Liu, B.; Moreu, F.

2018-07-01

According to railroad managers, displacement of railroad bridges under service loads is an important parameter in the condition assessment and performance evaluation. However, measuring bridge responses in the field is often costly and labor-intensive. This paper proposes a low-cost, efficient wireless intelligent sensor (LEWIS) platform that can compute in real-time the dynamic transverse displacements of railroad bridges under service loads. This sensing platform drives on an open-source Arduino ecosystem and combines low-cost microcontrollers with affordable accelerometers and wireless transmission modules. The proposed LEWIS system is designed to reconstruct dynamic displacements from acceleration measurements onboard, eliminating the need for offline post-processing, and to transmit the data in real-time to a base station where the inspector at the bridge can see the displacements while the train is crossing, or to a remote office if so desired by internet. Researchers validated the effectiveness of the new LEWIS by conducting a series of laboratory experiments. A shake table setup simulated transverse bridge displacements measured on the field and excited the proposed platform, a commercially available wired expensive accelerometer, and reference LVDT displacement sensor. The responses obtained from the wireless system were compared to the displacements reconstructed from commercial accelerometer readings and the reference LVDT. The results of the laboratory experiments demonstrate that the proposed system is capable of reconstructing transverse displacements of railroad bridges under revenue service traffic accurately and transmitting the data in real-time wirelessly. In conclusion, the platform presented in this paper can be used in the performance assessment of railroad bridge network cost-effectively and accurately. Future work includes collecting real-time reference-free displacements of one railroad bridge in Colorado under train crossings to further prove LEWIS' suitability for engineering applications.

A framework for building real-time expert systems

NASA Technical Reports Server (NTRS)

Lee, S. Daniel

1991-01-01

The Space Station Freedom is an example of complex systems that require both traditional and artificial intelligence (AI) real-time methodologies. It was mandated that Ada should be used for all new software development projects. The station also requires distributed processing. Catastrophic failures on the station can cause the transmission system to malfunction for a long period of time, during which ground-based expert systems cannot provide any assistance to the crisis situation on the station. This is even more critical for other NASA projects that would have longer transmission delays (e.g., the lunar base, Mars missions, etc.). To address these issues, a distributed agent architecture (DAA) is proposed that can support a variety of paradigms based on both traditional real-time computing and AI. The proposed testbed for DAA is an autonomous power expert (APEX) which is a real-time monitoring and diagnosis expert system for the electrical power distribution system of the space station.

A real-time KLT implementation for radio-SETI applications

NASA Astrophysics Data System (ADS)

Melis, Andrea; Concu, Raimondo; Pari, Pierpaolo; Maccone, Claudio; Montebugnoli, Stelio; Possenti, Andrea; Valente, Giuseppe; Antonietti, Nicoló; Perrodin, Delphine; Migoni, Carlo; Murgia, Matteo; Trois, Alessio; Barbaro, Massimo; Bocchinu, Alessandro; Casu, Silvia; Lunesu, Maria Ilaria; Monari, Jader; Navarrini, Alessandro; Pisanu, Tonino; Schilliró, Francesco; Vacca, Valentina

2016-07-01

SETI, the Search for ExtraTerrestrial Intelligence, is the search for radio signals emitted by alien civilizations living in the Galaxy. Narrow-band FFT-based approaches have been preferred in SETI, since their computation time only grows like N*lnN, where N is the number of time samples. On the contrary, a wide-band approach based on the Kahrunen-Lo`eve Transform (KLT) algorithm would be preferable, but it would scale like N*N. In this paper, we describe a hardware-software infrastructure based on FPGA boards and GPU-based PCs that circumvents this computation-time problem allowing for a real-time KLT.

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

Real-Time Data Capture and Management Evaluation and Performance Measures : Evaluation Framework

DOT National Transportation Integrated Search

2011-09-01

Through connected vehicle research, the U.S. DOT Intelligent Transportation Systems Joint Program Office (ITS JPO) is leading an effort to assess the potential for systematic and dynamic data capture from vehicles, travelers and the transportation sy...

Demonstration of the application of traffic management center decision support tools : [summary].

DOT National Transportation Integrated Search

2013-03-01

Among the most important advances in transportation systems in recent years has been the development and implementation of intelligent transportation systems (ITS), which relies on several means of monitoring traffic flows, coupled with real-time and...

Development of a real-time vibrator tracking system for intelligent concrete consolidation.

DOT National Transportation Integrated Search

2014-01-01

Proper consolidation of concrete is critical to the long-term strength of concrete bridge structures. Vibration : is a commonly used method to make concrete owable and to remove the excessive entrapped air, therefore : contributing to proper concr...

TxDOT uses of real-time commercial traffic data : opportunity matrix.

DOT National Transportation Integrated Search

2012-01-01

Based on a TxDOT survey, a review of other state DOTs, and researcher understanding of Intelligent Transportation System (ITS) needs, the Texas Transportation Institute (TTI) team developed a comprehensive list of opportunities for TxDOT to consider ...

Statewide Intelligent Transportation Systems As-Is Agency Reports For Minnesota, Volume 6, City Of St. Paul

DOT National Transportation Integrated Search

1996-08-01

KEYWORDS: : TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS : THIS DOCUMENT PRESENTS THE METHODS, ASSUMPTIONS AND PROCEDURES USED TO COLLECT THE BASELINE INFORMATION. THE DOCUMENTATION OF SYSTEMS ...

Autonomous Monitoring of Radiation Environment and Personal Systems for Crew Enhanced SPE Protection (AMORE and PSYCHE)

NASA Astrophysics Data System (ADS)

Narici, L.; Baiocco, G.; Berrilli, F.; Giraudo, M.; Ottolenghi, A.; Rizzo, A.; Salina, G.

2018-02-01

Understand the relationship between SPE precursors, the related SPE radiation inside the Deep Space Gateway, and the associated risk levels, validating existing models, proposing countermeasures actions via a real time, autonomous intelligent system.

Addressing Risk Assessment for Patient Safety in Hospitals through Information Extraction in Medical Reports

NASA Astrophysics Data System (ADS)

Proux, Denys; Segond, Frédérique; Gerbier, Solweig; Metzger, Marie Hélène

Hospital Acquired Infections (HAI) is a real burden for doctors and risk surveillance experts. The impact on patients' health and related healthcare cost is very significant and a major concern even for rich countries. Furthermore required data to evaluate the threat is generally not available to experts and that prevents from fast reaction. However, recent advances in Computational Intelligence Techniques such as Information Extraction, Risk Patterns Detection in documents and Decision Support Systems allow now to address this problem.

Real-Time Detection and Tracking of Multiple People in Laser Scan Frames

NASA Astrophysics Data System (ADS)

Cui, J.; Song, X.; Zhao, H.; Zha, H.; Shibasaki, R.

This chapter presents an approach to detect and track multiple people ro bustly in real time using laser scan frames. The detection and tracking of people in real time is a problem that arises in a variety of different contexts. Examples in clude intelligent surveillance for security purposes, scene analysis for service robot, and crowd behavior analysis for human behavior study. Over the last several years, an increasing number of laser-based people-tracking systems have been developed in both mobile robotics platforms and fixed platforms using one or multiple laser scanners. It has been proved that processing on laser scanner data makes the tracker much faster and more robust than a vision-only based one in complex situations. In this chapter, we present a novel robust tracker to detect and track multiple people in a crowded and open area in real time. First, raw data are obtained that measures two legs for each people at a height of 16 cm from horizontal ground with multiple registered laser scanners. A stable feature is extracted using accumulated distribu tion of successive laser frames. In this way, the noise that generates split and merged measurements is smoothed well, and the pattern of rhythmic swinging legs is uti lized to extract each leg. Second, a probabilistic tracking model is presented, and then a sequential inference process using a Bayesian rule is described. A sequential inference process is difficult to compute analytically, so two strategies are presented to simplify the computation. In the case of independent tracking, the Kalman fil ter is used with a more efficient measurement likelihood model based on a region coherency property. Finally, to deal with trajectory fragments we present a concise approach to fuse just a little visual information from synchronized video camera to laser data. Evaluation with real data shows that the proposed method is robust and effective. It achieves a significant improvement compared with existing laser-based trackers.

Vision-Based Real-Time Traversable Region Detection for Mobile Robot in the Outdoors.

PubMed

Deng, Fucheng; Zhu, Xiaorui; He, Chao

2017-09-13

Environment perception is essential for autonomous mobile robots in human-robot coexisting outdoor environments. One of the important tasks for such intelligent robots is to autonomously detect the traversable region in an unstructured 3D real world. The main drawback of most existing methods is that of high computational complexity. Hence, this paper proposes a binocular vision-based, real-time solution for detecting traversable region in the outdoors. In the proposed method, an appearance model based on multivariate Gaussian is quickly constructed from a sample region in the left image adaptively determined by the vanishing point and dominant borders. Then, a fast, self-supervised segmentation scheme is proposed to classify the traversable and non-traversable regions. The proposed method is evaluated on public datasets as well as a real mobile robot. Implementation on the mobile robot has shown its ability in the real-time navigation applications.

Magnetron Sputtered Pulsed Laser Deposition Scale Up

DTIC Science & Technology

2003-08-14

2:721-726 34 S. J. P. Laube and E. F. Stark, “ Artificial Intellegence in Process Control of Pulsed Laser Deposition”, Proceedings of...The model would be based on mathematical simulation of real process data, neural-networks, or other artificial intelligence methods based on in situ...Laube and E. F. Stark, Proc. Symp. Artificial Intel. Real Time Control, Valencia, Spain, 3-5 Oct. ,1994, p.159-163. International Federation of

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.

PubMed

Tian, Shu; Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

PubMed Central

Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness. PMID:26693249

Making the Grid "Smart" Through "Smart" Microgrids: Real-Time Power Management of Microgrids with Multiple Distributed Generation Sources Using Intelligent Control

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

Nehrir, M. Hashem

In this Project we collaborated with two DOE National Laboratories, Pacific Northwest National Lab (PNNL) and Lawrence Berkeley National Lab (LBL). Dr. Hammerstrom of PNNL initially supported our project and was on the graduate committee of one of the Ph.D. students (graduated in 2014) who was supported by this project. He is also a committee member of a current graduate student of the PI who was supported by this project in the last two years (August 2014-July 2016). The graduate student is now supported be the Electrical and Computer Engineering (ECE) Department at Montana State University (MSU). Dr. Chris Marneymore » of LBL provided actual load data, and the software WEBOPT developed at LBL for microgrid (MG) design for our project. NEC-Labs America, a private industry, also supported our project, providing expert support and modest financial support. We also used the software “HOMER,” originally developed at the National Renewable Energy Laboratory (NREL) and the most recent version made available to us by HOMER Energy, Inc., for MG (hybrid energy system) unit sizing. We compared the findings from WebOpt and HOMER and designed appropriately sized hybrid systems for our case studies. The objective of the project was to investigate real-time power management strategies for MGs using intelligent control, considering maximum feasible energy sustainability, reliability and efficiency while, minimizing cost and undesired environmental impact (emissions). Through analytic and simulation studies, we evaluated the suitability of several heuristic and artificial-intelligence (AI)-based optimization techniques that had potential for real-time MG power management, including genetic algorithms (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and multi-agent systems (MAS), which is based on the negotiation of smart software-based agents. We found that PSO and MAS, in particular, distributed MAS, were more efficient and better suited for our work. We investigated the following: • Intelligent load control - demand response (DR) - for frequency stabilization in islanded MGs (partially supported by PNNL). • The impact of high penetration of solar photovoltaic (PV)-generated power at the distribution level (partially supported by PNNL). • The application of AI approaches to renewable (wind, PV) power forecasting (proposed by the reviewers of our proposal). • Application of AI approaches and DR for real-time MG power management (partially supported by NEC Labs-America) • Application of DR in dealing with the variability of wind power • Real-time MG power management using DR and storage (partially supported by NEC Labs-America) • Application of DR in enhancing the performance of load-frequency controller • MAS-based whole-sale and retail power market design for smart grid A« less

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Mike

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Where value lives in a networked world.

PubMed

Sawhney, M; Parikh, D

2001-01-01

While many management thinkers proclaim an era of radical uncertainty, authors Sawhney and Parikh assert that the seemingly endless upheavals of the digital age are more predictable than that: today's changes have a common root, and that root lies in the nature of intelligence in networks. Understanding the patterns of intelligence migration can help companies decipher and plan for the inevitable disruptions in today's business environment. Two patterns in network intelligence are reshaping industries and organizations. First, intelligence is decoupling--that is, modern high-speed networks are pushing back-end intelligence and front-end intelligence toward opposite ends of the network, making the ends the two major sources of potential profits. Second, intelligence is becoming more fluid and modular. Small units of intelligence now float freely like molecules in the ether, coalescing into temporary bundles whenever and wherever necessary to solve problems. The authors present four strategies that companies can use to profit from these patterns: arbitrage allows companies to move intelligence to new regions or countries where the cost of maintaining intelligence is lower; aggregation combines formerly isolated pieces of infrastructure intelligence into a large pool of shared infrastructure provided over a network; rewiring allows companies to connect islands of intelligence by creating common information backbones; and reassembly allows businesses to reorganize pieces of intelligence into coherent, personalized packages for customers. By being aware of patterns in network intelligence and by acting rather than reacting, companies can turn chaos into opportunity, say the authors.

Rule-based mechanisms of learning for intelligent adaptive flight control

NASA Technical Reports Server (NTRS)

Handelman, David A.; Stengel, Robert F.

1990-01-01

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

Sustainable Model for Public Health Emergency Operations Centers for Global Settings.

PubMed

Balajee, S Arunmozhi; Pasi, Omer G; Etoundi, Alain Georges M; Rzeszotarski, Peter; Do, Trang T; Hennessee, Ian; Merali, Sharifa; Alroy, Karen A; Phu, Tran Dac; Mounts, Anthony W

2017-10-01

Capacity to receive, verify, analyze, assess, and investigate public health events is essential for epidemic intelligence. Public health Emergency Operations Centers (PHEOCs) can be epidemic intelligence hubs by 1) having the capacity to receive, analyze, and visualize multiple data streams, including surveillance and 2) maintaining a trained workforce that can analyze and interpret data from real-time emerging events. Such PHEOCs could be physically located within a ministry of health epidemiology, surveillance, or equivalent department rather than exist as a stand-alone space and serve as operational hubs during nonoutbreak times but in emergencies can scale up according to the traditional Incident Command System structure.

Intelligence Is Associated With Voluntary Disclosure in Child Sexual Abuse Victims.

PubMed

Bae, Seung Min; Kang, Jae Myeong; Hwang, In Cheol; Cho, Hyeongrae; Cho, Seong-Jin

2017-09-01

The purpose of this study was (1) to determine whether intelligence level is associated with the pattern of the disclosure and (2) to elucidate which, between the verbal and performance intelligence, better reflect the pattern of disclosure in child and adolescent sexual abuse victims. Data were collected on 162 participants who visited a public center for sexually abused children and adolescents between January 2013 and December 2014. Demographic information, case characteristics, and disclosure pattern as well as intelligence quotients (IQs) of subjects were gathered. Intelligence was analyzed as level, full scale IQ, and the verbal and performance IQ. Eighty-one subjects (50.0%) voluntarily disclosed that they have been sexually abused. In regression analysis, intellectual level, age, and the number of perpetrators were associated with disclosure pattern. Full scale IQ was associated with the disclosure pattern (odds ratio = .983, 95% confidence interval = .968-.997, p = .017). When intelligence was divided into verbal and performance IQ, verbal IQ affected the pattern of disclosure (odds ratio = .973, 95% confidence interval = .956-.991, p = .003) with linear correlation (p = .001). We found that IQ was associated with the disclosure pattern. The intelligence, especially in verbal domain, is linearly correlated with the probability of voluntary disclosure. We suggest that special legal assistance and social concern are required for children and adolescent victims below normal intelligence to make them disclose the sexual abuse. Copyright © 2017 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Model-Unified Planning and Execution for Distributed Autonomous System Control

NASA Technical Reports Server (NTRS)

Aschwanden, Pascal; Baskaran, Vijay; Bernardini, Sara; Fry, Chuck; Moreno, Maria; Muscettola, Nicola; Plaunt, Chris; Rijsman, David; Tompkins, Paul

2006-01-01

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

Low Power Shoe Integrated Intelligent Wireless Gait Measurement System

NASA Astrophysics Data System (ADS)

Wahab, Y.; Mazalan, M.; Bakar, N. A.; Anuar, A. F.; Zainol, M. Z.; Hamzah, F.

2014-04-01

Gait analysis measurement is a method to assess and identify gait events and the measurements of dynamic, motion and pressure parameters involving the lowest part of the body. This significant analysis is widely used in sports, rehabilitation as well as other health diagnostic towards improving the quality of life. This paper presents a new system empowered by Inertia Measurement Unit (IMU), ultrasonic sensors, piezoceramic sensors array, XBee wireless modules and Arduino processing unit. This research focuses on the design and development of a low power ultra-portable shoe integrated wireless intelligent gait measurement using MEMS and recent microelectronic devices for foot clearance, orientation, error correction, gait events and pressure measurement system. It is developed to be cheap, low power, wireless, real time and suitable for real life in-door and out-door environment.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Objective speech quality evaluation of real-time speech coders

NASA Astrophysics Data System (ADS)

Viswanathan, V. R.; Russell, W. H.; Huggins, A. W. F.

1984-02-01

This report describes the work performed in two areas: subjective testing of a real-time 16 kbit/s adaptive predictive coder (APC) and objective speech quality evaluation of real-time coders. The speech intelligibility of the APC coder was tested using the Diagnostic Rhyme Test (DRT), and the speech quality was tested using the Diagnostic Acceptability Measure (DAM) test, under eight operating conditions involving channel error, acoustic background noise, and tandem link with two other coders. The test results showed that the DRT and DAM scores of the APC coder equalled or exceeded the corresponding test scores fo the 32 kbit/s CVSD coder. In the area of objective speech quality evaluation, the report describes the development, testing, and validation of a procedure for automatically computing several objective speech quality measures, given only the tape-recordings of the input speech and the corresponding output speech of a real-time speech coder.

Analysis of musical expression in audio signals

NASA Astrophysics Data System (ADS)

Dixon, Simon

2003-01-01

In western art music, composers communicate their work to performers via a standard notation which specificies the musical pitches and relative timings of notes. This notation may also include some higher level information such as variations in the dynamics, tempo and timing. Famous performers are characterised by their expressive interpretation, the ability to convey structural and emotive information within the given framework. The majority of work on audio content analysis focusses on retrieving score-level information; this paper reports on the extraction of parameters describing the performance, a task which requires a much higher degree of accuracy. Two systems are presented: BeatRoot, an off-line beat tracking system which finds the times of musical beats and tracks changes in tempo throughout a performance, and the Performance Worm, a system which provides a real-time visualisation of the two most important expressive dimensions, tempo and dynamics. Both of these systems are being used to process data for a large-scale study of musical expression in classical and romantic piano performance, which uses artificial intelligence (machine learning) techniques to discover fundamental patterns or principles governing expressive performance.

Reflexive reasoning for distributed real-time systems

NASA Technical Reports Server (NTRS)

Goldstein, David

1994-01-01

This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

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.

[Control of intelligent car based on electroencephalogram and neurofeedback].

PubMed

Li, Song; Xiong, Xin; Fu, Yunfa

2018-02-01

To improve the performance of brain-controlled intelligent car based on motor imagery (MI), a method based on neurofeedback (NF) with electroencephalogram (EEG) for controlling intelligent car is proposed. A mental strategy of MI in which the energy column diagram of EEG features related to the mental activity is presented to subjects with visual feedback in real time to train them to quickly master the skills of MI and regulate their EEG activity, and combination of multi-features fusion of MI and multi-classifiers decision were used to control the intelligent car online. The average, maximum and minimum accuracy of identifying instructions achieved by the trained group (trained by the designed feedback system before the experiment) were 85.71%, 90.47% and 76.19%, respectively and the corresponding accuracy achieved by the control group (untrained) were 73.32%, 80.95% and 66.67%, respectively. For the trained group, the average, longest and shortest time consuming were 92 s, 101 s, and 85 s, respectively, while for the control group the corresponding time were 115.7 s, 120 s, and 110 s, respectively. According to the results described above, it is expected that this study may provide a new idea for the follow-up development of brain-controlled intelligent robot by the neurofeedback with EEG related to MI.

Real time UNIX in embedded control -- A case study within context of LynxOS

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

Kleines, H.; Zwoll, K.

1996-02-01

Intelligent communication controllers for a layered protocol profile are a typical example of an embedded control application, where the classical approach for the software development is based on a proprietary real-time operating system kernel under which the individual layers are implemented as tasks. Based on the exemplary implementation of a derivative of MAP 3.0, an unusual and innovative approach is presented, where the protocol software is implemented under the UNIX-compatible real-time operating system LynxOS. The overall design of the embedded control application is presented under a more general view and economical implications as well as aspects of the development environmentmore » and performance are discussed.« less

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

The importance of motivation and emotion for explaining human cognition.

PubMed

Güss, C Dominik; Dörner, Dietrich

2017-01-01

Lake et al. discuss building blocks of human intelligence that are quite different from those of artificial intelligence. We argue that a theory of human intelligence has to incorporate human motivations and emotions. The interaction of motivation, emotion, and cognition is the real strength of human intelligence and distinguishes it from artificial intelligence.

Patterns, transitions and the role of leaders in the collective dynamics of a simple robotic flock

NASA Astrophysics Data System (ADS)

Tarcai, Norbert; Virágh, Csaba; Ábel, Dániel; Nagy, Máté; Várkonyi, Péter L.; Vásárhelyi, Gábor; Vicsek, Tamás

2011-04-01

We have developed an experimental setup of very simple self-propelled robots to observe collective motion emerging as a result of inelastic collisions only. A circular pool and commercial RC boats were the basis of our first setup, where we demonstrated that jamming, clustering, disordered and ordered motion are all present in such a simple experiment and showed that the noise level has a fundamental role in the generation of collective dynamics. Critical noise ranges and the transition characteristics between the different collective patterns were also examined. In our second experiment we used a real-time tracking system and a few steerable model boats to introduce intelligent leaders into the flock. We demonstrated that even a very small portion of guiding members can determine group direction and enhance ordering through inelastic collisions. We also showed that noise can facilitate and speed up ordering with leaders. Our work was extended with an agent-based simulation model, too, and close similarity between real and simulation results was observed. The simulation results show clear statistical evidence of three states and negative correlation between density and ordered motion due to the onset of jamming. Our experiments confirm the different theoretical studies and simulation results in the literature on the subject of collision-based, noise-dependent and leader-driven self-propelled particle systems.

SOLON: An autonomous vehicle mission planner

NASA Technical Reports Server (NTRS)

Dudziak, M. J.

1987-01-01

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

AI techniques in geomagnetic storm forecasting

NASA Astrophysics Data System (ADS)

Lundstedt, Henrik

This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

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.

Intelligent systems installed in building of research centre for research purposes

NASA Astrophysics Data System (ADS)

Matusov, Jozef; Mokry, Marian; Kolkova, Zuzana; Sedivy, Stefan

2016-06-01

The attractiveness of intelligent buildings is nowadays directly connected with higher level of comfort and also the economic mode of consumption energy for heating, cooling and the total consumption of electricity for electric devices. The technologies of intelligent buildings compared with conventional solutions allow dynamic optimization in real time and make it easy for operational message. The basic division of functionality in horizontal direction is possible divide in to two areas such as Economical sophisticated residential care about the comfort of people in the building and Security features. The paper deals with description of intelligent systems which has a building of Research Centre. The building has installed the latest technology for utilization of renewable energy and also latest systems of controlling and driving all devices which contribute for economy operation by achieving the highest thermal comfort and overall safety.

Autocorrelation factors and intelligibility of Japanese monosyllables in individuals with sensorineural hearing loss.

PubMed

Shimokura, Ryota; Akasaka, Sakie; Nishimura, Tadashi; Hosoi, Hiroshi; Matsui, Toshie

2017-02-01

Some Japanese monosyllables contain consonants that are not easily discernible for individuals with sensorineural hearing loss. However, the acoustic features that make these monosyllables difficult to discern have not been clearly identified. Here, this study used the autocorrelation function (ACF), which can capture temporal features of signals, to clarify the factors influencing speech intelligibility. For each monosyllable, five factors extracted from the ACF [Φ(0): total energy; τ 1 and ϕ 1 : delay time and amplitude of the maximum peak; τ e : effective duration; W ϕ (0) : spectral centroid], voice onset time, speech intelligibility index, and loudness level were compared with the percentage of correctly perceived articulations (144 ears) obtained by 50 Japanese vowel and consonant-vowel monosyllables produced by one female speaker. Results showed that median effective duration [(τ e ) med ] was strongly correlated with the percentage of correctly perceived articulations of the consonants (r = 0.87, p < 0.01). (τ e ) med values were computed by running ACFs with the time lag at which the magnitude of the logarithmic-ACF envelope had decayed to -10 dB. Effective duration is a measure of temporal pattern persistence, i.e., the duration over which the waveform maintains a stable pattern. The authors postulate that low recognition ability is related to degraded perception of temporal fluctuation patterns.

Knowledge base rule partitioning design for CLIPS

NASA Technical Reports Server (NTRS)

Mainardi, Joseph D.; Szatkowski, G. P.

1990-01-01

This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

Word aligned bitmap compression method, data structure, and apparatus

DOEpatents

Wu, Kesheng; Shoshani, Arie; Otoo, Ekow

2004-12-14

The Word-Aligned Hybrid (WAH) bitmap compression method and data structure is a relatively efficient method for searching and performing logical, counting, and pattern location operations upon large datasets. The technique is comprised of a data structure and methods that are optimized for computational efficiency by using the WAH compression method, which typically takes advantage of the target computing system's native word length. WAH is particularly apropos to infrequently varying databases, including those found in the on-line analytical processing (OLAP) industry, due to the increased computational efficiency of the WAH compressed bitmap index. Some commercial database products already include some version of a bitmap index, which could possibly be replaced by the WAH bitmap compression techniques for potentially increased operation speed, as well as increased efficiencies in constructing compressed bitmaps. Combined together, this technique may be particularly useful for real-time business intelligence. Additional WAH applications may include scientific modeling, such as climate and combustion simulations, to minimize search time for analysis and subsequent data visualization.

Fall Down Detection Under Smart Home System.

PubMed

Juang, Li-Hong; Wu, Ming-Ni

2015-10-01

Medical technology makes an inevitable trend for the elderly population, therefore the intelligent home care is an important direction for science and technology development, in particular, elderly in-home safety management issues become more and more important. In this research, a low of operation algorithm and using the triangular pattern rule are proposed, then can quickly detect fall-down movements of humanoid by the installation of a robot with camera vision at home that will be able to judge the fall-down movements of in-home elderly people in real time. In this paper, it will present a preliminary design and experimental results of fall-down movements from body posture that utilizes image pre-processing and three triangular-mass-central points to extract the characteristics. The result shows that the proposed method would adopt some characteristic value and the accuracy can reach up to 90 % for a single character posture. Furthermore the accuracy can be up to 100 % when a continuous-time sampling criterion and support vector machine (SVM) classifier are used.

Real-time video analysis for retail stores

NASA Astrophysics Data System (ADS)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

AI's Philosophical Underpinnings: A Thinking Person's Walk through the Twists and Turns of Artificial Intelligence's Meandering Path

NASA Technical Reports Server (NTRS)

Colombano, Silvano; Norvig, Peter (Technical Monitor)

2000-01-01

Few human endeavors can be viewed both as extremely successful and unsuccessful at the same time. This is typically the case when goals have not been well defined or have been shifting in time. This has certainly been true of Artificial Intelligence (AI). The nature of intelligence has been the object of much thought and speculation throughout the history of philosophy. It is in the nature of philosophy that real headway is sometimes made only when appropriate tools become available. Similarly the computer, coupled with the ability to program (at least in principle) any function, appeared to be the tool that could tackle the notion of intelligence. To suit the tool, the problem of the nature of intelligence was soon sidestepped in favor of this notion: If a probing conversation with a computer could not be distinguished from a conversation with a human, then AI had been achieved. This notion became known as the Turing test, after the mathematician Alan Turing who proposed it in 1950. Conceptually rich and interesting, these early efforts gave rise to a large portion of the field's framework. Key to AI, rather than the 'number crunching' typical of computers until then, was viewed as the ability to manipulate symbols and make logical inferences. To facilitate these tasks, AI languages such as LISP and Prolog were invented and used widely in the field. One idea that emerged and enabled some success with real world problems was the notion that 'most intelligence' really resided in knowledge. A phrase attributed to Feigenbaum, one of the pioneers, was 'knowledge is the power.' With this premise, the problem is shifted from 'how do we solve problems' to 'how do we represent knowledge.' A good knowledge representation scheme could allow one to draw conclusions from given premises. Such schemes took forms such as rules,frames and scripts. It allowed the building of what became known as expert systems or knowledge based systems (KBS).

Neural network pattern recognition of thermal-signature spectra for chemical defense

NASA Astrophysics Data System (ADS)

Carrieri, Arthur H.; Lim, Pascal I.

1995-05-01

We treat infrared patterns of absorption or emission by nerve and blister agent compounds (and simulants of this chemical group) as features for the training of neural networks to detect the compounds' liquid layers on the ground or their vapor plumes during evaporation by external heating. Training of a four-layer network architecture is composed of a backward-error-propagation algorithm and a gradient-descent paradigm. We conduct testing by feed-forwarding preprocessed spectra through the network in a scaled format consistent with the structure of the training-data-set representation. The best-performance weight matrix (spectral filter) evolved from final network training and testing with software simulation trials is electronically transferred to a set of eight artificial intelligence integrated circuits (ICs') in specific modular form (splitting of weight matrices). This form makes full use of all input-output IC nodes. This neural network computer serves an important real-time detection function when it is integrated into pre-and postprocessing data-handling units of a tactical prototype thermoluminescence sensor now under development at the Edgewood Research, Development, and Engineering Center.

Extraterrestrial Intelligence: What Would it Mean?

NASA Astrophysics Data System (ADS)

Impey, Chris

2015-04-01

Results from NASA's Kepler mission imply a hundred million Earth-like habitable worlds in the Milky Way galaxy, many of which formed billions of years before the Earth. Each of these worlds is likely to have all of the ingredients needed for biology. The real estate of time and space for the evolution of intelligent life is formidable, begging the question of whether or not we are alone in the universe. The implications of making contact have been explored extensively in science fiction and the popular culture, but less frequently in the serious scientific literature. Astronomers have carried out searches for extraterrestrial intelligence for over half a century, with no success so far. In practice, it is easier to search for alien technology than to discern intelligence of unknown function and form. In this talk, the modes of technology that can currently be detected are summarized, along with the implications of a timing argument than any detected civilization is likely to be much more advanced than ours. Fermi's famous question ``Where Are They?'' is as well posed now as it was sixty years ago. The existence of extraterrestrial intelligence would have profound practical, cultural, and religious implications for humanity.

Development of a mobile probe-based traffic data fusion and flow management platform for innovative public-private information-based partnerships.

DOT National Transportation Integrated Search

2011-10-17

"Under the aegis of Intelligent Transportation Systems (ITS), real-time traffic information provision strategies are being proposed to manage traffic congestion, alleviate the effects of incidents, enhance response efficiency after disasters, and imp...

An investigation of operational procedures for highway advisory radio systems : final report.

DOT National Transportation Integrated Search

1995-09-01

A key objective of Intelligent Transportation Systems (ITS) is to provide travelers with accurate, real-time information, helping them make better decisions about when to travel, what mode to use, and what route to take. An interface is necessary to ...

Applications for the environment : real-time information synthesis (AERIS) eco-signal operations : operational concept.

DOT National Transportation Integrated Search

2002-04-01

The Logical Architecture is based on a Computer Aided Systems Engineering (CASE) model of the requirements for the flow of data and control through the various functions included in Intelligent Transportation Systems (ITS). Data Dictionary is the com...

Development of Two Intelligent Spray Systems for Ornamental Nurseries

USDA-ARS?s Scientific Manuscript database

Current application technology for floral, nursery, and other specialty crop production wastes significant amounts of pesticides. Two different real-time variable-rate sprayer prototypes for ornamental nursery and tree crops were developed to deliver chemicals on target areas as needed. The first pr...

Automated feedback to foster safe driving in young drivers : Phase 2.

DOT National Transportation Integrated Search

2015-12-01

Intelligent Speed Adaptation (ISA) represents a promising approach to reduce speeding. A core principle for ISA systems is that they provide real-time feedback to drivers, prompting them to reduce speed when some threshold at or above the limit is re...

Autonomous Collision-Free Navigation of Microvehicles in Complex and Dynamically Changing Environments.

PubMed

Li, Tianlong; Chang, Xiaocong; Wu, Zhiguang; Li, Jinxing; Shao, Guangbin; Deng, Xinghong; Qiu, Jianbin; Guo, Bin; Zhang, Guangyu; He, Qiang; Li, Longqiu; Wang, Joseph

2017-09-26

Self-propelled micro- and nanoscale robots represent a rapidly emerging and fascinating robotics research area. However, designing autonomous and adaptive control systems for operating micro/nanorobotics in complex and dynamically changing environments, which is a highly demanding feature, is still an unmet challenge. Here we describe a smart microvehicle for precise autonomous navigation in complicated environments and traffic scenarios. The fully autonomous navigation system of the smart microvehicle is composed of a microscope-coupled CCD camera, an artificial intelligence planner, and a magnetic field generator. The microscope-coupled CCD camera provides real-time localization of the chemically powered Janus microsphere vehicle and environmental detection for path planning to generate optimal collision-free routes, while the moving direction of the microrobot toward a reference position is determined by the external electromagnetic torque. Real-time object detection offers adaptive path planning in response to dynamically changing environments. We demonstrate that the autonomous navigation system can guide the vehicle movement in complex patterns, in the presence of dynamically changing obstacles, and in complex biological environments. Such a navigation system for micro/nanoscale vehicles, relying on vision-based close-loop control and path planning, is highly promising for their autonomous operation in complex dynamic settings and unpredictable scenarios expected in a variety of realistic nanoscale scenarios.

Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

2015-12-01

A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

A Genuine TEAM Player

NASA Technical Reports Server (NTRS)

2001-01-01

Qualtech Systems, Inc. developed a complete software system with capabilities of multisignal modeling, diagnostic analysis, run-time diagnostic operations, and intelligent interactive reasoners. Commercially available as the TEAMS (Testability Engineering and Maintenance System) tool set, the software can be used to reveal unanticipated system failures. The TEAMS software package is broken down into four companion tools: TEAMS-RT, TEAMATE, TEAMS-KB, and TEAMS-RDS. TEAMS-RT identifies good, bad, and suspect components in the system in real-time. It reports system health results from onboard tests, and detects and isolates failures within the system, allowing for rapid fault isolation. TEAMATE takes over from where TEAMS-RT left off by intelligently guiding the maintenance technician through the troubleshooting procedure, repair actions, and operational checkout. TEAMS-KB serves as a model management and collection tool. TEAMS-RDS (TEAMS-Remote Diagnostic Server) has the ability to continuously assess a system and isolate any failure in that system or its components, in real time. RDS incorporates TEAMS-RT, TEAMATE, and TEAMS-KB in a large-scale server architecture capable of providing advanced diagnostic and maintenance functions over a network, such as the Internet, with a web browser user interface.

Intelligent fuzzy controller for event-driven real time systems

NASA Technical Reports Server (NTRS)

Grantner, Janos; Patyra, Marek; Stachowicz, Marian S.

1992-01-01

Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.

Soft optics in intelligent optical networks

NASA Astrophysics Data System (ADS)

Shue, Chikong; Cao, Yang

2001-10-01

In addition to the recent advances in Hard-optics that pushes the optical transmission speed, distance, wave density and optical switching capacity, Soft-optics provides the necessary intelligence and control software that reduces operational costs, increase efficiency, and enhances revenue generating services by automating optimal optical circuit placement and restoration, and enabling value-added new services like Optical VPN. This paper describes the advances in 1) Overall Hard-optics and Soft-optics 2) Layered hierarchy of Soft-optics 3) Component of Soft-optics, including hard-optics drivers, Management Soft-optics, Routing Soft-optics and System Soft-optics 4) Key component of Routing and System Soft-optics, namely optical routing and signaling (including UNI/NNI and GMPLS signaling). In summary, the soft-optics on a new generation of OXC's enables Intelligent Optical Networks to provide just-in-time service delivery and fast restoration, and real-time capacity management that eliminates stranded bandwidth. It reduces operational costs and provides new revenue opportunities.

Real-time threat assessment for critical infrastructure protection: data incest and conflict in evidential reasoning

NASA Astrophysics Data System (ADS)

Brandon, R.; Page, S.; Varndell, J.

2012-06-01

This paper presents a novel application of Evidential Reasoning to Threat Assessment for critical infrastructure protection. A fusion algorithm based on the PCR5 Dezert-Smarandache fusion rule is proposed which fuses alerts generated by a vision-based behaviour analysis algorithm and a-priori watch-list intelligence data. The fusion algorithm produces a prioritised event list according to a user-defined set of event-type severity or priority weightings. Results generated from application of the algorithm to real data and Behaviour Analysis alerts captured at London's Heathrow Airport under the EU FP7 SAMURAI programme are presented. A web-based demonstrator system is also described which implements the fusion process in real-time. It is shown that this system significantly reduces the data deluge problem, and directs the user's attention to the most pertinent alerts, enhancing their Situational Awareness (SA). The end-user is also able to alter the perceived importance of different event types in real-time, allowing the system to adapt rapidly to changes in priorities as the situation evolves. One of the key challenges associated with fusing information deriving from intelligence data is the issue of Data Incest. Techniques for handling Data Incest within Evidential Reasoning frameworks are proposed, and comparisons are drawn with respect to Data Incest management techniques that are commonly employed within Bayesian fusion frameworks (e.g. Covariance Intersection). The challenges associated with simultaneously dealing with conflicting information and Data Incest in Evidential Reasoning frameworks are also discussed.

Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program Awareness

DTIC Science & Technology

2012-10-23

Quantum Intelligence, Inc. She was principal investigator (PI) for six contracts awarded by the DoD Small Business Innovation Research (SBIR) Program. She...with at OSD? I hope you don’t mind if I indulge in a little ‘stream of consciousness ’ musing about where LLA could really add value. One of the...implemented by Quantum Intelligence, Inc. (QI, 2001–2012). The unique contribution of this architecture is to leverage a peer-to-peer agent network

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.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

Street Viewer: An Autonomous Vision Based Traffic Tracking System.

PubMed

Bottino, Andrea; Garbo, Alessandro; Loiacono, Carmelo; Quer, Stefano

2016-06-03

The development of intelligent transportation systems requires the availability of both accurate traffic information in real time and a cost-effective solution. In this paper, we describe Street Viewer, a system capable of analyzing the traffic behavior in different scenarios from images taken with an off-the-shelf optical camera. Street Viewer operates in real time on embedded hardware architectures with limited computational resources. The system features a pipelined architecture that, on one side, allows one to exploit multi-threading intensively and, on the other side, allows one to improve the overall accuracy and robustness of the system, since each layer is aimed at refining for the following layers the information it receives as input. Another relevant feature of our approach is that it is self-adaptive. During an initial setup, the application runs in learning mode to build a model of the flow patterns in the observed area. Once the model is stable, the system switches to the on-line mode where the flow model is used to count vehicles traveling on each lane and to produce a traffic information summary. If changes in the flow model are detected, the system switches back autonomously to the learning mode. The accuracy and the robustness of the system are analyzed in the paper through experimental results obtained on several different scenarios and running the system for long periods of time.

Real-time full-motion color Flash lidar for target detection and identification

NASA Astrophysics Data System (ADS)

Nelson, Roy; Coppock, Eric; Craig, Rex; Craner, Jeremy; Nicks, Dennis; von Niederhausern, Kurt

2015-05-01

Greatly improved understanding of areas and objects of interest can be gained when real time, full-motion Flash LiDAR is fused with inertial navigation data and multi-spectral context imagery. On its own, full-motion Flash LiDAR provides the opportunity to exploit the z dimension for improved intelligence vs. 2-D full-motion video (FMV). The intelligence value of this data is enhanced when it is combined with inertial navigation data to produce an extended, georegistered data set suitable for a variety of analysis. Further, when fused with multispectral context imagery the typical point cloud now becomes a rich 3-D scene which is intuitively obvious to the user and allows rapid cognitive analysis with little or no training. Ball Aerospace has developed and demonstrated a real-time, full-motion LIDAR system that fuses context imagery (VIS to MWIR demonstrated) and inertial navigation data in real time, and can stream these information-rich geolocated/fused 3-D scenes from an airborne platform. In addition, since the higher-resolution context camera is boresighted and frame synchronized to the LiDAR camera and the LiDAR camera is an array sensor, techniques have been developed to rapidly interpolate the LIDAR pixel values creating a point cloud that has the same resolution as the context camera, effectively creating a high definition (HD) LiDAR image. This paper presents a design overview of the Ball TotalSight™ LIDAR system along with typical results over urban and rural areas collected from both rotary and fixed-wing aircraft. We conclude with a discussion of future work.

Decision-making conflict and the neural efficiency hypothesis of intelligence: a functional near-infrared spectroscopy investigation.

PubMed

Di Domenico, Stefano I; Rodrigo, Achala H; Ayaz, Hasan; Fournier, Marc A; Ruocco, Anthony C

2015-04-01

Research on the neural efficiency hypothesis of intelligence (NEH) has revealed that the brains of more intelligent individuals consume less energy when performing easy cognitive tasks but more energy when engaged in difficult mental operations. However, previous studies testing the NEH have relied on cognitive tasks that closely resemble psychometric tests of intelligence, potentially confounding efficiency during intelligence-test performance with neural efficiency per se. The present study sought to provide a novel test of the NEH by examining patterns of prefrontal activity while participants completed an experimental paradigm that is qualitatively distinct from the contents of psychometric tests of intelligence. Specifically, participants completed a personal decision-making task (e.g., which occupation would you prefer, dancer or chemist?) in which they made a series of forced choices according to their subjective preferences. The degree of decisional conflict (i.e., choice difficulty) between the available response options was manipulated on the basis of participants' unique preference ratings for the target stimuli, which were obtained prior to scanning. Evoked oxygenation of the prefrontal cortex was measured using 16-channel continuous-wave functional near-infrared spectroscopy. Consistent with the NEH, intelligence predicted decreased activation of the right inferior frontal gyrus (IFG) during low-conflict situations and increased activation of the right-IFG during high-conflict situations. This pattern of right-IFG activity among more intelligent individuals was complemented by faster reaction times in high-conflict situations. These results provide new support for the NEH and suggest that the neural efficiency of more intelligent individuals generalizes to the performance of cognitive tasks that are distinct from intelligence tests. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling Real-Time Applications with Reusable Design Patterns

NASA Astrophysics Data System (ADS)

Rekhis, Saoussen; Bouassida, Nadia; Bouaziz, Rafik

Real-Time (RT) applications, which manipulate important volumes of data, need to be managed with RT databases that deal with time-constrained data and time-constrained transactions. In spite of their numerous advantages, RT databases development remains a complex task, since developers must study many design issues related to the RT domain. In this paper, we tackle this problem by proposing RT design patterns that allow the modeling of structural and behavioral aspects of RT databases. We show how RT design patterns can provide design assistance through architecture reuse of reoccurring design problems. In addition, we present an UML profile that represents patterns and facilitates further their reuse. This profile proposes, on one hand, UML extensions allowing to model the variability of patterns in the RT context and, on another hand, extensions inspired from the MARTE (Modeling and Analysis of Real-Time Embedded systems) profile.

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Intelligence's likelihood and evolutionary time frame

NASA Astrophysics Data System (ADS)

Bogonovich, Marc

2011-04-01

This paper outlines hypotheses relevant to the evolution of intelligent life and encephalization in the Phanerozoic. If general principles are inferable from patterns of Earth life, implications could be drawn for astrobiology. Many of the outlined hypotheses, relevant data, and associated evolutionary and ecological theory are not frequently cited in astrobiological journals. Thus opportunity exists to evaluate reviewed hypotheses with an astrobiological perspective. A quantitative method is presented for testing one of the reviewed hypotheses (hypothesis i; the diffusion hypothesis). Questions are presented throughout, which illustrate that the question of intelligent life's likelihood can be expressed as multiple, broadly ranging, more tractable questions.

The effect of cerebral palsy on arithmetic accuracy is mediated by working memory, intelligence, early numeracy, and instruction time.

PubMed

Jenks, Kathleen M; de Moor, Jan; van Lieshout, Ernest C D M; Maathuis, Karel G B; Keus, Inge; Gorter, Jan Willem

2007-01-01

The development of addition and subtraction accuracy was assessed in first graders with cerebral palsy (CP) in both mainstream (16) and special education (41) and a control group of first graders in mainstream education (16). The control group out-performed the CP groups in addition and subtraction accuracy and this difference could not be fully explained by differences in intelligence. Both CP groups showed evidence of working memory deficits. The three groups exhibited different developmental patterns in the area of early numeracy skills. Children with CP in special education were found to receive less arithmetic instruction and instruction time was positively related to arithmetic accuracy. Structural equation modeling revealed that the effect of CP on arithmetic accuracy is mediated by intelligence, working memory, early numeracy, and instruction time.

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

NASA Technical Reports Server (NTRS)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

Automated feedback to foster safe driving in young drivers: phase 2 : traffic tech.

DOT National Transportation Integrated Search

2015-12-01

Intelligent Speed Adaptation (ISA) provides a promising approach to reduce speeding. A core principle of ISA is real-time feedback that lets drivers know when they are driving over the speed limit. The overall goal of the study was to provide insight...

Sensing, Measurement, and Forecasting | Grid Modernization | NREL

Science.gov Websites

into operational intelligence to support grid operations and planning. Photo of solar resource monitoring equipment Grid operations involve assessing the grid's health in real time, predicting its to hours and days-to support advances in power system operations and planning. Capabilities Solar

Microscopic Car Modeling for Intelligent Traffic and Scenario Generation in the UCF Driving Simulator : Year 2

DOT National Transportation Integrated Search

2000-01-01

A multi-year project was initiated to introduce autonomous vehicles in the University of Central Florida (UCF) Driving Simulator for real-time interaction with the simulator vehicle. This report describes the progress during the second year. In the f...

Quantum Speedup for Active Learning Agents

NASA Astrophysics Data System (ADS)

Paparo, Giuseppe Davide; Dunjko, Vedran; Makmal, Adi; Martin-Delgado, Miguel Angel; Briegel, Hans J.

2014-07-01

Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.

Games and machine learning: a powerful combination in an artificial intelligence course

NASA Astrophysics Data System (ADS)

Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

2010-03-01

Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

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.

Adjustment of gripping force by optical systems

NASA Astrophysics Data System (ADS)

Jalba, C. K.; Barz, C.

2018-01-01

With increasing automation, robotics also requires ever more intelligent solutions in the handling of various tasks. In this context, many grippers must also be re-designed. For this, they must always be adapted for different requirements. The equipment of the gripper systems with sensors should help to make the gripping process more intelligent. In order to achieve such objectives, optical systems can also be used. This work analyzes how the gripping force can be adjusted by means of an optical recognition. The result of this work is the creation of a connection between optical recognition, tolerances, gripping force and real-time control. In this way, algorithms can be created, with the aid of which robot grippers as well as other gripping systems become more intelligent.

Forward collision warning based on kernelized correlation filters

NASA Astrophysics Data System (ADS)

Pu, Jinchuan; Liu, Jun; Zhao, Yong

2017-07-01

A vehicle detection and tracking system is one of the indispensable methods to reduce the occurrence of traffic accidents. The nearest vehicle is the most likely to cause harm to us. So, this paper will do more research on about the nearest vehicle in the region of interest (ROI). For this system, high accuracy, real-time and intelligence are the basic requirement. In this paper, we set up a system that combines the advanced KCF tracking algorithm with the HaarAdaBoost detection algorithm. The KCF algorithm reduces computation time and increase the speed through the cyclic shift and diagonalization. This algorithm satisfies the real-time requirement. At the same time, Haar features also have the same advantage of simple operation and high speed for detection. The combination of this two algorithm contribute to an obvious improvement of the system running rate comparing with previous works. The detection result of the HaarAdaBoost classifier provides the initial value for the KCF algorithm. This fact optimizes KCF algorithm flaws that manual car marking in the initial phase, which is more scientific and more intelligent. Haar detection and KCF tracking with Histogram of Oriented Gradient (HOG) ensures the accuracy of the system. We evaluate the performance of framework on dataset that were self-collected. The experimental results demonstrate that the proposed method is robust and real-time. The algorithm can effectively adapt to illumination variation, even in the night it can meet the detection and tracking requirements, which is an improvement compared with the previous work.

A coupled duration-focused architecture for real-time music-to-score alignment.

PubMed

Cont, Arshia

2010-06-01

The capacity for real-time synchronization and coordination is a common ability among trained musicians performing a music score that presents an interesting challenge for machine intelligence. Compared to speech recognition, which has influenced many music information retrieval systems, music's temporal dynamics and complexity pose challenging problems to common approximations regarding time modeling of data streams. In this paper, we propose a design for a real-time music-to-score alignment system. Given a live recording of a musician playing a music score, the system is capable of following the musician in real time within the score and decoding the tempo (or pace) of its performance. The proposed design features two coupled audio and tempo agents within a unique probabilistic inference framework that adaptively updates its parameters based on the real-time context. Online decoding is achieved through the collaboration of the coupled agents in a Hidden Hybrid Markov/semi-Markov framework, where prediction feedback of one agent affects the behavior of the other. We perform evaluations for both real-time alignment and the proposed temporal model. An implementation of the presented system has been widely used in real concert situations worldwide and the readers are encouraged to access the actual system and experiment the results.

Infrared Sensor System for Mobile-Robot Positioning in Intelligent Spaces

PubMed Central

Gorostiza, Ernesto Martín; Galilea, José Luis Lázaro; Meca, Franciso Javier Meca; Monzú, David Salido; Zapata, Felipe Espinosa; Puerto, Luis Pallarés

2011-01-01

The aim of this work was to position a Mobile Robot in an Intelligent Space, and this paper presents a sensorial system for measuring differential phase-shifts in a sinusoidally modulated infrared signal transmitted from the robot. Differential distances were obtained from these phase-shifts, and the position of the robot was estimated by hyperbolic trilateration. Due to the extremely severe trade-off between SNR, angle (coverage) and real-time response, a very accurate design and device selection was required to achieve good precision with wide coverage and acceptable robot speed. An I/Q demodulator was used to measure phases with one-stage synchronous demodulation to DC. A complete set of results from real measurements, both for distance and position estimations, is provided to demonstrate the validity of the system proposed, comparing it with other similar indoor positioning systems. PMID:22163907

Real-time artificial intelligence issues in the development of the adaptive tactical navigator

NASA Technical Reports Server (NTRS)

Green, Peter E.; Glasson, Douglas P.; Pomarede, Jean-Michel L.; Acharya, Narayan A.

1987-01-01

Adaptive Tactical Navigation (ATN) is a laboratory prototype of a knowledge based system to provide navigation system management and decision aiding in the next generation of tactical aircraft. ATN's purpose is to manage a set of multimode navigation equipment, dynamically selecting the best equipment to use in accordance with mission goals and phase, threat environment, equipment malfunction status, and battle damage. ATN encompasses functions as diverse as sensor data interpretation, diagnosis, and planning. Real time issues that were identified in ATN and the approaches used to address them are addressed. Functional requirements and a global architecture for the ATN system are described. Decision making with time constraints are discussed. Two subproblems are identified; making decisions with incomplete information and with limited resources. Approaches used in ATN to address real time performance are described and simulation results are discussed.

Near Real-Time Call Detail Record ETL Flows

NASA Astrophysics Data System (ADS)

Cochinwala, Munir; Panagos, Euthimios

Telecommunication companies face significant business challenges as they strive to reduce subscriber churn and increase average revenue per user (ARPU) by offering new services and incorporating new functionality into existing services. The increased number of service offerings and available functionality result in an ever growing volume of call detail records (CDRs). For many services (e.g., pre-paid), CDRs need to be processed and analyzed in near real-time for several reasons, including charging, on-line subscriber access to their accounts, and analytics for predicting subscriber usage and preventing fraudulent activity. In this paper, we describe the challenges associated with near real-time extract, transform, and load (ETL) of CDR data warehouse flows for supporting both the operational and business intelligence needs of telecommunication services, and we present our approach to addressing these challenges.

Design and Realization of Silhouette Operation Platform Based on GIS

NASA Astrophysics Data System (ADS)

Fu, Jia; Cui, Xinqiang; Yuan, Zhengteng

2018-01-01

Artificial weather effects after several generations of unremitting efforts in many provinces, municipalities and districts have become a regular business to serve the community. In the actual operation of the actual impact of weather operations, onsite job terminal system functional integration is not high, such as the operation process cumbersome operation instructions unreasonable, the weather data lag, the data form of a single factor and other factors seriously affect the weather conditions, Sexual and intuitive improvement. Therefore, this paper adopts the Android system as the carrier for the design and implementation of the silhouette intelligent terminal system. The intelligent terminal system has carried on the preliminary deployment trial in the real-time intelligent command system which realizes the weather operation in a province, and has formed a centralized, unified and digital artificial influence in combination with the self-developed multi-function server system platform and the remote centre command system Weather operation communication network, to achieve intelligent terminal and remote centre commander between the efficient, timely and stable information exchange, improve the shadow of the economic and social benefits, basically reached the initial design purpose.

Spin-Off Successes of SETI Research at Berkeley

NASA Astrophysics Data System (ADS)

Douglas, K. A.; Anderson, D. P.; Bankay, R.; Chen, H.; Cobb, J.; Korpela, E. J.; Lebofsky, M.; Parsons, A.; von Korff, J.; Werthimer, D.

2009-12-01

Our group contributes to the Search for Extra-Terrestrial Intelligence (SETI) by developing and using world-class signal processing computers to analyze data collected on the Arecibo telescope. Although no patterned signal of extra-terrestrial origin has yet been detected, and the immediate prospects for making such a detection are highly uncertain, the SETI@home project has nonetheless proven the value of pursuing such research through its impact on the fields of distributed computing, real-time signal processing, and radio astronomy. The SETI@home project has spun off the Center for Astronomy Signal Processing and Electronics Research (CASPER) and the Berkeley Open Infrastructure for Networked Computing (BOINC), both of which are responsible for catalyzing a smorgasbord of new research in scientific disciplines in countries around the world. Futhermore, the data collected and archived for the SETI@home project is proving valuable in data-mining experiments for mapping neutral galatic hydrogen and for detecting black-hole evaporation.

Intelligent cooperation: A framework of pedagogic practice in the operating room.

PubMed

Sutkin, Gary; Littleton, Eliza B; Kanter, Steven L

2018-04-01

Surgeons who work with trainees must address their learning needs without compromising patient safety. We used a constructivist grounded theory approach to examine videos of five teaching surgeries. Attending surgeons were interviewed afterward while watching cued videos of their cases. Codes were iteratively refined into major themes, and then constructed into a larger framework. We present a novel framework, Intelligent Cooperation, which accounts for the highly adaptive, iterative features of surgical teaching in the operating room. Specifically, we define Intelligent Cooperation as a sequence of coordinated exchanges between attending and trainee that accomplishes small surgical steps while simultaneously uncovering the trainee's learning needs. Intelligent Cooperation requires the attending to accurately determine learning needs, perform real-time needs assessment, provide critical scaffolding, and work with the learner to accomplish the next step in the surgery. This is achieved through intense, coordinated verbal and physical cooperation. Copyright © 2017 Elsevier Inc. All rights reserved.

Controllable Ag nanostructure patterning in a microfluidic channel for real-time SERS systems.

PubMed

Leem, Juyoung; Kang, Hyun Wook; Ko, Seung Hwan; Sung, Hyung Jin

2014-03-07

We present a microfluidic patterning system for fabricating nanostructured Ag thin films via a polyol method. The fabricated Ag thin films can be used immediately in a real-time SERS sensing system. The Ag thin films are formed on the inner surfaces of a microfluidic channel so that a Ag-patterned Si wafer and a Ag-patterned PDMS channel are produced by the fabrication. The optimum sensing region and fabrication duration for effective SERS detection were determined. As SERS active substrates, the patterned Ag thin films exhibit an enhancement factor (EF) of 4.25 × 10(10). The Ag-patterned polymer channel was attached to a glass substrate and used as a microfluidic sensing system for the real-time monitoring of biomolecule concentrations. This microfluidic patterning system provides a low-cost process for the fabrication of materials that are useful in medical and pharmaceutical detection and can be employed in mass production.

Extracting foreground ensemble features to detect abnormal crowd behavior in intelligent video-surveillance systems

NASA Astrophysics Data System (ADS)

Chan, Yi-Tung; Wang, Shuenn-Jyi; Tsai, Chung-Hsien

2017-09-01

Public safety is a matter of national security and people's livelihoods. In recent years, intelligent video-surveillance systems have become important active-protection systems. A surveillance system that provides early detection and threat assessment could protect people from crowd-related disasters and ensure public safety. Image processing is commonly used to extract features, e.g., people, from a surveillance video. However, little research has been conducted on the relationship between foreground detection and feature extraction. Most current video-surveillance research has been developed for restricted environments, in which the extracted features are limited by having information from a single foreground; they do not effectively represent the diversity of crowd behavior. This paper presents a general framework based on extracting ensemble features from the foreground of a surveillance video to analyze a crowd. The proposed method can flexibly integrate different foreground-detection technologies to adapt to various monitored environments. Furthermore, the extractable representative features depend on the heterogeneous foreground data. Finally, a classification algorithm is applied to these features to automatically model crowd behavior and distinguish an abnormal event from normal patterns. The experimental results demonstrate that the proposed method's performance is both comparable to that of state-of-the-art methods and satisfies the requirements of real-time applications.

Optical Pattern Recognition With Self-Amplification

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1994-01-01

In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

Analyzing Learner Language: Towards a Flexible Natural Language Processing Architecture for Intelligent Language Tutors

ERIC Educational Resources Information Center

Amaral, Luiz; Meurers, Detmar; Ziai, Ramon

2011-01-01

Intelligent language tutoring systems (ILTS) typically analyze learner input to diagnose learner language properties and provide individualized feedback. Despite a long history of ILTS research, such systems are virtually absent from real-life foreign language teaching (FLT). Taking a step toward more closely linking ILTS research to real-life…

Real-time robot deliberation by compilation and monitoring of anytime algorithms

NASA Technical Reports Server (NTRS)

Zilberstein, Shlomo

1994-01-01

Anytime algorithms are algorithms whose quality of results improves gradually as computation time increases. Certainty, accuracy, and specificity are metrics useful in anytime algorighm construction. It is widely accepted that a successful robotic system must trade off between decision quality and the computational resources used to produce it. Anytime algorithms were designed to offer such a trade off. A model of compilation and monitoring mechanisms needed to build robots that can efficiently control their deliberation time is presented. This approach simplifies the design and implementation of complex intelligent robots, mechanizes the composition and monitoring processes, and provides independent real time robotic systems that automatically adjust resource allocation to yield optimum performance.

Agents in real-time collaborative systems

NASA Astrophysics Data System (ADS)

Mitchell, David

1996-01-01

Desktop conferencing systems, providing voice- or video-conferencing with some form of data sharing, have become increasingly popular. Unlike asynchronous collaborative systems such as email, little attention has been devoted to the place of agents in such real-time systems. This paper examines some of the ways in which agents can be used to support such apparently simple tasks as the setting up and answering of calls. Three agent categories, locators, routers and responders, are defined and some simple examples discussed. Several ways in which such agents can collaborate, providing the basis of an intelligent network, are identified.

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

A Real-Time Knowledge Based Expert System For Diagnostic Problem Solving

NASA Astrophysics Data System (ADS)

Esteva, Juan C.; Reynolds, Robert G.

1986-03-01

This paper is a preliminary report of a real-time expert system which is concerned with the detection and diagnosis of electrical deviations in on-board vehicle-based electrical systems. The target systems are being tested at radio frequencies to evaluate their capability to be operated at designed levels of efficiency in an electromagnetic environment. The measurement of this capability is known as ElectroMagnetic Compatibility (EMC). The Intelligent Deviation Diagnosis (IDD) system consists of two basic modules the Automatic Data Acquisition Module (ADAM) and the Diagnosis System (DS). In this paper only the diagnosis system is described.

A computer assisted intelligent storm outage evaluator for power distribution systems

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

Balakrishnan, R.; Pahwa, A.

1990-07-01

The lower voltage part of the power distribution system (primary and secondary sub-systems) does not have the provision for real-time status feedback, and as a result evaluation of outages is an extremely difficult task, especially during system emergencies caused by tornadoes and ice-storms. In this paper, a knowledge based approach is proposed for evaluation of storm related outages in the distribution systems. At the outset, binary voltage sensors capable of transmitting the real-time voltage on/off symptoms are recommended to be installed at strategic locations in the distribution system.

Research of real-time video processing system based on 6678 multi-core DSP

NASA Astrophysics Data System (ADS)

Li, Xiangzhen; Xie, Xiaodan; Yin, Xiaoqiang

2017-10-01

In the information age, the rapid development in the direction of intelligent video processing, complex algorithm proposed the powerful challenge on the performance of the processor. In this article, through the FPGA + TMS320C6678 frame structure, the image to fog, merge into an organic whole, to stabilize the image enhancement, its good real-time, superior performance, break through the traditional function of video processing system is simple, the product defects such as single, solved the video application in security monitoring, video, etc. Can give full play to the video monitoring effectiveness, improve enterprise economic benefits.

Real Time Network Monitoring and Reporting System

ERIC Educational Resources Information Center

Massengale, Ricky L., Sr.

2009-01-01

With the ability of modern system developers to develop intelligent programs that allows machines to learn, modify and evolve themselves, current trends of reactionary methods to detect and eradicate malicious software code from infected machines is proving to be too costly. Addressing malicious software after an attack is the current methodology…

A New Architecture for Improved Human Behavior in Military Simulations

DTIC Science & Technology

2008-04-01

forces were using motorcycle couriers to avoid U.S. intelligence capabilities in the early days of Operation Iraqi Freedom (OIF), there were certainly...Games ( MMORPG ) engage millions of game players in near-real-time computing environments. Games such as World of Warcraft® attract players to

Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream

NASA Astrophysics Data System (ADS)

Ding, Yulin; Lin, Hui; Li, Rongrong

2016-06-01

Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led to large estimation error. In order to achieve the best generalization error, it is an important challenge for the data cleaning methodology to be able to characterize the behavior of data stream distributions and adaptively update a model to include new information and remove old information. However, the complicated data changing property invalidates traditional data cleaning methods, which rely on the assumption of a stationary data distribution, and drives the need for more dynamic and adaptive online data cleaning methods. To overcome these shortcomings, this paper presents a change semantics constrained online filtering method for real-time observational data. Based on the principle that the filter parameter should vary in accordance to the data change patterns, this paper embeds semantic description, which quantitatively depicts the change patterns in the data distribution to self-adapt the filter parameter automatically. Real-time observational water level data streams of different precipitation scenarios are selected for testing. Experimental results prove that by means of this method, more accurate and reliable water level information can be available, which is prior to scientific and prompt flood assessment and decision-making.

Intelligent lead: a novel HRI sensor for guide robots.

PubMed

Cho, Keum-Bae; Lee, Beom-Hee

2012-01-01

This paper addresses the introduction of a new Human Robot Interaction (HRI) sensor for guide robots. Guide robots for geriatric patients or the visually impaired should follow user's control command, keeping a certain desired distance allowing the user to work freely. Therefore, it is necessary to acquire control commands and a user's position on a real-time basis. We suggest a new sensor fusion system to achieve this objective and we will call this sensor the "intelligent lead". The objective of the intelligent lead is to acquire a stable distance from the user to the robot, speed-control volume and turn-control volume, even when the robot platform with the intelligent lead is shaken on uneven ground. In this paper we explain a precise Extended Kalman Filter (EKF) procedure for this. The intelligent lead physically consists of a Kinect sensor, the serial linkage attached with eight rotary encoders, and an IMU (Inertial Measurement Unit) and their measurements are fused by the EKF. A mobile robot was designed to test the performance of the proposed sensor system. After installing the intelligent lead in the mobile robot, several tests are conducted to verify that the mobile robot with the intelligent lead is capable of achieving its goal points while maintaining the appropriate distance between the robot and the user. The results show that we can use the intelligent lead proposed in this paper as a new HRI sensor joined a joystick and a distance measure in the mobile environments such as the robot and the user are moving at the same time.

An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation.

PubMed

Lin, Chin-Teng; Chang, Kuan-Cheng; Lin, Chun-Ling; Chiang, Chia-Cheng; Lu, Shao-Wei; Chang, Shih-Sheng; Lin, Bor-Shyh; Liang, Hsin-Yueh; Chen, Ray-Jade; Lee, Yuan-Teh; Ko, Li-Wei

2010-05-01

This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.

Development of dog-like retrieving capability in a ground robot

NASA Astrophysics Data System (ADS)

MacKenzie, Douglas C.; Ashok, Rahul; Rehg, James M.; Witus, Gary

2013-01-01

This paper presents the Mobile Intelligence Team's approach to addressing the CANINE outdoor ground robot competition. The competition required developing a robot that provided retrieving capabilities similar to a dog, while operating fully autonomously in unstructured environments. The vision team consisted of Mobile Intelligence, the Georgia Institute of Technology, and Wayne State University. Important computer vision aspects of the project were the ability to quickly learn the distinguishing characteristics of novel objects, searching images for the object as the robot drove a search pattern, identifying people near the robot for safe operations, correctly identify the object among distractors, and localizing the object for retrieval. The classifier used to identify the objects will be discussed, including an analysis of its performance, and an overview of the entire system architecture presented. A discussion of the robot's performance in the competition will demonstrate the system's successes in real-world testing.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

PubMed Central

Mateo, Carlos M.; Gil, Pablo; Torres, Fernando

2016-01-01

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID:27164102

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands.

PubMed

Mateo, Carlos M; Gil, Pablo; Torres, Fernando

2016-05-05

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object's surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand's fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Human-directed local autonomy for motion guidance and coordination in an intelligent manufacturing system

NASA Astrophysics Data System (ADS)

Alford, W. A.; Kawamura, Kazuhiko; Wilkes, Don M.

1997-12-01

This paper discusses the problem of integrating human intelligence and skills into an intelligent manufacturing system. Our center has jointed the Holonic Manufacturing Systems (HMS) Project, an international consortium dedicated to developing holonic systems technologies. One of our contributions to this effort is in Work Package 6: flexible human integration. This paper focuses on one activity, namely, human integration into motion guidance and coordination. Much research on intelligent systems focuses on creating totally autonomous agents. At the Center for Intelligent Systems (CIS), we design robots that interact directly with a human user. We focus on using the natural intelligence of the user to simplify the design of a robotic system. The problem is finding ways for the user to interact with the robot that are efficient and comfortable for the user. Manufacturing applications impose the additional constraint that the manufacturing process should not be disturbed; that is, frequent interacting with the user could degrade real-time performance. Our research in human-robot interaction is based on a concept called human directed local autonomy (HuDL). Under this paradigm, the intelligent agent selects and executes a behavior or skill, based upon directions from a human user. The user interacts with the robot via speech, gestures, or other media. Our control software is based on the intelligent machine architecture (IMA), an object-oriented architecture which facilitates cooperation and communication among intelligent agents. In this paper we describe our research testbed, a dual-arm humanoid robot and human user, and the use of this testbed for a human directed sorting task. We also discuss some proposed experiments for evaluating the integration of the human into the robot system. At the time of this writing, the experiments have not been completed.

A Probabilistic Ontology Development Methodology

DTIC Science & Technology

2014-06-01

Test, and Evaluation; Acquisition; and Planning and Marketing ," in Handbook of Systems Engineering and Management .: John Wiley & Sons, 2009, pp...Intelligence and knowledge management . However, many real world problems in these disciplines are burdened by incomplete information and other sources...knowledge engineering, Artificial Intelligence and knowledge management . However, many real world problems in these disciplines are burdened by

Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty.

PubMed

Casnici, Niccolò; Dondio, Pierpaolo; Casarin, Roberto; Squazzoni, Flaminio

2015-01-01

This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks.

Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty

PubMed Central

Casnici, Niccolò; Dondio, Pierpaolo; Casarin, Roberto; Squazzoni, Flaminio

2015-01-01

This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks. PMID:26244550

Flight Investigation of Prescribed Simultaneous Independent Surface Excitations for Real-Time Parameter Identification

NASA Technical Reports Server (NTRS)

Moes, Timothy R.; Smith, Mark S.; Morelli, Eugene A.

2003-01-01

Near real-time stability and control derivative extraction is required to support flight demonstration of Intelligent Flight Control System (IFCS) concepts being developed by NASA, academia, and industry. Traditionally, flight maneuvers would be designed and flown to obtain stability and control derivative estimates using a postflight analysis technique. The goal of the IFCS concept is to be able to modify the control laws in real time for an aircraft that has been damaged in flight. In some IFCS implementations, real-time parameter identification (PID) of the stability and control derivatives of the damaged aircraft is necessary for successfully reconfiguring the control system. This report investigates the usefulness of Prescribed Simultaneous Independent Surface Excitations (PreSISE) to provide data for rapidly obtaining estimates of the stability and control derivatives. Flight test data were analyzed using both equation-error and output-error PID techniques. The equation-error PID technique is known as Fourier Transform Regression (FTR) and is a frequency-domain real-time implementation. Selected results were compared with a time-domain output-error technique. The real-time equation-error technique combined with the PreSISE maneuvers provided excellent derivative estimation in the longitudinal axis. However, the PreSISE maneuvers as presently defined were not adequate for accurate estimation of the lateral-directional derivatives.

Perceived intelligence is associated with measured intelligence in men but not women.

PubMed

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape.

Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women

PubMed Central

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

Background The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. Methodology/Principal Findings We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. Conclusions These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape. PMID:24651120

Epistasis analysis using artificial intelligence.

PubMed

Moore, Jason H; Hill, Doug P

2015-01-01

Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

Spacecraft Health Automated Reasoning Prototype (SHARP): The fiscal year 1989 SHARP portability evaluations task for NASA Solar System Exploration Division's Voyager project

NASA Technical Reports Server (NTRS)

Atkinson, David J.; Doyle, Richard J.; James, Mark L.; Kaufman, Tim; Martin, R. Gaius

1990-01-01

A Spacecraft Health Automated Reasoning Prototype (SHARP) portability study is presented. Some specific progress is described on the portability studies, plans for technology transfer, and potential applications of SHARP and related artificial intelligence technology to telescience operations. The application of SHARP to Voyager telecommunications was a proof-of-capability demonstration of artificial intelligence as applied to the problem of real time monitoring functions in planetary mission operations. An overview of the design and functional description of the SHARP system is also presented as it was applied to Voyager.

Knowledge representation into Ada parallel processing

NASA Technical Reports Server (NTRS)

Masotto, Tom; Babikyan, Carol; Harper, Richard

1990-01-01

The Knowledge Representation into Ada Parallel Processing project is a joint NASA and Air Force funded project to demonstrate the execution of intelligent systems in Ada on the Charles Stark Draper Laboratory fault-tolerant parallel processor (FTPP). Two applications were demonstrated - a portion of the adaptive tactical navigator and a real time controller. Both systems are implemented as Activation Framework Objects on the Activation Framework intelligent scheduling mechanism developed by Worcester Polytechnic Institute. The implementations, results of performance analyses showing speedup due to parallelism and initial efficiency improvements are detailed and further areas for performance improvements are suggested.

Novel intelligent real-time position tracking system using FPGA and fuzzy logic.

PubMed

Soares dos Santos, Marco P; Ferreira, J A F

2014-03-01

The main aim of this paper is to test if FPGAs are able to achieve better position tracking performance than software-based soft real-time platforms. For comparison purposes, the same controller design was implemented in these architectures. A Multi-state Fuzzy Logic controller (FLC) was implemented both in a Xilinx(®) Virtex-II FPGA (XC2v1000) and in a soft real-time platform NI CompactRIO(®)-9002. The same sampling time was used. The comparative tests were conducted using a servo-pneumatic actuation system. Steady-state errors lower than 4 μm were reached for an arbitrary vertical positioning of a 6.2 kg mass when the controller was embedded into the FPGA platform. Performance gains up to 16 times in the steady-state error, up to 27 times in the overshoot and up to 19.5 times in the settling time were achieved by using the FPGA-based controller over the software-based FLC controller. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

The efficacy of real-time colour Doppler flow imaging on endoscopic ultrasonography for differential diagnosis between neoplastic and non-neoplastic gallbladder polyps.

PubMed

Kim, Su Young; Cho, Jae Hee; Kim, Eui Joo; Chung, Dong Hae; Kim, Kun Kuk; Park, Yeon Ho; Kim, Yeon Suk

2018-05-01

We evaluated the usefulness of real-time colour Doppler flow (CDF) endoscopic ultrasonography (EUS) for differentiating neoplastic gallbladder (GB) polyps from non-neoplastic polyps. Between August 2014 and December 2016, a total of 233 patients with GB polyps who underwent real-time CDF-EUS were consecutively enrolled in this prospective study. CDF imaging was subjectively categorized for each patient as: strong CDF pattern, weak CDF pattern and no CDF pattern. Of the 233 patients, 115 underwent surgical resection. Of these, there were 90 cases of non-neoplastic GB polyps and 23 cases of neoplastic GB polyps. In a multivariate analysis, a strong CDF pattern was the most significant predictive factor for neoplastic polyps; sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 52.2 %, 79.4 %, 38.7 %, 86.9 % and 73.9 %, respectively. Solitary polyp and polyp size were associated with an increased risk of neoplasm. The presence of a strong CDF pattern as well as solitary and larger polyps on EUS may be predictive of neoplastic GB polyps. As real-time CDF-EUS poses no danger to the patient and requires no additional equipment, it is likely to become a supplemental tool for the differential diagnosis of GB polyps. • Differential diagnosis between neoplastic polyps and non-neoplastic polyps of GB is limited. • The use of real-time CDF-EUS was convenient, with high agreement between operators. • The real-time CDF-EUS is helpful in differential diagnosis of GB polyps.

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB)

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Rajkumar, T.

2003-01-01

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

Intelligent launch and range operations virtual testbed (ILRO-VTB)

NASA Astrophysics Data System (ADS)

Bardina, Jorge; Rajkumar, Thirumalainambi

2003-09-01

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

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

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

DOE PAGES

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

2016-08-10

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

A generic flexible and robust approach for intelligent real-time video-surveillance systems

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Delaigle, Jean-Francois; Bastide, Arnaud; Macq, Benoit

2004-05-01

In this article we present a generic, flexible and robust approach for an intelligent real-time video-surveillance system. A previous version of the system was presented in [1]. The goal of these advanced tools is to provide help to operators by detecting events of interest in visual scenes and highlighting alarms and compute statistics. The proposed system is a multi-camera platform able to handle different standards of video inputs (composite, IP, IEEE1394 ) and which can basically compress (MPEG4), store and display them. This platform also integrates advanced video analysis tools, such as motion detection, segmentation, tracking and interpretation. The design of the architecture is optimised to playback, display, and process video flows in an efficient way for video-surveillance application. The implementation is distributed on a scalable computer cluster based on Linux and IP network. It relies on POSIX threads for multitasking scheduling. Data flows are transmitted between the different modules using multicast technology and under control of a TCP-based command network (e.g. for bandwidth occupation control). We report here some results and we show the potential use of such a flexible system in third generation video surveillance system. We illustrate the interest of the system in a real case study, which is the indoor surveillance.

An intelligent traceability system: Efficient tool for a supply chain sustainability

NASA Astrophysics Data System (ADS)

Bougdira, Abdesselam; Ahaitouf, Abdelaziz; Akharraz, Ismail

2016-07-01

The supply chain sustainability becomes a necessity for a smooth, a rapid and a fluid economic transaction. To reach a sustainable supply chain, we propose to focus attention on products and their lifecycle. So, we consider the traceability as a major success key to ensure the supply chain sustainability. For that, we consider a supply chain design that use an intelligent products traced by an intelligent traceability system. This system identifies, restores history and properties of a product, besides it tracks, in real-time a product. This solution can, also, bring, in the product environment, appropriate adjustments to prevent any risk of threatening qualities for the product. So, it helps supply chain contributors making the sustainable adjustments and the instant benchmark of the supply chain sustainability.

Decision Facilitator for Launch Operations using Intelligent Agents

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar; Bardina, Jorge

2005-01-01

Launch operations require millions of micro-decisions which contribute to the macro decision of 'Go/No-Go' for a launch. Knowledge workers"(such as managers and technical professionals) need information in a timely precise manner as it can greatly affect mission success. The intelligent agent (web search agent) uses the words of a hypertext markup language document which is connected through the internet. The intelligent agent's actions are to determine if its goal of seeking a website containing a specified target (e.g., keyword or phrase), has been met. There are few parameters that should be defined for the keyword search like "Go" and "No-Go". Instead of visiting launch and range decision making servers individually, the decision facilitator constantly connects to all servers, accumulating decisions so the final decision can be decided in a timely manner. The facilitator agent uses the singleton design pattern, which ensures that only a single instance of the facilitator agent exists at one time. Negotiations could proceed between many agents resulting in a final decision. This paper describes details of intelligent agents and their interaction to derive an unified decision support system.

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

PubMed

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

2018-06-04

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

Real-time diagnostics of the reusable rocket engine using on-line system identification

NASA Technical Reports Server (NTRS)

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

1990-01-01

A model-based failure diagnosis system has been proposed for real-time diagnosis of SSME failures. Actuation, sensor, and system degradation failure modes are all considered by the proposed system. In the case of SSME actuation failures, it was shown that real-time identification can effectively be used for failure diagnosis purposes. It is a direct approach since it reduces the detection, isolation, and the estimation of the extent of the failures to the comparison of parameter values before and after the failure. As with any model-based failure detection system, the proposed approach requires a fault model that embodies the essential characteristics of the failure process. The proposed diagnosis approach has the added advantage that it can be used as part of an intelligent control system for failure accommodation purposes.

Prototype space station automation system delivered and demonstrated at NASA

NASA Technical Reports Server (NTRS)

Block, Roger F.

1987-01-01

The Automated Subsystem Control for Life Support System (ASCLSS) program has successfully developed and demonstrated a generic approach to the automation and control of Space Station subsystems. The hierarchical and distributed real time controls system places the required controls authority at every level of the automation system architecture. As a demonstration of the automation technique, the ASCLSS system automated the Air Revitalization Group (ARG) of the Space Station regenerative Environmental Control and Life Support System (ECLSS) using real-time, high fidelity simulators of the ARG processess. This automation system represents an early flight prototype and an important test bed for evaluating Space Station controls technology including future application of ADA software in real-time control and the development and demonstration of embedded artificial intelligence and expert systems (AI/ES) in distributed automation and controls systems.

Artificial intelligence and its impact on combat aircraft

NASA Technical Reports Server (NTRS)

Ott, Lawrence M.; Abbot, Kathy; Kleider, Alfred; Moon, D.; Retelle, John

1987-01-01

As the threat becomes more sophisticated and weapon systems more complex to meet the threat, the need for machines to assist the pilot in the assessment of information becomes paramount. This is particularly true in real-time, high stress situations. The advent of artificial intelligence (AI) technology offers the opportunity to make quantum advances in the application of machine technology. However, if AI systems are to find their way into combat aircraft, they must meet certain criteria. The systems must be responsive, reliable, easy to use, flexible, and understandable. These criteria are compared with the current status used in a combat airborne application. Current AI systems deal with nonreal time applications and require significant user interaction. On the other hand, aircraft applications require real time, minimum human interaction systems. In order to fill the gap between where technology is now and where it must be for aircraft applications, considerable government research is ongoing in NASA, DARPA, and three services. The ongoing research is briefly summarized. Finally, recognizing that AI technology is in its embryonic stage, and the aircraft needs are very demanding, a number of issues arise. These issues are delineated and findings are provided where appropriate.

AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

PubMed

Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

2018-05-01

The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging neuromorphic architectures.

A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.

PubMed

Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

2017-03-06

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

Values and limitations of applied science in the real world [book review

Treesearch

Christel C. Kern

2012-01-01

How can the applied scientist provide timely, useful results to the land manager whose job is to save and sustain our complex ecosystems under the scrutiny of the profession, public, and policymakers? Author Robert J. Cabin tells his story in Intelligent Tinkering: Bridging the Gap between Science and Practice.

Improving Forest Wildfire Suppression Using Penetrating Reconnaissance And Real Time Data Transfer

NASA Astrophysics Data System (ADS)

Greer, Jerry D.

1990-02-01

The suppression of a wildfire is analogous to a combat action. Fires, like battles, spread fast and suppression forces must be highly mobile. The enemy, (in this case) the wildfire, is lethal in that it kills or destroys forces, equipment, and natural resources left in its path. The suppression action must be carried on day and night until the "enemy" is contained. Both air operations and ground forces are used. Just as in a combat situation, wildfire suppression forces need penetrating reconnaissance with real time data transfer. This paper presents a review of the current system of intelligence gathering on a wildfire where aerial observers, infrared detectors, and ground intelligence officers gather data and either radio or carry the data to the command center. It then attempts to show how some current military reconnaissance systems might be applied to wildfire control processes. The payoffs would include improved safety for both air and ground forces and faster containment of the wildfire which would reduce forest resources lost and decrease the total monetary cost of the containment action.

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.

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.

Season of birth and childhood intelligence: findings from the Aberdeen Children of the 1950s cohort study.

PubMed

Lawlor, Debbie A; Clark, Heather; Ronalds, Georgina; Leon, David A

2006-09-01

In this study, 2 main hypotheses have been put forward to explain the variation in childhood intelligence or school performance by season of birth. In the first hypothesis, it is suggested that it is due to school policy concerning school entry, whereas the second suggests that a seasonally patterned exposure such as temperature, maternal nutrition, or infection during critical periods of brain development have a lasting effect on intelligence. To determine whether childhood performance on tests of different domains of intelligence is patterned by season of birth and to examine possible mechanisms for any associations. 12,150 individuals born in Aberdeen, Scotland between 1950 and 1956. Birth cohort study in which the variation in different domains of childhood intelligence measured at ages 7, 9, and 11 by season of birth were examined. Reading ability at age 9 and arithmetic ability at age 11 varied by season of birth, with lowest scores among those born in autumn or early winter (September-December) and highest scores among those born in later winter or spring (February-April); p=.002 for joint sine-cosine functions for reading ability at age 9 and p=.05 for sine-cosine function for arithmetic ability at age 11. The child's perception and understanding of pictorial differences at age 7, verbal reasoning at 11, and English language ability at 11 did not vary by season of birth. Age at starting primary school and age relative to class peers were both associated with the different measurements of childhood intelligence and both attenuated the association between month of birth and reading ability at age 9 and arithmetic ability at age 11 towards the null. Both adjusted and unadjusted differences in reading ability at age 9 and arithmetic ability at age 11 between those born from September to December compared with other times of the year were less than 0.1 of a standard deviation of the test scores. Ambient temperature around the time of conception, during gestation, and around the time of birth did not affect intelligence. Any variation in mean childhood intelligence by season of birth is weak and largely explained by age at school entry and age relative to class peers.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-05-30

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-01-01

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control. PMID:28556817

Quality versus intelligibility: studying human preferences for American Sign Language video

NASA Astrophysics Data System (ADS)

Ciaramello, Frank M.; Hemami, Sheila S.

2011-03-01

Real-time videoconferencing using cellular devices provides natural communication to the Deaf community. For this application, compressed American Sign Language (ASL) video must be evaluated in terms of the intelligibility of the conversation and not in terms of the overall aesthetic quality of the video. This work presents a paired comparison experiment to determine the subjective preferences of ASL users in terms of the trade-off between intelligibility and quality when varying the proportion of the bitrate allocated explicitly to the regions of the video containing the signer. A rate-distortion optimization technique, which jointly optimizes a quality criteria and an intelligibility criteria according to a user-specified parameter, generates test video pairs for the subjective experiment. Experimental results suggest that at sufficiently high bitrates, all users prefer videos in which the non-signer regions in the video are encoded with some nominal rate. As the total encoding bitrate decreases, users generally prefer video in which a greater proportion of the rate is allocated to the signer. The specific operating points preferred in the quality-intelligibility trade-off vary with the demographics of the users.

Balancing a simulated inverted pendulum through motor imagery: an EEG-based real-time control paradigm.

PubMed

Yue, Jingwei; Zhou, Zongtan; Jiang, Jun; Liu, Yadong; Hu, Dewen

2012-08-30

Most brain-computer interfaces (BCIs) are non-time-restraint systems. However, the method used to design a real-time BCI paradigm for controlling unstable devices is still a challenging problem. This paper presents a real-time feedback BCI paradigm for controlling an inverted pendulum on a cart (IPC). In this paradigm, sensorimotor rhythms (SMRs) were recorded using 15 active electrodes placed on the surface of the subject's scalp. Subsequently, common spatial pattern (CSP) was used as the basic filter to extract spatial patterns. Finally, linear discriminant analysis (LDA) was used to translate the patterns into control commands that could stabilize the simulated inverted pendulum. Offline trainings were employed to teach the subjects to execute corresponding mental tasks, such as left/right hand motor imagery. Five subjects could successfully balance the online inverted pendulum for more than 35s. The results demonstrated that BCIs are able to control nonlinear unstable devices. Furthermore, the demonstration and extension of real-time continuous control might be useful for the real-life application and generalization of BCI. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.

1992-01-01

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Research on robot mobile obstacle avoidance control based on visual information

NASA Astrophysics Data System (ADS)

Jin, Jiang

2018-03-01

Robots to detect obstacles and control robots to avoid obstacles has been a key research topic of robot control. In this paper, a scheme of visual information acquisition is proposed. By judging visual information, the visual information is transformed into the information source of path processing. In accordance with the established route, in the process of encountering obstacles, the algorithm real-time adjustment trajectory to meet the purpose of intelligent control of mobile robots. Simulation results show that, through the integration of visual sensing information, the obstacle information is fully obtained, while the real-time and accuracy of the robot movement control is guaranteed.

LIA: An Intelligent Advisor for E-Learning

ERIC Educational Resources Information Center

Capuano, Nicola; Gaeta, Matteo; Marengo, Agostino; Miranda, Sergio; Orciuoli, Francesco; Ritrovato, Pierluigi

2009-01-01

Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA)…

Development of a food spoilage indicator for monitoring freshness of skinless chicken breast.

PubMed

Rukchon, Chompoonoot; Nopwinyuwong, Atchareeya; Trevanich, Sudsai; Jinkarn, Tunyarut; Suppakul, Panuwat

2014-12-01

A colorimetric mixed-pH dye-based indicator with potential for the development of intelligent packaging, as a "chemical barcode" for real-time monitoring of skinless chicken breast spoilage, is described. Also investigated was the relationship between the numbers of microorganisms and the amount of volatile compounds. This on-package indicator contains two groups of pH-sensitive dyes, one of which is a mixture of bromothymol blue and methyl red, while the other is a mixture of bromothymol blue, bromocresol green and phenol red. Carbon dioxide (CO2) was used as a spoilage metabolite because the degree of spoilage was related to the amount of increased CO2, and which was more than the level of total volatile basic nitrogen (TVB-N) during the storage period. Characteristics of the two groups of indicator solutions were studied, as well as their response to CO2. A kinetic approach was used to correlate the response of the indicator label to the changes in skinless chicken breast spoilage. Color changes, in terms of total color difference of a mixed-pH dye-based indicator, correlated well with CO2 levels of skinless chicken breast. Trials on skinless chicken breast samples have verified that the indicator response correlates with microbial growth patterns, thus enabling real-time monitoring of spoilage either at various constant temperatures or with temperature fluctuation. Copyright © 2014 Elsevier B.V. All rights reserved.

A Real-Time Interactive System for Facial Makeup of Peking Opera

NASA Astrophysics Data System (ADS)

Cai, Feilong; Yu, Jinhui

In this paper we present a real-time interactive system for making facial makeup of Peking Opera. First, we analyze the process of drawing facial makeup and characteristics of the patterns used in it, and then construct a SVG pattern bank based on local features like eye, nose, mouth, etc. Next, we pick up some SVG patterns from the pattern bank and composed them to make a new facial makeup. We offer a vector-based free form deformation (FFD) tool to edit patterns and, based on editing, our system creates automatically texture maps for a template head model. Finally, the facial makeup is rendered on the 3D head model in real time. Our system offers flexibility in designing and synthesizing various 3D facial makeup. Potential applications of the system include decoration design, digital museum exhibition and education of Peking Opera.

Working memory training may increase working memory capacity but not fluid intelligence.

PubMed

Harrison, Tyler L; Shipstead, Zach; Hicks, Kenny L; Hambrick, David Z; Redick, Thomas S; Engle, Randall W

2013-12-01

Working memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working memory capacity correlate positively with many measures of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working memory capacity and thereby performance on the real-world tasks that rely on working memory capacity. In the study reported here, we demonstrated that training on complex working memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.

Multiple pedestrian detection using IR LED stereo camera

NASA Astrophysics Data System (ADS)

Ling, Bo; Zeifman, Michael I.; Gibson, David R. P.

2007-09-01

As part of the U.S. Department of Transportations Intelligent Vehicle Initiative (IVI) program, the Federal Highway Administration (FHWA) is conducting R&D in vehicle safety and driver information systems. There is an increasing number of applications where pedestrian monitoring is of high importance. Visionbased pedestrian detection in outdoor scenes is still an open challenge. People dress in very different colors that sometimes blend with the background, wear hats or carry bags, and stand, walk and change directions unpredictably. The background is various, containing buildings, moving or parked cars, bicycles, street signs, signals, etc. Furthermore, existing pedestrian detection systems perform only during daytime, making it impossible to detect pedestrians at night. Under FHWA funding, we are developing a multi-pedestrian detection system using IR LED stereo camera. This system, without using any templates, detects the pedestrians through statistical pattern recognition utilizing 3D features extracted from the disparity map. A new IR LED stereo camera is being developed, which can help detect pedestrians during daytime and night time. Using the image differencing and denoising, we have also developed new methods to estimate the disparity map of pedestrians in near real time. Our system will have a hardware interface with the traffic controller through wireless communication. Once pedestrians are detected, traffic signals at the street intersections will change phases to alert the drivers of approaching vehicles. The initial test results using images collected at a street intersection show that our system can detect pedestrians in near real time.

Information gathering, management and transfering for geospacial intelligence

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-07-01

Information is a key subject in modern organization operations. The success of joint and combined operations with organizations partners depends on the accurate information and knowledge flow concerning the operations theatre: provision of resources, environment evolution, markets location, where and when an event occurred. As in the past and nowadays we cannot conceive modern operations without maps and geo-spatial information (GI). Information and knowledge management is fundamental to the success of organizational decisions in an uncertainty environment. The georeferenced information management is a process of knowledge management, it begins in the raw data and ends on generating knowledge. GI and intelligence systems allow us to integrate all other forms of intelligence and can be a main platform to process and display geo-spatial-time referenced events. Combining explicit knowledge with peoples know-how to generate a continuous learning cycle that supports real time decisions mitigates the influences of fog of everyday competition and provides the knowledge supremacy. Extending the preliminary analysis done in [1], this work applies the exploratory factor analysis to a questionnaire about the GI and intelligence management in an organization company allowing to identify future lines of action to improve information process sharing and exploration of all the potential of this important resource.

Real-Time Assessment of Fatigue in Patients With Multiple Sclerosis: How Does It Relate to Commonly Used Self-Report Fatigue Questionnaires?

PubMed

Heine, Martin; van den Akker, Lizanne Eva; Blikman, Lyan; Hoekstra, Trynke; van Munster, Erik; Verschuren, Olaf; Visser-Meily, Anne; Kwakkel, Gert

2016-11-01

(1) To assess real-time patterns of fatigue; (2) to assess the association between a real-time fatigue score and 3 commonly used questionnaires (Checklist Individual Strength [CIS] fatigue subscale, Modified Fatigue Impact Scale (MFIS), and Fatigue Severity Scale [FSS]); and (3) to establish factors that confound the association between the real-time fatigue score and the conventional fatigue questionnaires in patients with multiple sclerosis (MS). Cross-sectional study. MS-specialized outpatient facility. Ambulant patients with MS (N=165) experiencing severe self-reported fatigue. Not applicable. A real-time fatigue score was assessed by sending participants 4 text messages on a particular day (How fatigued do you feel at this moment?; score range, 0-10). Latent class growth mixed modeling was used to determine diurnal patterns of fatigue. Regression analyses were used to assess the association between the mean real-time fatigue score and the CIS fatigue subscale, MFIS, and FSS. Significant associations were tested for candidate confounders (eg, disease severity, work status, sleepiness). Four significantly different fatigue profiles were identified by the real-time fatigue score, namely a stable high (n=79), increasing (n=57), stable low (n=16), and decreasing (n=13). The conventional questionnaires correlated poorly (r<.300) with the real-time fatigue score. The Epworth Sleepiness Scale significantly reduced the regression coefficient between the real-time fatigue score and conventional questionnaires, ranging from 15.4% to 35%. Perceived fatigue showed 4 different diurnal patterns in patients with MS. Severity of sleepiness is an important confounder to take into account in the assessment of fatigue. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Training emotional intelligence improves both emotional intelligence and depressive symptoms in inpatients with borderline personality disorder and depression.

PubMed

Jahangard, Leila; Haghighi, Mohammad; Bajoghli, Hafez; Ahmadpanah, Mohammad; Ghaleiha, Ali; Zarrabian, Mohammad Kazem; Brand, Serge

2012-09-01

Borderline personality disorder (BPD) is defined as a pervasive pattern of instability in emotion, mood and interpersonal relationships, with a comorbidity between PBD and depressive disorders (DD). A key competence for successful management of interpersonal relationships is emotional intelligence (EI). Given the low EI of patients suffering from BPD, the present study aimed at investigating the effect on both emotional intelligence and depression of training emotional intelligence in patients with BPD and DD. A total of 30 inpatients with BPD and DD (53% females; mean age 24.20 years) took part in the study. Patients were randomly assigned either to the treatment or to the control group. Pre- and post-testing 4 weeks later involved experts' rating of depressive disorder and self-reported EI. The treatment group received 12 sessions of training in components of emotional intelligence. Relative to the control group, EI increased significantly in the treatment group over time. Depressive symptoms decreased significantly over time in both groups, though improvement was greater in the treatment than the control group. For inpatients suffering from BPD and DD, regular skill training in EI can be successfully implemented and leads to improvements both in EI and depression. Results suggest an additive effect of EI training on both EI and depressive symptoms.

Intelligence and Schooling. Fueling the Education Explosion: Proceedings of Conference 2 (Cleveland, Ohio, November 17-18, 1983).

ERIC Educational Resources Information Center

Gardner, Mary, Ed.; Reed-Mundell, Charlene, Ed.

These proceedings contain presentations from a conference whose major topics were real-world intelligence, artificial intelligence, and linkage between the education and corporate sectors. "People, Perspectives...Potential and Possibilities" (Elyse S. Fleming), which was the conference's closing speech, briefly summarizes the information…

Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

PubMed

Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

2010-12-01

The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns. Copyright © 2010 Elsevier Ltd. All rights reserved.

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

NASA Technical Reports Server (NTRS)

Chen, Alexander Y.

1990-01-01

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Greenhouse intelligent control system based on microcontroller

NASA Astrophysics Data System (ADS)

Zhang, Congwei

2018-04-01

As one of the hallmarks of agricultural modernization, intelligent greenhouse has the advantages of high yield, excellent quality, no pollution and continuous planting. Taking AT89S52 microcontroller as the main controller, the greenhouse intelligent control system uses soil moisture sensor, temperature and humidity sensors, light intensity sensor and CO2 concentration sensor to collect measurements and display them on the 12864 LCD screen real-time. Meantime, climate parameter values can be manually set online. The collected measured values are compared with the set standard values, and then the lighting, ventilation fans, warming lamps, water pumps and other facilities automatically start to adjust the climate such as light intensity, CO2 concentration, temperature, air humidity and soil moisture of the greenhouse parameter. So, the state of the environment in the greenhouse Stabilizes and the crop grows in a suitable environment.

Boosting medical diagnostics by pooling independent judgments

PubMed Central

Kurvers, Ralf H. J. M.; Herzog, Stefan M.; Hertwig, Ralph; Krause, Jens; Carney, Patricia A.; Bogart, Andy; Argenziano, Giuseppe; Zalaudek, Iris; Wolf, Max

2016-01-01

Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors’ diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches. PMID:27432950

The anticipatory profile. An attempt to describe anticipation as process

NASA Astrophysics Data System (ADS)

Nadin, Mihai

2012-01-01

Inductive class representation and the more comprehensive evolving transformation system (ETS) are congenial to the subject matter of anticipation. In substantiating this assertion, we examine the epistemological premises of a new form of representation, of interest to pattern recognition and Artificial Intelligence (AI), but even more to the study of living systems. Some concepts, such as classes, time and time scale, and generative processes are examined in detail with respect to their pertinence to anticipation. Finally, pattern generation and ETS programming are suggested.

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

Considerations in development of expert systems for real-time space applications

NASA Technical Reports Server (NTRS)

Murugesan, S.

1988-01-01

Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications.

A Real Time Controller For Applications In Smart Structures

NASA Astrophysics Data System (ADS)

Ahrens, Christian P.; Claus, Richard O.

1990-02-01

Research in smart structures, especially the area of vibration suppression, has warranted the investigation of advanced computing environments. Real time PC computing power has limited development of high order control algorithms. This paper presents a simple Real Time Embedded Control System (RTECS) in an application of Intelligent Structure Monitoring by way of modal domain sensing for vibration control. It is compared to a PC AT based system for overall functionality and speed. The system employs a novel Reduced Instruction Set Computer (RISC) microcontroller capable of 15 million instructions per second (MIPS) continuous performance and burst rates of 40 MIPS. Advanced Complimentary Metal Oxide Semiconductor (CMOS) circuits are integrated on a single 100 mm by 160 mm printed circuit board requiring only 1 Watt of power. An operating system written in Forth provides high speed operation and short development cycles. The system allows for implementation of Input/Output (I/O) intensive algorithms and provides capability for advanced system development.

Achieving Real-Time Tracking Mobile Wireless Sensors Using SE-KFA

NASA Astrophysics Data System (ADS)

Kadhim Hoomod, Haider, Dr.; Al-Chalabi, Sadeem Marouf M.

2018-05-01

Nowadays, Real-Time Achievement is very important in different fields, like: Auto transport control, some medical applications, celestial body tracking, controlling agent movements, detections and monitoring, etc. This can be tested by different kinds of detection devices, which named "sensors" as such as: infrared sensors, ultrasonic sensor, radars in general, laser light sensor, and so like. Ultrasonic Sensor is the most fundamental one and it has great impact and challenges comparing with others especially when navigating (as an agent). In this paper, concerning to the ultrasonic sensor, sensor(s) detecting and delimitation by themselves then navigate inside a limited area to estimating Real-Time using Speed Equation with Kalman Filter Algorithm as an intelligent estimation algorithm. Then trying to calculate the error comparing to the factual rate of tracking. This paper used Ultrasonic Sensor HC-SR04 with Arduino-UNO as Microcontroller.

[Research on the High Efficiency Data Communication Repeater Based on STM32F103].

PubMed

Zhang, Yahui; Li, Zheng; Chen, Guangfei

2015-11-01

To improve the radio frequency (RF) transmission distance of the wireless terminal of the medical internet of things (LOT), to realize the real-time and efficient data communication, the intelligent relay system based on STM32F103 single chip microcomputer (SCM) is proposed. The system used nRF905 chip to achieve the collection, of medical and health information of patients in the 433 MHz band, used SCM to control the serial port to Wi-Fi module to transmit information from 433 MHz to 2.4 GHz wireless Wi-Fi band, and used table look-up algorithm of ready list to improve the efficiency of data communications. The design can realize real-time and efficient data communication. The relay which is easy to use with high practical value can extend the distance and mode of data transmission and achieve real-time transmission of data.

Synthesis of compact patterns for NMR relaxation decay in intelligent "electronic tongue" for analyzing heavy oil composition

NASA Astrophysics Data System (ADS)

Lapshenkov, E. M.; Volkov, V. Y.; Kulagin, V. P.

2018-05-01

The article is devoted to the problem of pattern creation of the NMR sensor signal for subsequent recognition by the artificial neural network in the intelligent device "the electronic tongue". The specific problem of removing redundant data from the spin-spin relaxation signal pattern that is used as a source of information in analyzing the composition of oil and petroleum products is considered. The method is proposed that makes it possible to remove redundant data of the relaxation decay pattern but without introducing additional distortion. This method is based on combining some relaxation decay curve intervals that increment below the noise level such that the increment of the combined intervals is above the noise level. In this case, the relaxation decay curve samples that are located inside the combined intervals are removed from the pattern. This method was tested on the heavy-oil NMR signal patterns that were created by using the Carr-Purcell-Meibum-Gill (CPMG) sequence for recording the relaxation process. Parameters of CPMG sequence are: 100 μs - time interval between 180° pulses, 0.4s - duration of measurement. As a result, it was revealed that the proposed method allowed one to reduce the number of samples 15 times (from 4000 to 270), and the maximum detected root mean square error (RMS error) equals 0.00239 (equivalent to signal-to-noise ratio 418).

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Fuzzy control of burnout of multilayer ceramic actuators

NASA Astrophysics Data System (ADS)

Ling, Alice V.; Voss, David; Christodoulou, Leo

1996-08-01

To improve the yield and repeatability of the burnout process of multilayer ceramic actuators (MCAs), an intelligent processing of materials (IPM-based) control system has been developed for the manufacture of MCAs. IPM involves the active (ultimately adaptive) control of a material process using empirical or analytical models and in situ sensing of critical process states (part features and process parameters) to modify the processing conditions in real time to achieve predefined product goals. Thus, the three enabling technologies for the IPM burnout control system are process modeling, in situ sensing and intelligent control. This paper presents the design of an IPM-based control strategy for the burnout process of MCAs.

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

Narrative Balance Management in an Intelligent Biosafety Training Application for Improving User Performance

ERIC Educational Resources Information Center

Alvarez, Nahum; Sanchez-Ruiz, Antonio; Cavazza, Marc; Shigematsu, Mika; Prendinger, Helmut

2015-01-01

The use of three-dimensional virtual environments in training applications supports the simulation of complex scenarios and realistic object behaviour. While these environments have the potential to provide an advanced training experience to students, it is difficult to design and manage a training session in real time due to the number of…

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.

Intelligent surgical laser system configuration and software implementation

NASA Astrophysics Data System (ADS)

Hsueh, Chi-Fu T.; Bille, Josef F.

1992-06-01

An intelligent surgical laser system, which can help the ophthalmologist to achieve higher precision and control during their procedures, has been developed by ISL as model CLS 4001. In addition to the laser and laser delivery system, the system is also equipped with a vision system (IPU), robotics motion control (MCU), and a tracking closed loop system (ETS) that tracks the eye in three dimensions (X, Y and Z). The initial patient setup is computer controlled with guidance from the vision system. The tracking system is automatically engaged when the target is in position. A multi-level tracking system is developed by integrating our vision and tracking systems which have been able to maintain our laser beam precisely on target. The capabilities of the automatic eye setup and the tracking in three dimensions provides for improved accuracy and measurement repeatability. The system is operated through the Surgical Control Unit (SCU). The SCU communicates with the IPU and the MCU through both ethernet and RS232. Various scanning pattern (i.e., line, curve, circle, spiral, etc.) can be selected with given parameters. When a warning is activated, a voice message is played that will normally require a panel touch acknowledgement. The reliability of the system is ensured in three levels: (1) hardware, (2) software real time monitoring, and (3) user. The system is currently under clinical validation.

Residential Consumer-Centric Demand-Side Management Based on Energy Disaggregation-Piloting Constrained Swarm Intelligence: Towards Edge Computing

PubMed Central

Hu, Yu-Chen

2018-01-01

The emergence of smart Internet of Things (IoT) devices has highly favored the realization of smart homes in a down-stream sector of a smart grid. The underlying objective of Demand Response (DR) schemes is to actively engage customers to modify their energy consumption on domestic appliances in response to pricing signals. Domestic appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption intelligently. Besides, to residential customers for DR implementation, maintaining a balance between energy consumption cost and users’ comfort satisfaction is a challenge. Hence, in this paper, a constrained Particle Swarm Optimization (PSO)-based residential consumer-centric load-scheduling method is proposed. The method can be further featured with edge computing. In contrast with cloud computing, edge computing—a method of optimizing cloud computing technologies by driving computing capabilities at the IoT edge of the Internet as one of the emerging trends in engineering technology—addresses bandwidth-intensive contents and latency-sensitive applications required among sensors and central data centers through data analytics at or near the source of data. A non-intrusive load-monitoring technique proposed previously is utilized to automatic determination of physical characteristics of power-intensive home appliances from users’ life patterns. The swarm intelligence, constrained PSO, is used to minimize the energy consumption cost while considering users’ comfort satisfaction for DR implementation. The residential consumer-centric load-scheduling method proposed in this paper is evaluated under real-time pricing with inclining block rates and is demonstrated in a case study. The experimentation reported in this paper shows the proposed residential consumer-centric load-scheduling method can re-shape loads by home appliances in response to DR signals. Moreover, a phenomenal reduction in peak power consumption is achieved by 13.97%. PMID:29702607

Physical activity patterns in morbidly obese and normal-weight women.

PubMed

Kwon, Soyang; Mohammad, Jamal; Samuel, Isaac

2011-01-01

To compare physical activity patterns between morbidly obese and normal-weight women. Daily physical activity of 18 morbidly obese and 7 normal-weight women aged 30-58 years was measured for 2 days using the Intelligent Device for Energy Expenditure and Activity (IDEEA) device. The obese group spent about 2 hr/day less standing and 30 min/day less walking than did the normal-weight group. Time spent standing (standing time) was positively associated with time spent walking (walking time). Age- and walking time-adjusted standing time did not differ according to weight status. Promoting standing may be a strategy to increase walking.

A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

NASA Astrophysics Data System (ADS)

Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.

2011-12-01

This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

Overview of Intelligent Power Controller Development for the Deep Space Gateway

NASA Technical Reports Server (NTRS)

Csank, Jeffrey

2017-01-01

Intelligent, or autonomous, control of a spacecraft is an enabling technology that must be developed for deep space human exploration. NASAs current long term human space platform, the International Space Station, which is in Low Earth Orbit, is in almost continuous communication with ground based mission control. This allows near real-time control of all the vehicle core systems, including power, to be controlled by the ground. As focus shifts from Low Earth Orbit, communication time-lag and communication bandwidth limitations beyond geosynchronous orbit does not permit this type of operation. This presentation contains ongoing work at NASA to develop an architecture for autonomous power control and the vehicle manager which monitors, coordinates, and delegates to all the on-board subsystems to enable autonomous control of the complete spacecraft.

Exploratory analysis of real personal emergency response call conversations: considerations for personal emergency response spoken dialogue systems.

PubMed

Young, Victoria; Rochon, Elizabeth; Mihailidis, Alex

2016-11-14

The purpose of this study was to derive data from real, recorded, personal emergency response call conversations to help improve the artificial intelligence and decision making capability of a spoken dialogue system in a smart personal emergency response system. The main study objectives were to: develop a model of personal emergency response; determine categories for the model's features; identify and calculate measures from call conversations (verbal ability, conversational structure, timing); and examine conversational patterns and relationships between measures and model features applicable for improving the system's ability to automatically identify call model categories and predict a target response. This study was exploratory and used mixed methods. Personal emergency response calls were pre-classified according to call model categories identified qualitatively from response call transcripts. The relationships between six verbal ability measures, three conversational structure measures, two timing measures and three independent factors: caller type, risk level, and speaker type, were examined statistically. Emergency medical response services were the preferred response for the majority of medium and high risk calls for both caller types. Older adult callers mainly requested non-emergency medical service responders during medium risk situations. By measuring the number of spoken words-per-minute and turn-length-in-words for the first spoken utterance of a call, older adult and care provider callers could be identified with moderate accuracy. Average call taker response time was calculated using the number-of-speaker-turns and time-in-seconds measures. Care providers and older adults used different conversational strategies when responding to call takers. The words 'ambulance' and 'paramedic' may hold different latent connotations for different callers. The data derived from the real personal emergency response recordings may help a spoken dialogue system classify incoming calls by caller type with moderate probability shortly after the initial caller utterance. Knowing the caller type, the target response for the call may be predicted with some degree of probability and the output dialogue could be tailored to this caller type. The average call taker response time measured from real calls may be used to limit the conversation length in a spoken dialogue system before defaulting to a live call taker.

Characterizing the uncertainty of classification methods and its impact on the performance of crowdsourcing

NASA Astrophysics Data System (ADS)

Ribera, Javier; Tahboub, Khalid; Delp, Edward J.

2015-03-01

Video surveillance systems are widely deployed for public safety. Real-time monitoring and alerting are some of the key requirements for building an intelligent video surveillance system. Real-life settings introduce many challenges that can impact the performance of real-time video analytics. Video analytics are desired to be resilient to adverse and changing scenarios. In this paper we present various approaches to characterize the uncertainty of a classifier and incorporate crowdsourcing at the times when the method is uncertain about making a particular decision. Incorporating crowdsourcing when a real-time video analytic method is uncertain about making a particular decision is known as online active learning from crowds. We evaluate our proposed approach by testing a method we developed previously for crowd flow estimation. We present three different approaches to characterize the uncertainty of the classifier in the automatic crowd flow estimation method and test them by introducing video quality degradations. Criteria to aggregate crowdsourcing results are also proposed and evaluated. An experimental evaluation is conducted using a publicly available dataset.

Knowledge Reasoning with Semantic Data for Real-Time Data Processing in Smart Factory

PubMed Central

Wang, Shiyong; Li, Di; Liu, Chengliang

2018-01-01

The application of high-bandwidth networks and cloud computing in manufacturing systems will be followed by mass data. Industrial data analysis plays important roles in condition monitoring, performance optimization, flexibility, and transparency of the manufacturing system. However, the currently existing architectures are mainly for offline data analysis, not suitable for real-time data processing. In this paper, we first define the smart factory as a cloud-assisted and self-organized manufacturing system in which physical entities such as machines, conveyors, and products organize production through intelligent negotiation and the cloud supervises this self-organized process for fault detection and troubleshooting based on data analysis. Then, we propose a scheme to integrate knowledge reasoning and semantic data where the reasoning engine processes the ontology model with real time semantic data coming from the production process. Based on these ideas, we build a benchmarking system for smart candy packing application that supports direct consumer customization and flexible hybrid production, and the data are collected and processed in real time for fault diagnosis and statistical analysis. PMID:29415444

Comparison of turbulence mitigation algorithms

NASA Astrophysics Data System (ADS)

Kozacik, Stephen T.; Paolini, Aaron; Sherman, Ariel; Bonnett, James; Kelmelis, Eric

2017-07-01

When capturing imagery over long distances, atmospheric turbulence often degrades the data, especially when observation paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms has different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for postprocessing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005. We will compare techniques from the literature with our commercially available, real-time, GPU-accelerated turbulence mitigation software. These comparisons will be made using real (not synthetic), experimentally obtained data for a variety of conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation. Additionally, we will present a technique for quantitatively comparing turbulence mitigation algorithms using real images of radial resolution targets.

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.

Experimental and theoretical studies of active control of resistive wall mode growth in the EXTRAP T2R reversed-field pinch

NASA Astrophysics Data System (ADS)

Drake, J. R.; Brunsell, P. R.; Yadikin, D.; Cecconello, M.; Malmberg, J. A.; Gregoratto, D.; Paccagnella, R.; Bolzonella, T.; Manduchi, G.; Marrelli, L.; Ortolani, S.; Spizzo, G.; Zanca, P.; Bondeson, A.; Liu, Y. Q.

2005-07-01

Active feedback control of resistive wall modes (RWMs) has been demonstrated in the EXTRAP T2R reversed-field pinch experiment. The control system includes a sensor consisting of an array of magnetic coils (measuring mode harmonics) and an actuator consisting of a saddle coil array (producing control harmonics). Closed-loop (feedback) experiments using a digital controller based on a real time Fourier transform of sensor data have been studied for cases where the feedback gain was constant and real for all harmonics (corresponding to an intelligent-shell) and cases where the feedback gain could be set for selected harmonics, with both real and complex values (targeted harmonics). The growth of the dominant RWMs can be reduced by feedback for both the intelligent-shell and targeted-harmonic control systems. Because the number of toroidal positions of the saddle coils in the array is half the number of the sensors, it is predicted and observed experimentally that the control harmonic spectrum has sidebands. Individual unstable harmonics can be controlled with real gains. However if there are two unstable mode harmonics coupled by the sideband effect, control is much less effective with real gains. According to the theory, complex gains give better results for (slowly) rotating RWMs, and experiments support this prediction. In addition, open loop experiments have been used to observe the effects of resonant field errors applied to unstable, marginally stable and robustly stable modes. The observed effects of field errors are consistent with the thin-wall model, where mode growth is proportional to the resonant field error amplitude and the wall penetration time for that mode harmonic.

The Physics of Intelligence

ERIC Educational Resources Information Center

Escultura, E. E.

2012-01-01

This paper explores the physics of intelligence and provides an overview of what happens in the brain when a person is engaged in mental activity that we classify under thought or intelligence. It traces the formation of a concept starting with reception of visible or detectable signals from the real world by and external to the sense organs,…

A Comparison of the Single-sided (Gen II) and Double-sided (Gen I) Combat Arms Earplugs (CAE): Acoustic Properties, Human Performance, and User Acceptance

DTIC Science & Technology

2012-12-01

results of steady-state and impulse noise attenuation objective and real-ear measurements; localization and speech intelligibility human performance... Intelligibility 12 6.1 Method...12 Figure 8. Speech intelligibility testing of Gen I CAE and Gen II CAE

The German Intelligibility in Context Scale (ICS-G): Reliability and Validity Evidence

ERIC Educational Resources Information Center

Neumann, Sandra; Rietz, Christian; Stenneken, Prisca

2017-01-01

Background: In 2012 the Intelligibility in Context Scale (ICS) was published as a parent-report screening assessment that considers parents' perceptions of their children's functional intelligibility with a range of communication partners that differ in levels of authority and familiarity in real-life situations. To date, the ICS has been…

The Application of Sensors on Guardrails for the Purpose of Real Time Impact Detection

DTIC Science & Technology

2012-03-01

collection methods ; however, there are major differences in the measures of performance for policy goals and objectives (U.S. DOT, 2002). The goal here is...seriousness of this issue has motivated the US Department of Transportation and Transportation Research Board to develop and deploy new methods and... methods to integrate new sensing capabilities into existing Intelligent Transportation Systems in a time efficient and cost effective manner. In

Near Real-Time Event Detection & Prediction Using Intelligent Software Agents

DTIC Science & Technology

2006-03-01

value was 0.06743. Multiple autoregressive integrated moving average ( ARIMA ) models were then build to see if the raw data, differenced data, or...slight improvement. The best adjusted r^2 value was found to be 0.1814. Successful results were not expected from linear or ARIMA -based modelling ...appear, 2005. [63] Mora-Lopez, L., Mora, J., Morales-Bueno, R., et al. Modelling time series of climatic parameters with probabilistic finite

Measuring the Performance and Intelligence of Systems: Proceedings of the 2001 PerMIS Workshop

DTIC Science & Technology

2001-09-04

35 1.1 Interval Mathematics for Analysis of Multiresolutional Systems V. Kreinovich, Univ. of Texas, R. Alo, Univ. of Houston-Downtown...the possible combinations. In non-deterministic real- time systems , the problem is compounded by the uncertainty in the execution times of various...multiresolutional, multiscale ) in their essence because of multiresolutional character of the meaning of words [Rieger, 01]. In integrating systems , the presence of a

Outline for a theory of intelligence

NASA Technical Reports Server (NTRS)

Albus, James S.

1991-01-01

Intelligence is defined as that which produces successful behavior. Intelligence is assumed to result from natural selection. A model is proposed that integrates knowledge from research in both natural and artificial systems. The model consists of a hierarchical system architecture wherein: (1) control bandwidth decreases about an order of magnitude at each higher level, (2) perceptual resolution of spatial and temporal patterns contracts about an order-of-magnitude at each higher level, (3) goals expand in scope and planning horizons expand in space and time about an order-of-magnitude at each higher level, and (4) models of the world and memories of events expand their range in space and time by about an order-of-magnitude at each higher level. At each level, functional modules perform behavior generation (task decomposition planning and execution), world modeling, sensory processing, and value judgment. Sensory feedback control loops are closed at every level.

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.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Development of an automated ultrasonic testing system

NASA Astrophysics Data System (ADS)

Shuxiang, Jiao; Wong, Brian Stephen

2005-04-01

Non-Destructive Testing is necessary in areas where defects in structures emerge over time due to wear and tear and structural integrity is necessary to maintain its usability. However, manual testing results in many limitations: high training cost, long training procedure, and worse, the inconsistent test results. A prime objective of this project is to develop an automatic Non-Destructive testing system for a shaft of the wheel axle of a railway carriage. Various methods, such as the neural network, pattern recognition methods and knowledge-based system are used for the artificial intelligence problem. In this paper, a statistical pattern recognition approach, Classification Tree is applied. Before feature selection, a thorough study on the ultrasonic signals produced was carried out. Based on the analysis of the ultrasonic signals, three signal processing methods were developed to enhance the ultrasonic signals: Cross-Correlation, Zero-Phase filter and Averaging. The target of this step is to reduce the noise and make the signal character more distinguishable. Four features: 1. The Auto Regressive Model Coefficients. 2. Standard Deviation. 3. Pearson Correlation 4. Dispersion Uniformity Degree are selected. And then a Classification Tree is created and applied to recognize the peak positions and amplitudes. Searching local maximum is carried out before feature computing. This procedure reduces much computation time in the real-time testing. Based on this algorithm, a software package called SOFRA was developed to recognize the peaks, calibrate automatically and test a simulated shaft automatically. The automatic calibration procedure and the automatic shaft testing procedure are developed.

Superior pattern processing is the essence of the evolved human brain

PubMed Central

Mattson, Mark P.

2014-01-01

Humans have long pondered the nature of their mind/brain and, particularly why its capacities for reasoning, communication and abstract thought are far superior to other species, including closely related anthropoids. This article considers superior pattern processing (SPP) as the fundamental basis of most, if not all, unique features of the human brain including intelligence, language, imagination, invention, and the belief in imaginary entities such as ghosts and gods. SPP involves the electrochemical, neuronal network-based, encoding, integration, and transfer to other individuals of perceived or mentally-fabricated patterns. During human evolution, pattern processing capabilities became increasingly sophisticated as the result of expansion of the cerebral cortex, particularly the prefrontal cortex and regions involved in processing of images. Specific patterns, real or imagined, are reinforced by emotional experiences, indoctrination and even psychedelic drugs. Impaired or dysregulated SPP is fundamental to cognitive and psychiatric disorders. A broader understanding of SPP mechanisms, and their roles in normal and abnormal function of the human brain, may enable the development of interventions that reduce irrational decisions and destructive behaviors. PMID:25202234

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.

Microscopic 3D measurement of dynamic scene using optimized pulse-width-modulation binary fringe

NASA Astrophysics Data System (ADS)

Hu, Yan; Chen, Qian; Feng, Shijie; Tao, Tianyang; Li, Hui; Zuo, Chao

2017-10-01

Microscopic 3-D shape measurement can supply accurate metrology of the delicacy and complexity of MEMS components of the final devices to ensure their proper performance. Fringe projection profilometry (FPP) has the advantages of noncontactness and high accuracy, making it widely used in 3-D measurement. Recently, tremendous advance of electronics development promotes 3-D measurements to be more accurate and faster. However, research about real-time microscopic 3-D measurement is still rarely reported. In this work, we effectively combine optimized binary structured pattern with number-theoretical phase unwrapping algorithm to realize real-time 3-D shape measurement. A slight defocusing of our proposed binary patterns can considerably alleviate the measurement error based on phase-shifting FPP, making the binary patterns have the comparable performance with ideal sinusoidal patterns. Real-time 3-D measurement about 120 frames per second (FPS) is achieved, and experimental result of a vibrating earphone is presented.

Wireless powering and data telemetry for biomedical implants.

PubMed

Young, Darrin J

2009-01-01

Wireless powering and data telemetry techniques for two biomedical implant studies based on (1) wireless in vivo EMG sensor for intelligent prosthetic control and (2) adaptively RF powered implantable bio-sensing microsystem for real-time genetically engineered mice monitoring are presented. Inductive-coupling-based RF powering and passive data telemetry is effective for wireless in vivo EMG sensing, where the internal and external RF coils are positioned with a small separation distance and fixed orientation. Adaptively controlled RF powering and active data transmission are critical for mobile implant application such as real-time physiological monitoring of untethered laboratory animals. Animal implant studies have been successfully completed to demonstrate the wireless and batteryless in vivo sensing capabilities.

Improving the Robustness of Real-Time Myoelectric Pattern Recognition against Arm Position Changes in Transradial Amputees

PubMed Central

Geng, Yanjuan; Wei, Yue

2017-01-01

Previous studies have showed that arm position variations would significantly degrade the classification performance of myoelectric pattern-recognition-based prosthetic control, and the cascade classifier (CC) and multiposition classifier (MPC) have been proposed to minimize such degradation in offline scenarios. However, it remains unknown whether these proposed approaches could also perform well in the clinical use of a multifunctional prosthesis control. In this study, the online effect of arm position variation on motion identification was evaluated by using a motion-test environment (MTE) developed to mimic the real-time control of myoelectric prostheses. The performance of different classifier configurations in reducing the impact of arm position variation was investigated using four real-time metrics based on dataset obtained from transradial amputees. The results of this study showed that, compared to the commonly used motion classification method, the CC and MPC configurations improved the real-time performance across seven classes of movements in five different arm positions (8.7% and 12.7% increments of motion completion rate, resp.). The results also indicated that high offline classification accuracy might not ensure good real-time performance under variable arm positions, which necessitated the investigation of the real-time control performance to gain proper insight on the clinical implementation of EMG-pattern-recognition-based controllers for limb amputees. PMID:28523276

Evolution of the speech intelligibility of prelinguistically deaf children who received a cochlear implant

NASA Astrophysics Data System (ADS)

Bouchard, Marie-Eve; Cohen, Henri; Lenormand, Marie-Therese

2005-04-01

The 2 main objectives of this investigation are (1) to assess the evolution of the speech intelligibility of 12 prelinguistically deaf children implanted between 25 and 78 months of age and (2) to clarify the influence of the age at implantation on the intelligibility. Speech productions videorecorded at 6, 18 and 36 months following surgery during a standardized free play session. Selected syllables were then presented to 40 adults listeners who were asked to identify the vowels or the consonants they heard and to judge the quality of the segments. Perceived vowels were then located in the vocalic space whereas consonants were classified according to voicing, manner and place of articulation. 3 (Groups) ×3 (Times) ANOVA with repeated measures revealed a clear influence of time as well as age at implantation on the acquisition patterns. Speech intelligibility of these implanted children tended to improve as their experience with the device increased. Based on these results, it is proposed that sensory restoration following cochlear implant served as a probe to develop articulatory strategies allowing them to reach the intended acoustico-perceptual target.

An efficient sequential approach to tracking multiple objects through crowds for real-time intelligent CCTV systems.

PubMed

Li, Liyuan; Huang, Weimin; Gu, Irene Yu-Hua; Luo, Ruijiang; Tian, Qi

2008-10-01

Efficiency and robustness are the two most important issues for multiobject tracking algorithms in real-time intelligent video surveillance systems. We propose a novel 2.5-D approach to real-time multiobject tracking in crowds, which is formulated as a maximum a posteriori estimation problem and is approximated through an assignment step and a location step. Observing that the occluding object is usually less affected by the occluded objects, sequential solutions for the assignment and the location are derived. A novel dominant color histogram (DCH) is proposed as an efficient object model. The DCH can be regarded as a generalized color histogram, where dominant colors are selected based on a given distance measure. Comparing with conventional color histograms, the DCH only requires a few color components (31 on average). Furthermore, our theoretical analysis and evaluation on real data have shown that DCHs are robust to illumination changes. Using the DCH, efficient implementations of sequential solutions for the assignment and location steps are proposed. The assignment step includes the estimation of the depth order for the objects in a dispersing group, one-by-one assignment, and feature exclusion from the group representation. The location step includes the depth-order estimation for the objects in a new group, the two-phase mean-shift location, and the exclusion of tracked objects from the new position in the group. Multiobject tracking results and evaluation from public data sets are presented. Experiments on image sequences captured from crowded public environments have shown good tracking results, where about 90% of the objects have been successfully tracked with the correct identification numbers by the proposed method. Our results and evaluation have indicated that the method is efficient and robust for tracking multiple objects (>or= 3) in complex occlusion for real-world surveillance scenarios.

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

Lodhia, P.; Antonious, A.; Esat, I.

There has been much recent interest in the application of artificial intelligence systems to real world problems. Substantial interest has been shown in their application to investment markets. Artificial Neural Networks are the most common technique here. This paper is concerned with the use of ANNs in forecasting exchange rates. Much research has been carried out in currency markets. However, many of the studies use end of day or average quotes for currencies as a basis for prediction. A growing school of thought propose that markets are non-random in the short-term and can be shown to follow patterns. This short-termmore » time span can be described as being a period when the markets are inefficient at price adjustments. The use of intraday data is an ideal testing ground for ANNs based research. This paper aims to study the intraday forecasting of the US Dollar/German Deutschmark and to address the question of whether ANNs can make acceptable predictions. The problems of forecasting in such a complex environment will be addressed.« less

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.

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.

KANTS: a stigmergic ant algorithm for cluster analysis and swarm art.

PubMed

Fernandes, Carlos M; Mora, Antonio M; Merelo, Juan J; Rosa, Agostinho C

2014-06-01

KANTS is a swarm intelligence clustering algorithm inspired by the behavior of social insects. It uses stigmergy as a strategy for clustering large datasets and, as a result, displays a typical behavior of complex systems: self-organization and global patterns emerging from the local interaction of simple units. This paper introduces a simplified version of KANTS and describes recent experiments with the algorithm in the context of a contemporary artistic and scientific trend called swarm art, a type of generative art in which swarm intelligence systems are used to create artwork or ornamental objects. KANTS is used here for generating color drawings from the input data that represent real-world phenomena, such as electroencephalogram sleep data. However, the main proposal of this paper is an art project based on well-known abstract paintings, from which the chromatic values are extracted and used as input. Colors and shapes are therefore reorganized by KANTS, which generates its own interpretation of the original artworks. The project won the 2012 Evolutionary Art, Design, and Creativity Competition.

A heterogeneous artificial stock market model can benefit people against another financial crisis

PubMed Central

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis. PMID:29912893

A heterogeneous artificial stock market model can benefit people against another financial crisis.

PubMed

Yang, Haijun; Chen, Shuheng

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

RISMA: A Rule-based Interval State Machine Algorithm for Alerts Generation, Performance Analysis and Monitoring Real-Time Data Processing

NASA Astrophysics Data System (ADS)

Laban, Shaban; El-Desouky, Aly

2013-04-01

The monitoring of real-time systems is a challenging and complicated process. So, there is a continuous need to improve the monitoring process through the use of new intelligent techniques and algorithms for detecting exceptions, anomalous behaviours and generating the necessary alerts during the workflow monitoring of such systems. The interval-based or period-based theorems have been discussed, analysed, and used by many researches in Artificial Intelligence (AI), philosophy, and linguistics. As explained by Allen, there are 13 relations between any two intervals. Also, there have also been many studies of interval-based temporal reasoning and logics over the past decades. Interval-based theorems can be used for monitoring real-time interval-based data processing. However, increasing the number of processed intervals makes the implementation of such theorems a complex and time consuming process as the relationships between such intervals are increasing exponentially. To overcome the previous problem, this paper presents a Rule-based Interval State Machine Algorithm (RISMA) for processing, monitoring, and analysing the behaviour of interval-based data, received from real-time sensors. The proposed intelligent algorithm uses the Interval State Machine (ISM) approach to model any number of interval-based data into well-defined states as well as inferring them. An interval-based state transition model and methodology are presented to identify the relationships between the different states of the proposed algorithm. By using such model, the unlimited number of relationships between similar large numbers of intervals can be reduced to only 18 direct relationships using the proposed well-defined states. For testing the proposed algorithm, necessary inference rules and code have been designed and applied to the continuous data received in near real-time from the stations of International Monitoring System (IMS) by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). The CLIPS expert system shell has been used as the main rule engine for implementing the algorithm rules. Python programming language and the module "PyCLIPS" are used for building the necessary code for algorithm implementation. More than 1.7 million intervals constitute the Concise List of Frames (CLF) from 20 different seismic stations have been used for evaluating the proposed algorithm and evaluating stations behaviour and performance. The initial results showed that proposed algorithm can help in better understanding of the operation and performance of those stations. Different important information, such as alerts and some station performance parameters, can be derived from the proposed algorithm. For IMS interval-based data and at any period of time it is possible to analyze station behavior, determine the missing data, generate necessary alerts, and to measure some of station performance attributes. The details of the proposed algorithm, methodology, implementation, experimental results, advantages, and limitations of this research are presented. Finally, future directions and recommendations are discussed.

Fish swarm intelligent to optimize real time monitoring of chips drying using machine vision

NASA Astrophysics Data System (ADS)

Hendrawan, Y.; Hawa, L. C.; Damayanti, R.

2018-03-01

This study attempted to apply machine vision-based chips drying monitoring system which is able to optimise the drying process of cassava chips. The objective of this study is to propose fish swarm intelligent (FSI) optimization algorithms to find the most significant set of image features suitable for predicting water content of cassava chips during drying process using artificial neural network model (ANN). Feature selection entails choosing the feature subset that maximizes the prediction accuracy of ANN. Multi-Objective Optimization (MOO) was used in this study which consisted of prediction accuracy maximization and feature-subset size minimization. The results showed that the best feature subset i.e. grey mean, L(Lab) Mean, a(Lab) energy, red entropy, hue contrast, and grey homogeneity. The best feature subset has been tested successfully in ANN model to describe the relationship between image features and water content of cassava chips during drying process with R2 of real and predicted data was equal to 0.9.

Real Rules of Inference

DTIC Science & Technology

1986-01-01

the AAAI Workshop on Uncertainty and Probability in Artificial Intelligence , 1985. [McC771 McCarthy, J. "Epistemological Problems of Aritificial ...NUMBER OF PAGES Artificial Intelligence , Data Fusion, Inference, Probability, 30 Philosophy, Inheritance Hierachies, Default Reasoning ia.PRCECODE I...prominent philosophers Glymour and Thomason even applaud the uninhibited steps: Artificial Intelligence has done us the service not only of reminding us

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).

i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

NASA Technical Reports Server (NTRS)

1990-01-01

The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

Bionic Vision-Based Intelligent Power Line Inspection System

PubMed Central

Ma, Yunpeng; He, Feijia; Xu, Jinxin

2017-01-01

Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism in this intelligent inspection system is used to detect and track power lines in image sequences according to the shape information of power lines, and the binocular visual model is used to calculate the 3D coordinate information of obstacles and power lines. In order to improve the real time and accuracy of the system, we propose a new matching strategy based on the traditional SURF algorithm. The experimental results show that the system is able to accurately locate the position of the obstacles around power lines automatically, and the designed power line inspection system is effective in complex backgrounds, and there are no missing detection instances under different conditions. PMID:28203269

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 analysis keratometer

NASA Technical Reports Server (NTRS)

Adachi, Iwao P. (Inventor); Adachi, Yoshifumi (Inventor); Frazer, Robert E. (Inventor)

1987-01-01

A computer assisted keratometer in which a fiducial line pattern reticle illuminated by CW or pulsed laser light is projected on a corneal surface through lenses, a prismoidal beamsplitter quarterwave plate, and objective optics. The reticle surface is curved as a conjugate of an ideal corneal curvature. The fiducial image reflected from the cornea undergoes a polarization shift through the quarterwave plate and beamsplitter whereby the projected and reflected beams are separated and directed orthogonally. The reflected beam fiducial pattern forms a moire pattern with a replica of the first recticle. This moire pattern contains transverse aberration due to differences in curvature between the cornea and the ideal corneal curvature. The moire pattern is analyzed in real time by computer which displays either the CW moire pattern or a pulsed mode analysis of the transverse aberration of the cornea under observation, in real time. With the eye focused on a plurality of fixation points in succession, a survey of the entire corneal topography is made and a contour map or three dimensional plot of the cornea can be made as a computer readout in addition to corneal radius and refractive power analysis.

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

Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis

PubMed Central

Forss, Sofia I. F.; Willems, Erik; Call, Josep; van Schaik, Carel P.

2016-01-01

Cultural species can - or even prefer to - learn their skills from conspecifics. According to the cultural intelligence hypothesis, selection on underlying mechanisms not only improves this social learning ability but also the asocial (individual) learning ability. Thus, species with systematically richer opportunities to socially acquire knowledge and skills should over time evolve to become more intelligent. We experimentally compared the problem-solving ability of Sumatran orang-utans (Pongo abelii), which are sociable in the wild, with that of the closely related, but more solitary Bornean orang-utans (P. pygmaeus), under the homogeneous environmental conditions provided by zoos. Our results revealed that Sumatrans showed superior innate problem-solving skills to Borneans, and also showed greater inhibition and a more cautious and less rough exploration style. This pattern is consistent with the cultural intelligence hypothesis, which predicts that the more sociable of two sister species experienced stronger selection on cognitive mechanisms underlying learning. PMID:27466052

Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis.

PubMed

Forss, Sofia I F; Willems, Erik; Call, Josep; van Schaik, Carel P

2016-07-28

Cultural species can - or even prefer to - learn their skills from conspecifics. According to the cultural intelligence hypothesis, selection on underlying mechanisms not only improves this social learning ability but also the asocial (individual) learning ability. Thus, species with systematically richer opportunities to socially acquire knowledge and skills should over time evolve to become more intelligent. We experimentally compared the problem-solving ability of Sumatran orang-utans (Pongo abelii), which are sociable in the wild, with that of the closely related, but more solitary Bornean orang-utans (P. pygmaeus), under the homogeneous environmental conditions provided by zoos. Our results revealed that Sumatrans showed superior innate problem-solving skills to Borneans, and also showed greater inhibition and a more cautious and less rough exploration style. This pattern is consistent with the cultural intelligence hypothesis, which predicts that the more sociable of two sister species experienced stronger selection on cognitive mechanisms underlying learning.

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.

An architecture for intelligent task interruption

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Narayan, Srini

1990-01-01

In the design of real time systems the capability for task interruption is often considered essential. The problem of task interruption in knowledge-based domains is examined. It is proposed that task interruption can be often avoided by using appropriate functional architectures and knowledge engineering principles. Situations for which task interruption is indispensable, a preliminary architecture based on priority hierarchies is described.

Testing and Evaluation of Low-Light Sensors to Enhance Intelligence, Surveillance, and Reconnaissance (ISR) and Real-Time Situational Awareness

DTIC Science & Technology

2009-03-01

infrared, thermal , or night vision applications. Understanding the true capabilities and limitations of the ALAN camera and its applicability to a...an option to more expensive infrared, thermal , or night vision applications. Ultimately, it will be clear whether the configuration of the Kestrel...45  A.  THERMAL CAMERAS................................................................................45  1

Parallel Artificial Intelligence Search Techniques for Real Time Applications.

DTIC Science & Technology

1987-12-01

list) (cond ((atom e) e) ((setq a-list (match ’((> v)) e nil)) (inf-to-pre (match-value ’v a-list))) ((setq a-list (match ’((+ 1) (restrict ? oneplus ...defun oneplus (x) 2 (equal x ’) :,- ""find the value of a key into an association list. 7,. :" (defun match-value (key a-list) : : (cadr (assoc key a

An Experimental Design of a Foundational Framework for the Application of Affective Computing to Soaring Flight Simulation and Training

ERIC Educational Resources Information Center

Moon, Shannon

2017-01-01

In the absence of tools for intelligent tutoring systems for soaring flight simulation training, this study evaluated a framework foundation to measure pilot performance, affect, and physiological response to training in real-time. Volunteers were asked to perform a series of flight tasks selected from Federal Aviation Administration Practical…

Integrated Vehicle Health Management (IVHM) for Aerospace Systems

NASA Technical Reports Server (NTRS)

Baroth, Edmund C.; Pallix, Joan

2006-01-01

To achieve NASA's ambitious Integrated Space Transportation Program objectives, aerospace systems will implement a variety of new concept in health management. System level integration of IVHM technologies for real-time control and system maintenance will have significant impact on system safety and lifecycle costs. IVHM technologies will enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. IVHM also has the potential to reduce, or even eliminate many of the costly inspections and operations activities required by current and future aerospace systems. This presentation will describe the array of NASA programs participating in the development of IVHM technologies for NASA missions. Future vehicle systems will use models of the system, its environment, and other intelligent agents with which they may interact. IVHM will be incorporated into future mission planners, reasoning engines, and adaptive control systems that can recommend or execute commands enabling the system to respond intelligently in real time. In the past, software errors and/or faulty sensors have been identified as significant contributors to mission failures. This presentation will also address the development and utilization of highly dependable sohare and sensor technologies, which are key components to ensure the reliability of IVHM systems.

Energy-Saving Tunnel Illumination System Based on LED's Intelligent Control

NASA Astrophysics Data System (ADS)

Guo, Shanshan; Gu, Hanting; Wu, Lan; Jiang, Shuixiu

2011-02-01

At present there is a lot of electric energy wastage in tunnel illumination, whose design is based on the maximum brightness outside and the maximum vehicle speed all year round. LED's energy consumption is low, and the control of its brightness is simple and effective. It can be quickly adjusted between 0-100% of its maximum brightness, and will not affect the service life. Therefore, using LED as tunnel's illumination source, we can achieve a good energy saving effect. According to real-time data acquisition of vehicle speed, traffic flow and brightness outside the tunnel, the auto real-time control of tunnel illumination can be achieved. And the system regulated the LED luminance by means of combination of LED power module and intelligent control module. The tunnel information was detected by inspection equipments, which included luminometer, vehicle detector, and received by RTU(Remote Terminal Unit), then synchronously transmitted to PC. After data processing, RTU emitted the dimming signal to the LED driver to adjust the brightness of LED. Despite the relatively high cost of high-power LED lights, the enormous energy-saving effect and the well-behaved controllability is beyond compare to other lighting devices.

Reinforcement learning in supply chains.

PubMed

Valluri, Annapurna; North, Michael J; Macal, Charles M

2009-10-01

Effective management of supply chains creates value and can strategically position companies. In practice, human beings have been found to be both surprisingly successful and disappointingly inept at managing supply chains. The related fields of cognitive psychology and artificial intelligence have postulated a variety of potential mechanisms to explain this behavior. One of the leading candidates is reinforcement learning. This paper applies agent-based modeling to investigate the comparative behavioral consequences of three simple reinforcement learning algorithms in a multi-stage supply chain. For the first time, our findings show that the specific algorithm that is employed can have dramatic effects on the results obtained. Reinforcement learning is found to be valuable in multi-stage supply chains with several learning agents, as independent agents can learn to coordinate their behavior. However, learning in multi-stage supply chains using these postulated approaches from cognitive psychology and artificial intelligence take extremely long time periods to achieve stability which raises questions about their ability to explain behavior in real supply chains. The fact that it takes thousands of periods for agents to learn in this simple multi-agent setting provides new evidence that real world decision makers are unlikely to be using strict reinforcement learning in practice.

IMIS: An intelligence microscope imaging system

NASA Technical Reports Server (NTRS)

Caputo, Michael; Hunter, Norwood; Taylor, Gerald

1994-01-01

Until recently microscope users in space relied on traditional microscopy techniques that required manual operation of the microscope and recording of observations in the form of written notes, drawings, or photographs. This method was time consuming and required the return of film and drawings from space for analysis. No real-time data analysis was possible. Advances in digital and video technologies along with recent developments in article intelligence will allow future space microscopists to have a choice of three additional modes of microscopy: remote coaching, remote control, and automation. Remote coaching requires manual operations of the microscope with instructions given by two-way audio/video transmission during critical phases of the experiment. When using the remote mode of microscopy, the Principal Investigator controls the microscope from the ground. The automated mode employs artificial intelligence to control microscope functions and is the only mode that can be operated in the other three modes as well. The purpose of this presentation is to discuss the advantages and disadvantages of the four modes of of microscopy and how the IMIS, a proposed intelligent microscope imaging system, can be used as a model for developing and testing concepts, operating procedures, and equipment design of specifications required to provide a comprehensive microscopy/imaging capability onboard Space Station Freedom.

Data-Mining-Based Intelligent Differential Relaying for Transmission Lines Including UPFC and Wind Farms.

PubMed

Jena, Manas Kumar; Samantaray, Subhransu Ranjan

2016-01-01

This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.

Automatic diagnosis of tuberculosis disease based on Plasmonic ELISA and color-based image classification.

PubMed

AbuHassan, Kamal J; Bakhori, Noremylia M; Kusnin, Norzila; Azmi, Umi Z M; Tania, Marzia H; Evans, Benjamin A; Yusof, Nor A; Hossain, M A

2017-07-01

Tuberculosis (TB) remains one of the most devastating infectious diseases and its treatment efficiency is majorly influenced by the stage at which infection with the TB bacterium is diagnosed. The available methods for TB diagnosis are either time consuming, costly or not efficient. This study employs a signal generation mechanism for biosensing, known as Plasmonic ELISA, and computational intelligence to facilitate automatic diagnosis of TB. Plasmonic ELISA enables the detection of a few molecules of analyte by the incorporation of smart nanomaterials for better sensitivity of the developed detection system. The computational system uses k-means clustering and thresholding for image segmentation. This paper presents the results of the classification performance of the Plasmonic ELISA imaging data by using various types of classifiers. The five-fold cross-validation results show high accuracy rate (>97%) in classifying TB images using the entire data set. Future work will focus on developing an intelligent mobile-enabled expert system to diagnose TB in real-time. The intelligent system will be clinically validated and tested in collaboration with healthcare providers in Malaysia.

Using multiple sensors for printed circuit board insertion

NASA Technical Reports Server (NTRS)

Sood, Deepak; Repko, Michael C.; Kelley, Robert B.

1989-01-01

As more and more activities are performed in space, there will be a greater demand placed on the information handling capacity of people who are to direct and accomplish these tasks. A promising alternative to full-time human involvement is the use of semi-autonomous, intelligent robot systems. To automate tasks such as assembly, disassembly, repair and maintenance, the issues presented by environmental uncertainties need to be addressed. These uncertainties are introduced by variations in the computed position of the robot at different locations in its work envelope, variations in part positioning, and tolerances of part dimensions. As a result, the robot system may not be able to accomplish the desired task without the help of sensor feedback. Measurements on the environment allow real time corrections to be made to the process. A design and implementation of an intelligent robot system which inserts printed circuit boards into a card cage are presented. Intelligent behavior is accomplished by coupling the task execution sequence with information derived from three different sensors: an overhead three-dimensional vision system, a fingertip infrared sensor, and a six degree of freedom wrist-mounted force/torque sensor.

On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels.

PubMed

Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho; Kim, Hee-Kang

2018-03-11

Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services.

On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels

PubMed Central

Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho

2018-01-01

Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services. PMID:29534483

Real-time Fatigue and Free-Living Physical Activity in Hematopoietic Stem Cell Transplantation Cancer Survivors and Healthy Controls: A Preliminary Examination of the Temporal, Dynamic Relationship.

PubMed

Hacker, Eileen Danaher; Kim, Inah; Park, Chang; Peters, Tara

Fatigue and physical inactivity, critical problems facing cancer survivors, impact overall health and functioning. Our group designed a novel methodology to evaluate the temporal, dynamic patterns in real-world settings. Using real-time technology, the temporal, dynamic relationship between real-time fatigue and free-living is described and compared in cancer survivors who were treated with hematopoietic stem cell transplantation (n = 25) and age- and gender-matched healthy controls (n = 25). Subjects wore wrist actigraphs on their nondominant hand to assess free-living physical activity, measured in 1-minute epochs, over 7 days. Subjects entered real-time fatigue assessments directly into the subjective event marker of the actigraph 5 times per day. Running averages of mean 1-minute activity counts 30, 60, and 120 minutes before and after each real-time fatigue score were correlated with real-time fatigue using generalized estimating equations, RESULTS:: A strong inverse relationship exists between real-time fatigue and subsequent free-living physical activity. This inverse relationship suggests that increasing real-time fatigue limits subsequent physical activity (B range= -0.002 to -0.004; P < .001). No significant differences in the dynamic patterns of real-time fatigue and free-living physical activity were found between groups. To our knowledge, this is the first study to document the temporal and potentially causal relationship between real-time fatigue and free-living physical activity in real-world setting. These findings suggest that fatigue drives the subsequent physical activity and the relationship may not be bidirectional. Understanding the temporal, dynamic relationship may have important health implications for developing interventions to address fatigue in cancer survivors.

Exploration of Metaphorical and Contextual Affect Sensing in a Virtual Improvisational Drama

NASA Astrophysics Data System (ADS)

Zhang, Li

Real-time affect detection from open-ended text-based dialogue is challenging but essential for the building of effective intelligent user interfaces. In this paper, we report updated developments of an affect detection model from text, including affect detection from one particular type of metaphorical affective expression (cooking metaphor) and affect detection based on context. The overall affect detection model has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. Evaluation for the updated affect detection component is also provided. Our work contributes to the conference themes on engagement and emotion, interactions in games, storytelling and narrative in education, and virtual characters/agents development.

Rapid prototyping facility for flight research in artificial-intelligence-based flight systems concepts

NASA Technical Reports Server (NTRS)

Duke, E. L.; Regenie, V. A.; Deets, D. A.

1986-01-01

The Dryden Flight Research Facility of the NASA Ames Research Facility of the NASA Ames Research Center is developing a rapid prototyping facility for flight research in flight systems concepts that are based on artificial intelligence (AI). The facility will include real-time high-fidelity aircraft simulators, conventional and symbolic processors, and a high-performance research aircraft specially modified to accept commands from the ground-based AI computers. This facility is being developed as part of the NASA-DARPA automated wingman program. This document discusses the need for flight research and for a national flight research facility for the rapid prototyping of AI-based avionics systems and the NASA response to those needs.

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.

Ubiquitous Computing Services Discovery and Execution Using a Novel Intelligent Web Services Algorithm

PubMed Central

Choi, Okkyung; Han, SangYong

2007-01-01

Ubiquitous Computing makes it possible to determine in real time the location and situations of service requesters in a web service environment as it enables access to computers at any time and in any place. Though research on various aspects of ubiquitous commerce is progressing at enterprises and research centers, both domestically and overseas, analysis of a customer's personal preferences based on semantic web and rule based services using semantics is not currently being conducted. This paper proposes a Ubiquitous Computing Services System that enables a rule based search as well as semantics based search to support the fact that the electronic space and the physical space can be combined into one and the real time search for web services and the construction of efficient web services thus become possible.

Test plan : I-40 TTIS route diversion study

DOT National Transportation Integrated Search

1998-01-01

The four sections of this report summarize the benefits seen in real-world applications of Intelligent Transportation Systems (ITS) in: metropolitan areas; rural areas; commercial trucking; and intelligent vehicle systems. For the lay reader, this re...

A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences.

PubMed

Karaboga, D; Aslan, S

2016-04-27

The great majority of biological sequences share significant similarity with other sequences as a result of evolutionary processes, and identifying these sequence similarities is one of the most challenging problems in bioinformatics. In this paper, we present a discrete artificial bee colony (ABC) algorithm, which is inspired by the intelligent foraging behavior of real honey bees, for the detection of highly conserved residue patterns or motifs within sequences. Experimental studies on three different data sets showed that the proposed discrete model, by adhering to the fundamental scheme of the ABC algorithm, produced competitive or better results than other metaheuristic motif discovery techniques.

Effect of filtration of signals of brain activity on quality of recognition of brain activity patterns using artificial intelligence methods

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Musatov, Vyachaslav Yu.

2018-02-01

In present work we studied features of the human brain states classification, corresponding to the real movements of hands and legs. For this purpose we used supervised learning algorithm based on feed-forward artificial neural networks (ANNs) with error back-propagation along with the support vector machine (SVM) method. We compared the quality of operator movements classification by means of EEG signals obtained experimentally in the absence of preliminary processing and after filtration in different ranges up to 25 Hz. It was shown that low-frequency filtering of multichannel EEG data significantly improved accuracy of operator movements classification.