Integrated identification, modeling and control with applications

NASA Astrophysics Data System (ADS)

Shi, Guojun

This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing controller such that the active control energy is minimized. A weighted q-Markov COVER method is introduced for identification with measurement noise. The result is use to develop an iterative closed loop identification/control design algorithm. The effectiveness of the algorithm is illustrated by experimental results.

Inverse problem studies of biochemical systems with structure identification of S-systems by embedding training functions in a genetic algorithm.

PubMed

Sarode, Ketan Dinkar; Kumar, V Ravi; Kulkarni, B D

2016-05-01

An efficient inverse problem approach for parameter estimation, state and structure identification from dynamic data by embedding training functions in a genetic algorithm methodology (ETFGA) is proposed for nonlinear dynamical biosystems using S-system canonical models. Use of multiple shooting and decomposition approach as training functions has been shown for handling of noisy datasets and computational efficiency in studying the inverse problem. The advantages of the methodology are brought out systematically by studying it for three biochemical model systems of interest. By studying a small-scale gene regulatory system described by a S-system model, the first example demonstrates the use of ETFGA for the multifold aims of the inverse problem. The estimation of a large number of parameters with simultaneous state and network identification is shown by training a generalized S-system canonical model with noisy datasets. The results of this study bring out the superior performance of ETFGA on comparison with other metaheuristic approaches. The second example studies the regulation of cAMP oscillations in Dictyostelium cells now assuming limited availability of noisy data. Here, flexibility of the approach to incorporate partial system information in the identification process is shown and its effect on accuracy and predictive ability of the estimated model are studied. The third example studies the phenomenological toy model of the regulation of circadian oscillations in Drosophila that follows rate laws different from S-system power-law. For the limited noisy data, using a priori information about properties of the system, we could estimate an alternate S-system model that showed robust oscillatory behavior with predictive abilities. Copyright © 2016 Elsevier Inc. All rights reserved.

The Accuracy of Parameter Estimation in System Identification of Noisy Aircraft Load Measurement. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Kong, Jeffrey

1994-01-01

This thesis focuses on the subject of the accuracy of parameter estimation and system identification techniques. Motivated by a complicated load measurement from NASA Dryden Flight Research Center, advanced system identification techniques are needed. The objective of this problem is to accurately predict the load experienced by the aircraft wing structure during flight determined from a set of calibrated load and gage response relationship. We can then model the problem as a black box input-output system identification from which the system parameter has to be estimated. Traditional LS (Least Square) techniques and the issues of noisy data and model accuracy are addressed. A statistical bound reflecting the change in residual is derived in order to understand the effects of the perturbations on the data. Due to the intrinsic nature of the LS problem, LS solution faces the dilemma of the trade off between model accuracy and noise sensitivity. A method of conflicting performance indices is presented, thus allowing us to improve the noise sensitivity while at the same time configuring the degredation of the model accuracy. SVD techniques for data reduction are studied and the equivalence of the Correspondence Analysis (CA) and Total Least Squares Criteria are proved. We also looked at nonlinear LS problems with NASA F-111 data set as an example. Conventional methods are neither easily applicable nor suitable for the specific load problem since the exact model of the system is unknown. Neural Network (NN) does not require prior information on the model of the system. This robustness motivated us to apply the NN techniques on our load problem. Simulation results for the NN methods used in both the single load and the 'warning signal' problems are both useful and encouraging. The performance of the NN (for single load estimate) is better than the LS approach, whereas no conventional approach was tried for the 'warning signals' problems. The NN design methodology is also presented. The use of SVD, CA and Collinearity Index methods are used to reduce the number of neurons in a layer.

Galerkin approximation for inverse problems for nonautonomous nonlinear distributed systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1988-01-01

An abstract framework and convergence theory is developed for Galerkin approximation for inverse problems involving the identification of nonautonomous nonlinear distributed parameter systems. A set of relatively easily verified conditions is provided which are sufficient to guarantee the existence of optimal solutions and their approximation by a sequence of solutions to a sequence of approximating finite dimensional identification problems. The approach is based on the theory of monotone operators in Banach spaces and is applicable to a reasonably broad class of nonlinear distributed systems. Operator theoretic and variational techniques are used to establish a fundamental convergence result. An example involving evolution systems with dynamics described by nonstationary quasilinear elliptic operators along with some applications are presented and discussed.

Research of mine water source identification based on LIF technology

NASA Astrophysics Data System (ADS)

Zhou, Mengran; Yan, Pengcheng

2016-09-01

According to the problem that traditional chemical methods to the mine water source identification takes a long time, put forward a method for rapid source identification system of mine water inrush based on the technology of laser induced fluorescence (LIF). Emphatically analyzes the basic principle of LIF technology. The hardware composition of LIF system are analyzed and the related modules were selected. Through the fluorescence experiment with the water samples of coal mine in the LIF system, fluorescence spectra of water samples are got. Traditional water source identification mainly according to the ion concentration representative of the water, but it is hard to analysis the ion concentration of the water from the fluorescence spectra. This paper proposes a simple and practical method of rapid identification of water by fluorescence spectrum, which measure the space distance between unknown water samples and standard samples, and then based on the clustering analysis, the category of the unknown water sample can be get. Water source identification for unknown samples verified the reliability of the LIF system, and solve the problem that the current coal mine can't have a better real-time and online monitoring on water inrush, which is of great significance for coal mine safety in production.

Other Challenges in the Development of the Orbiter Environmental Control Hardware

NASA Technical Reports Server (NTRS)

Gibb, J. W.; Mcintosh, M. E.; Heinrich, S. R.; Thomas, E.; Steele, M.; Schubert, F.; Koszenski, E. P.; Wynveen, R. A.; Murray, R. W.; Schelkopf, J. D.

1985-01-01

Development of the Space Shuttle orbiter environmental control and life support system (ECLSS) included the identification and resolution of several interesting problems in several systems. Some of these problems occurred late in the program, including the flight phase. Problems and solutions related to the ammonia boiler system (ABS), smoke detector, water/hydrogen separator, and waste collector system (WCS) are addressed.

System identification using Nuclear Norm & Tabu Search optimization

NASA Astrophysics Data System (ADS)

Ahmed, Asif A.; Schoen, Marco P.; Bosworth, Ken W.

2018-01-01

In recent years, subspace System Identification (SI) algorithms have seen increased research, stemming from advanced minimization methods being applied to the Nuclear Norm (NN) approach in system identification. These minimization algorithms are based on hard computing methodologies. To the authors’ knowledge, as of now, there has been no work reported that utilizes soft computing algorithms to address the minimization problem within the nuclear norm SI framework. A linear, time-invariant, discrete time system is used in this work as the basic model for characterizing a dynamical system to be identified. The main objective is to extract a mathematical model from collected experimental input-output data. Hankel matrices are constructed from experimental data, and the extended observability matrix is employed to define an estimated output of the system. This estimated output and the actual - measured - output are utilized to construct a minimization problem. An embedded rank measure assures minimum state realization outcomes. Current NN-SI algorithms employ hard computing algorithms for minimization. In this work, we propose a simple Tabu Search (TS) algorithm for minimization. TS algorithm based SI is compared with the iterative Alternating Direction Method of Multipliers (ADMM) line search optimization based NN-SI. For comparison, several different benchmark system identification problems are solved by both approaches. Results show improved performance of the proposed SI-TS algorithm compared to the NN-SI ADMM algorithm.

Optimized System Identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Longman, Richard W.

1999-01-01

In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

Identification of Successive ``Unobservable'' Cyber Data Attacks in Power Systems Through Matrix Decomposition

NASA Astrophysics Data System (ADS)

Gao, Pengzhi; Wang, Meng; Chow, Joe H.; Ghiocel, Scott G.; Fardanesh, Bruce; Stefopoulos, George; Razanousky, Michael P.

2016-11-01

This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting "unobservable" cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.

Continuous-time system identification of a smoking cessation intervention

NASA Astrophysics Data System (ADS)

Timms, Kevin P.; Rivera, Daniel E.; Collins, Linda M.; Piper, Megan E.

2014-07-01

Cigarette smoking is a major global public health issue and the leading cause of preventable death in the United States. Toward a goal of designing better smoking cessation treatments, system identification techniques are applied to intervention data to describe smoking cessation as a process of behaviour change. System identification problems that draw from two modelling paradigms in quantitative psychology (statistical mediation and self-regulation) are considered, consisting of a series of continuous-time estimation problems. A continuous-time dynamic modelling approach is employed to describe the response of craving and smoking rates during a quit attempt, as captured in data from a smoking cessation clinical trial. The use of continuous-time models provide benefits of parsimony, ease of interpretation, and the opportunity to work with uneven or missing data.

APPLYING OPERATIONAL ANALYSIS TO URBAN EDUCATIONAL SYSTEMS, A WORKING PAPER.

ERIC Educational Resources Information Center

SISSON, ROGER L.

OPERATIONS RESEARCH CONCEPTS ARE POTENTIALLY USEFUL FOR STUDY OF SUCH LARGE URBAN SCHOOL DISTRICT PROBLEMS AS INFORMATION FLOW, PHYSICAL STRUCTURE OF THE DISTRICT, ADMINISTRATIVE DECISION MAKING BOARD POLICY FUNCTIONS, AND THE BUDGET STRUCTURE. OPERATIONAL ANALYSIS REQUIRES (1) IDENTIFICATION OF THE SYSTEM UNDER STUDY, (2) IDENTIFICATION OF…

Recent Applications of the Volterra Theory to Aeroelastic Phenomena

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Haji, Muhammad R; Prazenica, Richard J.

2005-01-01

The identification of nonlinear aeroelastic systems based on the Volterra theory of nonlinear systems is presented. Recent applications of the theory to problems in experimental aeroelasticity are reviewed. These results include the identification of aerodynamic impulse responses, the application of higher-order spectra (HOS) to wind-tunnel flutter data, and the identification of nonlinear aeroelastic phenomena from flight flutter test data of the Active Aeroelastic Wing (AAW) aircraft.

An approximation theory for the identification of linear thermoelastic systems

NASA Technical Reports Server (NTRS)

Rosen, I. G.; Su, Chien-Hua Frank

1990-01-01

An abstract approximation framework and convergence theory for the identification of thermoelastic systems is developed. Starting from an abstract operator formulation consisting of a coupled second order hyperbolic equation of elasticity and first order parabolic equation for heat conduction, well-posedness is established using linear semigroup theory in Hilbert space, and a class of parameter estimation problems is then defined involving mild solutions. The approximation framework is based upon generic Galerkin approximation of the mild solutions, and convergence of solutions of the resulting sequence of approximating finite dimensional parameter identification problems to a solution of the original infinite dimensional inverse problem is established using approximation results for operator semigroups. An example involving the basic equations of one dimensional linear thermoelasticity and a linear spline based scheme are discussed. Numerical results indicate how the approach might be used in a study of damping mechanisms in flexible structures.

Aerodynamic parameter estimation via Fourier modulating function techniques

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1995-01-01

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1990-01-01

Parameter identification for nonlinear aerodynamic systems is examined. It is presumed that the underlying model can be arranged into an input/output (I/O) differential operator equation of a generic form. The algorithm estimation is especially efficient since the equation error can be integrated exactly given any I/O pair to obtain an algebraic function of the parameters. The algorithm for parameter identification was extended to the order determination problem for linear differential system. The degeneracy in a least squares estimate caused by feedback was addressed. A method of frequency analysis for determining the transfer function G(j omega) from transient I/O data was formulated using complex valued Fourier based modulating functions in contrast with the trigonometric modulating functions for the parameter estimation problem. A simulation result of applying the algorithm is given under noise-free conditions for a system with a low pass transfer function.

Eyewitness identification: Bayesian information gain, base-rate effect equivalency curves, and reasonable suspicion.

PubMed

Wells, Gary L; Yang, Yueran; Smalarz, Laura

2015-04-01

We provide a novel Bayesian treatment of the eyewitness identification problem as it relates to various system variables, such as instruction effects, lineup presentation format, lineup-filler similarity, lineup administrator influence, and show-ups versus lineups. We describe why eyewitness identification is a natural Bayesian problem and how numerous important observations require careful consideration of base rates. Moreover, we argue that the base rate in eyewitness identification should be construed as a system variable (under the control of the justice system). We then use prior-by-posterior curves and information-gain curves to examine data obtained from a large number of published experiments. Next, we show how information-gain curves are moderated by system variables and by witness confidence and we note how information-gain curves reveal that lineups are consistently more proficient at incriminating the guilty than they are at exonerating the innocent. We then introduce a new type of analysis that we developed called base rate effect-equivalency (BREE) curves. BREE curves display how much change in the base rate is required to match the impact of any given system variable. The results indicate that even relatively modest changes to the base rate can have more impact on the reliability of eyewitness identification evidence than do the traditional system variables that have received so much attention in the literature. We note how this Bayesian analysis of eyewitness identification has implications for the question of whether there ought to be a reasonable-suspicion criterion for placing a person into the jeopardy of an identification procedure. (c) 2015 APA, all rights reserved).

AGARD Flight Test Techniques Series. Volume 2. Identification of Dynamic Systems

DTIC Science & Technology

1985-01-01

should not depend upon it to solve the problem autonomously. The analyst’s strong point is in formulating the problem; the computer’s strength is in...of derivation for the output-error method is to reduce the problem to the static form of Chapter 5. We will see that the dinamic system make- the

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

A Minority Student Data Bank and More: The Ultimate College Identification and Tracking System.

ERIC Educational Resources Information Center

Cruz, Ramon

The computerized Identification-Placement-Tracking-System (IPTS) was developed at the University of California, Los Angeles, Educational Opportunity Center (EOC) as a remedy to problems in interschool coordination. As the IPTS currently functions, the EOC students select up to three colleges of interest for future matriculation. The schools are…

System Identification for the Clipper Liberty C96 Wind Turbine

NASA Astrophysics Data System (ADS)

Showers, Daniel

System identification techniques are powerful tools that help improve modeling capabilities of real world dynamic systems. These techniques are well established and have been successfully used on countless systems in many areas. However, wind turbines provide a unique challenge for system identification because of the difficulty in measuring its primary input: wind. This thesis first motivates the problem by demonstrating the challenges with wind turbine system identification using both simulations and real data. It then suggests techniques toward successfully identifying a dynamic wind turbine model including the notion of an effective wind speed and how it might be measured. Various levels of simulation complexity are explored for insights into calculating an effective wind speed. In addition, measurements taken from the University of Minnesota's Clipper Liberty C96 research wind turbine are used for a preliminary investigation into the effective wind speed calculation and system identification of a real world wind turbine.

Identification of dynamic characteristics of flexible rotors as dynamic inverse problem

NASA Technical Reports Server (NTRS)

Roisman, W. P.; Vajingortin, L. D.

1991-01-01

The problem of dynamic and balancing of flexible rotors were considered, which were set and solved as the problem of the identification of flexible rotor systems, which is the same as the inverse problem of the oscillation theory dealing with the task of the identifying the outside influences and system parameters on the basis of the known laws of motion. This approach to the problem allows the disclosure the picture of disbalances throughout the rotor-under-test (which traditional methods of flexible rotor balancing, based on natural oscillations, could not provide), and identify dynamic characteristics of the system, which correspond to a selected mathematical model. Eventually, various methods of balancing were developed depending on the special features of the machines as to their design, technology, and operation specifications. Also, theoretical and practical methods are given for the flexible rotor balancing at far from critical rotation frequencies, which does not necessarily require the knowledge forms of oscillation, dissipation, and elasticity and inertia characteristics, and to use testing masses.

Numerical Experimentation with Maximum Likelihood Identification in Static Distributed Systems

NASA Technical Reports Server (NTRS)

Scheid, R. E., Jr.; Rodriguez, G.

1985-01-01

Many important issues in the control of large space structures are intimately related to the fundamental problem of parameter identification. One might also ask how well this identification process can be carried out in the presence of noisy data since no sensor system is perfect. With these considerations in mind the algorithms herein are designed to treat both the case of uncertainties in the modeling and uncertainties in the data. The analytical aspects of maximum likelihood identification are considered in some detail in another paper. The questions relevant to the implementation of these schemes are dealt with, particularly as they apply to models of large space structures. The emphasis is on the influence of the infinite dimensional character of the problem on finite dimensional implementations of the algorithms. Those areas of current and future analysis are highlighted which indicate the interplay between error analysis and possible truncations of the state and parameter spaces.

A visual surveillance system for person re-identification

NASA Astrophysics Data System (ADS)

El-Alfy, Hazem; Muramatsu, Daigo; Teranishi, Yuuichi; Nishinaga, Nozomu; Makihara, Yasushi; Yagi, Yasushi

2017-03-01

We attempt the problem of autonomous surveillance for person re-identification. This is an active research area, where most recent work focuses on the open challenges of re-identification, independently of prerequisites of detection and tracking. In this paper, we are interested in designing a complete surveillance system, joining all the pieces of the puzzle together. We start by collecting our own dataset from multiple cameras. Then, we automate the process of detection and tracking of human subjects in the scenes, followed by performing the re-identification task. We evaluate the recognition performance of our system, report its strengths, discuss open challenges and suggest ways to address them.

Nutrition Problem Classification for Children and Youth.

ERIC Educational Resources Information Center

Health Services Administration (DHEW/PHS), Rockville, MD. Bureau of Community Health Services.

This nutrition problem classification system is an attempt to classify the nutritional needs and problems of children and youth. Its two most important uses are problem identification and monitoring for individual patients and creation of an information base for developing program plans for intervention in a service population. The classification…

Psychology Problem Classification for Children and Youth.

ERIC Educational Resources Information Center

Minnesota Systems Research, Inc., Washington, DC.

The development of Psychology Problem Classification is an early step in the direction of providing a uniform nomenclature for classifying the needs and problems of children and youth. There are many potential uses for a diagnostic classification and coding system. The two most important uses for the practitioner are problem identification and…

Progress Report on the Development of Child Abuse Prevention, Identification, and Treatment Systems in Eastern Europe

ERIC Educational Resources Information Center

Lewis, Owen; Sargent, John; Chaffin, Mark; Friedrich, William N.; Cunningham, Nicholas; Cantor, Pamela; Coffey, Pamela Sumner; Villani, Susan; Beard, Philip R.; Clifft, Mary Ann; Greenspun, David

2004-01-01

Problem: After the Soviet Union dissolved in 1989, it became apparent that there was little recognition of the problems of child abuse and neglect, professionally, legally, or societally. There were no effective systems or laws in place to deal with these problems. Method: Beginning in 1995 the Children's Mental Health Alliance, in conjunction…

Identification procedure for epistemic uncertainties using inverse fuzzy arithmetic

NASA Astrophysics Data System (ADS)

Haag, T.; Herrmann, J.; Hanss, M.

2010-10-01

For the mathematical representation of systems with epistemic uncertainties, arising, for example, from simplifications in the modeling procedure, models with fuzzy-valued parameters prove to be a suitable and promising approach. In practice, however, the determination of these parameters turns out to be a non-trivial problem. The identification procedure to appropriately update these parameters on the basis of a reference output (measurement or output of an advanced model) requires the solution of an inverse problem. Against this background, an inverse method for the computation of the fuzzy-valued parameters of a model with epistemic uncertainties is presented. This method stands out due to the fact that it only uses feedforward simulations of the model, based on the transformation method of fuzzy arithmetic, along with the reference output. An inversion of the system equations is not necessary. The advancement of the method presented in this paper consists of the identification of multiple input parameters based on a single reference output or measurement. An optimization is used to solve the resulting underdetermined problems by minimizing the uncertainty of the identified parameters. Regions where the identification procedure is reliable are determined by the computation of a feasibility criterion which is also based on the output data of the transformation method only. For a frequency response function of a mechanical system, this criterion allows a restriction of the identification process to some special range of frequency where its solution can be guaranteed. Finally, the practicability of the method is demonstrated by covering the measured output of a fluid-filled piping system by the corresponding uncertain FE model in a conservative way.

Level-set techniques for facies identification in reservoir modeling

NASA Astrophysics Data System (ADS)

Iglesias, Marco A.; McLaughlin, Dennis

2011-03-01

In this paper we investigate the application of level-set techniques for facies identification in reservoir models. The identification of facies is a geometrical inverse ill-posed problem that we formulate in terms of shape optimization. The goal is to find a region (a geologic facies) that minimizes the misfit between predicted and measured data from an oil-water reservoir. In order to address the shape optimization problem, we present a novel application of the level-set iterative framework developed by Burger in (2002 Interfaces Free Bound. 5 301-29 2004 Inverse Problems 20 259-82) for inverse obstacle problems. The optimization is constrained by (the reservoir model) a nonlinear large-scale system of PDEs that describes the reservoir dynamics. We reformulate this reservoir model in a weak (integral) form whose shape derivative can be formally computed from standard results of shape calculus. At each iteration of the scheme, the current estimate of the shape derivative is utilized to define a velocity in the level-set equation. The proper selection of this velocity ensures that the new shape decreases the cost functional. We present results of facies identification where the velocity is computed with the gradient-based (GB) approach of Burger (2002) and the Levenberg-Marquardt (LM) technique of Burger (2004). While an adjoint formulation allows the straightforward application of the GB approach, the LM technique requires the computation of the large-scale Karush-Kuhn-Tucker system that arises at each iteration of the scheme. We efficiently solve this system by means of the representer method. We present some synthetic experiments to show and compare the capabilities and limitations of the proposed implementations of level-set techniques for the identification of geologic facies.

A Novel Identification Methodology for the Coordinate Relationship between a 3D Vision System and a Legged Robot.

PubMed

Chai, Xun; Gao, Feng; Pan, Yang; Qi, Chenkun; Xu, Yilin

2015-04-22

Coordinate identification between vision systems and robots is quite a challenging issue in the field of intelligent robotic applications, involving steps such as perceiving the immediate environment, building the terrain map and planning the locomotion automatically. It is now well established that current identification methods have non-negligible limitations such as a difficult feature matching, the requirement of external tools and the intervention of multiple people. In this paper, we propose a novel methodology to identify the geometric parameters of 3D vision systems mounted on robots without involving other people or additional equipment. In particular, our method focuses on legged robots which have complex body structures and excellent locomotion ability compared to their wheeled/tracked counterparts. The parameters can be identified only by moving robots on a relatively flat ground. Concretely, an estimation approach is provided to calculate the ground plane. In addition, the relationship between the robot and the ground is modeled. The parameters are obtained by formulating the identification problem as an optimization problem. The methodology is integrated on a legged robot called "Octopus", which can traverse through rough terrains with high stability after obtaining the identification parameters of its mounted vision system using the proposed method. Diverse experiments in different environments demonstrate our novel method is accurate and robust.

[The state legal and expert identification aspects of protecting the right of the person for citizens of the Russian Federation].

PubMed

Bykov, I Iu; Kolkutin, V V; Tolmachev, I A; Dmitriev, E G

2000-04-01

The article deals with the questions concerning the problem of person identification, different extreme situations. This problem is closely connected with ensuring of national security of Russia. The authors give the definition of person's right in contact with constant threat to violate this right. Two categories of person's properties are analysed (material and not material) with the help of which it is possible to establish identity of man and his personality. It is noted that protection of person's rights is carried out in six forms. For the first time the possibilities to create organisational system of person identification in the form of Federal service are discussed that must be legislatively secured. Scientific investigation of this problem allowed the authors to submit concrete proposals concerning the question of organisation of state service for person identification.

Credit risk identification and suggestions of electricity market

NASA Astrophysics Data System (ADS)

He, Chuan; Wang, Haichao; Chen, Zhongyuan; Hao, Yuxing; Jiang, Hailong; Qian, Hanhan; Wang, Meibao

2018-03-01

The power industry has a long history of credit problems, and the power industry has credit problems such as power users defaulting on electricity bills before the new electricity reform. With the reform of the power system, the credit problems in the power industry will be more complicated. How to effectively avoid the risk factors existing in the course of market operation and how to safeguard the fairness and standardization of market operation is an urgent problem to be solved. This paper first describes the credit risk in power market, and analyzes the components of credit risk identification in power market, puts forward suggestions on power market risk management.

Social Work Problem Classification for Children and Youth.

ERIC Educational Resources Information Center

Minnesota Systems Research, Inc., Washington, DC.

The development of the Social Work Problem Classification is an early step in the provision of a uniform nomenclature for classifying the needs and problems of children and youth. There are many potential uses for a diagnostic classification and coding system. The two most important for the practitioner are: (1) problem identification and…

ODEion--a software module for structural identification of ordinary differential equations.

PubMed

Gennemark, Peter; Wedelin, Dag

2014-02-01

In the systems biology field, algorithms for structural identification of ordinary differential equations (ODEs) have mainly focused on fixed model spaces like S-systems and/or on methods that require sufficiently good data so that derivatives can be accurately estimated. There is therefore a lack of methods and software that can handle more general models and realistic data. We present ODEion, a software module for structural identification of ODEs. Main characteristic features of the software are: • The model space is defined by arbitrary user-defined functions that can be nonlinear in both variables and parameters, such as for example chemical rate reactions. • ODEion implements computationally efficient algorithms that have been shown to efficiently handle sparse and noisy data. It can run a range of realistic problems that previously required a supercomputer. • ODEion is easy to use and provides SBML output. We describe the mathematical problem, the ODEion system itself, and provide several examples of how the system can be used. Available at: http://www.odeidentification.org.

On Restructurable Control System Theory

NASA Technical Reports Server (NTRS)

Athans, M.

1983-01-01

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

A program for identification of linear systems

NASA Technical Reports Server (NTRS)

Buell, J.; Kalaba, R.; Ruspini, E.; Yakush, A.

1971-01-01

A program has been written for the identification of parameters in certain linear systems. These systems appear in biomedical problems, particularly in compartmental models of pharmacokinetics. The method presented here assumes that some of the state variables are regularly modified by jump conditions. This simulates administration of drugs following some prescribed drug regime. Parameters are identified by a least-square fit of the linear differential system to a set of experimental observations. The method is especially suited when the interval of observation of the system is very long.

Research on the transfer learning of the vehicle logo recognition

NASA Astrophysics Data System (ADS)

Zhao, Wei

2017-08-01

The Convolutional Neural Network of Deep Learning has been a huge success in the field of image intelligent transportation system can effectively solve the traffic safety, congestion, vehicle management and other problems of traffic in the city. Vehicle identification is a vital part of intelligent transportation, and the effective information in vehicles is of great significance to vehicle identification. With the traffic system on the vehicle identification technology requirements are getting higher and higher, the vehicle as an important type of vehicle information, because it should not be removed, difficult to change and other features for vehicle identification provides an important method. The current vehicle identification recognition (VLR) is mostly used to extract the characteristics of the method of classification, which for complex classification of its generalization ability to be some constraints, if the use of depth learning technology, you need a lot of training samples. In this paper, the method of convolution neural network based on transfer learning can solve this problem effectively, and it has important practical application value in the task of vehicle mark recognition.

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

Identification challenges for large space structures

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1990-01-01

The paper examines the on-orbit modal identification of large space structures, stressing the importance of planning and experience, in preparation for the Space Station Structural Characterization Experiment (SSSCE) for the Space Station Freedom. The necessary information to foresee and overcome practical difficulties is considered in connection with seven key factors, including test objectives, dynamic complexity of the structure, data quality, extent of exploratory studies, availability and understanding of software tools, experience with similar problems, and pretest analytical conditions. These factors affect identification success in ground tests. Comparisons with similar ground tests of assembled systems are discussed, showing that the constraints of space tests make these factors more significant. The absence of data and experiences relating to on-orbit modal identification testing is shown to make identification a uniquely mathematical problem, although all spacecraft are constructed and verified by proven engineering methods.

Application of statistical process control and process capability analysis procedures in orbiter processing activities at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Safford, Robert R.; Jackson, Andrew E.; Swart, William W.; Barth, Timothy S.

1994-01-01

Successful ground processing at KSC requires that flight hardware and ground support equipment conform to specifications at tens of thousands of checkpoints. Knowledge of conformance is an essential requirement for launch. That knowledge of conformance at every requisite point does not, however, enable identification of past problems with equipment, or potential problem areas. This paper describes how the introduction of Statistical Process Control and Process Capability Analysis identification procedures into existing shuttle processing procedures can enable identification of potential problem areas and candidates for improvements to increase processing performance measures. Results of a case study describing application of the analysis procedures to Thermal Protection System processing are used to illustrate the benefits of the approaches described in the paper.

Input-output identification of controlled discrete manufacturing systems

NASA Astrophysics Data System (ADS)

Estrada-Vargas, Ana Paula; López-Mellado, Ernesto; Lesage, Jean-Jacques

2014-03-01

The automated construction of discrete event models from observations of external system's behaviour is addressed. This problem, often referred to as system identification, allows obtaining models of ill-known (or even unknown) systems. In this article, an identification method for discrete event systems (DESs) controlled by a programmable logic controller is presented. The method allows processing a large quantity of observed long sequences of input/output signals generated by the controller and yields an interpreted Petri net model describing the closed-loop behaviour of the automated DESs. The proposed technique allows the identification of actual complex systems because it is sufficiently efficient and well adapted to cope with both the technological characteristics of industrial controllers and data collection requirements. Based on polynomial-time algorithms, the method is implemented as an efficient software tool which constructs and draws the model automatically; an overview of this tool is given through a case study dealing with an automated manufacturing system.

Methods for optimizing solutions when considering group arguments by team of experts

NASA Astrophysics Data System (ADS)

Chernyi, Sergei; Budnik, Vlad

2017-11-01

The article is devoted to methods of expert evaluation. The technology of expert evaluation is presented from the standpoint of precedent structures. In this paper, an aspect of the mathematical basis for constructing a component of decision analysis is considered. In fact, this approach leaves out any identification of their knowledge and skills of simulating organizational and manufacturing situations and taking efficient managerial decisions; it doesn't enable any identification and assessment of their knowledge on the basis of multi-informational and least loss-making methods and information technologies. Hence the problem is to research and develop a methodology for systemic identification of professional problem-focused knowledge acquired by employees operating adaptive automated systems of training management (AASTM operators), which shall also further the theory and practice of the intelligence-related aspects thereof.

A Novel Identification Methodology for the Coordinate Relationship between a 3D Vision System and a Legged Robot

PubMed Central

Chai, Xun; Gao, Feng; Pan, Yang; Qi, Chenkun; Xu, Yilin

2015-01-01

Coordinate identification between vision systems and robots is quite a challenging issue in the field of intelligent robotic applications, involving steps such as perceiving the immediate environment, building the terrain map and planning the locomotion automatically. It is now well established that current identification methods have non-negligible limitations such as a difficult feature matching, the requirement of external tools and the intervention of multiple people. In this paper, we propose a novel methodology to identify the geometric parameters of 3D vision systems mounted on robots without involving other people or additional equipment. In particular, our method focuses on legged robots which have complex body structures and excellent locomotion ability compared to their wheeled/tracked counterparts. The parameters can be identified only by moving robots on a relatively flat ground. Concretely, an estimation approach is provided to calculate the ground plane. In addition, the relationship between the robot and the ground is modeled. The parameters are obtained by formulating the identification problem as an optimization problem. The methodology is integrated on a legged robot called “Octopus”, which can traverse through rough terrains with high stability after obtaining the identification parameters of its mounted vision system using the proposed method. Diverse experiments in different environments demonstrate our novel method is accurate and robust. PMID:25912350

Criteria for opiate identification using liquid chromatography linked to tandem mass spectrometry: problems in routine practice.

PubMed

Fox, Elizabeth J; Twigger, Shirley; Allen, Keith R

2009-01-01

Liquid chromatography linked to tandem mass spectrometry (LC/MS/MS) is being increasingly used for drug confirmation. At present, no official criteria exist for drug identification using this technique although the European Union (EU) criteria for compound identification have been adopted. These criteria are evaluated with respect to opiate confirmation by LC/MS/MS and problems highlighted. Urine samples screened positive for opiates by immunoassay were subjected to confirmation by LC/MS/MS using multiple reaction monitoring (MRM) and two separate buffer systems of pH 6.8 and 8.0, respectively. The EU criteria for compound identification were applied for confirmation of morphine, 6-monoacetylmorphine (6MAM), codeine and dihydrocodeine (DHC). Using the pH 6.8 buffer, confirmation could be achieved for 84%, 94%, 96% and 95%, respectively, for samples demonstrating MRM chromatographic peaks at retention times for morphine, 6MAM, codeine and DHC. Failure to meet the EU criteria was mainly attributed to low signal-to-noise (S:N) ratios or excessively high drug concentrations. Isobaric interferences and poor chromatography were also contributing factors. The identification of morphine was considerably improved with chromatography at pH 8.0 owing to resolution of interferences. Oxycodone metabolites were a potential problem for the identification of DHC. Isobaric interferences can pose a problem with drug identification using LC/MS/MS. Optimizing chromatographic conditions is important to overcome these interferences. Consideration needs to be given to investigating drug metabolites as well as parent drugs in method development.

Estimation on nonlinear damping in second order distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1989-01-01

An approximation and convergence theory for the identification of nonlinear damping in abstract wave equations is developed. It is assumed that the unknown dissipation mechanism to be identified can be described by a maximal monotone operator acting on the generalized velocity. The stiffness is assumed to be linear and symmetric. Functional analytic techniques are used to establish that solutions to a sequence of finite dimensional (Galerkin) approximating identification problems in some sense approximate a solution to the original infinite dimensional inverse problem.

A constrained robust least squares approach for contaminant release history identification

NASA Astrophysics Data System (ADS)

Sun, Alexander Y.; Painter, Scott L.; Wittmeyer, Gordon W.

2006-04-01

Contaminant source identification is an important type of inverse problem in groundwater modeling and is subject to both data and model uncertainty. Model uncertainty was rarely considered in the previous studies. In this work, a robust framework for solving contaminant source recovery problems is introduced. The contaminant source identification problem is first cast into one of solving uncertain linear equations, where the response matrix is constructed using a superposition technique. The formulation presented here is general and is applicable to any porous media flow and transport solvers. The robust least squares (RLS) estimator, which originated in the field of robust identification, directly accounts for errors arising from model uncertainty and has been shown to significantly reduce the sensitivity of the optimal solution to perturbations in model and data. In this work, a new variant of RLS, the constrained robust least squares (CRLS), is formulated for solving uncertain linear equations. CRLS allows for additional constraints, such as nonnegativity, to be imposed. The performance of CRLS is demonstrated through one- and two-dimensional test problems. When the system is ill-conditioned and uncertain, it is found that CRLS gave much better performance than its classical counterpart, the nonnegative least squares. The source identification framework developed in this work thus constitutes a reliable tool for recovering source release histories in real applications.

Restructurable Controls

NASA Technical Reports Server (NTRS)

Montoya, R. J. (Compiler); Howell, W. E. (Compiler); Bundick, W. T. (Compiler); Ostroff, A. J. (Compiler); Hueschen, R. M. (Compiler); Belcastro, C. M. (Compiler)

1983-01-01

Restructurable control system theory, robust reconfiguration for high reliability and survivability for advanced aircraft, restructurable controls problem definition and research, experimentation, system identification methods applied to aircraft, a self-repairing digital flight control system, and state-of-the-art theory application are addressed.

A knowledge-based, concept-oriented view generation system for clinical data.

PubMed

Zeng, Q; Cimino, J J

2001-04-01

Information overload is a well-known problem for clinicians who must review large amounts of data in patient records. Concept-oriented views, which organize patient data around clinical concepts such as diagnostic strategies and therapeutic goals, may offer a solution to the problem of information overload. However, although concept-oriented views are desirable, they are difficult to create and maintain. We have developed a general-purpose, knowledge-based approach to the generation of concept-oriented views and have developed a system to test our approach. The system creates concept-oriented views through automated identification of relevant patient data. The knowledge in the system is represented by both a semantic network and rules. The key relevant data identification function is accomplished by a rule-based traversal of the semantic network. This paper focuses on the design and implementation of the system; an evaluation of the system is reported separately.

Electronic Performance Support Systems: Comparison of Types of Integration Levels on Performance Outcomes

ERIC Educational Resources Information Center

Phillips, Sharon A.

2013-01-01

Selecting appropriate performance improvement interventions is a critical component of a comprehensive model of performance improvement. Intervention selection is an interconnected process involving analysis of an organization's environment, definition of the performance problem, and identification of a performance gap and identification of causal…

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M.; Peterson, Gilbert L.; Agaian, Sos S.

2007-04-01

Images and data files provide an excellent opportunity for concealing illegal or clandestine material. Currently, there are over 250 different tools which embed data into an image without causing noticeable changes to the image. From a forensics perspective, when a system is confiscated or an image of a system is generated the investigator needs a tool that can scan and accurately identify files suspected of containing malicious information. The identification process is termed the steganalysis problem which focuses on both blind identification, in which only normal images are available for training, and multi-class identification, in which both the clean and stego images at several embedding rates are available for training. In this paper an investigation of a clustering and classification technique (Expectation Maximization with mixture models) is used to determine if a digital image contains hidden information. The steganalysis problem is for both anomaly detection and multi-class detection. The various clusters represent clean images and stego images with between 1% and 10% embedding percentage. Based on the results it is concluded that the EM classification technique is highly suitable for both blind detection and the multi-class problem.

Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.

PubMed

Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping

2018-01-01

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.

Expert system prototype developments for NASA-KSC business and engineering applications

NASA Technical Reports Server (NTRS)

Ragusa, James M.; Gonzalez, Avelino J.

1988-01-01

Prototype expert systems developed for a variety of NASA projects in the business/management and engineering domains are discussed. Business-related problems addressed include an assistant for simulating launch vehicle processing, a plan advisor for the acquisition of automated data processing equipment, and an expert system for the identification of customer requirements. Engineering problems treated include an expert system for detecting potential ignition sources in LOX and gaseous-oxygen transportation systems and an expert system for hazardous-gas detection.

Comparison of two matrix-assisted laser desorption ionization-time of flight mass spectrometry methods with conventional phenotypic identification for routine identification of bacteria to the species level.

PubMed

Cherkaoui, Abdessalam; Hibbs, Jonathan; Emonet, Stéphane; Tangomo, Manuela; Girard, Myriam; Francois, Patrice; Schrenzel, Jacques

2010-04-01

Bacterial identification relies primarily on culture-based methodologies requiring 24 h for isolation and an additional 24 to 48 h for species identification. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is an emerging technology newly applied to the problem of bacterial species identification. We evaluated two MALDI-TOF MS systems with 720 consecutively isolated bacterial colonies under routine clinical laboratory conditions. Isolates were analyzed in parallel on both devices, using the manufacturers' default recommendations. We compared MS with conventional biochemical test system identifications. Discordant results were resolved with "gold standard" 16S rRNA gene sequencing. The first MS system (Bruker) gave high-confidence identifications for 680 isolates, of which 674 (99.1%) were correct; the second MS system (Shimadzu) gave high-confidence identifications for 639 isolates, of which 635 (99.4%) were correct. Had MS been used for initial testing and biochemical identification used only in the absence of high-confidence MS identifications, the laboratory would have saved approximately US$5 per isolate in marginal costs and reduced average turnaround time by more than an 8-h shift, with no loss in accuracy. Our data suggest that implementation of MS as a first test strategy for one-step species identification would improve timeliness and reduce isolate identification costs in clinical bacteriology laboratories now.

Approximation methods for inverse problems involving the vibration of beams with tip bodies

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1984-01-01

Two cubic spline based approximation schemes for the estimation of structural parameters associated with the transverse vibration of flexible beams with tip appendages are outlined. The identification problem is formulated as a least squares fit to data subject to the system dynamics which are given by a hybrid system of coupled ordinary and partial differential equations. The first approximation scheme is based upon an abstract semigroup formulation of the state equation while a weak/variational form is the basis for the second. Cubic spline based subspaces together with a Rayleigh-Ritz-Galerkin approach were used to construct sequences of easily solved finite dimensional approximating identification problems. Convergence results are briefly discussed and a numerical example demonstrating the feasibility of the schemes and exhibiting their relative performance for purposes of comparison is provided.

Finite-time master-slave synchronization and parameter identification for uncertain Lurie systems.

PubMed

Wang, Tianbo; Zhao, Shouwei; Zhou, Wuneng; Yu, Weiqin

2014-07-01

This paper investigates the finite-time master-slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master-slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Music Identification System Using MPEG-7 Audio Signature Descriptors

PubMed Central

You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

2013-01-01

This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

Pole-zero form fractional model identification in frequency domain

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

Mansouri, R.; Djamah, T.; Djennoune, S.

2009-03-05

This paper deals with system identification in the frequency domain using non integer order models given in the pole-zero form. The usual identification techniques cannot be used in this case because of the non integer orders of differentiation which makes the problem strongly nonlinear. A general identification method based on Levenberg-Marquardt algorithm is developed and allows to estimate the (2n+2m+1) parameters of the model. Its application to identify the ''skin effect'' of a squirrel cage induction machine modeling is then presented.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Performance metrics for the evaluation of hyperspectral chemical identification systems

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

User Identification and Tracking in an Educational Web Environment.

ERIC Educational Resources Information Center

Marzo-Lazaro, J. L.; Verdu-Carbo, T.; Fabregat-Gesa, R.

This paper describes a solution to the user identification and tracking problem within an educational World Wide Web environment. The paper begins with an overview of the Teaching Support System project at the University of Girona (Spain); the main objective of the project is to create an integrated set of tools for teachers to use to create and…

BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

PubMed

Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

2013-01-01

De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents. We devised a novel stepwise hybrid approach designed to improve the current strategies used for text de-identification. The proposed system is based on a previous study on the best de-identification methods for VHA documents. This best-of-breed automated clinical text de-identification system (aka BoB) tackles the problem as two separate tasks: (1) maximize patient confidentiality by redacting as much protected health information (PHI) as possible; and (2) leave de-identified documents in a usable state preserving as much clinical information as possible. We evaluated BoB with a manually annotated corpus of a variety of VHA clinical notes, as well as with the 2006 i2b2 de-identification challenge corpus. We present evaluations at the instance- and token-level, with detailed results for BoB's main components. Moreover, an existing text de-identification system was also included in our evaluation. BoB's design efficiently takes advantage of the methods implemented in its pipeline, resulting in high sensitivity values (especially for sensitive PHI categories) and a limited number of false positives. Our system successfully addressed VHA clinical document de-identification, and its hybrid stepwise design demonstrates robustness and efficiency, prioritizing patient confidentiality while leaving most clinical information intact.

Computational methods for the identification of spatially varying stiffness and damping in beams

NASA Technical Reports Server (NTRS)

Banks, H. T.; Rosen, I. G.

1986-01-01

A numerical approximation scheme for the estimation of functional parameters in Euler-Bernoulli models for the transverse vibration of flexible beams with tip bodies is developed. The method permits the identification of spatially varying flexural stiffness and Voigt-Kelvin viscoelastic damping coefficients which appear in the hybrid system of ordinary and partial differential equations and boundary conditions describing the dynamics of such structures. An inverse problem is formulated as a least squares fit to data subject to constraints in the form of a vector system of abstract first order evolution equations. Spline-based finite element approximations are used to finite dimensionalize the problem. Theoretical convergence results are given and numerical studies carried out on both conventional (serial) and vector computers are discussed.

Identity method for particle number fluctuations and correlations

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

Gorenstein, M. I.

An incomplete particle identification distorts the observed event-by-event fluctuations of the hadron chemical composition in nucleus-nucleus collisions. A new experimental technique called the identity method was recently proposed. It eliminated the misidentification problem for one specific combination of the second moments in a system of two hadron species. In the present paper, this method is extended to calculate all the second moments in a system with an arbitrary number of hadron species. Special linear combinations of the second moments are introduced. These combinations are presented in terms of single-particle variables and can be found experimentally from the event-by-event averaging. Themore » mathematical problem is then reduced to solving a system of linear equations. The effect of incomplete particle identification is fully eliminated from the final results.« less

Tools for Protecting the Privacy of Specific Individuals in Video

NASA Astrophysics Data System (ADS)

Chen, Datong; Chang, Yi; Yan, Rong; Yang, Jie

2007-12-01

This paper presents a system for protecting the privacy of specific individuals in video recordings. We address the following two problems: automatic people identification with limited labeled data, and human body obscuring with preserved structure and motion information. In order to address the first problem, we propose a new discriminative learning algorithm to improve people identification accuracy using limited training data labeled from the original video and imperfect pairwise constraints labeled from face obscured video data. We employ a robust face detection and tracking algorithm to obscure human faces in the video. Our experiments in a nursing home environment show that the system can obtain a high accuracy of people identification using limited labeled data and noisy pairwise constraints. The study result indicates that human subjects can perform reasonably well in labeling pairwise constraints with the face masked data. For the second problem, we propose a novel method of body obscuring, which removes the appearance information of the people while preserving rich structure and motion information. The proposed approach provides a way to minimize the risk of exposing the identities of the protected people while maximizing the use of the captured data for activity/behavior analysis.

Adaptive infinite impulse response system identification using modified-interior search algorithm with Lèvy flight.

PubMed

Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva

2017-03-01

In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Dental x-ray image segmentation

NASA Astrophysics Data System (ADS)

Said, Eyad; Fahmy, Gamal F.; Nassar, Diaa; Ammar, Hany

2004-08-01

Law enforcement agencies have been exploiting biometric identifiers for decades as key tools in forensic identification. With the evolution in information technology and the huge volume of cases that need to be investigated by forensic specialists, it has become important to automate forensic identification systems. While, ante mortem (AM) identification, that is identification prior to death, is usually possible through comparison of many biometric identifiers, postmortem (PM) identification, that is identification after death, is impossible using behavioral biometrics (e.g. speech, gait). Moreover, under severe circumstances, such as those encountered in mass disasters (e.g. airplane crashers) or if identification is being attempted more than a couple of weeks postmortem, under such circumstances, most physiological biometrics may not be employed for identification, because of the decay of soft tissues of the body to unidentifiable states. Therefore, a postmortem biometric identifier has to resist the early decay that affects body tissues. Because of their survivability and diversity, the best candidates for postmortem biometric identification are the dental features. In this paper we present an over view about an automated dental identification system for Missing and Unidentified Persons. This dental identification system can be used by both law enforcement and security agencies in both forensic and biometric identification. We will also present techniques for dental segmentation of X-ray images. These techniques address the problem of identifying each individual tooth and how the contours of each tooth are extracted.

Educational Environment Risks: Problems of Identification and Classification

ERIC Educational Resources Information Center

Kayumova, Leysan R.; Zakirova, Venera G.

2016-01-01

The relevance of the research problem is determined by the multidimensionality of educational environment, that is the system of business and interpersonal relationships of educational process subjects. The maintenance of these relations defines quality and nature of risks for teachers and their pupils. The article aims to identify and justify the…

Transportation and the Mentally Retarded.

ERIC Educational Resources Information Center

President's Committee on Mental Retardation, Washington, DC.

Reported were the results of a contract that involved identification, description, and categorization of the nature of transportation problems for the mentally retarded by means of analysis of existing studies, two surveys, and an inventory of specialized programs and systems operating in the United States. One major problem was found to be…

An Intelligent Tutoring System for Antibody Identification

PubMed Central

Smith, Philip J.; Miller, Thomas E.; Fraser, Jane M.

1990-01-01

Empirical studies of medical technology students indicate that there is considerable need for additional skill development in performing tasks such as antibody identification. While this need is currently met by on-the-job training after employment, computer-based tutoring systems offer an alternative or supplemental problem-based learning environment that could be more cost effective. We have developed a prototype for such a tutoring system as part of a project to develop educational tools for the field of transfusion medicine. This system provides a microworld in which students can explore and solve cases, receiving assistance and tutoring from the computer as needed.

Wireless monitoring of the biological object state at microwave frequencies: A review

NASA Astrophysics Data System (ADS)

Vendik, I. B.; Vendik, O. G.; Kozlov, D. S.; Munina, I. V.; Pleskachev, V. V.; Rusakov, A. S.; Tural'chuk, P. A.

2016-01-01

Radio-frequency identification systems used for the remote diagnostics of diseases and contactless monitoring and assessment of human health are reviewed. The propagation of electromagnetic waves inside a biological medium and along interfaces between different media, as well as the problem of telemetry data acquisition from implanted systems or system on the human body surface using wireless sensors, is considered. Emphasis is on radio-frequency identification systems that use far-field electromagnetic radiation, since they are necessary in emergency situations to find injured people in hard-to-reach places and assess the state of emergency response workers.

The aviation safety reporting system

NASA Technical Reports Server (NTRS)

Reynard, W. D.

1984-01-01

The aviation safety reporting system, an accident reporting system, is presented. The system identifies deficiencies and discrepancies and the data it provides are used for long term identification of problems. Data for planning and policy making are provided. The system offers training in safety education to pilots. Data and information are drawn from the available data bases.

A Systems Analysis Role Play Case: We Sell Stuff, Inc.

ERIC Educational Resources Information Center

Mitri, Michel; Cole, Carey

2007-01-01

Most systems development projects incorporate some sort of life cycle approach in their development. Whether the development methodology involves a traditional life cycle, prototyping, rapid application development, or some other approach, the first step usually involves a system investigation, which includes problem identification, feasibility…

Analysis and application of minimum variance discrete time system identification

NASA Technical Reports Server (NTRS)

Kaufman, H.; Kotob, S.

1975-01-01

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1993-01-01

This final technical report covers a three and one-half year period preceding February 28, 1993 during which support was provided under NASA Grant NAG-1-1065. Following a general description of the system identification problem and a brief survey of methods to attack it, the basic ideas behind the approach taken in this research effort are presented. The results obtained are described with reference to the published work, including the five semiannual progress reports previously submitted and two interim technical reports.

Estimation and identification study for flexible vehicles

NASA Technical Reports Server (NTRS)

Jazwinski, A. H.; Englar, T. S., Jr.

1973-01-01

Techniques are studied for the estimation of rigid body and bending states and the identification of model parameters associated with the single-axis attitude dynamics of a flexible vehicle. This problem is highly nonlinear but completely observable provided sufficient attitude and attitude rate data is available and provided all system bending modes are excited in the observation interval. A sequential estimator tracks the system states in the presence of model parameter errors. A batch estimator identifies all model parameters with high accuracy.

CTPP handbook : an instructional guide to the 1990 census transportation planning package

DOT National Transportation Integrated Search

1999-06-01

An analysis effort was undertaken to illustrate the advantages of a geographic information system (GIS)-based crash analysis system. The problem selected was the identification and analysis of high-truck-crash locations, both along designated truck c...

Subspace algorithms for identifying separable-in-denominator 2D systems with deterministic-stochastic inputs

NASA Astrophysics Data System (ADS)

Ramos, José A.; Mercère, Guillaume

2016-12-01

In this paper, we present an algorithm for identifying two-dimensional (2D) causal, recursive and separable-in-denominator (CRSD) state-space models in the Roesser form with deterministic-stochastic inputs. The algorithm implements the N4SID, PO-MOESP and CCA methods, which are well known in the literature on 1D system identification, but here we do so for the 2D CRSD Roesser model. The algorithm solves the 2D system identification problem by maintaining the constraint structure imposed by the problem (i.e. Toeplitz and Hankel) and computes the horizontal and vertical system orders, system parameter matrices and covariance matrices of a 2D CRSD Roesser model. From a computational point of view, the algorithm has been presented in a unified framework, where the user can select which of the three methods to use. Furthermore, the identification task is divided into three main parts: (1) computing the deterministic horizontal model parameters, (2) computing the deterministic vertical model parameters and (3) computing the stochastic components. Specific attention has been paid to the computation of a stabilised Kalman gain matrix and a positive real solution when required. The efficiency and robustness of the unified algorithm have been demonstrated via a thorough simulation example.

Enriched Imperialist Competitive Algorithm for system identification of magneto-rheological dampers

NASA Astrophysics Data System (ADS)

Talatahari, Siamak; Rahbari, Nima Mohajer

2015-10-01

In the current research, the imperialist competitive algorithm is dramatically enhanced and a new optimization method dubbed as Enriched Imperialist Competitive Algorithm (EICA) is effectively introduced to deal with high non-linear optimization problems. To conduct a close examination of its functionality and efficacy, the proposed metaheuristic optimization approach is actively employed to sort out the parameter identification of two different types of hysteretic Bouc-Wen models which are simulating the non-linear behavior of MR dampers. Two types of experimental data are used for the optimization problems to minutely examine the robustness of the proposed EICA. The obtained results self-evidently demonstrate the high adaptability of EICA to suitably get to the bottom of such non-linear and hysteretic problems.

Teaching Case: A Systems Analysis Role-Play Exercise and Assignment

ERIC Educational Resources Information Center

Mitri, Michel; Cole, Carey; Atkins, Laura

2017-01-01

This paper presents a role-play exercise and assignment that provides an active learning experience related to the system investigation phase of an SDLC. Whether using waterfall or agile approaches, the first SDLC step usually involves system investigation activities, including problem identification, feasibility study, cost-benefit analysis, and…

Managing Risk on the Final Frontier

NASA Technical Reports Server (NTRS)

Lengyel, David M.; Newman, J. S.

2009-01-01

The National Aeronautics and Space Administration (NASA). Exploration Systems Mission Directorate (ESMD) has combined the Continuous Risk Management (CRM) discipline with innovative knowledge management (KM) practices to more effectively enable the accomplishment of work. CRM enables proactive problem identification and problem solving in the complex world of rocket science. while KM is used to improve this process.

The Quality Control of Data in a Clinical Database System—The Patient Identification Problem *

PubMed Central

Lai, J. Chi-Sang; Covvey, H.D.; Sevcik, K.C.; Wigle, E.D.

1981-01-01

Ensuring the accuracy of patient identification and the linkage of records with the appropriate patient owner is the first level of quality control of data in a clinical database system. Without a unique patient identifier, the fact that patient identity may be recorded at different places and times means that multiple identities may be associated with a given patient and new records associated with any of these identities. Even when a unique patient identifier is utilized, errors introduced in the data handling process can result in the same problems. The outcome is that the retrieval request for a given record may fail, or an erroneously identified record may be retrieved. We have studied each of the ways this fundamental problem occurs and propose a solution based on record linkage techniques to detect errors of this type. Specifically, we propose a patient identification scheme for the situation where no unique health identifier is available and detail a method to find patient records with erroneous identifiers.

Identification and Support of Outstanding Astronomy Students

NASA Astrophysics Data System (ADS)

Stoev, A. D.; Bozhurova, E. S.

2006-08-01

The aims, organizational plan and syllabus of a specialized Astronomy School with a subject of training students for participation in the International Astronomy Olympiad, are presented. Thematic frame includes basic educational activities during the preparation and self-preparation of the students and their participation in astronomical Olympiads. A model of identification and selection of outstanding students for astronomical Olympiads has been developed. Examples of didactic systems of problems for development of mathematical, physical and astronomical skills are shown. The programme ends with individual training for solving problems on astronomy and astrophysics. Possibilities, which the characteristic, non-standard astronomical problems give for stimulating the creative and original thinking, are specified. Basic psychological condition for development of the students' creative potential - transformation of the cognitive content in emotional one - is demonstrated. The programme of identification and support of outstanding students on astronomy is realized in collaboration with The Ministry of Education and Science, Public Astronomical Observatories and Planetaria, Institute of Astronomy - Bulgarian Academy of Sciences, and The Union of Astronomers in Bulgaria.

Classification of cancerous cells based on the one-class problem approach

NASA Astrophysics Data System (ADS)

Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

1996-03-01

One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

Study of systems and techniques for data base management

NASA Technical Reports Server (NTRS)

1976-01-01

Data management areas were studied to identify pertinent problems and issues that will affect future NASA data users in terms of performance and cost. Specific topics discussed include the identifications of potential NASA data users other than those normally discussed, consideration affecting the clustering of minicomputers, low cost computer system for information retrieval and analysis, the testing of minicomputer based data base management systems, ongoing work related to the use of dedicated systems for data base management, and the problems of data interchange among a community of NASA data users.

Problem identification for Virginia's highway safety plan.

DOT National Transportation Integrated Search

1982-01-01

Problem identification is recognized as an important component of highway safety planning. Under the NHTSA/FHWA concept, problem identification is the first step in program planning and in the development of effective countermeasure programs. The ann...

FORTRAN Automated Code Evaluation System (faces) system documentation, version 2, mod 0. [error detection codes/user manuals (computer programs)

NASA Technical Reports Server (NTRS)

1975-01-01

A system is presented which processes FORTRAN based software systems to surface potential problems before they become execution malfunctions. The system complements the diagnostic capabilities of compilers, loaders, and execution monitors rather than duplicating these functions. Also, it emphasizes frequent sources of FORTRAN problems which require inordinate manual effort to identify. The principle value of the system is extracting small sections of unusual code from the bulk of normal sequences. Code structures likely to cause immediate or future problems are brought to the user's attention. These messages stimulate timely corrective action of solid errors and promote identification of 'tricky' code. Corrective action may require recoding or simply extending software documentation to explain the unusual technique.

Development of adolescents' peer crowd identification in relation to changes in problem behaviors.

PubMed

Doornwaard, Suzan M; Branje, Susan; Meeus, Wim H J; ter Bogt, Tom F M

2012-09-01

This 5-wave longitudinal study, which included 1,313 Dutch adolescents, examined the development of peer crowd identification in relation to changes in problem behaviors. Adolescents from 2 age cohorts annually reported their identification with 7 peer crowds and their levels of internalizing and externalizing problem behaviors. Univariate latent growth curve analyses revealed declines (i.e., "Hip Hoppers" and "Metal Heads") or declines followed by stabilization (i.e., "Nonconformists") in identification with nonconventional crowds and increases (i.e., "Elites" and "Brains") or declines followed by stabilization (i.e., "Normals" and "Jocks") in identification with conventional crowds. Multivariate latent growth curve analyses indicated that stronger and more persistent identifications with nonconventional crowds were generally associated with more problem behaviors throughout adolescence. In contrast, stronger and more persistent identifications with conventional crowds were generally associated with fewer problem behaviors throughout adolescence with the notable exception of Brains, who showed a mixed pattern. Though characterized by fewer externalizing problems, this group did report more anxiety problems. These findings and their implications are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

NASA Astrophysics Data System (ADS)

Marzban, Hamid Reza

2018-05-01

In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

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

NASA Technical Reports Server (NTRS)

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

1971-01-01

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

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Lofberg, Johan; Brenner, Martin J.

2006-01-01

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

On the orthogonalised reverse path method for nonlinear system identification

NASA Astrophysics Data System (ADS)

Muhamad, P.; Sims, N. D.; Worden, K.

2012-09-01

The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general multi-degree-of-freedom (MDOF) system can be solved using the conditioned reverse path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): pp. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach - the orthogonalised reverse path (ORP) method - is illustrated here using data from simulated single-degree-of-freedom (SDOF) and MDOF systems.

Adaptive control of periodic systems

NASA Astrophysics Data System (ADS)

Tian, Zhiling

2009-12-01

Adaptive control is needed to cope with parametric uncertainty in dynamical systems. The adaptive control of LTI systems in both discrete and continuous time has been studied for four decades and the results are currently used widely in many different fields. In recent years, interest has shifted to the adaptive control of time-varying systems. It is known that the adaptive control of arbitrarily rapidly time-varying systems is in general intractable, but systems with periodically time-varying parameters (LTP systems) which have much more structure, are amenable to mathematical analysis. Further, there is also a need for such control in practical problems which have arisen in industry during the past twenty years. This thesis is the first attempt to deal with the adaptive control of LTP systems. Adaptive Control involves estimation of unknown parameters, adjusting the control parameters based on the estimates, and demonstrating that the overall system is stable. System theoretic properties such as stability, controllability, and observability play an important role both in formulating of the problems, as well as in generating solutions for them. For LTI systems, these properties have been studied since 1960s, and algebraic conditions that have to be satisfied to assure these properties are now well established. In the case of LTP systems, these properties can be expressed only in terms of transition matrices that are much more involved than those for LTI systems. Since adaptive control problems can be formulated only when these properties are well understood, it is not surprising that systematic efforts have not been made thus far for formulating and solving adaptive control problems that arise in LTP systems. Even in the case of LTI systems, it is well recognized that problems related to adaptive discrete-time system are not as difficult as those that arise in the continuous-time systems. This is amply evident in the solutions that were derived in the 1980s and 1990s for all the important problems. These differences are even more amplified in the LTP case; some problems in continuous time cannot even be formulated precisely. This thesis consequently focuses primarily on the adaptive identification and control of discrete-time systems, and derives most of the results that currently exist in the literature for LTI systems. Based on these investigations of discrete-time adaptive systems, attempts are made in the thesis to examine their continuous-time counterparts, and discuss the principal difficulties encountered. The dissertation examines critically the system theoretic properties of LTP systems in Chapter 2, and the mathematical framework provided for their analysis by Floquet theory in Chapter 3. Assuming that adaptive identification and control problems can be formulated precisely, a unified method of developing stable adaptive laws using error models is treated in Chapter 4. Chapter 5 presents a detailed study of the adaptation in SISO discrete-time LTP systems, and represents the core of the thesis. The important problems of identification, stabilization, regulation, and tracking of arbitrary signals are investigated, and practically implementable stable adaptive laws are derived. The dissertation concludes with a discussion of continuous-time adaptive control in Chapter 6 and discrete multivariable systems in Chapter 7. Directions for future research are indicated towards the end of the dissertation.

Integrated CAD/CAM: Problems, prognosis, and role of IPAD

NASA Technical Reports Server (NTRS)

Nilson, E. N.

1980-01-01

Major technology problems impede the development and evolution of totally integrated interactive CAD/CAM systems. IPAD is playing an important role in the identification of these problems and is contributing significantly to their solution. It is the purpose of this presentation to examine some of these issues, look at the prognosis of obtaining effective solutions, and point up some of the past and expected contributions of IPAD to this technology.

MIMO system identification using frequency response data

NASA Technical Reports Server (NTRS)

Medina, Enrique A.; Irwin, R. D.; Mitchell, Jerrel R.; Bukley, Angelia P.

1992-01-01

A solution to the problem of obtaining a multi-input, multi-output statespace model of a system from its individual input/output frequency responses is presented. The Residue Identification Algorithm (RID) identifies the system poles from a transfer function model of the determinant of the frequency response data matrix. Next, the residue matrices of the modes are computed guaranteeing that each input/output frequency response is fitted in the least squares sense. Finally, a realization of the system is computed. Results of the application of RID to experimental frequency responses of a large space structure ground test facility are presented and compared to those obtained via the Eigensystem Realization Algorithm.

Identification of control targets in Boolean molecular network models via computational algebra.

PubMed

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

Emotional System for Military Target Identification

DTIC Science & Technology

2009-10-01

algorithm [23], and used it to solve a facial recognition problem. In other works [24,25], we explored the potential of using emotional neural...other application areas, such as security ( facial recognition ) and medical (blood cell identification), can be also efficiently used in military...Application of an emotional neural network to facial recognition . Neural Computing and Applications, 18(4), 309-320. [25] Khashman, A. (2009). Blood cell

Aeroservoelastic Uncertainty Model Identification from Flight Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

2001-01-01

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Parameter estimation in nonlinear distributed systems - Approximation theory and convergence results

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1988-01-01

An abstract approximation framework and convergence theory is described for Galerkin approximations applied to inverse problems involving nonlinear distributed parameter systems. Parameter estimation problems are considered and formulated as the minimization of a least-squares-like performance index over a compact admissible parameter set subject to state constraints given by an inhomogeneous nonlinear distributed system. The theory applies to systems whose dynamics can be described by either time-independent or nonstationary strongly maximal monotonic operators defined on a reflexive Banach space which is densely and continuously embedded in a Hilbert space. It is demonstrated that if readily verifiable conditions on the system's dependence on the unknown parameters are satisfied, and the usual Galerkin approximation assumption holds, then solutions to the approximating problems exist and approximate a solution to the original infinite-dimensional identification problem.

Monitoring Design for Source Identification in Water Distribution Systems

EPA Science Inventory

The design of sensor networks for the purpose of monitoring for contaminants in water distribution systems is currently an active area of research. Much of the effort has been directed at the contamination detection problem and the expression of public health protection objective...

Neural network application to comprehensive engine diagnostics

NASA Technical Reports Server (NTRS)

Marko, Kenneth A.

1994-01-01

We have previously reported on the use of neural networks for detection and identification of faults in complex microprocessor controlled powertrain systems. The data analyzed in those studies consisted of the full spectrum of signals passing between the engine and the real-time microprocessor controller. The specific task of the classification system was to classify system operation as nominal or abnormal and to identify the fault present. The primary concern in earlier work was the identification of faults, in sensors or actuators in the powertrain system as it was exercised over its full operating range. The use of data from a variety of sources, each contributing some potentially useful information to the classification task, is commonly referred to as sensor fusion and typifies the type of problems successfully addressed using neural networks. In this work we explore the application of neural networks to a different diagnostic problem, the diagnosis of faults in newly manufactured engines and the utility of neural networks for process control.

Model and Data Reduction for Control, Identification and Compressed Sensing

NASA Astrophysics Data System (ADS)

Kramer, Boris

This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decomposition, which is demonstrated to produce highly accurate solutions at low rank. The method is parallelizable, easy to implement for practitioners, and is a first step towards a matrix free approach to solve AREs. Numerical examples for n ≥ 106 unknowns are presented. In Chapter 4, we develop a system identification method which is motivated by tangential interpolation. This addresses the challenge of fitting linear time invariant systems to input-output responses of complex dynamics, where the number of inputs and outputs is relatively large. The method reduces the computational burden imposed by a full singular value decomposition, by carefully choosing directions on which to project the impulse response prior to assembly of the Hankel matrix. The identification and model reduction step follows from the eigensystem realization algorithm. We present three numerical examples, a mass spring damper system, a heat transfer problem, and a fluid dynamics system. We obtain error bounds and stability results for this method. Chapter 5 deals with control and observation design for parameter dependent dynamical systems. We address this by using local parametric reduced order models, which can be used online. Data available from simulations of the system at various configurations (parameters, boundary conditions) is used to extract a sparse basis to represent the dynamics (via dynamic mode decomposition). Subsequently, a new, compressed sensing based classification algorithm is developed which incorporates the extracted dynamic information into the sensing basis. We show that this augmented classification basis makes the method more robust to noise, and results in superior identification of the correct parameter. Numerical examples consist of a Navier-Stokes, as well as a Boussinesq flow application.

DOE`s nation-wide system for access control can solve problems for the federal government

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

Callahan, S.; Tomes, D.; Davis, G.

1996-07-01

The U.S. Department of Energy`s (DOE`s) ongoing efforts to improve its physical and personnel security systems while reducing its costs, provide a model for federal government visitor processing. Through the careful use of standardized badges, computer databases, and networks of automated access control systems, the DOE is increasing the security associated with travel throughout the DOE complex, and at the same time, eliminating paperwork, special badging, and visitor delays. The DOE is also improving badge accountability, personnel identification assurance, and access authorization timeliness and accuracy. Like the federal government, the DOE has dozens of geographically dispersed locations run by manymore » different contractors operating a wide range of security systems. The DOE has overcome these obstacles by providing data format standards, a complex-wide virtual network for security, the adoption of a standard high security system, and an open-systems-compatible link for any automated access control system. If the location`s level of security requires it, positive visitor identification is accomplished by personal identification number (PIN) and/or by biometrics. At sites with automated access control systems, this positive identification is integrated into the portals.« less

Modern control concepts in hydrology. [parameter identification in adaptive stochastic control approach

NASA Technical Reports Server (NTRS)

Duong, N.; Winn, C. B.; Johnson, G. R.

1975-01-01

Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Computational system identification of continuous-time nonlinear systems using approximate Bayesian computation

NASA Astrophysics Data System (ADS)

Krishnanathan, Kirubhakaran; Anderson, Sean R.; Billings, Stephen A.; Kadirkamanathan, Visakan

2016-11-01

In this paper, we derive a system identification framework for continuous-time nonlinear systems, for the first time using a simulation-focused computational Bayesian approach. Simulation approaches to nonlinear system identification have been shown to outperform regression methods under certain conditions, such as non-persistently exciting inputs and fast-sampling. We use the approximate Bayesian computation (ABC) algorithm to perform simulation-based inference of model parameters. The framework has the following main advantages: (1) parameter distributions are intrinsically generated, giving the user a clear description of uncertainty, (2) the simulation approach avoids the difficult problem of estimating signal derivatives as is common with other continuous-time methods, and (3) as noted above, the simulation approach improves identification under conditions of non-persistently exciting inputs and fast-sampling. Term selection is performed by judging parameter significance using parameter distributions that are intrinsically generated as part of the ABC procedure. The results from a numerical example demonstrate that the method performs well in noisy scenarios, especially in comparison to competing techniques that rely on signal derivative estimation.

Creating Community Change to Improve Youth Development: The Communities That Care System

ERIC Educational Resources Information Center

Brooke-Weiss, Blaire; Haggerty, Kevin P.; Fagan, Abigail A.; Hawkins, J. David; Cady, Rick

2008-01-01

Advances in prevention science in the past 25 years provide important direction for neighborhood and community efforts to improve the lives of youth. Prevention scientists have applied a public health approach to youth problems such as drug use and delinquency, and have shown that these problems can be prevented. The identification of risk and…

Non-parametric identification of multivariable systems: A local rational modeling approach with application to a vibration isolation benchmark

NASA Astrophysics Data System (ADS)

Voorhoeve, Robbert; van der Maas, Annemiek; Oomen, Tom

2018-05-01

Frequency response function (FRF) identification is often used as a basis for control systems design and as a starting point for subsequent parametric system identification. The aim of this paper is to develop a multiple-input multiple-output (MIMO) local parametric modeling approach for FRF identification of lightly damped mechanical systems with improved speed and accuracy. The proposed method is based on local rational models, which can efficiently handle the lightly-damped resonant dynamics. A key aspect herein is the freedom in the multivariable rational model parametrizations. Several choices for such multivariable rational model parametrizations are proposed and investigated. For systems with many inputs and outputs the required number of model parameters can rapidly increase, adversely affecting the performance of the local modeling approach. Therefore, low-order model structures are investigated. The structure of these low-order parametrizations leads to an undesired directionality in the identification problem. To address this, an iterative local rational modeling algorithm is proposed. As a special case recently developed SISO algorithms are recovered. The proposed approach is successfully demonstrated on simulations and on an active vibration isolation system benchmark, confirming good performance of the method using significantly less parameters compared with alternative approaches.

[Organizational problems of disaster victim identification in mass casualties as exemplified by Tu 154-M and Airbus A310 passenger plane crashes].

PubMed

Volkov, A V; Kolkutin, V V; Klevno, V A; Shkol'nikov, B V; Kornienko, I V

2008-01-01

Managerial experience is described that was gained during the large-scale work on victim identification following mass casualties in the Tu 154-M and Airbus A310 passenger plane crashes. The authors emphasize the necessity to set up a specialized agency of constant readiness meeting modern requirements for the implementation of a system of measures for personality identification. This agency must incorporate relevant departments of the Ministries of Health, Defense, and Emergency Situations as well as investigative authorities and other organizations.

Identification of genes in anonymous DNA sequences. Final report: Report period, 15 April 1993--15 April 1994

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

Fields, C.A.

1994-09-01

This Report concludes the DOE Human Genome Program project, ``Identification of Genes in Anonymous DNA Sequence.`` The central goals of this project have been (1) understanding the problem of identifying genes in anonymous sequences, and (2) development of tools, primarily the automated identification system gm, for identifying genes. The activities supported under the previous award are summarized here to provide a single complete report on the activities supported as part of the project from its inception to its completion.

AGARD Flight Test Techniques Series. Volume 3. Identification of Dynamic Systems - Applications to Aircraft. Part 1. The Output Error Approach

DTIC Science & Technology

1986-12-01

poorly written problem statements. We decline to artificially create difficulties for experimentation. Others have encountered these issues and treated...you lose some of the weaning. The method also does not extend well to nonlinear or time-varying system (sometimes it can be don#. but it creates ...thereby introduced creates problems and solves nothing. For variable-geometry aircraft, some projects establish reference geometry values that change as

A taxonomy of inductive problems.

PubMed

Kemp, Charles; Jern, Alan

2014-02-01

Inductive inferences about objects, features, categories, and relations have been studied for many years, but there are few attempts to chart the range of inductive problems that humans are able to solve. We present a taxonomy of inductive problems that helps to clarify the relationships between familiar inductive problems such as generalization, categorization, and identification, and that introduces new inductive problems for psychological investigation. Our taxonomy is founded on the idea that semantic knowledge is organized into systems of objects, features, categories, and relations, and we attempt to characterize all of the inductive problems that can arise when these systems are partially observed. Recent studies have begun to address some of the new problems in our taxonomy, and future work should aim to develop unified theories of inductive reasoning that explain how people solve all of the problems in the taxonomy.

Study on road sign recognition in LabVIEW

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Asymptotic inference in system identification for the atom maser.

PubMed

Catana, Catalin; van Horssen, Merlijn; Guta, Madalin

2012-11-28

System identification is closely related to control theory and plays an increasing role in quantum engineering. In the quantum set-up, system identification is usually equated to process tomography, i.e. estimating a channel by probing it repeatedly with different input states. However, for quantum dynamical systems such as quantum Markov processes, it is more natural to consider the estimation based on continuous measurements of the output, with a given input that may be stationary. We address this problem using asymptotic statistics tools, for the specific example of estimating the Rabi frequency of an atom maser. We compute the Fisher information of different measurement processes as well as the quantum Fisher information of the atom maser, and establish the local asymptotic normality of these statistical models. The statistical notions can be expressed in terms of spectral properties of certain deformed Markov generators, and the connection to large deviations is briefly discussed.

Measuring the drinking behaviour of individual pigs housed in group using radio frequency identification (RFID).

PubMed

Maselyne, J; Adriaens, I; Huybrechts, T; De Ketelaere, B; Millet, S; Vangeyte, J; Van Nuffel, A; Saeys, W

2016-09-01

Changes in the drinking behaviour of pigs may indicate health, welfare or productivity problems. Automated monitoring and analysis of drinking behaviour could allow problems to be detected, thus improving farm productivity. A high frequency radio frequency identification (HF RFID) system was designed to register the drinking behaviour of individual pigs. HF RFID antennas were placed around four nipple drinkers and connected to a reader via a multiplexer. A total of 55 growing-finishing pigs were fitted with radio frequency identification (RFID) ear tags, one in each ear. RFID-based drinking visits were created from the RFID registrations using a bout criterion and a minimum and maximum duration criterion. The HF RFID system was successfully validated by comparing RFID-based visits with visual observations and flow meter measurements based on visit overlap. Sensitivity was at least 92%, specificity 93%, precision 90% and accuracy 93%. RFID-based drinking duration had a high correlation with observed drinking duration (R 2=0.88) and water usage (R 2=0.71). The number of registrations after applying the visit criteria had an even higher correlation with the same two variables (R 2=0.90 and 0.75, respectively). There was also a correlation between number of RFID visits and number of observed visits (R 2=0.84). The system provides good quality information about the drinking behaviour of individual pigs. As health or other problems affect the pigs' drinking behaviour, analysis of the RFID data could allow problems to be detected and signalled to the farmer. This information can help to improve the productivity and economics of the farm as well as the health and welfare of the pigs.

An approximation theory for nonlinear partial differential equations with applications to identification and control

NASA Technical Reports Server (NTRS)

Banks, H. T.; Kunisch, K.

1982-01-01

Approximation results from linear semigroup theory are used to develop a general framework for convergence of approximation schemes in parameter estimation and optimal control problems for nonlinear partial differential equations. These ideas are used to establish theoretical convergence results for parameter identification using modal (eigenfunction) approximation techniques. Results from numerical investigations of these schemes for both hyperbolic and parabolic systems are given.

Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem

NASA Astrophysics Data System (ADS)

Rustamov, Samir; Mustafayev, Elshan; Clements, Mark A.

2018-04-01

The context analysis of customer requests in a natural language call routing problem is investigated in the paper. One of the most significant problems in natural language call routing is a comprehension of client request. With the aim of finding a solution to this issue, the Hybrid HMM and ANFIS models become a subject to an examination. Combining different types of models (ANFIS and HMM) can prevent misunderstanding by the system for identification of user intention in dialogue system. Based on these models, the hybrid system may be employed in various language and call routing domains due to nonusage of lexical or syntactic analysis in classification process.

The California corridor transportation system: A design summary

NASA Technical Reports Server (NTRS)

1990-01-01

A design group was assembled to find and research criteria relevent to the design of a California Corridor Transportation System. The efforts of this group included defining the problem, conducting a market analysis, formulation of a demand model, identification and evaluation of design drivers, and the systematic development of a solution. The problems of the current system were analyzed and used to determine design drivers, which were divided into the broad categories of cost, convenience, feasibility, environment, safety, and social impact. The relative importance of individual problems was addressed, resulting in a hierarchy of design drivers. Where possible, methods of evaluating the relative merit of proposed systems with respect to each driver were developed. Short takeoff vertical landing aircraft concepts are also discussed for supersonic fighters.

Evolutionary fuzzy modeling human diagnostic decisions.

PubMed

Peña-Reyes, Carlos Andrés

2004-05-01

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.

Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record

NASA Astrophysics Data System (ADS)

Relan, Rishi; Tiels, Koen; Marconato, Anna; Dreesen, Philippe; Schoukens, Johan

2018-05-01

Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper, a methodology to identify a parsimonious discrete-time nonlinear state space model (NLSS) for the nonlinear dynamical system with relatively short data record is proposed. The capability of the NLSS model structure is demonstrated by introducing two different initialisation schemes, one of them using multivariate polynomials. In addition, a method using first-order information of the multivariate polynomials and tensor decomposition is employed to obtain the parsimonious decoupled representation of the set of multivariate real polynomials estimated during the identification of NLSS model. Finally, the experimental verification of the model structure is done on the cascaded water-benchmark identification problem.

Application of dynamic recurrent neural networks in nonlinear system identification

NASA Astrophysics Data System (ADS)

Du, Yun; Wu, Xueli; Sun, Huiqin; Zhang, Suying; Tian, Qiang

2006-11-01

An adaptive identification method of simple dynamic recurrent neural network (SRNN) for nonlinear dynamic systems is presented in this paper. This method based on the theory that by using the inner-states feed-back of dynamic network to describe the nonlinear kinetic characteristics of system can reflect the dynamic characteristics more directly, deduces the recursive prediction error (RPE) learning algorithm of SRNN, and improves the algorithm by studying topological structure on recursion layer without the weight values. The simulation results indicate that this kind of neural network can be used in real-time control, due to its less weight values, simpler learning algorithm, higher identification speed, and higher precision of model. It solves the problems of intricate in training algorithm and slow rate in convergence caused by the complicate topological structure in usual dynamic recurrent neural network.

Nonlinear system identification technique validation

NASA Astrophysics Data System (ADS)

Rudko, M.; Bussgang, J. J.

1982-01-01

This final technical report describes the results obtained by SIGNATRON, Inc. of Lexington MA on Air Force Contract F30602-80-C-0104 for Rome Air Development Center. The objective of this effort is to develop a technique for identifying system response of nonlinear circuits by measurements of output response to known inputs. The report describes results of a study into the system identification technique based on the pencil-of-function method previously explored by Jain (1974) and Ewen (1979). The procedure identified roles of the linear response and is intended as a first step in nonlinear response and is intended as a first step in nonlinear circuit identification. There are serious implementation problems associated with the original approach such as loss of accuracy due to repeated integrations, lack of good measures of accuracy and computational iteration to identify the number of poles.

Recursive inversion of externally defined linear systems

NASA Technical Reports Server (NTRS)

Bach, Ralph E., Jr.; Baram, Yoram

1988-01-01

The approximate inversion of an internally unknown linear system, given by its impulse response sequence, by an inverse system having a finite impulse response, is considered. The recursive least squares procedure is shown to have an exact initialization, based on the triangular Toeplitz structure of the matrix involved. The proposed approach also suggests solutions to the problems of system identification and compensation.

Hot background” of the mobile inelastic neutron scattering system for soil carbon analysis

USDA-ARS?s Scientific Manuscript database

The problem of gamma spectrum peaks identification arises when conducting soil carbon (and other elements) analysis using the mobile inelastic neutron scattering (MINS) system. Some gamma spectrum peaks could be associated with radioisotopes appearing due to neutron activation of both the MINS syste...

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

An Approach for Removing Redundant Data from RFID Data Streams

PubMed Central

Mahdin, Hairulnizam; Abawajy, Jemal

2011-01-01

Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches. PMID:22163730

Identification of dynamic systems, theory and formulation

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1985-01-01

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Summary of research in applied mathematics, numerical analysis, and computer sciences

NASA Technical Reports Server (NTRS)

1986-01-01

The major categories of current ICASE research programs addressed include: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effective numerical methods; computational problems in engineering and physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and computer systems and software, especially vector and parallel computers.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2014-02-06

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems.

PubMed

Ayvaz, M Tamer

2010-09-20

This study proposes a linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. In the proposed model, MODFLOW and MT3DMS packages are used to simulate the flow and transport processes in the groundwater system. These models are then integrated with an optimization model which is based on the heuristic harmony search (HS) algorithm. In the proposed simulation-optimization model, the locations and release histories of the pollution sources are treated as the explicit decision variables and determined through the optimization model. Also, an implicit solution procedure is proposed to determine the optimum number of pollution sources which is an advantage of this model. The performance of the proposed model is evaluated on two hypothetical examples for simple and complex aquifer geometries, measurement error conditions, and different HS solution parameter sets. Identified results indicated that the proposed simulation-optimization model is an effective way and may be used to solve the inverse pollution source identification problems. Copyright (c) 2010 Elsevier B.V. All rights reserved.

A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

PubMed Central

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing. PMID:22919273

A survey and proposed framework on the soft biometrics technique for human identification in intelligent video surveillance system.

PubMed

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.

2015-12-01

The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.

Software Risk Identification for Interplanetary Probes

NASA Technical Reports Server (NTRS)

Dougherty, Robert J.; Papadopoulos, Periklis E.

2005-01-01

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

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Kearney, Robert E.; Galiana, Henrietta L.

2005-01-01

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

Identification of the structure parameters using short-time non-stationary stochastic excitation

NASA Astrophysics Data System (ADS)

Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra

2011-07-01

In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.

A survey on hysteresis modeling, identification and control

NASA Astrophysics Data System (ADS)

Hassani, Vahid; Tjahjowidodo, Tegoeh; Do, Thanh Nho

2014-12-01

The various mathematical models for hysteresis such as Preisach, Krasnosel'skii-Pokrovskii (KP), Prandtl-Ishlinskii (PI), Maxwell-Slip, Bouc-Wen and Duhem are surveyed in terms of their applications in modeling, control and identification of dynamical systems. In the first step, the classical formalisms of the models are presented to the reader, and more broadly, the utilization of the classical models is considered for development of more comprehensive models and appropriate controllers for corresponding systems. In addition, the authors attempt to encourage the reader to follow the existing mathematical models of hysteresis to resolve the open problems.

Recursive inversion of externally defined linear systems by FIR filters

NASA Technical Reports Server (NTRS)

Bach, Ralph E., Jr.; Baram, Yoram

1989-01-01

The approximate inversion of an internally unknown linear system, given by its impulse response sequence, by an inverse system having a finite impulse response, is considered. The recursive least-squares procedure is shown to have an exact initialization, based on the triangular Toeplitz structure of the matrix involved. The proposed approach also suggests solutions to the problem of system identification and compensation.

Linear and nonlinear trending and prediction for AVHRR time series data

NASA Technical Reports Server (NTRS)

Smid, J.; Volf, P.; Slama, M.; Palus, M.

1995-01-01

The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

[Role of medical information processing for quality assurance in obstetrics].

PubMed

Selbmann, H K

1983-06-01

The paradigma of problem-orientated assuring of the professional quality of medical case is a kind of "control loop system" consisting of the following 5 steps: routine observation, identification of the problem, analysis of the problem, translation of problem solutions into daily practice and control as to whether the problem has been solved or eliminated. Medical data processing, which involves documentation, electronic data processing and statistics, can make substantial contributions especially to the steps of observation, identification of the problem, and follow-up control. Perinatal data collection, which has already been introduced in 6 Länder of the Federal Republic of Germany, has supplied ample proof of this. These operations were conducted under the heading "internal clinical assuring of quality with external aid". Those clinics who participated in this programme, were given the necessary aid in self-observation (questionnaires, clinical statistics), and they were also given comparative informative data to help them in identifying the problems (clinical profiles, etc.). It is entirely left to the responsibility of the clinics themselves--voluntary cooperation and guarantee of remaining anonymous being a matter of course -- to draw their own consequences from the collected data and to translate these into clinical everyday practice.

An Experience of CACSD for Networked Control Systems: From Mechatronic Platform Identification to Control Implementation

ERIC Educational Resources Information Center

Losada, Cristina; Espinosa, Felipe; Santos, Carlos; Gálvez, Manuel; Bueno, Emilio J.; Marrón, Marta; Rodríguez, Francisco J.

2016-01-01

Continual advances in information and communication technologies (ICT) are revolutionizing virtual education and bringing new tools on the market that provide virtual solutions to a range of problems. Nevertheless, nonvirtual experimentation using computer-aided control system design tools is still fundamental for future engineers. This paper…

Recursive Inversion By Finite-Impulse-Response Filters

NASA Technical Reports Server (NTRS)

Bach, Ralph E., Jr.; Baram, Yoram

1991-01-01

Recursive approximation gives least-squares best fit to exact response. Algorithm yields finite-impulse-response approximation of unknown single-input/single-output, causal, time-invariant, linear, real system, response of which is sequence of impulses. Applicable to such system-inversion problems as suppression of echoes and identification of target from its scatter response to incident impulse.

A New Aloha Anti-Collision Algorithm Based on CDMA

NASA Astrophysics Data System (ADS)

Bai, Enjian; Feng, Zhu

The tags' collision is a common problem in RFID (radio frequency identification) system. The problem has affected the integrity of the data transmission during the process of communication in the RFID system. Based on analysis of the existing anti-collision algorithm, a novel anti-collision algorithm is presented. The new algorithm combines the group dynamic frame slotted Aloha algorithm with code division multiple access technology. The algorithm can effectively reduce the collision probability between tags. Under the same number of tags, the algorithm is effective in reducing the reader recognition time and improve overall system throughput rate.

Knowledge-Acquisition Tool For Expert System

NASA Technical Reports Server (NTRS)

Disbrow, James D.; Duke, Eugene L.; Regenie, Victoria A.

1988-01-01

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

Correlation techniques to determine model form in robust nonlinear system realization/identification

NASA Technical Reports Server (NTRS)

Stry, Greselda I.; Mook, D. Joseph

1991-01-01

The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature is the ability to identify nonlinear dynamic systems without prior assumption regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.

Remote Sensing and Problems of the Hydrosphere

NASA Technical Reports Server (NTRS)

Goldberg, E. D. (Editor)

1979-01-01

A discussion of freshwater and marine systems is presented including areas of the classification of lakes, identification and quantification of major functional groups of phytoplankton, sources and sinks of biochemical factors, and temporal and regional variability of surface features. Atmospheric processes linked to hydrospheric process through the transfer of matter via aerosols and gases are discussed. Particle fluxes to the aquatic environment and global geochemical problems are examined.

A maximum power point prediction method for group control of photovoltaic water pumping systems based on parameter identification

NASA Astrophysics Data System (ADS)

Chen, B.; Su, J. H.; Guo, L.; Chen, J.

2017-06-01

This paper puts forward a maximum power estimation method based on the photovoltaic array (PVA) model to solve the optimization problems about group control of the PV water pumping systems (PVWPS) at the maximum power point (MPP). This method uses the improved genetic algorithm (GA) for model parameters estimation and identification in view of multi P-V characteristic curves of a PVA model, and then corrects the identification results through least square method. On this basis, the irradiation level and operating temperature under any condition are able to estimate so an accurate PVA model is established and the MPP none-disturbance estimation is achieved. The simulation adopts the proposed GA to determine parameters, and the results verify the accuracy and practicability of the methods.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges

PubMed Central

Villaverde, Alejandro F.; Banga, Julio R.

2014-01-01

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology? PMID:24307566

A Solution of the System of Partial Differential Equations Which Describe the Propagation of Acoustic Pulses in Layered Fluid Media,

DTIC Science & Technology

transformed problem. Then using several changes of integration variables, the inverse transform is obtained by direct identification without recourse to the complex Laplace transform inversion integral. (Author)

Fault Identification Based on Nlpca in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhang, Yagang; Wang, Zengping; Zhang, Jinfang

2012-07-01

The fault is inevitable in any complex systems engineering. Electric power system is essentially a typically nonlinear system. It is also one of the most complex artificial systems in this world. In our researches, based on the real-time measurements of phasor measurement unit, under the influence of white Gaussian noise (suppose the standard deviation is 0.01, and the mean error is 0), we used mainly nonlinear principal component analysis theory (NLPCA) to resolve fault identification problem in complex electrical engineering. The simulation results show that the fault in complex electrical engineering is usually corresponding to the variable with the maximum absolute value coefficient in the first principal component. These researches will have significant theoretical value and engineering practical significance.

Adaptive/learning control of large space structures - System identification techniques. [for multi-configuration flexible spacecraft

NASA Technical Reports Server (NTRS)

Thau, F. E.; Montgomery, R. C.

1980-01-01

Techniques developed for the control of aircraft under changing operating conditions are used to develop a learning control system structure for a multi-configuration, flexible space vehicle. A configuration identification subsystem that is to be used with a learning algorithm and a memory and control process subsystem is developed. Adaptive gain adjustments can be achieved by this learning approach without prestoring of large blocks of parameter data and without dither signal inputs which will be suppressed during operations for which they are not compatible. The Space Shuttle Solar Electric Propulsion (SEP) experiment is used as a sample problem for the testing of adaptive/learning control system algorithms.

Barriers and Facilitators of Responding to Problem Gambling: Perspectives from Australian Mental Health Services.

PubMed

Rodda, S N; Manning, V; Dowling, N A; Lee, S J; Lubman, D I

2018-03-01

Despite high rates of comorbidity between problem gambling and mental health disorders, few studies have examined barriers or facilitators to the implementation of screening for problem gambling in mental health services. This exploratory qualitative study identified key themes associated with screening in mental health services. Semi-structured interviews were undertaken with 30 clinicians and managers from 11 mental health services in Victoria, Australia. Major themes and subthemes were identified using qualitative content analysis. Six themes emerged including competing priorities, importance of routine screening, access to appropriate screening tools, resources, patient responsiveness and workforce development. Barriers to screening included a focus on immediate risk as well as gambling being often considered as a longer-term concern. Clinicians perceived problem gambling as a relatively rare condition, but did acknowledge the need for brief screening. Facilitators to screening were changes to system processes, such as identification of an appropriate brief screening instrument, mandating its use as part of routine screening, as well as funded workforce development activities in the identification and management of problem gambling.

Maximum likelihood identification and optimal input design for identifying aircraft stability and control derivatives

NASA Technical Reports Server (NTRS)

Stepner, D. E.; Mehra, R. K.

1973-01-01

A new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion. It is shown that this new method is capable of processing data from both linear and nonlinear models, both with and without process noise and includes output error and equation error methods as special cases. The first application of this method to flight test data is reported for lateral maneuvers of the HL-10 and M2/F3 lifting bodies, including the extraction of stability and control derivatives in the presence of wind gusts. All the problems encountered in this identification study are discussed. Several different methods (including a priori weighting, parameter fixing and constrained parameter values) for dealing with identifiability and uniqueness problems are introduced and the results given. The method for the design of optimal inputs for identifying the parameters of linear dynamic systems is also given. The criterion used for the optimization is the sensitivity of the system output to the unknown parameters. Several simple examples are first given and then the results of an extensive stability and control dervative identification simulation for a C-8 aircraft are detailed.

Space-based infrared sensors of space target imaging effect analysis

NASA Astrophysics Data System (ADS)

Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang

2018-02-01

Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Nonlinear model updating applied to the IMAC XXXII Round Robin benchmark system

NASA Astrophysics Data System (ADS)

Kurt, Mehmet; Moore, Keegan J.; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2017-05-01

We consider the application of a new nonlinear model updating strategy to a computational benchmark system. The approach relies on analyzing system response time series in the frequency-energy domain by constructing both Hamiltonian and forced and damped frequency-energy plots (FEPs). The system parameters are then characterized and updated by matching the backbone branches of the FEPs with the frequency-energy wavelet transforms of experimental and/or computational time series. The main advantage of this method is that no nonlinearity model is assumed a priori, and the system model is updated solely based on simulation and/or experimental measured time series. By matching the frequency-energy plots of the benchmark system and its reduced-order model, we show that we are able to retrieve the global strongly nonlinear dynamics in the frequency and energy ranges of interest, identify bifurcations, characterize local nonlinearities, and accurately reconstruct time series. We apply the proposed methodology to a benchmark problem, which was posed to the system identification community prior to the IMAC XXXII (2014) and XXXIII (2015) Conferences as a "Round Robin Exercise on Nonlinear System Identification". We show that we are able to identify the parameters of the non-linear element in the problem with a priori knowledge about its position.

Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building

PubMed Central

Min, Kyung-Won; Kim, Junhee; Park, Sung-Ah; Park, Chan-Soo

2013-01-01

This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring. As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. It is noteworthy that application of the proposed methodology is not necessarily confined to the wooden structure exampled in the paper. PMID:24227999

Structural Aspects of System Identification

NASA Technical Reports Server (NTRS)

Glover, Keith

1973-01-01

The problem of identifying linear dynamical systems is studied by considering structural and deterministic properties of linear systems that have an impact on stochastic identification algorithms. In particular considered is parametrization of linear systems so that there is a unique solution and all systems in appropriate class can be represented. It is assumed that a parametrization of system matrices has been established from a priori knowledge of the system, and the question is considered of when the unknown parameters of this system can be identified from input/output observations. It is assumed that the transfer function can be asymptotically identified, and the conditions are derived for the local, global and partial identifiability of the parametrization. Then it is shown that, with the right formulation, identifiability in the presence of feedback can be treated in the same way. Similarly the identifiability of parametrizations of systems driven by unobserved white noise is considered using the results from the theory of spectral factorization.

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Hammer, J. M.; Morris, N. M.; Knaeuper, A. E.; Brown, E. N.; Lewis, C. M.; Yoon, W. C.

1984-01-01

Two project areas were pursued: the intelligent cockpit and human problem solving. The first area involves an investigation of the use of advanced software engineering methods to aid aircraft crews in procedure selection and execution. The second area is focused on human problem solving in dynamic environments, particulary in terms of identification of rule-based models land alternative approaches to training and aiding. Progress in each area is discussed.

Current algorithmic solutions for peptide-based proteomics data generation and identification.

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

Peptide-based proteomic data sets are ever increasing in size and complexity. These data sets provide computational challenges when attempting to quickly analyze spectra and obtain correct protein identifications. Database search and de novo algorithms must consider high-resolution MS/MS spectra and alternative fragmentation methods. Protein inference is a tricky problem when analyzing large data sets of degenerate peptide identifications. Combining multiple algorithms for improved peptide identification puts significant strain on computational systems when investigating large data sets. This review highlights some of the recent developments in peptide and protein identification algorithms for analyzing shotgun mass spectrometry data when encountering the aforementioned hurdles. Also explored are the roles that analytical pipelines, public spectral libraries, and cloud computing play in the evolution of peptide-based proteomics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Review: Optimization methods for groundwater modeling and management

NASA Astrophysics Data System (ADS)

Yeh, William W.-G.

2015-09-01

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

External Stakeholders of Higher Education Institutions in Poland: Their Identification and Significance

ERIC Educational Resources Information Center

Piotrowska-Piatek, Agnieszka

2017-01-01

In the context of the ongoing changes in the management systems of higher education, the issue of higher education institutions' (HEIs) relationships with external stakeholders are of key importance. This article discusses this problem from the perspective of Polish higher education system. The aim of it is to answer the following questions: (1)…

The Characteristics of the Systems of Continuing Pedagogical Education in Great Britain, Canada and the USA

ERIC Educational Resources Information Center

Mukan, Nataliya; Myskiv, Iryna; Kravets, Svitlana

2016-01-01

In the article the systems of continuing pedagogical education in Great Britain, Canada and the USA have been characterized. The main objectives are defined as the theoretical analysis of scientific-pedagogical literature, which highlights different aspects of the problem under research; identification of the common and distinctive features of the…

Identification and Intervention for Students Who Are Visually Impaired and Who Have Autism Spectrum Disorders

ERIC Educational Resources Information Center

Li, Alicia

2009-01-01

At least 60% of children with disabilities have multiple disabilities including visual impairments (VI). Because the visual system is neurologically based, any problems of the neurological system will also likely affect vision. The estimated number of students with VI and additional disabilities has increased significantly over the years. Since…

The Effect of a Course Management System (CMS)-Supported Strategy Instruction on EFL Reading Comprehension and Strategy Use

ERIC Educational Resources Information Center

Tsai, Yea-Ru; Talley, Paul C.

2014-01-01

This paper reports on the effect of a Moodle-supported strategy instruction on both reading comprehension and strategy use among EFL (English as a Foreign Language) students. Specific reading strategy training was first integrated into a Moodle system, which included reading exercises on problem identification, monitoring comprehension,…

Pediatrician identification of child behavior problems: the roles of parenting factors and cross-practice differences.

PubMed

Dempster, Robert M; Wildman, Beth G; Langkamp, Diane; Duby, John C

2012-06-01

While most primary care pediatricians acknowledge the importance of identifying child behavior problems, fewer than 2% of children with a diagnosable psychological disorder are referred for mental health care in any given year. The present study examined the potential role of parental characteristics (parental affect, parenting style, and parenting self-efficacy) in pediatrician identification of child behavior problems, and determined whether these relationships differed across practices. Parents of 831 children between 2 and 16 years completed questionnaires regarding demographic information, their child's behavior, their affect, their parenting style, and their parenting self-efficacy. Pediatricians completed a brief questionnaire following visits in four community-based primary care practices in the Midwest. Logistic regressions controlling for child behavior and demographic predictors of pediatrician identification found that an authoritarian parenting style, in which parents yell or strongly negatively react to problem behavior, was negatively associated with likelihood of identification in the overall sample. However, the variables that were predictive of pediatrician identification differed depending on the specific practice. Parental characteristics can aid in understanding which children are likely to be identified by their pediatrician as having behavioral problems. The finding that practices differed on which variables were associated with pediatrician identification suggests the need to potentially individualize interventions to certain physicians and practices to improve identification of child behavior problems in primary care.

Naïve Bayes Approach for Expert System Design of Children Skin Identification Based on Android

NASA Astrophysics Data System (ADS)

Hartatik; Purnomo, A.; Hartono, R.; Munawaroh, H.

2018-03-01

The development of technology gives some benefits to each person that we can use it properly and correctly. Technology has helped humans in every way. Such as the excess task of an expert in providing information or answers to a problem. Thus problem that often occurs is skin disease that affecting on child. That because the skin of children still vulnerable to the environment. The application was developed using the naïve Bayes algorithm. Through this application, users can consult with a system like an expert to know the symptoms that occur to the child and find the correct treatment to solve the problems.

Radio Frequency Identification (RFID) in medical environment: Gaussian Derivative Frequency Modulation (GDFM) as a novel modulation technique with minimal interference properties.

PubMed

Rieche, Marie; Komenský, Tomás; Husar, Peter

2011-01-01

Radio Frequency Identification (RFID) systems in healthcare facilitate the possibility of contact-free identification and tracking of patients, medical equipment and medication. Thereby, patient safety will be improved and costs as well as medication errors will be reduced considerably. However, the application of RFID and other wireless communication systems has the potential to cause harmful electromagnetic disturbances on sensitive medical devices. This risk mainly depends on the transmission power and the method of data communication. In this contribution we point out the reasons for such incidents and give proposals to overcome these problems. Therefore a novel modulation and transmission technique called Gaussian Derivative Frequency Modulation (GDFM) is developed. Moreover, we carry out measurements to show the inteference properties of different modulation schemes in comparison to our GDFM.

System-wide identification of wild-type SUMO-2 conjugation sites

PubMed Central

Hendriks, Ivo A.; D'Souza, Rochelle C.; Chang, Jer-Gung; Mann, Matthias; Vertegaal, Alfred C. O.

2015-01-01

SUMOylation is a reversible post-translational modification (PTM) regulating all nuclear processes. Identification of SUMOylation sites by mass spectrometry (MS) has been hampered by bulky tryptic fragments, which thus far necessitated the use of mutated SUMO. Here we present a SUMO-specific protease-based methodology which circumvents this problem, dubbed Protease-Reliant Identification of SUMO Modification (PRISM). PRISM allows for detection of SUMOylated proteins as well as identification of specific sites of SUMOylation while using wild-type SUMO. The method is generic and could be widely applied to study lysine PTMs. We employ PRISM in combination with high-resolution MS to identify SUMOylation sites from HeLa cells under standard growth conditions and in response to heat shock. We identified 751 wild-type SUMOylation sites on endogenous proteins, including 200 dynamic SUMO sites in response to heat shock. Thus, we have developed a method capable of quantitatively studying wild-type mammalian SUMO at the site-specific and system-wide level. PMID:26073453

Interventions for Disorders of Change.

ERIC Educational Resources Information Center

Kaplan, David M.

1982-01-01

Describes a unique body of psychosocial disorders, disorders of changes, that have been ignored as serious human problems with unhappy consequences. Suggests early identification of cases and outreach are necessary to treat these acute disturbances, which require multiple interventions with individuals, families, and systems. (Author)

Chemistry, manufacturing and controls in passive transdermal drug delivery systems.

PubMed

Goswami, Tarun; Audett, Jay

2015-01-01

Transdermal drug delivery systems (TDDS) are used for the delivery of the drugs through the skin into the systemic circulation by applying them to the intact skin. The development of TDDS is a complex and multidisciplinary affair which involves identification of suitable drug, excipients and various other components. There have been numerous problems reported with respect to TDDS quality and performance. These problems can be reduced by appropriately addressing chemistry, manufacturing and controls requirements, which would thereby result in development of robust TDDS product and processes. This article provides recommendations on the chemistry, manufacturing and controls focusing on the unique technical aspects of TDDS.

Modern control concepts in hydrology

NASA Technical Reports Server (NTRS)

Duong, N.; Johnson, G. R.; Winn, C. B.

1974-01-01

Two approaches to an identification problem in hydrology are presented based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time invariant or time dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and conform with results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second, by using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Applications of space teleoperator technology to the problems of the handicapped

NASA Technical Reports Server (NTRS)

Malone, T. B.; Deutsch, S.; Rubin, G.; Shenk, S. W.

1973-01-01

The identification of feasible and practical applications of space teleoperator technology for the problems of the handicapped were studied. A teleoperator system is defined by NASA as a remotely controlled, cybernetic, man-machine system designed to extend and augment man's sensory, manipulative, and locomotive capabilities. Based on a consideration of teleoperator systems, the scope of the study was limited to an investigation of these handicapped persons limited in sensory, manipulative, and locomotive capabilities. If the technology being developed for teleoperators has any direct application, it must be in these functional areas. Feasible and practical applications of teleoperator technology for the problems of the handicapped are described, and design criteria are presented with each application. A development plan is established to bring the application to the point of use.

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

PubMed

Nease, Beth M; Haney, Tina S

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

Discovering Knowledge from AIS Database for Application in VTS

NASA Astrophysics Data System (ADS)

Tsou, Ming-Cheng

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

Post-procedural Care in Interventional Radiology: What Every Interventional Radiologist Should Know-Part II: Catheter Care and Management of Common Systemic Post-procedural Complications.

PubMed

Taslakian, Bedros; Sridhar, Divya

2017-09-01

Interventional radiology (IR) has evolved into a full-fledged clinical specialty with attendant comprehensive patient care responsibilities. Providing excellent and thorough clinical care is as essential to the practice of IR as achieving technical success in procedures. Basic clinical skills that every interventional radiologist should learn include routine management of percutaneously inserted drainage and vascular catheters and rapid effective management of common systemic post-procedural complications. A structured approach to post-procedural care, including routine follow-up and early identification and management of complications, facilitates efficient and thorough management with an emphasis on quality and patient safety. The aim of this second part, in conjunction with part 1, is to complete the comprehensive review of post-procedural care in patients undergoing interventional radiology procedures. We discuss common problems encountered after insertion of drainage and vascular catheters and describe effective methods of troubleshooting these problems. Commonly encountered systemic complications in IR are described, and ways for immediate identification and management of these complications are provided.

A theoretical framework for convergence and continuous dependence of estimates in inverse problems for distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.

1988-01-01

Numerical techniques for parameter identification in distributed-parameter systems are developed analytically. A general convergence and stability framework (for continuous dependence on observations) is derived for first-order systems on the basis of (1) a weak formulation in terms of sesquilinear forms and (2) the resolvent convergence form of the Trotter-Kato approximation. The extension of this framework to second-order systems is considered.

Wiener-Hammerstein system identification - an evolutionary approach

NASA Astrophysics Data System (ADS)

Naitali, Abdessamad; Giri, Fouad

2016-01-01

The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

Parametric robust control and system identification: Unified approach

NASA Technical Reports Server (NTRS)

Keel, Leehyun

1994-01-01

Despite significant advancement in the area of robust parametric control, the problem of synthesizing such a controller is still a wide open problem. Thus, we attempt to give a solution to this important problem. Our approach captures the parametric uncertainty as an H(sub infinity) unstructured uncertainty so that H(sub infinity) synthesis techniques are applicable. Although the techniques cannot cope with the exact parametric uncertainty, they give a reasonable guideline to model the unstructured uncertainty that contains the parametric uncertainty. An additional loop shaping technique is also introduced to relax its conservatism.

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

Lindorff, D. P.; Carroll, R. L.

1973-01-01

A survey of the literature in which Liapunov's second method is used in determining the control law is presented, with emphasis placed on the model-tracking adaptive control problem. Forty references are listed. Following a brief tutorial exposition of the adaptive control problem, the techniques for treating reduction of order, disturbance and time-varying parameters, multivariable systems, identification, and adaptive observers are discussed. The method is critically evaluated, particularly with respect to possibilities for application.

Semiannual report, 1 April - 30 September 1991

NASA Technical Reports Server (NTRS)

1991-01-01

The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software for parallel computers. Research in these areas is discussed.

Intellectual Classification of Black and White Children in Special Education Programs Using the WISC-III and the Cognitive Assessment System.

ERIC Educational Resources Information Center

Naglieri, Jack A.; Rojahn, Johannes

2001-01-01

Comparison of the Wechsler Intelligence Scale for Children (Third Edition) and the Cognitive Assessment System (CAS) with 78 special education students found that the WISC-III identified more children, especially more black children, as having mental retardation. Results imply that the problem of disproportionate identification of black children…

Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques.

PubMed

Xiao, Xiang; Zhu, Hao; Liu, Wei-Jie; Yu, Xiao-Ting; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-01-01

The International 10/20 system is an important head-surface-based positioning system for transcranial brain mapping techniques, e.g., fNIRS and TMS. As guidance for probe placement, the 10/20 system permits both proper ROI coverage and spatial consistency among multiple subjects and experiments in a MRI-free context. However, the traditional manual approach to the identification of 10/20 landmarks faces problems in reliability and time cost. In this study, we propose a semi-automatic method to address these problems. First, a novel head surface reconstruction algorithm reconstructs head geometry from a set of points uniformly and sparsely sampled on the subject's head. Second, virtual 10/20 landmarks are determined on the reconstructed head surface in computational space. Finally, a visually-guided real-time navigation system guides the experimenter to each of the identified 10/20 landmarks on the physical head of the subject. Compared with the traditional manual approach, our proposed method provides a significant improvement both in reliability and time cost and thus could contribute to improving both the effectiveness and efficiency of 10/20-guided MRI-free probe placement.

Evaluation of the Hanford 200 West Groundwater Treatment System: Fluidized Bed Bioreactor

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

Looney, Brian B.; Jackson, Dennis G.; Dickson, John O.

A fluidized bed reactor (FBR) in the 200W water treatment facility at Hanford is removing nitrate from groundwater as part of the overall pump-treat-reinject process. Control of the FBR bed solids has proven challenging, impacting equipment, increasing operations and maintenance (O&M), and limiting the throughput of the facility. In response to the operational challenges, the Department of Energy Richland Office (DOE-RL) commissioned a technical assistance team to facilitate a system engineering evaluation and provide focused support recommendations to the Hanford Team. The DOE Environmental Management (EM) technical assistance process is structured to identify and triage technologies and strategies that addressmore » the target problem(s). The process encourages brainstorming and dialog and allows rapid identification and prioritization of possible options. Recognizing that continuous operation of a large-scale FBR is complex, requiring careful attention to system monitoring data and changing conditions, the technical assistance process focused on explicit identification of the available control parameters (“knobs”), how these parameters interact and impact the FBR system, and how these can be adjusted under different scenarios to achieve operational goals. The technical assistance triage process was performed in collaboration with the Hanford team.« less

The visual information system

Treesearch

Merlyn J. Paulson

1979-01-01

This paper outlines a project level process (V.I.S.) which utilizes very accurate and flexible computer algorithms in combination with contemporary site analysis and design techniques for visual evaluation, design and management. The process provides logical direction and connecting bridges through problem identification, information collection and verification, visual...

Identification of alcohol-pedestrian crash problems among selected racial/ethnic groups

DOT National Transportation Integrated Search

1997-09-01

Pedestrians who had been drinking make up about half of all adult pedestrian crash fatalities. About one-third of all adult pedestrian victims were at BACs of 15% or more (NHTSA's Fatality Analysis Reporting System (FARS), 1984-1993). This study exam...

Counseling Conservative and Fundamentalist Christians: Issues and Implications for the Counselor.

ERIC Educational Resources Information Center

Hannon, J. Wade; And Others

1994-01-01

Explores special considerations for counseling adherents of fundamentalist Christian belief systems. Discusses identification of fundamentalists and assessment of the impact of religiosity on presenting counseling problems. Reviews oppressive effects of fundamentalist patriarchal beliefs and practices on women in counseling, and gives suggestions…

Evaluating Physician Competency: What Difference Does It Make?

ERIC Educational Resources Information Center

Brockway, Barbara Stephens

1978-01-01

A system for evaluating clinical competency of residents was designed to test expert opinions as well as the skills of the practitioner. Four measures of clinical competency were included: data collection completeness; problem identification accuracy; interview skills; and patient and physician assessment. (Author/MH)

Lower Sensitivity to Happy and Angry Facial Emotions in Young Adults with Psychiatric Problems

PubMed Central

Vrijen, Charlotte; Hartman, Catharina A.; Lodder, Gerine M. A.; Verhagen, Maaike; de Jonge, Peter; Oldehinkel, Albertine J.

2016-01-01

Many psychiatric problem domains have been associated with emotion-specific biases or general deficiencies in facial emotion identification. However, both within and between psychiatric problem domains, large variability exists in the types of emotion identification problems that were reported. Moreover, since the domain-specificity of the findings was often not addressed, it remains unclear whether patterns found for specific problem domains can be better explained by co-occurrence of other psychiatric problems or by more generic characteristics of psychopathology, for example, problem severity. In this study, we aimed to investigate associations between emotion identification biases and five psychiatric problem domains, and to determine the domain-specificity of these biases. Data were collected as part of the ‘No Fun No Glory’ study and involved 2,577 young adults. The study participants completed a dynamic facial emotion identification task involving happy, sad, angry, and fearful faces, and filled in the Adult Self-Report Questionnaire, of which we used the scales depressive problems, anxiety problems, avoidance problems, Attention-Deficit Hyperactivity Disorder (ADHD) problems and antisocial problems. Our results suggest that participants with antisocial problems were significantly less sensitive to happy facial emotions, participants with ADHD problems were less sensitive to angry emotions, and participants with avoidance problems were less sensitive to both angry and happy emotions. These effects could not be fully explained by co-occurring psychiatric problems. Whereas this seems to indicate domain-specificity, inspection of the overall pattern of effect sizes regardless of statistical significance reveals generic patterns as well, in that for all psychiatric problem domains the effect sizes for happy and angry emotions were larger than the effect sizes for sad and fearful emotions. As happy and angry emotions are strongly associated with approach and avoidance mechanisms in social interaction, these mechanisms may hold the key to understanding the associations between facial emotion identification and a wide range of psychiatric problems. PMID:27920735

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

Negated bio-events: analysis and identification

PubMed Central

2013-01-01

Background Negation occurs frequently in scientific literature, especially in biomedical literature. It has previously been reported that around 13% of sentences found in biomedical research articles contain negation. Historically, the main motivation for identifying negated events has been to ensure their exclusion from lists of extracted interactions. However, recently, there has been a growing interest in negative results, which has resulted in negation detection being identified as a key challenge in biomedical relation extraction. In this article, we focus on the problem of identifying negated bio-events, given gold standard event annotations. Results We have conducted a detailed analysis of three open access bio-event corpora containing negation information (i.e., GENIA Event, BioInfer and BioNLP’09 ST), and have identified the main types of negated bio-events. We have analysed the key aspects of a machine learning solution to the problem of detecting negated events, including selection of negation cues, feature engineering and the choice of learning algorithm. Combining the best solutions for each aspect of the problem, we propose a novel framework for the identification of negated bio-events. We have evaluated our system on each of the three open access corpora mentioned above. The performance of the system significantly surpasses the best results previously reported on the BioNLP’09 ST corpus, and achieves even better results on the GENIA Event and BioInfer corpora, both of which contain more varied and complex events. Conclusions Recently, in the field of biomedical text mining, the development and enhancement of event-based systems has received significant interest. The ability to identify negated events is a key performance element for these systems. We have conducted the first detailed study on the analysis and identification of negated bio-events. Our proposed framework can be integrated with state-of-the-art event extraction systems. The resulting systems will be able to extract bio-events with attached polarities from textual documents, which can serve as the foundation for more elaborate systems that are able to detect mutually contradicting bio-events. PMID:23323936

On Complete Control and Synchronization of Zhang Chaotic System with Uncertain Parameters using Adaptive Control Method

NASA Astrophysics Data System (ADS)

Tirandaz, Hamed

2018-03-01

Chaos control and synchronization of chaotic systems is seemingly a challenging problem and has got a lot of attention in recent years due to its numerous applications in science and industry. This paper concentrates on the control and synchronization problem of the three-dimensional (3D) Zhang chaotic system. At first, an adaptive control law and a parameter estimation law are achieved for controlling the behavior of the Zhang chaotic system. Then, non-identical synchronization of Zhang chaotic system is provided with considering the Lü chaotic system as the follower system. The synchronization problem and parameters identification are achieved by introducing an adaptive control law and a parameters estimation law. Stability analysis of the proposed method is proved by the Lyapanov stability theorem. In addition, the convergence of the estimated parameters to their truly unknown values are evaluated. Finally, some numerical simulations are carried out to illustrate and to validate the effectiveness of the suggested method.

Inverse problems in 1D hemodynamics on systemic networks: a sequential approach.

PubMed

Lombardi, D

2014-02-01

In this work, a sequential approach based on the unscented Kalman filter is applied to solve inverse problems in 1D hemodynamics, on a systemic network. For instance, the arterial stiffness is estimated by exploiting cross-sectional area and mean speed observations in several locations of the arteries. The results are compared with those ones obtained by estimating the pulse wave velocity and the Moens-Korteweg formula. In the last section, a perspective concerning the identification of the terminal models parameters and peripheral circulation (modeled by a Windkessel circuit) is presented. Copyright © 2013 John Wiley & Sons, Ltd.

Performance study of LMS based adaptive algorithms for unknown system identification

NASA Astrophysics Data System (ADS)

Javed, Shazia; Ahmad, Noor Atinah

2014-07-01

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

Performance study of LMS based adaptive algorithms for unknown system identification

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

Javed, Shazia; Ahmad, Noor Atinah

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signalmore » is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.« less

[Problems in organization of medical criminological registration and personality identification for subjects occupationally exposed to life risk].

PubMed

Shcherbakov, V V

2000-01-01

The paper discusses problems in organization of identification studies under conditions of mass deaths as exemplified by forensic medical records of medical criminological identification studies of subjects killed during war conflict in Chechnya. The evolution of the organization model of identification studies is shown transformation of organization philosophy, formation of expert algorithms, formalization and technologic realization of expert solutions.

K-State Problem Identification Rating Scales for College Students

ERIC Educational Resources Information Center

Robertson, John M.; Benton, Stephen L.; Newton, Fred B.; Downey, Ronald G.; Marsh, Patricia A.; Benton, Sheryl A.; Tseng, Wen-Chih; Shin, Kang-Hyun

2006-01-01

The K-State Problem Identification Rating Scales, a new screening instrument for college counseling centers, gathers information about clients' presenting symptoms, functioning levels, and readiness to change. Three studies revealed 7 scales: Mood Difficulties, Learning Problems, Food Concerns, Interpersonal Conflicts, Career Uncertainties,…

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

ERIC Educational Resources Information Center

Goodman, Bradley A.

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

A gradient based algorithm to solve inverse plane bimodular problems of identification

NASA Astrophysics Data System (ADS)

Ran, Chunjiang; Yang, Haitian; Zhang, Guoqing

2018-02-01

This paper presents a gradient based algorithm to solve inverse plane bimodular problems of identifying constitutive parameters, including tensile/compressive moduli and tensile/compressive Poisson's ratios. For the forward bimodular problem, a FE tangent stiffness matrix is derived facilitating the implementation of gradient based algorithms, for the inverse bimodular problem of identification, a two-level sensitivity analysis based strategy is proposed. Numerical verification in term of accuracy and efficiency is provided, and the impacts of initial guess, number of measurement points, regional inhomogeneity, and noisy data on the identification are taken into accounts.

Intellectual system of identification of Arabic graphics

NASA Astrophysics Data System (ADS)

Abdoullayeva, Gulchin G.; Aliyev, Telman A.; Gurbanova, Nazakat G.

2001-08-01

The studies made by using the domain of graphic images allowed creating facilities of the artificial intelligence for letters, letter combinations etc. for various graphics and prints. The work proposes a system of recognition and identification of symbols of the Arabic graphics, which has its own specificity as compared to Latin and Cyrillic ones. The starting stage of the recognition and the identification is coding with further entry of information into a computer. Here the problem of entry is one of the essentials. For entry of a large volume of information in the unit of time a scanner is usually employed. Along with the scanner the authors suggest their elaboration of technical facilities for effective input and coding of the information. For refinement of symbols not identified from the scanner mostly for a small bulk of information the developed coding devices are used directly in the process of writing. The functional design of the software is elaborated on the basis of the heuristic model of the creative activity of a researcher and experts in the description and estimation of states of the weakly formalizable systems on the strength of the methods of identification and of selection of geometric features.

Radar signal categorization using a neural network

NASA Technical Reports Server (NTRS)

Anderson, James A.; Gately, Michael T.; Penz, P. Andrew; Collins, Dean R.

1991-01-01

Neural networks were used to analyze a complex simulated radar environment which contains noisy radar pulses generated by many different emitters. The neural network used is an energy minimizing network (the BSB model) which forms energy minima - attractors in the network dynamical system - based on learned input data. The system first determines how many emitters are present (the deinterleaving problem). Pulses from individual simulated emitters give rise to separate stable attractors in the network. Once individual emitters are characterized, it is possible to make tentative identifications of them based on their observed parameters. As a test of this idea, a neural network was used to form a small data base that potentially could make emitter identifications.

Biometric recognition using 3D ear shape.

PubMed

Yan, Ping; Bowyer, Kevin W

2007-08-01

Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and 3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario on a database of 415 subjects and 1,386 total probes.

Manual LANDSAT data analysis for crop type identification

NASA Technical Reports Server (NTRS)

Hay, C. M. (Principal Investigator)

1979-01-01

The process of manual identification of crop type by human analysts and problems associated in LACIE that were associated with manual crop identification measurement procedures are described. Research undertaken in cooperation with LACIE operations by the supporting research community to effect solutions to, or obtain greater understanding of the problems is discussed.

Early Identification of Developmental Delays through Surveillance, Screening, and Diagnostic Evaluation

ERIC Educational Resources Information Center

Pizur-Barnekow, Kris; Erickson, Stephanie; Johnston, Mark; Bass, Tamicah; Lucinski, Loraine; Bleuel, Dan

2010-01-01

Developmental and behavioral problems in young children are prevalent in the United States. While young children experience an increased prevalence of such problems, a lack of early identification services continues to exist. Not only are early identification services required under American law, such as the Individual with Disabilities Education…

Parameter identification of material constants in a composite shell structure

NASA Technical Reports Server (NTRS)

Martinez, David R.; Carne, Thomas G.

1988-01-01

One of the basic requirements in engineering analysis is the development of a mathematical model describing the system. Frequently comparisons with test data are used as a measurement of the adequacy of the model. An attempt is typically made to update or improve the model to provide a test verified analysis tool. System identification provides a systematic procedure for accomplishing this task. The terms system identification, parameter estimation, and model correlation all refer to techniques that use test information to update or verify mathematical models. The goal of system identification is to improve the correlation of model predictions with measured test data, and produce accurate, predictive models. For nonmetallic structures the modeling task is often difficult due to uncertainties in the elastic constants. A finite element model of the shell was created, which included uncertain orthotropic elastic constants. A modal survey test was then performed on the shell. The resulting modal data, along with the finite element model of the shell, were used in a Bayes estimation algorithm. This permitted the use of covariance matrices to weight the confidence in the initial parameter values as well as confidence in the measured test data. The estimation procedure also employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem.

Cumulative reports and publications through December 31, 1991

NASA Technical Reports Server (NTRS)

1992-01-01

A reports and publications list is given from the Institute for Computer Applications in Science and Engineering (ICASE) through December 31, 1991. The major categories of the current ICASE research program are; numerical methods, control and parameter identification problems, computational problems in engineering and the physical sciences, and computer systems and software. Since ICASE reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when available.

Fundamental Mechanisms of NeuroInformation Processing: Inverse Problems and Spike Processing

DTIC Science & Technology

2016-08-04

platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution...example. We investigated the following nonlinear identification problem: given both the input signal u and the time sequence (tk)k2Z at the output of...from a time sequence is to be contrasted with existing methods for rate-based models in neuroscience. In such models the output of the system is taken

A comparison of Heuristic method and Llewellyn’s rules for identification of redundant constraints

NASA Astrophysics Data System (ADS)

Estiningsih, Y.; Farikhin; Tjahjana, R. H.

2018-03-01

Important techniques in linear programming is modelling and solving practical optimization. Redundant constraints are consider for their effects on general linear programming problems. Identification and reduce redundant constraints are for avoidance of all the calculations associated when solving an associated linear programming problems. Many researchers have been proposed for identification redundant constraints. This paper a compararison of Heuristic method and Llewellyn’s rules for identification of redundant constraints.

Identification of Bouc-Wen hysteretic parameters based on enhanced response sensitivity approach

NASA Astrophysics Data System (ADS)

Wang, Li; Lu, Zhong-Rong

2017-05-01

This paper aims to identify parameters of Bouc-Wen hysteretic model using time-domain measured data. It follows a general inverse identification procedure, that is, identifying model parameters is treated as an optimization problem with the nonlinear least squares objective function. Then, the enhanced response sensitivity approach, which has been shown convergent and proper for such kind of problems, is adopted to solve the optimization problem. Numerical tests are undertaken to verify the proposed identification approach.

A knowledge-based approach to identification and adaptation in dynamical systems control

NASA Technical Reports Server (NTRS)

Glass, B. J.; Wong, C. M.

1988-01-01

Artificial intelligence techniques are applied to the problems of model form and parameter identification of large-scale dynamic systems. The object-oriented knowledge representation is discussed in the context of causal modeling and qualitative reasoning. Structured sets of rules are used for implementing qualitative component simulations, for catching qualitative discrepancies and quantitative bound violations, and for making reconfiguration and control decisions that affect the physical system. These decisions are executed by backward-chaining through a knowledge base of control action tasks. This approach was implemented for two examples: a triple quadrupole mass spectrometer and a two-phase thermal testbed. Results of tests with both of these systems demonstrate that the software replicates some or most of the functionality of a human operator, thereby reducing the need for a human-in-the-loop in the lower levels of control of these complex systems.

Entanglement and the fermion sign problem in auxiliary field quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Broecker, Peter; Trebst, Simon

2016-08-01

Quantum Monte Carlo simulations of fermions are hampered by the notorious sign problem whose most striking manifestation is an exponential growth of sampling errors with the number of particles. With the sign problem known to be an NP-hard problem and any generic solution thus highly elusive, the Monte Carlo sampling of interacting many-fermion systems is commonly thought to be restricted to a small class of model systems for which a sign-free basis has been identified. Here we demonstrate that entanglement measures, in particular the so-called Rényi entropies, can intrinsically exhibit a certain robustness against the sign problem in auxiliary-field quantum Monte Carlo approaches and possibly allow for the identification of global ground-state properties via their scaling behavior even in the presence of a strong sign problem. We corroborate these findings via numerical simulations of fermionic quantum phase transitions of spinless fermions on the honeycomb lattice at and below half filling.

A new specimen management system using RFID technology.

PubMed

Shim, Hun; Uh, Young; Lee, Seung Hwan; Yoon, Young Ro

2011-12-01

The specimen management system with barcode needs to be improved in order to solve inherent problems in work performance. This study describes the application of Radio Frequency Identification (RFID) which is the solution for the problems associated with specimen labeling and management. A new specimen management system and architecture with RFID technology for clinical laboratory was designed. The suggested system was tested in various conditions such as durability to temperature and aspect of effective utilization of new work flow under a virtual hospital clinical laboratory environment. This system demonstrates its potential application in clinical laboratories for improving work flow and specimen management. The suggested specimen management system with RFID technology has advantages in comparison to the traditional specimen management system with barcode in the aspect of mass specimen processing, robust durability of temperature, humidity changes, and effective specimen tracking.

Africa’s Evolving Infosystems: A Pathway to Security and Stability

DTIC Science & Technology

2011-03-01

Another problem involved the development of a missing persons identification system to be deployed in the aftermath of a hurricane or other...Activism in Africa (Cape Town: Pamba- zuka Press, 2010). 26 Sheila Kinkade and Katrin Verclas, Wireless Technology for Social Change (Wash- ington, DC: UN

Identification and Control of Pollution from Salt Water Intrusion.

ERIC Educational Resources Information Center

Environmental Protection Agency, Washington, DC. Office of Water Programs.

This document contains informational guidelines for identifying and evaluating the nature and extent of pollution from salt water intrusion. The intent of these guidelines is to provide a basic framework for assessing salt water intrusion problems and their relationship to the total hydrologic system, and to provide assistance in developing…

Intelligent Tutoring and the Development of Argumentative Competence

ERIC Educational Resources Information Center

Paneque, Juan J.; Cobo, Pedro; Fortuny, Josep M.

2017-01-01

This ethnographical study aims to interpret how an intelligent tutorial system, geogebraTUTOR, mediates to the student's argumentative processes. Data consisted of four geometrical problems proposed to a group of four students aged 16-17. Qualitative analysis of two selected cases led to the identification of the development of argumentative…

The Self-Help Group Model: A Review

ERIC Educational Resources Information Center

Jaques, Marceline E.; Patterson, Kathleen M.

1974-01-01

Self-help mutual aid groups are organized by peers who share a common problem. Through group identification, mutual support, and modeling, behavior is directed toward learning a new coping life style. The self-help group model is considered here as a viable and necessary part of a total rehabilitation service system. (Author)

A Contextual Model for Identity Management (IdM) Interfaces

ERIC Educational Resources Information Center

Fuller, Nathaniel J.

2014-01-01

The usability of Identity Management (IdM) systems is highly dependent upon design that simplifies the processes of identification, authentication, and authorization. Recent findings reveal two critical problems that degrade IdM usability: (1) unfeasible techniques for managing various digital identifiers, and (2) ambiguous security interfaces.…

George A. Towns Elementary School. Atlanta, Georgia

ERIC Educational Resources Information Center

Burt, Ralph H.

1976-01-01

A project testing solar heating and cooling in an existing building, the George A. Towns Elementary School, is intended to provide information on system design and performance, allow the identification and correction of problems encountered in installing large units, and gauge community/user reaction to solar equipment. (Author/MLF)

Putting the Power of Configuration in the Hands of the Users

NASA Technical Reports Server (NTRS)

Al-Shihabi, Mary-Jo; Brown, Mark; Rigolini, Marianne

2011-01-01

Goal was to reduce the overall cost of human space flight while maintaining the most demanding standards for safety and mission success. In support of this goal, a project team was chartered to replace 18 legacy Space Shuttle nonconformance processes and systems with one fully integrated system Problem Reporting and Corrective Action (PRACA) processes provide a closed-loop system for the identification, disposition, resolution, closure, and reporting of all Space Shuttle hardware/software problems PRACA processes are integrated throughout the Space Shuttle organizational processes and are critical to assuring a safe and successful program Primary Project Objectives Develop a fully integrated system that provides an automated workflow with electronic signatures Support multiple NASA programs and contracts with a single "system" architecture Define standard processes, implement best practices, and minimize process variations

Model identification of signal transduction networks from data using a state regulator problem.

PubMed

Gadkar, K G; Varner, J; Doyle, F J

2005-03-01

Advances in molecular biology provide an opportunity to develop detailed models of biological processes that can be used to obtain an integrated understanding of the system. However, development of useful models from the available knowledge of the system and experimental observations still remains a daunting task. In this work, a model identification strategy for complex biological networks is proposed. The approach includes a state regulator problem (SRP) that provides estimates of all the component concentrations and the reaction rates of the network using the available measurements. The full set of the estimates is utilised for model parameter identification for the network of known topology. An a priori model complexity test that indicates the feasibility of performance of the proposed algorithm is developed. Fisher information matrix (FIM) theory is used to address model identifiability issues. Two signalling pathway case studies, the caspase function in apoptosis and the MAP kinase cascade system, are considered. The MAP kinase cascade, with measurements restricted to protein complex concentrations, fails the a priori test and the SRP estimates are poor as expected. The apoptosis network structure used in this work has moderate complexity and is suitable for application of the proposed tools. Using a measurement set of seven protein concentrations, accurate estimates for all unknowns are obtained. Furthermore, the effects of measurement sampling frequency and quality of information in the measurement set on the performance of the identified model are described.

Applications of aerospace technology to petroleum exploration. Volume 1: Efforts and results

NASA Technical Reports Server (NTRS)

Jaffe, L. D.

1976-01-01

The feasibility of applying aerospace techniques to help solve significant problems in petroleum exploration is studied. Through contacts with petroleum industry and petroleum service industry, important petroleum exploration problems were identified. For each problem, areas of aerospace technology that might aid in its solution were also identified where possible. Topics selected for investigation include: seismic reflection systems; down-hole acoustic techniques; identification of geological analogies; drilling methods; remote geological sensing; and sea floor imaging and mapping. Specific areas of aerospace technology are applied to 21 concepts formulated from the topics of concern.

Perceived Ethnic Discrimination and Problem Behaviors in Muslim Immigrant Early Adolescents: Moderating Effects of Ethnic, Religious, and National Group Identification

ERIC Educational Resources Information Center

Maes, Marlies; Stevens, Gonneke W. J. M.; Verkuyten, Maykel

2014-01-01

Previous research has identified ethnic group identification as a moderator in the relationship between perceived ethnic discrimination and problem behaviors in ethnic minority children. However, little is known about the influence of religious and host national identification on this relationship. This study investigated the moderating role of…

[Continuous quality improvement in anesthesia].

PubMed

Gaitini, L; Vaida, S; Madgar, S

1998-01-01

Slow continuous quality improvement (SCQI) in anesthesia is a process that allows identification of problems and their causes. Implementing measures to correct them and continuous monitoring to ensure that the problems have been eliminated are necessary. The basic assumption of CQI is that the employees of an organization are competent and working to the best of their abilities. If problems occur they are the consequences of inadequacies in the process rather that in the individual. The CQI program is a dynamic but gradual system that invokes a slower rate of response in comparison with other quality methods, like quality assurance. Spectacular results following a system change are not to be expected an the ideal is slow and continuous improvement. A SCQI program was adapted by our department in May 1994, according to the recommendations of the American Society of Anesthesiologists. Problem identification was based on 65 clinical indicators, reflecting negative events related to anesthesia. Data were collected using a specially designed computer database. 4 events were identified as crossing previously established thresholds (hypertension, hypotension, hypoxia and inadequate nerve block). Statistical process control was used to establish stability of the system and whether negative events were influenced only by the common causes. The causes responsible for these negative events were identified using specific SCQI tools, such as control-charts, cause-effect diagrams and Pareto diagrams. Hypertension and inadequate nerve block were successfully managed. The implementation of corrective measures for the other events that cross the threshold is still in evolution. This program requires considerable dedication on the part of the staff, and it is hoped that it will improve our clinical performance.

Fluorine disposal

NASA Technical Reports Server (NTRS)

Rakow, A.

1983-01-01

A preliminary design of an F2 dispoal system for HELSTF is presented along with recommendations on operational policy and identification of potential operational problems. The analysis is based on sizing a system to handle two different modes of the HELSTF Fluorine Flow System (one operational and one catastrophic). This information should serve both as a guide to a final detailed design for HELSTF as well as a reference for subsequent monitoring and/or modification of the system which consists of a charcoal reactor followed by a dry soda lime scrubber.

Marking parts to aid robot vision

NASA Technical Reports Server (NTRS)

Bales, J. W.; Barker, L. K.

1981-01-01

The premarking of parts for subsequent identification by a robot vision system appears to be beneficial as an aid in the automation of certain tasks such as construction in space. A simple, color coded marking system is presented which allows a computer vision system to locate an object, calculate its orientation, and determine its identity. Such a system has the potential to operate accurately, and because the computer shape analysis problem has been simplified, it has the ability to operate in real time.

A Characterization of t/s-Diagnosability and Sequential t-Diagnosability in Designs

DTIC Science & Technology

1990-10-01

41 151 161 171 181 r91 1101 REFERENCES K.-Y. Chwa and S. L. Hakimi, “On fault identification in diagnosable systems,” ZEEE Tmns. Comput...1975, pp. 167-170. S. L. Hakimi and A. T. Amin, “Characterization of the connection assignment problem of diagnosable systems,” ZEEE Trans. Comput...S. Karunanithi and A. D. Friedman, “Analysis of digital systems using a new measure of system diagnosis,” ZEEE Trans. Cornput., vol. C- A

[Evidential value of dental materials identification by infrared spectroscopy in forensic medicine opinionating].

PubMed

Wachowiak, Roman; Strach, Bogna

2007-01-01

The potential for a release of dental restoration material or a spontaneous loss of a tooth structure fragment in the course of mastication frequently requires a reliable identification of the lost fragment in order to confirm its origin. The consequences of incidental mechanical injuries -- in view of the presence of dangerous solid fragments -- become particularly important in cases of using a chewing gum. The problem involves distinguishing between the structure of a fragment of restoration or a broken tooth structure and incidental contaminants of chewing gum produced in the process of gum manufacturing. The consequences of mechanical injuries or exposure to potential structural tooth damage in the course of gum chewing provide a subject for numerous litigations against manufacturer of chewing gum and require appropriate identification of the material. The studies were conducted using solid phase infrared spectroscopy in the range of 500-4000 wavelength (cm(-1)) for a quick identification of dental materials used in the dental practice. A database of infrared transmission spectra characteristic of commonly employed dental filling materials was prepared to provide a systemic reference system, useful in controversial interpretation cases.

Signal Prediction With Input Identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Chen, Ya-Chin

1999-01-01

A novel coding technique is presented for signal prediction with applications including speech coding, system identification, and estimation of input excitation. The approach is based on the blind equalization method for speech signal processing in conjunction with the geometric subspace projection theory to formulate the basic prediction equation. The speech-coding problem is often divided into two parts, a linear prediction model and excitation input. The parameter coefficients of the linear predictor and the input excitation are solved simultaneously and recursively by a conventional recursive least-squares algorithm. The excitation input is computed by coding all possible outcomes into a binary codebook. The coefficients of the linear predictor and excitation, and the index of the codebook can then be used to represent the signal. In addition, a variable-frame concept is proposed to block the same excitation signal in sequence in order to reduce the storage size and increase the transmission rate. The results of this work can be easily extended to the problem of disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. Simulations are included to demonstrate the proposed method.

Modeling and parameter identification of impulse response matrix of mechanical systems

NASA Astrophysics Data System (ADS)

Bordatchev, Evgueni V.

1998-12-01

A method for studying the problem of modeling, identification and analysis of mechanical system dynamic characteristic in view of the impulse response matrix for the purpose of adaptive control is developed here. Two types of the impulse response matrices are considered: (i) on displacement, which describes the space-coupled relationship between vectors of the force and simulated displacement, which describes the space-coupled relationship between vectors of the force and simulated displacement and (ii) on acceleration, which also describes the space-coupled relationship between the vectors of the force and measured acceleration. The idea of identification consists of: (a) the practical obtaining of the impulse response matrix on acceleration by 'impact-response' technique; (b) the modeling and parameter estimation of the each impulse response function on acceleration through the fundamental representation of the impulse response function on displacement as a sum of the damped sine curves applying linear and non-linear least square methods; (c) simulating the impulse provides the additional possibility to calculate masses, damper and spring constants. The damped natural frequencies are used as a priori information and are found through the standard FFT analysis. The problem of double numerical integration is avoided by taking two derivations of the fundamental dynamic model of a mechanical system as linear combination of the mass-damper-spring subsystems. The identified impulse response matrix on displacement represents the dynamic properties of the mechanical system. From the engineering point of view, this matrix can be also understood as a 'dynamic passport' of the mechanical system and can be used for dynamic certification and analysis of the dynamic quality. In addition, the suggested approach mathematically reproduces amplitude-frequency response matrix in a low-frequency band and on zero frequency. This allows the possibility of determining the matrix of the static stiffness due to dynamic testing over the time of 10- 15 minutes. As a practical example, the dynamic properties in view of the impulse and frequency response matrices of the lathe spindle are obtained, identified and investigated. The developed approach for modeling and parameter identification appears promising for a wide range o industrial applications; for example, rotary systems.

A truncated generalized singular value decomposition algorithm for moving force identification with ill-posed problems

NASA Astrophysics Data System (ADS)

Chen, Zhen; Chan, Tommy H. T.

2017-08-01

This paper proposes a new methodology for moving force identification (MFI) from the responses of bridge deck. Based on the existing time domain method (TDM), the MFI problem eventually becomes solving the linear algebraic equation in the form Ax = b . The vector b is usually contaminated by an unknown error e generating from measurement error, which often called the vector e as ''noise''. With the ill-posed problems that exist in the inverse problem, the identification force would be sensitive to the noise e . The proposed truncated generalized singular value decomposition method (TGSVD) aims at obtaining an acceptable solution and making the noise to be less sensitive to perturbations with the ill-posed problems. The illustrated results show that the TGSVD has many advantages such as higher precision, better adaptability and noise immunity compared with TDM. In addition, choosing a proper regularization matrix L and a truncation parameter k are very useful to improve the identification accuracy and to solve ill-posed problems when it is used to identify the moving force on bridge.

Combined state and parameter identification of nonlinear structural dynamical systems based on Rao-Blackwellization and Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Abhinav, S.; Manohar, C. S.

2018-03-01

The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.

Estimation of nonlinear pilot model parameters including time delay.

NASA Technical Reports Server (NTRS)

Schiess, J. R.; Roland, V. R.; Wells, W. R.

1972-01-01

Investigation of the feasibility of using a Kalman filter estimator for the identification of unknown parameters in nonlinear dynamic systems with a time delay. The problem considered is the application of estimation theory to determine the parameters of a family of pilot models containing delayed states. In particular, the pilot-plant dynamics are described by differential-difference equations of the retarded type. The pilot delay, included as one of the unknown parameters to be determined, is kept in pure form as opposed to the Pade approximations generally used for these systems. Problem areas associated with processing real pilot response data are included in the discussion.

The Metaproteome of "Park Grass" soil - a reference for EU soil science

NASA Astrophysics Data System (ADS)

Quinn, Gerry; Dudley, Ed; Doerr, Stefan; Matthews, Peter; Halen, Ingrid; Walley, Richard; Ashton, Rhys; Delmont, Tom; Francis, Lewis; Gazze, Salvatore Andrea; Van Keulen, Geertje

2016-04-01

Soil metaproteomics, the systemic extraction and identification of proteins from a soil, is key to understanding the biological and physical processes that occur within the soil at a molecular level. Until recently, direct extraction of proteins from complex soils have yielded only dozens of protein identifications due to interfering substances, such as humic acids and clay, which co-extract and/or strongly adsorb protein, often causing problems in downstream processing, e.g. mass spectrometry. Furthermore, the current most successful, direct, proteomic extraction protocol favours larger molecular weight and/or heat-stable proteins due to its extraction protocol. We have now developed a novel, faster, direct soil protein extraction protocol which also addressed the problem of interfering substances, while only requiring less than 1 gram of material per extraction. We extracted protein from the 'Genomic Observatory' Park Grass at Rothamsted Research (UK), an ideally suited geographic site as it is the longest (>150 years) continually studied experiment on ungrazed permanent grassland in the world, for which a rich history of environmental/ecological data has been collected, including high quality publically available metagenome DNA sequences. Using this improved methodology, in conjunction with the creation of high quality, curated metagenomic sequence databases, we have been able to significantly improve protein identifications from one soil due to extracting a similar number of proteins that were >90% different when compared to the best current direct protocol. This optimised metaproteomics protocol has now enabled identification of thousands of proteins from one soil, leading therefore to a deeper insight of soil system processes at the molecular scale.

Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

NASA Technical Reports Server (NTRS)

Srivastava, Ashok, N.; Akella, Ram; Diev, Vesselin; Kumaresan, Sakthi Preethi; McIntosh, Dawn M.; Pontikakis, Emmanuel D.; Xu, Zuobing; Zhang, Yi

2006-01-01

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0-

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

PubMed Central

Urbanowicz, Ryan J.; Granizo-Mackenzie, Ambrose; Moore, Jason H.

2014-01-01

Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful class of evolutionary algorithms which distribute the learned solution over a sizable population of rules. However their application to complex real world data mining problems, such as genetic association studies, has been limited. Traditional knowledge discovery strategies for M-LCS rule populations involve sorting and manual rule inspection. While this approach may be sufficient for simpler problems, the confounding influence of noise and the need to discriminate between predictive and non-predictive attributes calls for additional strategies. Additionally, tests of significance must be adapted to M-LCS analyses in order to make them a viable option within fields that require such analyses to assess confidence. In this work we introduce an M-LCS analysis pipeline that combines uniquely applied visualizations with objective statistical evaluation for the identification of predictive attributes, and reliable rule generalizations in noisy single-step data mining problems. This work considers an alternative paradigm for knowledge discovery in M-LCSs, shifting the focus from individual rules to a global, population-wide perspective. We demonstrate the efficacy of this pipeline applied to the identification of epistasis (i.e., attribute interaction) and heterogeneity in noisy simulated genetic association data. PMID:25431544

Linear CCD attitude measurement system based on the identification of the auxiliary array CCD

NASA Astrophysics Data System (ADS)

Hu, Yinghui; Yuan, Feng; Li, Kai; Wang, Yan

2015-10-01

Object to the high precision flying target attitude measurement issues of a large space and large field of view, comparing existing measurement methods, the idea is proposed of using two array CCD to assist in identifying the three linear CCD with multi-cooperative target attitude measurement system, and to address the existing nonlinear system errors and calibration parameters and more problems with nine linear CCD spectroscopic test system of too complicated constraints among camera position caused by excessive. The mathematical model of binocular vision and three linear CCD test system are established, co-spot composition triangle utilize three red LED position light, three points' coordinates are given in advance by Cooperate Measuring Machine, the red LED in the composition of the three sides of a triangle adds three blue LED light points as an auxiliary, so that array CCD is easier to identify three red LED light points, and linear CCD camera is installed of a red filter to filter out the blue LED light points while reducing stray light. Using array CCD to measure the spot, identifying and calculating the spatial coordinates solutions of red LED light points, while utilizing linear CCD to measure three red LED spot for solving linear CCD test system, which can be drawn from 27 solution. Measured with array CCD coordinates auxiliary linear CCD has achieved spot identification, and has solved the difficult problems of multi-objective linear CCD identification. Unique combination of linear CCD imaging features, linear CCD special cylindrical lens system is developed using telecentric optical design, the energy center of the spot position in the depth range of convergence in the direction is perpendicular to the optical axis of the small changes ensuring highprecision image quality, and the entire test system improves spatial object attitude measurement speed and precision.

Parameter identification using a creeping-random-search algorithm

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1971-01-01

A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.

A review of output-only structural mode identification literature employing blind source separation methods

NASA Astrophysics Data System (ADS)

Sadhu, A.; Narasimhan, S.; Antoni, J.

2017-09-01

Output-only modal identification has seen significant activity in recent years, especially in large-scale structures where controlled input force generation is often difficult to achieve. This has led to the development of new system identification methods which do not require controlled input. They often work satisfactorily if they satisfy some general assumptions - not overly restrictive - regarding the stochasticity of the input. Hundreds of papers covering a wide range of applications appear every year related to the extraction of modal properties from output measurement data in more than two dozen mechanical, aerospace and civil engineering journals. In little more than a decade, concepts of blind source separation (BSS) from the field of acoustic signal processing have been adopted by several researchers and shown that they can be attractive tools to undertake output-only modal identification. Originally intended to separate distinct audio sources from a mixture of recordings, mathematical equivalence to problems in linear structural dynamics have since been firmly established. This has enabled many of the developments in the field of BSS to be modified and applied to output-only modal identification problems. This paper reviews over hundred articles related to the application of BSS and their variants to output-only modal identification. The main contribution of the paper is to present a literature review of the papers which have appeared on the subject. While a brief treatment of the basic ideas are presented where relevant, a comprehensive and critical explanation of their contents is not attempted. Specific issues related to output-only modal identification and the relative advantages and limitations of BSS methods both from theoretical and application standpoints are discussed. Gap areas requiring additional work are also summarized and the paper concludes with possible future trends in this area.

An Optimization Code for Nonlinear Transient Problems of a Large Scale Multidisciplinary Mathematical Model

NASA Astrophysics Data System (ADS)

Takasaki, Koichi

This paper presents a program for the multidisciplinary optimization and identification problem of the nonlinear model of large aerospace vehicle structures. The program constructs the global matrix of the dynamic system in the time direction by the p-version finite element method (pFEM), and the basic matrix for each pFEM node in the time direction is described by a sparse matrix similarly to the static finite element problem. The algorithm used by the program does not require the Hessian matrix of the objective function and so has low memory requirements. It also has a relatively low computational cost, and is suited to parallel computation. The program was integrated as a solver module of the multidisciplinary analysis system CUMuLOUS (Computational Utility for Multidisciplinary Large scale Optimization of Undense System) which is under development by the Aerospace Research and Development Directorate (ARD) of the Japan Aerospace Exploration Agency (JAXA).

[The present and future state of minimized extracorporeal circulation].

PubMed

Meng, Fan; Yang, Ming

2013-05-01

Minimized extracorporeal circulation improved in the postoperative side effects of conventional extracorporeal circulation is a kind of new extracorporeal circulation. This paper introduces the principle, characteristics, applications and related research of minimized extracorporeal circulation. For the problems of systemic inflammatory response syndrome and limited assist time, the article proposes three development direction including system miniaturization and integration, pulsatile blood pump and the adaptive control by human parameter identification.

Optimal Sensor Scheduling for Multiple Hypothesis Testing

DTIC Science & Technology

1981-09-01

Naval Research, under contract N00014-77-0532 is gratpfully acknowledged. 2 Laboratory for Information and Decision Systems , MIT Room 35-213, Cambridge...treat the more general problem [9,10]. However, two common threads connect these approaches: they obtain feedback laws mapping posterior destributions ...objective of a detection or identification algorithm is to produce correct estimates of the true state of a system . It is also bene- ficial if these

Volterra-series-based nonlinear system modeling and its engineering applications: A state-of-the-art review

NASA Astrophysics Data System (ADS)

Cheng, C. M.; Peng, Z. K.; Zhang, W. M.; Meng, G.

2017-03-01

Nonlinear problems have drawn great interest and extensive attention from engineers, physicists and mathematicians and many other scientists because most real systems are inherently nonlinear in nature. To model and analyze nonlinear systems, many mathematical theories and methods have been developed, including Volterra series. In this paper, the basic definition of the Volterra series is recapitulated, together with some frequency domain concepts which are derived from the Volterra series, including the general frequency response function (GFRF), the nonlinear output frequency response function (NOFRF), output frequency response function (OFRF) and associated frequency response function (AFRF). The relationship between the Volterra series and other nonlinear system models and nonlinear problem solving methods are discussed, including the Taylor series, Wiener series, NARMAX model, Hammerstein model, Wiener model, Wiener-Hammerstein model, harmonic balance method, perturbation method and Adomian decomposition. The challenging problems and their state of arts in the series convergence study and the kernel identification study are comprehensively introduced. In addition, a detailed review is then given on the applications of Volterra series in mechanical engineering, aeroelasticity problem, control engineering, electronic and electrical engineering.

Response to ``Comment on `Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks''' [Chaos 17, 038101 (2007)

NASA Astrophysics Data System (ADS)

Yu, Wenwu; Cao, Jinde

2007-09-01

Parameter identification of dynamical systems from time series has received increasing interest due to its wide applications in secure communication, pattern recognition, neural networks, and so on. Given the driving system, parameters can be estimated from the time series by using an adaptive control algorithm. Recently, it has been reported that for some stable systems, in which parameters are difficult to be identified [Li et al., Phys Lett. A 333, 269-270 (2004); Remark 5 in Yu and Cao, Physica A 375, 467-482 (2007); and Li et al., Chaos 17, 038101 (2007)], and in this paper, a brief discussion about whether parameters can be identified from time series is investigated. From some detailed analyses, the problem of why parameters of stable systems can be hardly estimated is discussed. Some interesting examples are drawn to verify the proposed analysis.

Individually Identifiable Surface Acoustic Wave Sensors, Tags and Systems

NASA Technical Reports Server (NTRS)

Hines, Jacqueline H. (Inventor); Solie, Leland P. (Inventor); Tucker, Dana Y. G. (Inventor); Hines, Andrew T. (Inventor)

2017-01-01

A surface-launched acoustic wave sensor tag system for remotely sensing and/or providing identification information using sets of surface acoustic wave (SAW) sensor tag devices is characterized by acoustic wave device embodiments that include coding and other diversity techniques to produce groups of sensors that interact minimally, reducing or alleviating code collision problems typical of prior art coded SAW sensors and tags, and specific device embodiments of said coded SAW sensor tags and systems. These sensor/tag devices operate in a system which consists of one or more uniquely identifiable sensor/tag devices and a wireless interrogator. The sensor device incorporates an antenna for receiving incident RF energy and re-radiating the tag identification information and the sensor measured parameter(s). Since there is no power source in or connected to the sensor, it is a passive sensor. The device is wirelessly interrogated by the interrogator.

Installation Restoration Program. Phase II: Stage 1 Problem Confirmation Study, Duluth International Airport, Duluth, Minnesota.

DTIC Science & Technology

1984-10-01

8 iii "i t-. Table of Contents (cont.) Section Title Page -APPENDIX A Acronyms, Definitions, Nomenclature and Units of Measure B Scope of Work, Task...Identification/Records Search Phase II - Problem Confirmation and Quantification Phase III - Technology Base Development Phase IV - Corrective Action Only...Problem Identification/Records Search Phase II - Problem Confirmation and Quantification Phase III - Technology Base Development Phase IV - Corrective

Identification des objets et detection de leur alignement en utilisant la technologie RFID

NASA Astrophysics Data System (ADS)

Rahma, Zayoud

De nos jours, les vehicules motorises sont essentiels dans notre vie quotidienne, d'ou la necessite de leur approvisionnement en carburant. L'approvisionnement en carburant peut entrainer certains inconvenients, tels que: les files d'attente, la disponibilite non-continuelle du carburant et les fraudes. Les problemes d'attente et de disponibilite non-continuelle du carburant peuvent etre facilement resolus en allant a une autre station d'essence aux alentours si disponibles. Par contre le probleme de fraudes est plus difficile a resoudre. De ce fait, decoule notre solution qui consiste a developper un systeme intelligent pour la gestion d'approvisionnement en carburant afin de remedier a ce probleme de fraudes. Pour des raisons de surete, il faut eviter les risques d'etincelles dans l'environnement du carburant. En particulier, il convient de ne pas utiliser un systeme utilisant 1'electricite proche de la pompe, du tuyau ou du reservoir du carburant du vehicule. Nous avons choisi la technologie RFID (Radio Frequency IDentification) et avons opte pour l'utilisation des etiquettes passives, etant donne que les etiquettes semi-passives ou actives contiennent une batterie electrique et sont nettement plus cheres. Un vehicule motorise sera identifie avec une etiquette RFID passive collee au-dessus du goulot de son reservoir. Deux autres etiquettes RFID seront placees sur le pistolet de sorte que le flux du carburant ne sera autorise que lorsque les trois etiquettes sont alignees. Notre travail etait a la demande d'une entreprise petroliere ayant une chaine internationale de stations de carburant. Le travail consiste en la conception, par la recherche, du systeme requis et s'articule sur l'optimisation de la topologie des antennes et des etiquettes de sorte que le systeme juge qu'il y a alignement lorsque le bec du pistolet est fonce dans le goulot du reservoir, et par consequent autorise le versement du carburant. Dans tous les autres cas, le systeme doit juger qu'il n'y a pas alignement et par consequent le flux du carburant n'est pas autorise. Mots cles: RFID, identification, localisation, alignement, fraudes, station-service.

Design of high pressure oxygen filter for extravehicular activity life support system, volume 1

NASA Technical Reports Server (NTRS)

Wilson, B. A.

1977-01-01

The experience of the National Aeronautics and Space Administration (NASA) with extravehicular activity life support emergency oxygen supply subsystems has shown a large number of problems associated with particulate contamination. These problems have resulted in failures of high pressure oxygen component sealing surfaces. A high pressure oxygen filter was designed which would (a) control the particulate contamination level in the oxygen system to a five-micron glass bead rating, ten-micron absolute condition (b) withstand the dynamic shock condition resulting from the sudden opening of 8000 psi oxygen system shutoff valve. Results of the following program tasks are reported: (1) contaminant source identification tests, (2) dynamic system tests, (3) high pressure oxygen filter concept evaluation, (4) design, (5) fabrication, (6) test, and (7) application demonstration.

Retinal identification based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform.

PubMed

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-07-18

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

PubMed Central

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-01-01

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

Parental explanatory models of ADHD: gender and cultural variations.

PubMed

Bussing, Regina; Gary, Faye A; Mills, Terry L; Garvan, Cynthia Wilson

2003-10-01

This study describes parents' explanatory models of Attention Deficit Hyperactivity Disorder (ADHD) and examines model variation by child characteristics. Children with ADHD (N = 182) were identified from a school district population of elementary school students. A reliable coding system was developed for parental responses obtained in ethnographic interviews in order to convert qualitative into numerical data for quantitative analysis. African-American parents were less likely to connect the school system to ADHD problem identification, expressed fewer worries about ADHD-related school problems, and voiced fewer preferences for school interventions than Caucasian parents, pointing to a potential disconnect with the school system. More African-American than Caucasian parents were unsure about potential causes of and treatments for ADHD, indicating a need for culturally appropriate parent education approaches.

Using HPLC-Mass Spectrometry to Teach Proteomics Concepts with Problem-Based Techniques

ERIC Educational Resources Information Center

Short, Michael; Short, Anne; Vankempen, Rachel; Seymour, Michael; Burnatowska-Hledin, Maria

2010-01-01

Practical instruction of proteomics concepts was provided using high-performance liquid chromatography coupled with a mass selective detection system (HPLC-MS) for the analysis of simulated protein digests. The samples were prepared from selected dipeptides in order to facilitate the mass spectral identification. As part of the prelaboratory…

The problem of regime summaries of the data from radar observations. [for cloud system identification

NASA Technical Reports Server (NTRS)

Divinskaya, B. S.; Salman, Y. M.

1975-01-01

Peculiarities of the radar information about clouds are examined in comparison with visual data. An objective radar classification is presented and the relation of it to the meteorological classification is shown. The advisability of storage and summarization of the primary radar data for regime purposes is substantiated.

K-6 Early Intervention Project: Evaluation of the First Year of Implementation.

ERIC Educational Resources Information Center

McDaid, Janet L.

California's K-6 Early Intervention Project was established in 1986 under the authority of California Assembly Bill 1535, Pilot Project on Hyperactivity, to provide a system of early identification and assistance to children in kindergarten through grade 6 whose behavior problems interfere with learning. This report contains evaluation findings…

Multiple concurrent recursive least squares identification with application to on-line spacecraft mass-property identification

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2006-01-01

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.

Identifying problems and generating recommendations for enhancing complex systems: applying the abstraction hierarchy framework as an analytical tool.

PubMed

Xu, Wei

2007-12-01

This study adopts J. Rasmussen's (1985) abstraction hierarchy (AH) framework as an analytical tool to identify problems and pinpoint opportunities to enhance complex systems. The process of identifying problems and generating recommendations for complex systems using conventional methods is usually conducted based on incompletely defined work requirements. As the complexity of systems rises, the sheer mass of data generated from these methods becomes unwieldy to manage in a coherent, systematic form for analysis. There is little known work on adopting a broader perspective to fill these gaps. AH was used to analyze an aircraft-automation system in order to further identify breakdowns in pilot-automation interactions. Four steps follow: developing an AH model for the system, mapping the data generated by various methods onto the AH, identifying problems based on the mapped data, and presenting recommendations. The breakdowns lay primarily with automation operations that were more goal directed. Identified root causes include incomplete knowledge content and ineffective knowledge structure in pilots' mental models, lack of effective higher-order functional domain information displayed in the interface, and lack of sufficient automation procedures for pilots to effectively cope with unfamiliar situations. The AH is a valuable analytical tool to systematically identify problems and suggest opportunities for enhancing complex systems. It helps further examine the automation awareness problems and identify improvement areas from a work domain perspective. Applications include the identification of problems and generation of recommendations for complex systems as well as specific recommendations regarding pilot training, flight deck interfaces, and automation procedures.

Department of Defense picture archiving and communication system acceptance testing: results and identification of problem components.

PubMed

Allison, Scott A; Sweet, Clifford F; Beall, Douglas P; Lewis, Thomas E; Monroe, Thomas

2005-09-01

The PACS implementation process is complicated requiring a tremendous amount of time, resources, and planning. The Department of Defense (DOD) has significant experience in developing and refining PACS acceptance testing (AT) protocols that assure contract compliance, clinical safety, and functionality. The DOD's AT experience under the initial Medical Diagnostic Imaging Support System contract led to the current Digital Imaging Network-Picture Archiving and Communications Systems (DIN-PACS) contract AT protocol. To identify the most common system and component deficiencies under the current DIN-PACS AT protocol, 14 tri-service sites were evaluated during 1998-2000. Sixteen system deficiency citations with 154 separate types of limitations were noted with problems involving the workstation, interfaces, and the Radiology Information System comprising more than 50% of the citations. Larger PACS deployments were associated with a higher number of deficiencies. The most commonly cited systems deficiencies were among the most expensive components of the PACS.

Gesellschaft fuer angewandte Mathematik und Mechanik, Scientific Annual Meeting, Universitaet Hannover, Hanover, Federal Republic of Germany, Apr. 8-12, 1990, Reports

NASA Astrophysics Data System (ADS)

Various papers on applied mathematics and mechanics are presented. Among the individual topics addressed are: dynamical systems with time-varying or unsteady structure, micromechanical modeling of creep rupture, forced vibrations of elastic sandwich plates with thick surface layers, postbuckling of a complete spherical shell under a line load, differential-geometric approach to the multibody system dynamics, stability of an oscillator with stochastic parametric excitation, identification strategies for crack-formation in rotors, identification of physical parameters of FEMs, impact model for elastic and partly plastic impacts on objects, varying delay and stability in dynamical systems. Also discussed are: parameter identification of a hybrid model for vibration analysis using the FEM, vibration behavior of a labyrinth seal with through-flow, similarities in the boundary layer of fiber composite materials, distortion parameter in shell theories, elastoplastic crack problem at finite strain, algorithm for computing effective stiffnesses of plates with periodic structure, plasticity of metal-matrix composites in a mixed stress-strain space formation, constitutive equations in directly formulated plate theories, microbuckling and homogenization for long fiber composites.

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

2002-01-01

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Identification of related gene/protein names based on an HMM of name variations.

PubMed

Yeganova, L; Smith, L; Wilbur, W J

2004-04-01

Gene and protein names follow few, if any, true naming conventions and are subject to great variation in different occurrences of the same name. This gives rise to two important problems in natural language processing. First, can one locate the names of genes or proteins in free text, and second, can one determine when two names denote the same gene or protein? The first of these problems is a special case of the problem of named entity recognition, while the second is a special case of the problem of automatic term recognition (ATR). We study the second problem, that of gene or protein name variation. Here we describe a system which, given a query gene or protein name, identifies related gene or protein names in a large list. The system is based on a dynamic programming algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a fully trainable hidden Markov model.

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

NASA Technical Reports Server (NTRS)

Innocenti, M.; Napolitano, M.

2003-01-01

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

Sensitivity Analysis for some Water Pollution Problem

NASA Astrophysics Data System (ADS)

Le Dimet, François-Xavier; Tran Thu, Ha; Hussaini, Yousuff

2014-05-01

Sensitivity Analysis for Some Water Pollution Problems Francois-Xavier Le Dimet1 & Tran Thu Ha2 & M. Yousuff Hussaini3 1Université de Grenoble, France, 2Vietnamese Academy of Sciences, 3 Florida State University Sensitivity analysis employs some response function and the variable with respect to which its sensitivity is evaluated. If the state of the system is retrieved through a variational data assimilation process, then the observation appears only in the Optimality System (OS). In many cases, observations have errors and it is important to estimate their impact. Therefore, sensitivity analysis has to be carried out on the OS, and in that sense sensitivity analysis is a second order property. The OS can be considered as a generalized model because it contains all the available information. This presentation proposes a method to carry out sensitivity analysis in general. The method is demonstrated with an application to water pollution problem. The model involves shallow waters equations and an equation for the pollutant concentration. These equations are discretized using a finite volume method. The response function depends on the pollutant source, and its sensitivity with respect to the source term of the pollutant is studied. Specifically, we consider: • Identification of unknown parameters, and • Identification of sources of pollution and sensitivity with respect to the sources. We also use a Singular Evolutive Interpolated Kalman Filter to study this problem. The presentation includes a comparison of the results from these two methods. .

A class of least-squares filtering and identification algorithms with systolic array architectures

NASA Technical Reports Server (NTRS)

Kalson, Seth Z.; Yao, Kung

1991-01-01

A unified approach is presented for deriving a large class of new and previously known time- and order-recursive least-squares algorithms with systolic array architectures, suitable for high-throughput-rate and VLSI implementations of space-time filtering and system identification problems. The geometrical derivation given is unique in that no assumption is made concerning the rank of the sample data correlation matrix. This method utilizes and extends the concept of oblique projections, as used previously in the derivations of the least-squares lattice algorithms. Exponentially weighted least-squares criteria are considered for both sliding and growing memory.

Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

PubMed

Benoussaad, Mourad; Poignet, Philippe; Hayashibe, Mitsuhiro; Azevedo-Coste, Christine; Fattal, Charles; Guiraud, David

2013-06-01

We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

The quality of Indigenous identification in administrative health data in Australia: insights from studies using data linkage

PubMed Central

2012-01-01

Background Missing or incorrect Indigenous status in health records hinders monitoring of Indigenous health indicators. Linkage of administrative data has been used to improve the ascertainment of Indigenous status. Data linkage was pioneered in Western Australia (WA) and is now being used in other Australian states. This systematic review appraises peer-reviewed Australian studies that used data linkage to elucidate the impact of under-ascertainment of Indigenous status on health indicators. Methods A PubMed search identified eligible studies that used Australian linked data to interrogate Indigenous identification using more than one identifier and interrogated the impact of the different identifiers on estimation of Indigenous health indicators. Results Eight papers were included, five from WA and three from New South Wales (NSW). The WA papers included a self-identified Indigenous community cohort and showed improved identification in hospital separation data after 2000. In CVD hospitalised patients (2000–05), under-identification was greater in urban residents, older people and socially more advantaged Indigenous people, with varying algorithms giving different estimates of under-count. Age-standardised myocardial infarction incidence rates (2000–2004) increased by about 10%-15% with improved identification. Under-ascertainment of Indigenous identification overestimated secular improvements in life expectancy and mortality whereas correcting infectious disease notifications resulted in lower Indigenous/ non-Indigenous rate ratios. NSW has a history of poor Indigenous identification in administrative data systems, but the NSW papers confirmed the usefulness of data linkage for improving Indigenous identification and the potential for very different estimates of Indigenous disease indicators depending upon the algorithm used for identification. Conclusions Under-identification of Indigenous status must be addressed in health analyses concerning Indigenous health differentials – they cannot be ignored or wished away. This problem can be substantially diminished through data linkage. Under-identification of Indigenous status impacts differently in different disease contexts, generally resulting in under-estimation of absolute and relative Indigenous health indicators, but may perversely overestimate Indigenous rates and differentials in the setting of stigma-associated conditions such as sexually-transmitted and blood-borne virus infections. Under-numeration in Census surveys also needs consideration to address the added problem of denominator undercounts. PMID:23157943

[Morphological verification problems of Chernobyl factor influence on the testis of coal miners of Donbas-liquidators of Chernobyl accident].

PubMed

Danylov, Iu V; Motkov, K V; Shevchenko, T I

2013-01-01

Problem of a diagnostic of Chernobyl factor influences on different organs and systems of Chernobyl accident liquidators are remain actually until now. Though morbidly background which development at unfavorable work conditions in underground coalminers prevents from objective identification features of Chernobyl factor influences. The qualitative and quantitative histological and immunohistochemical law of morphogenesis changes in testis of Donbas's coalminer - non-liquidators Chernobyl accident in comparison with the group of Donbas's coalminers-liquidators Chernobyl accident, which we were stationed non determined problem. This reason stipulates to development and practical use of mathematical model of morphogenesis of a testis changes.

[Morphological verification problems of Chernobyl factor influence on the prostate of coalminers of Donbas--liquidators of Chernobyl accident].

PubMed

Danylov, Iu V; Motkov, K V; Shevchenko, T I

2013-12-01

Problem of a diagnostic of Chernobyl factor influences on different organs and systems of Chernobyl accident liquidators are remain actually until now. Though morbidly background which development at unfavorable work conditions in underground coalminers prevents from objective identification features of Chernobyl factor influences. The qualitative and quantitative histological and immunohistochemical law of morphogenesis changes in prostate of Donbas's coalminer-non-liquidators Chernobyl accident in comparison with the group of Donbas's coalminers-liquidators Chernobyl accident which we were stationed non determined problem. This reason stipulates to development and practical use of mathematical model of morphogenesis of a prostatic gland changes.

Identification errors in the blood transfusion laboratory: a still relevant issue for patient safety.

PubMed

Lippi, Giuseppe; Plebani, Mario

2011-04-01

Remarkable technological advances and increased awareness have both contributed to decrease substantially the uncertainty of the analytical phase, so that the manually intensive preanalytical activities currently represent the leading sources of errors in laboratory and transfusion medicine. Among preanalytical errors, misidentification and mistransfusion are still regarded as a considerable problem, posing serious risks for patient health and carrying huge expenses for the healthcare system. As such, a reliable policy of risk management should be readily implemented, developing through a multifaceted approach to prevent or limit the adverse outcomes related to transfusion reactions from blood incompatibility. This strategy encompasses root cause analysis, compliance with accreditation requirements, strict adherence to standard operating procedures, guidelines and recommendations for specimen collection, use of positive identification devices, rejection of potentially misidentified specimens, informatics data entry, query host communication, automated systems for patient identification and sample labeling and an adequate and safe environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effects of video compression on target acquisition performance

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Cha, Jae; Preece, Bradley

2008-04-01

The bandwidth requirements of modern target acquisition systems continue to increase with larger sensor formats and multi-spectral capabilities. To obviate this problem, still and moving imagery can be compressed, often resulting in greater than 100 fold decrease in required bandwidth. Compression, however, is generally not error-free and the generated artifacts can adversely affect task performance. The U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate recently performed an assessment of various compression techniques on static imagery for tank identification. In this paper, we expand this initial assessment by studying and quantifying the effect of various video compression algorithms and their impact on tank identification performance. We perform a series of controlled human perception tests using three dynamic simulated scenarios: target moving/sensor static, target static/sensor static, sensor tracking the target. Results of this study will quantify the effect of video compression on target identification and provide a framework to evaluate video compression on future sensor systems.

System justification, the denial of global warming, and the possibility of "system-sanctioned change".

PubMed

Feygina, Irina; Jost, John T; Goldsmith, Rachel E

2010-03-01

Despite extensive evidence of climate change and environmental destruction, polls continue to reveal widespread denial and resistance to helping the environment. It is posited here that these responses are linked to the motivational tendency to defend and justify the societal status quo in the face of the threat posed by environmental problems. The present research finds that system justification tendencies are associated with greater denial of environmental realities and less commitment to pro-environmental action. Moreover, the effects of political conservatism, national identification, and gender on denial of environmental problems are explained by variability in system justification tendencies. However, this research finds that it is possible to eliminate the negative effect of system justification on environmentalism by encouraging people to regard pro-environmental change as patriotic and consistent with protecting the status quo (i.e., as a case of "system-sanctioned change"). Theoretical and practical implications of these findings are discussed.

Optimization Parameters of Air-conditioning and Heat Insulation Systems of a Pressurized Cabins of Long-distance Airplanes

NASA Astrophysics Data System (ADS)

Gusev, Sergey A.; Nikolaev, Vladimir N.

2018-01-01

The method for determination of an aircraft compartment thermal condition, based on a mathematical model of a compartment thermal condition was developed. Development of solution techniques for solving heat exchange direct and inverse problems and for determining confidence intervals of parametric identification estimations was carried out. The required performance of air-conditioning, ventilation systems and heat insulation depth of crew and passenger cabins were received.

Challenging Aerospace Problems for Intelligent Systems

DTIC Science & Technology

2003-06-01

importance of each rule. Techniques such as logarithmic regression or Saaty’s AHP may be employed to apply the weights on to the fuzzy rules. 15-9 Given u...at which designs could be evaluated. This implies that modeling techniques such as neural networks, fuzzy systems and so on can play an important role...failure conditions [4-6]. These approaches apply techniques, such as neural networks, fuzzy logic, and parameter identification, to improve aircraft

Symposium Proceedings: Productivity Enhancement: Personnel Performance Assessment in Navy Systems, held October 12-14, 1977,

DTIC Science & Technology

1977-01-01

principles apply; however, special attention has to be given early in ana- ivsis to the number and kinds of discriminations required of the human observer...demands, to store, or to output desired information. Typically, these are not insurmountable problems, but they have to receive their due attention ... attention to calibration, data identification, noise, drift, and measureuent start/stop logic. Manual systems require special attention to the reliability of

The topology of the regularized integral surfaces of the 3-body problem

NASA Technical Reports Server (NTRS)

Easton, R.

1971-01-01

Momentum, angular momentum, and energy of integral surfaces in the planar three-body problem are considered. The end points of orbits which cross an isolating block are identified. It is shown that this identification has a unique extension to an identification which pairs the end points of orbits entering the block and which end in a binary collision with the end points of orbits leaving the block and which come from a binary collision. The problem of regularization is that of showing that the identification of the end points of crossing orbits has a continuous, unique extension. The regularized phase space for the three-body problem was obtained, as were regularized integral surfaces for the problem on which the three-body equations of motion induce flows. Finally the topology of these surfaces is described.

System Identification of X-33 Neural Network

NASA Technical Reports Server (NTRS)

Aggarwal, Shiv

2003-01-01

Modern flight control research has improved spacecraft survivability as its goal. To this end we need to have a failure detection system on board. In case the spacecraft is performing imperfectly, reconfiguration of control is needed. For that purpose we need to have parameter identification of spacecraft dynamics. Parameter identification of a system is called system identification. We treat the system as a black box which receives some inputs that lead to some outputs. The question is: what kind of parameters for a particular black box can correlate the observed inputs and outputs? Can these parameters help us to predict the outputs for a new given set of inputs? This is the basic problem of system identification. The X33 was supposed to have the onboard capability of evaluating the current performance and if needed to take the corrective measures to adapt to desired performance. The X33 is comprised of both rocket and aircraft vehicle design characteristics and requires, in general, analytical methods for evaluating its flight performance. Its flight consists of four phases: ascent, transition, entry and TAEM (Terminal Area Energy Management). It spends about 200 seconds in ascent phase, reaching an altitude of about 180,000 feet and a speed of about 10 to 15 Mach. During the transition phase which lasts only about 30 seconds, its altitude may increase to about 190,000 feet but its speed is reduced to about 9 Mach. At the beginning of this phase, the Main Engine is Cut Off (MECO) and the control is reconfigured with the help of aerosurfaces (four elevons, two flaps and two rudders) and reaction control system (RCS). The entry phase brings down the altitude of X33 to about 90,000 feet and its speed to about Mach 3. It spends about 250 seconds in this phase. Main engine is still cut off and the vehicle is controlled by complex maneuvers of aerosurfaces. The last phase TAEM lasts for about 450 seconds and the altitude and speed, both are reduced to zero. The present attempt, as a start, focuses only on the entry phase. Since the main engine remains cut off in this phase, there is no thrust acting on the system. This considerably simplifies the equations of motion. We introduce another simplification by assuming the system to be linear after some non-linearities are removed analytically from our consideration. Under these assumptions, the problem could be solved by Classical Statistics by employing the least sum of squares approach. Instead we chose to use the Neural Network method. This method has many advantages. It is modern, more efficient, can be adapted to work even when the assumptions are diluted. In fact, Neural Networks try to model the human brain and are capable of pattern recognition.

How Captain Amerika uses neural networks to fight crime

NASA Technical Reports Server (NTRS)

Rogers, Steven K.; Kabrisky, Matthew; Ruck, Dennis W.; Oxley, Mark E.

1994-01-01

Artificial neural network models can make amazing computations. These models are explained along with their application in problems associated with fighting crime. Specific problems addressed are identification of people using face recognition, speaker identification, and fingerprint and handwriting analysis (biometric authentication).

Shortage of human resources in the Hungarian health care system: short-term or long-term problem?

PubMed

Belicza, Eva; Réthelyi, János; Kullmann, Lajos

2003-01-01

The Quality-management Committee of the Hungarian Hospital Federation and the Semmelweis University Health Services Management Training Centre, recognizing the threats of the human resources shortage and the consequential quality problems in the delivery of health care services, have launched a program for identifying the major problems and developing recommendations for decision makers and health service managers. The identification of the problems was performed by a task force group using a systematic methodology, recommendations were based on these findings. Members of the task force group were delegated by the Hungarian Hospital Federation and the Health Services Management Training Centre. Additional members were invited from the Ministry of Health and various other professional organizations.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

Experiment design for pilot identification in compensatory tracking tasks

NASA Technical Reports Server (NTRS)

Wells, W. R.

1976-01-01

A design criterion for input functions in laboratory tracking tasks resulting in efficient parameter estimation is formulated. The criterion is that the statistical correlations between pairs of parameters be reduced in order to minimize the problem of nonuniqueness in the extraction process. The effectiveness of the method is demonstrated for a lower order dynamic system.

Probabilistic Ontology Architecture for a Terrorist Identification Decision Support System

DTIC Science & Technology

2014-06-01

in real-world problems requires probabilistic ontologies, which integrate the inferential reasoning power of probabilistic representations with the... inferential reasoning power of probabilistic representations with the first-order expressivity of ontologies. The Reference Architecture for...ontology, terrorism, inferential reasoning, architecture I. INTRODUCTION A. Background Whether by nature or design, the personas of terrorists are

The Rules Grid: Helping Children with Social Communication and Interaction Needs Manage Social Complexity

ERIC Educational Resources Information Center

Devlin, Niall

2009-01-01

This article introduces a new practical visual approach, the Rules Grid, to support children who have social communication and interaction needs. The Rules Grid involves a system whereby behaviours of concern can be broken down into smaller behavioural manifestations which in turn lead not only to problem identification and specification, but…

Academic Autonomy in a Rapidly Changing Higher Education Framework: Academia on the Procrustean Bed?

ERIC Educational Resources Information Center

Schmidt, Evanthia Kalpazidou; Langberg, Kamma

2008-01-01

In a number of European countries, the recognition of the university's key role in the evolution of the knowledge society--and in the identification and solving of political, socioeconomic, environmental, and cultural problems--has led to radical reforms of higher education systems. Denmark has implemented the most radical reforms of the region in…

Sociometric Clique Identification. Final Report.

ERIC Educational Resources Information Center

Kadushin, Charles

This report consists of four parts. The first part is a non-technical summary of the basic problem and an attempted solution. The second part is a technical review of the literature and a description of the basic algorithm used in the solution. The third part describes the use of the Sociogram System. The fourth part describes the use of CHAIN, a…

Inductive System for Reliable Magnesium Level Detection in a Titanium Reduction Reactor

NASA Astrophysics Data System (ADS)

Krauter, Nico; Eckert, Sven; Gundrum, Thomas; Stefani, Frank; Wondrak, Thomas; Frick, Peter; Khalilov, Ruslan; Teimurazov, Andrei

2018-05-01

The determination of the Magnesium level in a Titanium reduction retort by inductive methods is often hampered by the formation of Titanium sponge rings which disturb the propagation of electromagnetic signals between excitation and receiver coils. We present a new method for the reliable identification of the Magnesium level which explicitly takes into account the presence of sponge rings with unknown geometry and conductivity. The inverse problem is solved by a look-up-table method, based on the solution of the inductive forward problems for several tens of thousands parameter combinations.

Medical isotope identification with large mobile detection systems

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard

2012-10-01

The Remote Sensing laboratory (RSL) of National Security Technologies Inc. has built an array of large (5.08 - cm x 10.16 - cm x 40.6 - cm) thallium doped sodium iodide (NaI: Tl) scintillators to locate and screen gamma-ray emitting radioisotopes that are of interests to radiological emergency responders [1]. These vehicle mounted detectors provide the operators with rapid, simple, specific information for radiological threat assessment. Applications include large area inspection, customs inspection, border protection, emergency response, and monitoring of radiological facilities. These RSL mobile units are currently being upgraded to meet the Defense Threat Reduction Agency mission requirements for a next-generation system capable of detecting and identifying nuclear threat materials. One of the challenging problems faced by these gamma-ray detectors is the unambiguous identification of medical isotopes like 131I (364.49 keV [81.7%], 636.99 keV [7.17%]), 99Tcm (140.51 keV [89.1%]) and 67Ga (184.6 keV [19.7%], 300.2 [16.0%], 393.5 [4.5%] that are used in radionuclide therapy and often have overlapping gamma-ray energy regions of interest (ROI). The problem is made worse by short (about 5 seconds) acquisition time of the spectral data necessary for dynamic mobile detectors. This article describes attempts to identify medical isotopes from data collected from this mobile detection system in a short period of time (not exceeding 5 secs) and a large standoff distance (typically 10 meters) The mobile units offer identification capabilities that are based on hardware auto stabilization of the amplifier gain. The 1461 keV gamma-energy line from 40K is tracked. It uses gamma-ray energy windowing along with embedded mobile Gamma Detector Response and Analysis Software (GADRAS) [2] simultaneously to deconvolve any overlapping gamma-energy ROIs. These high sensitivity detectors are capable of resolving complex masking scenarios and exceed all ANSI N42.34 (2006) requirements for the identification of bare, shielded and multiple isotopes.

Global identification of stochastic dynamical systems under different pseudo-static operating conditions: The functionally pooled ARMAX case

NASA Astrophysics Data System (ADS)

Sakellariou, J. S.; Fassois, S. D.

2017-01-01

The identification of a single global model for a stochastic dynamical system operating under various conditions is considered. Each operating condition is assumed to have a pseudo-static effect on the dynamics and be characterized by a single measurable scheduling variable. Identification is accomplished within a recently introduced Functionally Pooled (FP) framework, which offers a number of advantages over Linear Parameter Varying (LPV) identification techniques. The focus of the work is on the extension of the framework to include the important FP-ARMAX model case. Compared to their simpler FP-ARX counterparts, FP-ARMAX models are much more general and offer improved flexibility in describing various types of stochastic noise, but at the same time lead to a more complicated, non-quadratic, estimation problem. Prediction Error (PE), Maximum Likelihood (ML), and multi-stage estimation methods are postulated, and the PE estimator optimality, in terms of consistency and asymptotic efficiency, is analytically established. The postulated estimators are numerically assessed via Monte Carlo experiments, while the effectiveness of the approach and its superiority over its FP-ARX counterpart are demonstrated via an application case study pertaining to simulated railway vehicle suspension dynamics under various mass loading conditions.

Conventional and Eccentric Uses of Crystallographic Databases in Practical Materials Identification Problems

PubMed Central

Kaduk, James A.

1996-01-01

The crystallographic databases are powerful and cost-effective tools for solving materials identification problems, both individually and in combination. Examples of the conventional and unconventional use of the databases in solving practical problems involving organic, coordination, and inorganic compounds are provided. The creation and use of fully-relational versions of the Powder Diffraction File and NIST Crystal Data are described. PMID:27805165

Creation of hybrid optoelectronic systems for document identification

NASA Astrophysics Data System (ADS)

Muravsky, Leonid I.; Voronyak, Taras I.; Kulynych, Yaroslav P.; Maksymenko, Olexander P.; Pogan, Ignat Y.

2001-06-01

Use of security devices based on a joint transform correlator (JTC) architecture for identification of credit cards and other products is very promising. The experimental demonstration of the random phase encoding technique for security verification shows that hybrid JTCs can be successfully utilized. The random phase encoding technique provides a very high protection level of products and things to be identified. However, the realization of this technique is connected with overcoming of the certain practical problems. To solve some of these problems and simultaneously to improve the security of documents and other products, we propose to use a transformed phase mask (TPM) as an input object in an optical correlator. This mask is synthesized from a random binary pattern (RBP), which is directly used to fabricate a reference phase mask (RPM). To obtain the TPM, we previously separate the RBP on a several parts (for example, K parts) of an arbitrary shape and further fabricate the TPM from this transformed RBP. The fabricated TPM can be bonded as the optical mark to any product or thing to be identified. If the RPM and the TPM are placed on the optical correlator input, the first diffracted order of the output correlation signal is containing the K narrow autocorrelation peaks. The distances between the peaks and the peak's intensities can be treated as the terms of the identification feature vector (FV) for the TPM identification.

FVID: Fishing Vessel Type Identification Based on VMS Trajectories

NASA Astrophysics Data System (ADS)

Huang, Haiguang; Hong, Feng; Liu, Jing; Liu, Chao; Feng, Yuan; Guo, Zhongwen

2018-05-01

Vessel Monitoring System (VMS) provides a new opportunity for quantified fishing research. Many approaches have been proposed to recognize fishing activities with VMS trajectories based on the types of fishing vessels. However, one research problem is still calling for solutions, how to identify the fishing vessel type based on only VMS trajectories. This problem is important because it requires the fishing vessel type as a preliminary to recognize fishing activities from VMS trajectories. This paper proposes fishing vessel type identification scheme (FVID) based only on VMS trajectories. FVID exploits feature engineering and machine learning schemes of XGBoost as its two key blocks and classifies fishing vessels into nine types. The dataset contains all the fishing vessel trajectories in the East China Sea in March 2017, including 10031 pre-registered fishing vessels and 1350 unregistered vessels of unknown types. In order to verify type identification accuracy, we first conduct a 4-fold cross-validation on the trajectories of registered fishing vessels. The classification accuracy is 95.42%. We then apply FVID to the unregistered fishing vessels to identify their types. After classifying the unregistered fishing vessel types, their fishing activities are further recognized based upon their types. At last, we calculate and compare the fishing density distribution in the East China Sea before and after applying the unregistered fishing vessels, confirming the importance of type identification of unregistered fishing vessels.

Optimizing medication safety in the home.

PubMed

LeBlanc, Raeanne Genevieve; Choi, Jeungok

2015-06-01

Medication safety among community-dwelling older adults in the United States is an ongoing health issue impacting health outcomes, chronic disease management, and aging in place at home. This article describes a medication safety improvement project that aimed to: (1) Increase the ability of participants to manage medications, (2) Identify and make necessary medication changes, (3) Create an accurate up-to-date medication list to be available in the home, and (4) Provide communication between the primary care provider, participant, and case manager. An in-home medication assessment was completed for 25 participants using an evidence-based medication management software system. This process was used to review medications; identify medication-related problems; create a shared medication list; and convey this information to the primary care provider, case manager, and client while addressing needed medication changes. Educational interventions on management and understanding of medications were provided to participants to emphasize the correct use of medications and use of a personal medication record. Outcome improvements included provision of an accurate medication list, early identification of medication-related problems, identification of drug duplication, and identification of medication self-management challenges that can be useful for optimizing medication safety-related home healthcare and inform future interventions.

Decision support systems in water and wastewater treatment process selection and design: a review.

PubMed

Hamouda, M A; Anderson, W B; Huck, P M

2009-01-01

The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.

Visual Recognition Software for Binary Classification and its Application to Pollen Identification

NASA Astrophysics Data System (ADS)

Punyasena, S. W.; Tcheng, D. K.; Nayak, A.

2014-12-01

An underappreciated source of uncertainty in paleoecology is the uncertainty of palynological identifications. The confidence of any given identification is not regularly reported in published results, so cannot be incorporated into subsequent meta-analyses. Automated identifications systems potentially provide a means of objectively measuring the confidence of a given count or single identification, as well as a mechanism for increasing sample sizes and throughput. We developed the software ARLO (Automated Recognition with Layered Optimization) to tackle difficult visual classification problems such as pollen identification. ARLO applies pattern recognition and machine learning to the analysis of pollen images. The features that the system discovers are not the traditional features of pollen morphology. Instead, general purpose image features, such as pixel lines and grids of different dimensions, size, spacing, and resolution, are used. ARLO adapts to a given problem by searching for the most effective combination of feature representation and learning strategy. We present a two phase approach which uses our machine learning process to first segment pollen grains from the background and then classify pollen pixels and report species ratios. We conducted two separate experiments that utilized two distinct sets of algorithms and optimization procedures. The first analysis focused on reconstructing black and white spruce pollen ratios, training and testing our classification model at the slide level. This allowed us to directly compare our automated counts and expert counts to slides of known spruce ratios. Our second analysis focused on maximizing classification accuracy at the individual pollen grain level. Instead of predicting ratios of given slides, we predicted the species represented in a given image window. The resulting analysis was more scalable, as we were able to adapt the most efficient parts of the methodology from our first analysis. ARLO was able to distinguish between the pollen of black and white spruce with an accuracy of ~83.61%. This compared favorably to human expert performance. At the writing of this abstract, we are also experimenting with experimenting with the analysis of higher diversity samples, including modern tropical pollen material collected from ground pollen traps.

Identification of the Radiative and Nonradiative Parts of a Wave Field

NASA Astrophysics Data System (ADS)

Hoenders, B. J.; Ferwerda, H. A.

2001-08-01

We present a method for decomposing a wave field, described by a second-order ordinary differential equation, into a radiative component and a nonradiative one, using a biorthonormal system related to the problem under consideration. We show that it is possible to select a special system such that the wave field is purely radiating. We discuss the differences and analogies with approaches which, unlike our approach, start from the corresponding sources of the field.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

The comprehensive community-based traffic safety program : phase I, problem identification for District 2 and District 7.

DOT National Transportation Integrated Search

1986-01-01

This report contains the initial Problem Identification for the Comprehensive Community-Based Traffic Safety Program (CCBP). Two DMV districts, District 2 and District 7, have been selected as the pilot areas for the CCBP, and because both districts ...

Comorbidity of Conduct Problems and ADHD: Identification of "Fledgling Psychopaths".

ERIC Educational Resources Information Center

Gresham, Frank M.; Lane, Kathleen L.; Lambros, Katina M.

2000-01-01

This article reviews the characteristics of children who exhibit a behavior pattern characterized by hyperactivity-impulsivity-inattention coupled with conduct problems such as fighting, stealing, truancy, noncompliance, and arguing. Procedures for early identification of these so-called "fledgling psychopaths" are described and discussed.…

Help-seeking behavior of patients with mental health problems visiting a tertiary care center in north India.

PubMed

Mishra, Nitin; Nagpal, Sajanjiv Singh; Chadda, Rakesh K; Sood, Mamta

2011-07-01

Patients with mental health problems in the nonwestern world seek help from a variety of sources, such as the family physicians, psychiatrists, psychologists, traditional faith-healers, or alternative medicine practitioners. Understanding the help-seeking behavior is important from the public health perspective. Two hundred new patients visiting a psychiatric outpatient service at a tertiary care hospital were interviewed on a semi-structured questionnaire for various services contacted by them for their mental health problems. Psychiatrists were the first choice in 45% of the cases followed by nonpsychiatric physicians and religious faith healers. Important reasons to seek help from different sources included easy accessibility, belief in the system, or particular healer and good reputation. Mean duration of treatment varied from 2.35 months with the alternative system practitioners to 16.63 months with the psychiatrists. The mean expenditure per visit to a service was highest for the nonpsychiatric physician and lowest for alternative system practitioners. Patients with mental health problems seek help from psychiatrists, nonpsychiatric physicians, faith healers, alternative system practitioners, and traditional faith healers for multiple reasons. It is important to sensitize various nonpsychiatric physicians with early identification and optimum management of mental disorders.

On multiple crack identification by ultrasonic scanning

NASA Astrophysics Data System (ADS)

Brigante, M.; Sumbatyan, M. A.

2018-04-01

The present work develops an approach which reduces operator equations arising in the engineering problems to the problem of minimizing the discrepancy functional. For this minimization, an algorithm of random global search is proposed, which is allied to some genetic algorithms. The efficiency of the method is demonstrated by the solving problem of simultaneous identification of several linear cracks forming an array in an elastic medium by using the circular Ultrasonic scanning.

Investigation of practical applications of H infinity control theory to the design of control systems for large space structures

NASA Technical Reports Server (NTRS)

Irwin, R. Dennis

1988-01-01

The applicability of H infinity control theory to the problems of large space structures (LSS) control was investigated. A complete evaluation to any technique as a candidate for large space structure control involves analytical evaluation, algorithmic evaluation, evaluation via simulation studies, and experimental evaluation. The results of analytical and algorithmic evaluations are documented. The analytical evaluation involves the determination of the appropriateness of the underlying assumptions inherent in the H infinity theory, the determination of the capability of the H infinity theory to achieve the design goals likely to be imposed on an LSS control design, and the identification of any LSS specific simplifications or complications of the theory. The resuls of the analytical evaluation are presented in the form of a tutorial on the subject of H infinity control theory with the LSS control designer in mind. The algorthmic evaluation of H infinity for LSS control pertains to the identification of general, high level algorithms for effecting the application of H infinity to LSS control problems, the identification of specific, numerically reliable algorithms necessary for a computer implementation of the general algorithms, the recommendation of a flexible software system for implementing the H infinity design steps, and ultimately the actual development of the necessary computer codes. Finally, the state of the art in H infinity applications is summarized with a brief outline of the most promising areas of current research.

Solutions and debugging for data consistency in multiprocessors with noncoherent caches

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

Bernstein, D.; Mendelson, B.; Breternitz, M. Jr.

1995-02-01

We analyze two important problems that arise in shared-memory multiprocessor systems. The stale data problem involves ensuring that data items in local memory of individual processors are current, independent of writes done by other processors. False sharing occurs when two processors have copies of the same shared data block but update different portions of the block. The false sharing problem involves guaranteeing that subsequent writes are properly combined. In modern architectures these problems are usually solved in hardware, by exploiting mechanisms for hardware controlled cache consistency. This leads to more expensive and nonscalable designs. Therefore, we are concentrating on softwaremore » methods for ensuring cache consistency that would allow for affordable and scalable multiprocessing systems. Unfortunately, providing software control is nontrivial, both for the compiler writer and for the application programmer. For this reason we are developing a debugging environment that will facilitate the development of compiler-based techniques and will help the programmer to tune his or her application using explicit cache management mechanisms. We extend the notion of a race condition for IBM Shared Memory System POWER/4, taking into consideration its noncoherent caches, and propose techniques for detection of false sharing problems. Identification of the stale data problem is discussed as well, and solutions are suggested.« less

Special event discrimination analysis: The TEXAR blind test and identification of the August 16, 1997 Kara Sea event. Final report, 13 September 1995--31 January 1998

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

Baumgardt, D.

1998-03-31

The International Monitoring System (IMS) for the Comprehensive Test Ban Treaty (CTBT) faces the serious challenge of being able to accurately and reliably identify seismic events in any region of the world. Extensive research has been performed in recent years on developing discrimination techniques which appear to classify seismic events into broad categories of source types, such as nuclear explosion, earthquake, and mine blast. This report examines in detail the problem of effectiveness of regional discrimination procedures in the application of waveform discriminants to Special Event identification and the issue of discriminant transportability.

Automatic measurement of images on astrometric plates

NASA Astrophysics Data System (ADS)

Ortiz Gil, A.; Lopez Garcia, A.; Martinez Gonzalez, J. M.; Yershov, V.

1994-04-01

We present some results on the process of automatic detection and measurement of objects in overlapped fields of astrometric plates. The main steps of our algorithm are the following: determination of the Scale and Tilt between charge coupled devices (CCD) and microscope coordinate systems and estimation of signal-to-noise ratio in each field;--image identification and improvement of its position and size;--image final centering;--image selection and storage. Several parameters allow the use of variable criteria for image identification, characterization and selection. Problems related with faint images and crowded fields will be approached by special techniques (morphological filters, histogram properties and fitting models).

[High Precision Identification of Igneous Rock Lithology by Laser Induced Breakdown Spectroscopy].

PubMed

Wang, Chao; Zhang, Wei-gang; Yan, Zhi-quan

2015-09-01

In the field of petroleum exploration, lithology identification of finely cuttings sample, especially high precision identification of igneous rock with similar property, has become one of the geological problems. In order to solve this problem, a new method is proposed based on element analysis of Laser-Induced Breakdown Spectroscopy (LIBS) and Total Alkali versus Silica (TAS) diagram. Using independent LIBS system, factors influencing spectral signal, such as pulse energy, acquisition time delay, spectrum acquisition method and pre-ablation are researched through contrast experiments systematically. The best analysis conditions of igneous rock are determined: pulse energy is 50 mJ, acquisition time delay is 2 μs, the analysis result is integral average of 20 different points of sample's surface, and pre-ablation has been proved not suitable for igneous rock sample by experiment. The repeatability of spectral data is improved effectively. Characteristic lines of 7 elements (Na, Mg, Al, Si, K, Ca, Fe) commonly used for lithology identification of igneous rock are determined, and igneous rock samples of different lithology are analyzed and compared. Calibration curves of Na, K, Si are generated by using national standard series of rock samples, and all the linearly dependent coefficients are greater than 0.9. The accuracy of quantitative analysis is investigated by national standard samples. Element content of igneous rock is analyzed quantitatively by calibration curve, and its lithology is identified accurately by the method of TAS diagram, whose accuracy rate is 90.7%. The study indicates that LIBS can effectively achieve the high precision identification of the lithology of igneous rock.

On the Directional Dependence and Null Space Freedom in Uncertainty Bound Identification

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

1997-01-01

In previous work, the determination of uncertainty models via minimum norm model validation is based on a single set of input and output measurement data. Since uncertainty bounds at each frequency is directionally dependent for multivariable systems, this will lead to optimistic uncertainty levels. In addition, the design freedom in the uncertainty model has not been utilized to further reduce uncertainty levels. The above issues are addressed by formulating a min- max problem. An analytical solution to the min-max problem is given to within a generalized eigenvalue problem, thus avoiding a direct numerical approach. This result will lead to less conservative and more realistic uncertainty models for use in robust control.

Use of an Online Clinical Process Support System as an Aid to Identification and Management of Developmental and Mental Health Problems.

PubMed

Howard, Barbara J; Sturner, Raymond

2017-12-01

To describe benefits and problems with screening and addressing developmental and behavioral problems in primary care and using an online clinical process support system as a solution. Screening has been found to have various implementation barriers including time costs, accuracy, workflow and knowledge of tools. In addition, training of clinicians in dealing with identified issues is lacking. Patients disclose more to and prefer computerized screening. An online clinical process support system (CHADIS) shows promise in addressing these issues. Use of a comprehensive panel of online pre-visit screens; linked decision support to provide moment-of-care training; and post-visit activities and resources for patient-specific education, monitoring and care coordination is an efficient way to make the entire process of screening and follow up care feasible in primary care. CHADIS fulfills these requirements and provides Maintenance of Certification credit to physicians as well as added income for screening efforts.

REIMR - A Process for Utilizing Liquid Rocket Propulsion-Oriented 'Lessons Learned' to Mitigate Development Risk in Nuclear Thermal Propulsion

NASA Technical Reports Server (NTRS)

Ballard, RIchard O.

2006-01-01

This paper is a summary overview of a study conducted at the NASA Marshall Space Flight Center (NASA MSFC) during the initial phases of the Space Launch Initiative (SLI) program to evaluate a large number of technical problems associated with the design, development, test, evaluation and operation of several major liquid propellant rocket engine systems (i.e., SSME, Fastrac, J-2, F-1). One of the primary results of this study was the identification of the Fundamental Root Causes that enabled the technical problems to manifest, and practices that can be implemented to prevent them from recurring in future propulsion system development efforts, such as that which is currently envisioned in the field of nuclear thermal propulsion (NTF). This paper will discuss the Fundamental Root Causes, cite some examples of how the technical problems arose from them, and provide a discussion of how they can be mitigated or avoided in the development of an NTP system

A service-oriented data access control model

NASA Astrophysics Data System (ADS)

Meng, Wei; Li, Fengmin; Pan, Juchen; Song, Song; Bian, Jiali

2017-01-01

The development of mobile computing, cloud computing and distributed computing meets the growing individual service needs. Facing with complex application system, it's an urgent problem to ensure real-time, dynamic, and fine-grained data access control. By analyzing common data access control models, on the basis of mandatory access control model, the paper proposes a service-oriented access control model. By regarding system services as subject and data of databases as object, the model defines access levels and access identification of subject and object, and ensures system services securely to access databases.

Gait recognition based on integral outline

NASA Astrophysics Data System (ADS)

Ming, Guan; Fang, Lv

2017-02-01

Biometric identification technology replaces traditional security technology, which has become a trend, and gait recognition also has become a hot spot of research because its feature is difficult to imitate and theft. This paper presents a gait recognition system based on integral outline of human body. The system has three important aspects: the preprocessing of gait image, feature extraction and classification. Finally, using a method of polling to evaluate the performance of the system, and summarizing the problems existing in the gait recognition and the direction of development in the future.

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

PubMed Central

Yoon, Hyungchul; Hoskere, Vedhus; Park, Jong-Woong; Spencer, Billie F.

2017-01-01

Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc.) are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs) to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1) estimation of an appropriate scale factor; and (2) compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach. PMID:28891985

Gain-Scheduled Fault Tolerance Control Under False Identification

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine (Technical Monitor)

2006-01-01

An active fault tolerant control (FTC) law is generally sensitive to false identification since the control gain is reconfigured for fault occurrence. In the conventional FTC law design procedure, dynamic variations due to false identification are not considered. In this paper, an FTC synthesis method is developed in order to consider possible variations of closed-loop dynamics under false identification into the control design procedure. An active FTC synthesis problem is formulated into an LMI optimization problem to minimize the upper bound of the induced-L2 norm which can represent the worst-case performance degradation due to false identification. The developed synthesis method is applied for control of the longitudinal motions of FASER (Free-flying Airplane for Subscale Experimental Research). The designed FTC law of the airplane is simulated for pitch angle command tracking under a false identification case.

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Multi-level damage identification with response reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

OPUS: Optimal Projection for Uncertain Systems. Volume 1

DTIC Science & Technology

1991-09-01

unifiedI control- design methodology that directly addresses these technology issues. 1 In particular, optimal projection theory addresses the need for...effects, and limited identification accuracy in a 1-g environment. The principal contribution of OPUS is a unified design methodology that...characterizing solutions to constrained control- design problems. Transforming OPUS into a practi- cal design methodology requires the development of

A Comparison of Rule-Based, K-Nearest Neighbor, and Neural Net Classifiers for Automated

Treesearch

Tai-Hoon Cho; Richard W. Conners; Philip A. Araman

1991-01-01

Over the last few years the authors have been involved in research aimed at developing a machine vision system for locating and identifying surface defects on materials. The particular problem being studied involves locating surface defects on hardwood lumber in a species independent manner. Obviously, the accurate location and identification of defects is of paramount...

XRF map identification problems based on a PDE electrodeposition model

NASA Astrophysics Data System (ADS)

Sgura, Ivonne; Bozzini, Benedetto

2017-04-01

In this paper we focus on the following map identification problem (MIP): given a morphochemical reaction-diffusion (RD) PDE system modeling an electrodepostion process, we look for a time t *, belonging to the transient dynamics and a set of parameters \\mathbf{p} , such that the PDE solution, for the morphology h≤ft(x,y,{{t}\\ast};\\mathbf{p}\\right) and for the chemistry θ ≤ft(x,y,{{t}\\ast};\\mathbf{p}\\right) approximates a given experimental map M *. Towards this aim, we introduce a numerical algorithm using singular value decomposition (SVD) and Frobenius norm to give a measure of error distance between experimental maps for h and θ and simulated solutions of the RD-PDE system on a fixed time integration interval. The technique proposed allows quantitative use of microspectroscopy images, such as XRF maps. Specifically, in this work we have modelled the morphology and manganese distributions of nanostructured components of innovative batteries and we have followed their changes resulting from ageing under operating conditions. The availability of quantitative information on space-time evolution of active materials in terms of model parameters will allow dramatic improvements in knowledge-based optimization of battery fabrication and operation.

Laser-induced dissociation processes of protonated glucose: dehydration reactions vs cross-ring dissociation

NASA Astrophysics Data System (ADS)

Dyakov, Y. A.; Kazaryan, M. A.; Golubkov, M. G.; Gubanova, D. P.; Bulychev, N. A.; Kazaryan, S. M.

2018-04-01

Studying the processes occurring in biological systems under irradiation is critically important for understanding the principles of working of biological systems. One of the main problems, which stimulate interest to the processes of photo-induced excitation and ionization of biomolecules, is the necessity of their identification by various mass spectrometry (MS) methods. While simple analysis of small molecules became a standard MS technique long time ago, recognition of large molecules, especially carbohydrates, is still a difficult problem, and requires sophisticated techniques and complicated computer analysis. Due to the large variety of substances in the samples, as far as the complexity of the processes occurring after excitation/ionization of the molecules, the recognition efficiency of MS technique in terms of carbohydrates is still not high enough. Additional theoretical and experimental analysis of ionization and dissociation processes in various kinds of polysaccharides, beginning from the simplest ones, is necessary. In our work, we extent previous theoretical and experimental studies of saccharides, and concentrate our attention to protonated glucose. In this article we paid the most attention to the cross-ring dissociation and water loss reactions due to their importance for identification of various isomers of hydrocarbon molecules (for example, distinguish α- and β-glucose).

[Scientific bases of the organization of psychiatric care: the solution of practical problems in the framework of priority research].

PubMed

Yastrebov, V S; Mitikhin, V G; Solokhina, T A; Mitikhina, I A

ОBJECTIVE: a system analysis and modeling for important areas of research of the organization of psychiatric services in Russia in the study mental health of the population, identification of factors affecting the formation of the contingent of persons with mental disorders, organizational and functional structure of mental health services and mental health care. The authors analyzed scientific publications on the problems of psychiatric care organization as well as the results of own research over the last 25 years using system analysis. The approach that allows a creation of a range of population models to monitor the status of mental health based on medical, demographic and social factors (more than 60 factors) of life was suggested. The basic models and approaches for the evaluation of activity of divisions of mental health services at the macro and micro-social levels, taking into account expert information and individual characteristics of patients and relatives, were demonstrated. To improve treatment quality, the models of identification of the factors, which positively or negatively influenced the commitment to psychopharmacotherapy of patients with schizophrenia and their families, were developed.

An investigation into the feasibility of locating portable medical devices using radio frequency identification devices and technology.

PubMed

Britton, J

2007-01-01

Portable medical devices represent an important resource for assisting healthcare delivery. The movement of portable devices often results in them being unavailable when needed. Tracking equipment using radiofrequency identification technology/devices (RFID) may provide a promising solution to the problems encountered in locating portable equipment. An RFID technology trial was undertaken at Royal Alexandra Hospital, Paisley. This involved the temporary installation of three active readers and attaching actively transmitting radio frequency tags to different portable medical devices. The active readers and computer system were linked using a bespoke data network. Tags and readers from two separate manufacturers were tested. Reliability difficulties were encountered when testing the technology from the first manufacturer, probably due to the casing of the medical device interfering with the signal from the tag. Improved results were obtained when using equipment from the second manufacturer with an overall error rate of 12.3%. Tags from this manufacturer were specifically designed to overcome problems observed with the first system tested. Findings from this proof of concept trial suggest that RFID technology could be used to track the location of equipment in a hospital.

Resident Evaluation and Remediation: A Comprehensive Approach

PubMed Central

Wu, Jim S.; Siewert, Bettina; Boiselle, Phillip M.

2010-01-01

Background A comprehensive evaluation and remediation program is an essential component of any residency program. The evaluation system should identify problems accurately and early and allow residents with problems to be assigned to a remediation program that effectively deals with them. Elements of a proactive remediation program include a process for outlining deficiencies, providing resources for improvement, communicating clear goals for acceptable performance, and reevaluating performance against these goals. Intervention In recognition of the importance of early detection and prompt remediation of the struggling resident, we sought to develop a multifaceted approach to resident evaluation with the aim of early identification and prompt remediation of difficulties. This article describes our comprehensive evaluation program and remediation program, which uses resources within our radiology department and institutional graduate medical education office. Discussion An effective evaluation system should identify problems accurately and early, whereas a proactive remediation program should effectively deal with issues once they are identified. PMID:21975628

Image enhancement and quality measures for dietary assessment using mobile devices

NASA Astrophysics Data System (ADS)

Xu, Chang; Zhu, Fengqing; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2012-03-01

Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. We are developing a system, known as the mobile device food record (mdFR), to automatically identify and quantify foods and beverages consumed based on analyzing meal images captured with a mobile device. The mdFR makes use of a fiducial marker and other contextual information to calibrate the imaging system so that accurate amounts of food can be estimated from the scene. Food identification is a difficult problem since foods can dramatically vary in appearance. Such variations may arise not only from non-rigid deformations and intra-class variability in shape, texture, color and other visual properties, but also from changes in illumination and viewpoint. To address the color consistency problem, this paper describes illumination quality assessment methods implemented on a mobile device and three post color correction methods.

Image Enhancement and Quality Measures for Dietary Assessment Using Mobile Devices

PubMed Central

Xu, Chang; Zhu, Fengqing; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2016-01-01

Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. We are developing a system, known as the mobile device food record (mdFR), to automatically identify and quantify foods and beverages consumed based on analyzing meal images captured with a mobile device. The mdFR makes use of a fiducial marker and other contextual information to calibrate the imaging system so that accurate amounts of food can be estimated from the scene. Food identification is a difficult problem since foods can dramatically vary in appearance. Such variations may arise not only from non-rigid deformations and intra-class variability in shape, texture, color and other visual properties, but also from changes in illumination and viewpoint. To address the color consistency problem, this paper describes illumination quality assessment methods implemented on a mobile device and three post color correction methods. PMID:28572695

Cause-and-effect analysis of risk management files to assess patient care in the emergency department.

PubMed

White, Andrew A; Wright, Seth W; Blanco, Roberto; Lemonds, Brent; Sisco, Janice; Bledsoe, Sandy; Irwin, Cindy; Isenhour, Jennifer; Pichert, James W

2004-10-01

Identifying the etiologies of adverse outcomes is an important first step in improving patient safety and reducing malpractice risks. However, relatively little is known about the causes of emergency department-related adverse outcomes. The objective was to describe a method for identification of common causes of adverse outcomes in an emergency department. This methodology potentially can suggest ways to improve care and might provide a model for identification of factors associated with adverse outcomes. This was a retrospective analysis of 74 consecutive files opened by a malpractice insurer between 1995 and 2000. Each risk-management file was analyzed to identify potential causes of adverse outcomes. The main outcomes were rater-assigned codes for alleged problems with care (e.g., failures of communication or problems related to diagnosis). About 50% of cases were related to injuries or abdominal complaints. A contributing cause was found in 92% of cases, and most had more than one contributing cause. The most frequent contributing categories included failure to diagnose (45%), supervision problems (31%), communication problems (30%), patient behavior (24%), administrative problems (20%), and documentation (20%). Specific relating factors within these categories, such as lack of timely resident supervision and failure to follow policies and procedures, were identified. This project documented that an aggregate analysis of risk-management files has the potential to identify shared causes related to real or perceived adverse outcomes. Several potentially correctable systems problems were identified using this methodology. These simple, descriptive management tools may be useful in identifying issues for problem solving and can be easily learned by physicians and managers.

New program for identification of child maltreatment in emergency department: preliminary data.

PubMed

Milani, Gregorio P; Vianello, Federica A; Cantoni, Barbara; Agostoni, Carlo; Fossali, Emilio F

2016-07-13

Early detection of child maltreatment in pediatric emergency department is one of the most important challenges for the Italian and European medical care system. Several interventions have been proposed, but results are often unquantifiable or inadequate to face this problem. We promoted an educational program and built up an interdisciplinary team to improve the identification and management of maltreated children. Aim of this study is to report preliminary results of these interventions. Meetings structured with lecture-based teaching and case-based lessons were focused on identification and management of maltreatment cases. An interdisciplinary team with forensic physicians, dermatologists, orthopedics, radiologists, gynecologists, oculists, psychologists and psychiatrics, was created to manage children with suspected diagnosis of maltreatment. We analysed the characteristics of subjects diagnosed after these interventions and their number was compared with the one in the two previous years. An increased rate of diagnoses of 16.9 % was found. Results of the reported program are encouraging, but many efforts are still mandatory to improve the child maltreatment identification in emergency departments.

Patient and Sample Identification. Out of the Maze?

PubMed

Lippi, Giuseppe; Chiozza, Laura; Mattiuzzi, Camilla; Plebani, Mario

2017-04-01

Patient and sample misidentification may cause significant harm or discomfort to the patients, especially when incorrect data is used for performing specific healthcare activities. It is hence obvious that efficient and quality care can only start from accurate patient identification. There are many opportunities for misidentification in healthcare and laboratory medicine, including homonymy, incorrect patient registration, reliance on wrong patient data, mistakes in order entry, collection of biological specimens from wrong patients, inappropriate sample labeling and inaccurate entry or erroneous transmission of test results through the laboratory information system. Many ongoing efforts are made to prevent this important healthcare problem, entailing streamlined strategies for identifying patients throughout the healthcare industry by means of traditional and innovative identifiers, as well as using technologic tools that may enhance both the quality and efficiency of blood tubes labeling. The aim of this article is to provide an overview about the liability of identification errors in healthcare, thus providing a pragmatic approach for diverging the so-called patient identification crisis.

Registrations of Assistance Dogs in California for Identification Tags: 1999–2012

PubMed Central

Yamamoto, Mariko; Lopez, Mayllynne T.; Hart, Lynette A.

2015-01-01

Dogs are filling a growing number of roles supporting people with various disabilities, leading to a chaotic situation in the U.S. Although the federal laws allow public access with working dogs only for people with disabilities, no governmental enforcement or management system for such dogs exists. Furthermore, there is no substantive way to confirm whether the dog is an adequately trained assistance dog or not, as neither the handlers nor the dogs are required to carry any particular certification or identification. Therefore, unqualified assistance dogs and incidents such as dog bites by assistance dogs sometimes are problems in the U.S. A governmental oversight system could reduce problems, but no information is available about the current uses of assistance dogs in the U.S. We aimed to investigate the current demographics of registered assistance dogs and the evolving patterns in uses of dogs during 1999–2012 in California. We acquired data on assistance dogs registered by animal control facilities throughout California. We used descriptive statistics to describe the uses of these assistance dogs. The number of assistance dogs sharply increased, especially service dogs, in the past decade. Dogs with small body sizes, and new types of service dogs, such as service dogs for psychiatric and medical assistance, strongly contributed to the increase. The Assistance Dog Identification tags sometimes were mistakenly issued to dogs not fitting the definition of assistance dogs under the law, such as emotional support animals and some cats; this reveals errors in the California governmental registering system. Seemingly inappropriate dogs also were registered, such as those registered for the first time at older than 10 years of age. This study reveals a prevalence of misuse and misunderstanding of regulations and legislation on assistance dogs in California. PMID:26287610

Feasibility of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) networking in university hospitals in Brussels.

PubMed

Martiny, D; Cremagnani, P; Gaillard, A; Miendje Deyi, V Y; Mascart, G; Ebraert, A; Attalibi, S; Dediste, A; Vandenberg, O

2014-05-01

The mutualisation of analytical platforms might be used to address rising healthcare costs. Our study aimed to evaluate the feasibility of networking a unique matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) system for common use in several university hospitals in Brussels, Belgium. During a one-month period, 1,055 successive bacterial isolates from the Brugmann University Hospital were identified on-site using conventional techniques; these same isolates were also identified using a MALDI-TOF MS system at the Porte de Hal Laboratory by sending target plates and identification projects via transportation and the INFECTIO_MALDI software (Infopartner, Nancy, France), respectively. The occurrence of transmission problems (<2 %) and human errors (<1 %) suggested that the system was sufficiently robust to be implemented in a network. With a median time-to-identification of 5 h and 11 min (78 min, min-max: 154-547), MALDI-TOF MS networking always provided a faster identification result than conventional techniques, except when chromogenic culture media and oxidase tests were used (p < 0.0001). However, the limited clinical benefits of the chromogenic culture media do not support their extra cost. Our financial analysis also suggested that MALDI-TOF MS networking could lead to substantial annual cost savings. MALDI-TOF MS networking presents many advantages, and few conventional techniques (optochin and oxidase tests) are required to ensure the same quality in patient care from the distant laboratory. Nevertheless, such networking should not be considered unless there is a reorganisation of workflow, efficient communication between teams, qualified technologists and a reliable IT department and helpdesk to manage potential connectivity problems.

System identification and model reduction using modulating function techniques

NASA Technical Reports Server (NTRS)

Shen, Yan

1993-01-01

Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

Problems of identification associated with victims of aerodisaster: the Port Harcourt experience in December 2005.

PubMed

Seleye-Fubara, D; Etebu, E N; Athanasius, B P

2012-01-01

The problems associated with identification of victims after mass disaster such as aero-accident require an elaborate study with an attempt at proffering solutions in the midst of limited facilities. This is a case study of aero-disaster carried out by the authors at Port Harcourt International Airport on 10th December 2005. Information was adequately disseminated through different media to alert the public to come for the identification of the bodies. The 106 victims were then separated into those whose bodies were intact with few areas of burns, crushed/multiple fractures, those with severe burns, and dismembered or disintegrated bodies. Problems of identification was noticed in 26 (24.5%) of the victims which form the basis for this study. Those disputed by more than one family n = 11 (42.3%), those without dispute but very difficult to identify n = 6 (23.1%) and those that could not be identified n = 9 (34.6%). The cause of the identification difficulty also ranged from total disintegration of the bodies n = 9 (34.6%), severely burnt bodies n = 12 (46.2%) to those crushed with multiple fractures n = 5 (19.2%). Problems of identification of severely injured victims of aero-disaster in a limited facility setting can be minimized if strict and well documented pre-travel biometric profiles are taken. Facility for DNA fingerprint, forensic odontologists and forensic anthropologist should be provided. There should also be institution of aviation accident investigation team (AAIT) and mass disaster planning team (MDPT) to aid the identification of victims and probe into the cause and effect of the accident.

Countering MANPADS: study of new concepts and applications: part two

NASA Astrophysics Data System (ADS)

Maltese, Dominique; Vergnolle, Jean-François; Aragones, Julien; Renaudat, Mathieu

2007-04-01

The latest events of ground-to-air Man Portable Air Defense (MANPAD) attacks against aircraft have revealed a new threat both for military and civilian aircraft. Consequently, the implementation of protecting systems (i.e. Directed Infra Red Counter Measure - DIRCM) in order to face IR guided missiles turns out to be now inevitable. In a near future, aircraft will have to possess detection, tracking, identification, targeting and jamming capabilities to face MANPAD threats. Besides, Multiple Missiles attacks become more and more current scenarios to deal with. In this paper, a practical example of DIRCM systems under study at SAGEM DEFENSE & SECURITY Company is presented. The article is the continuation of a previous SPIE one. Self-protection solutions include built-in and automatic locking-on, tracking, identification and laser jamming capabilities, including defeat assessment. Target Designations are provided by a Missile Warning System. Targets scenarios including multiple threats are considered to design systems architectures. In a first step, the article reminds the context, current and future threats (IR seekers of different generations...), and scenarios for system definition. Then, it focuses on potential self-protection systems under study at SAGEM DEFENSE & SECURITY Company. Different strategies including target identification, multi band laser and active imagery have been previously studied in order to design DIRCM System solutions. Thus, results of self-protection scenarios are provided for different MANPAD scenarios to highlight key problems to solve. Data have been obtained from simulation software modeling full DIRCM systems architectures on technical and operational scenarios (parametric studies).

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

NASA Astrophysics Data System (ADS)

Potters, M. G.; Bombois, X.; Mansoori, M.; Hof, Paul M. J. Van den

2016-08-01

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

A Computational Procedure for Identifying Bilinear Representations of Nonlinear Systems Using Volterra Kernels

NASA Technical Reports Server (NTRS)

Kvaternik, Raymond G.; Silva, Walter A.

2008-01-01

A computational procedure for identifying the state-space matrices corresponding to discrete bilinear representations of nonlinear systems is presented. A key feature of the method is the use of first- and second-order Volterra kernels (first- and second-order pulse responses) to characterize the system. The present method is based on an extension of a continuous-time bilinear system identification procedure given in a 1971 paper by Bruni, di Pillo, and Koch. The analytical and computational considerations that underlie the original procedure and its extension to the title problem are presented and described, pertinent numerical considerations associated with the process are discussed, and results obtained from the application of the method to a variety of nonlinear problems from the literature are presented. The results of these exploratory numerical studies are decidedly promising and provide sufficient credibility for further examination of the applicability of the method.

Instationary Generalized Stokes Equations in Partially Periodic Domains

NASA Astrophysics Data System (ADS)

Sauer, Jonas

2018-06-01

We consider an instationary generalized Stokes system with nonhomogeneous divergence data under a periodic condition in only some directions. The problem is set in the whole space, the half space or in (after an identification of the periodic directions with a torus) bounded domains with sufficiently regular boundary. We show unique solvability for all times in Muckenhoupt weighted Lebesgue spaces. The divergence condition is dealt with by analyzing the associated reduced Stokes system and in particular by showing maximal regularity of the partially periodic reduced Stokes operator.

Computational cameras for moving iris recognition

NASA Astrophysics Data System (ADS)

McCloskey, Scott; Venkatesha, Sharath

2015-05-01

Iris-based biometric identification is increasingly used for facility access and other security applications. Like all methods that exploit visual information, however, iris systems are limited by the quality of captured images. Optical defocus due to a small depth of field (DOF) is one such challenge, as is the acquisition of sharply-focused iris images from subjects in motion. This manuscript describes the application of computational motion-deblurring cameras to the problem of moving iris capture, from the underlying theory to system considerations and performance data.

Data fusion approach to threat assessment for radar resources management

NASA Astrophysics Data System (ADS)

Komorniczak, Wojciech; Pietrasinski, Jerzy; Solaiman, Basel

2002-03-01

The paper deals with the problem of the multifunction radar resources management. The problem consists of target/tasks ranking and tasks scheduling. The paper is focused on the target ranking, with the data fusion approach. The data from the radar (object's velocity, range, altitude, direction etc.), IFF system (Identification Friend or Foe) and ESM system (Electronic Support Measures - information concerning threat's electro - magnetic activities) is used to decide of the importance assignment for each detected target. The main problem consists of the multiplicity of various types of the input information. The information from the radar is of the probabilistic or ambiguous imperfection type and the IFF information is of evidential type. To take the advantage of these information sources the advanced data fusion system is necessary. The system should deal with the following situations: fusion of the evidential and fuzzy information, fusion of the evidential information and a'priori information. The paper describes the system which fuses the fuzzy and the evidential information without previous change to the same type of information. It is also described the proposal of using of the dynamic fuzzy qualifiers. The paper shows the results of the preliminary system's tests.

Implementation of an algorithm for cylindrical object identification using range data

NASA Technical Reports Server (NTRS)

Bozeman, Sylvia T.; Martin, Benjamin J.

1989-01-01

One of the problems in 3-D object identification and localization is addressed. In robotic and navigation applications the vision system must be able to distinguish cylindrical or spherical objects as well as those of other geometric shapes. An algorithm was developed to identify cylindrical objects in an image when range data is used. The algorithm incorporates the Hough transform for line detection using edge points which emerge from a Sobel mask. Slices of the data are examined to locate arcs of circles using the normal equations of an over-determined linear system. Current efforts are devoted to testing the computer implementation of the algorithm. Refinements are expected to continue in order to accommodate cylinders in various positions. A technique is sought which is robust in the presence of noise and partial occlusions.

Infection caused by thymidine-requiring, trimethoprim-resistant bacteria.

PubMed Central

King, C H; Shlaes, D M; Dul, M J

1983-01-01

We first noted the appearance of thymidine-requiring, gram-negative bacilli in clinical specimens 2 years ago. Since then we have seen 10 patients colonized or infected with these organisms. These strains do not grow on Mueller-Hinton media, growth on MacConkey agar is variable, and growth in API 20E (Analytab Products) and Enterobacteriaceae-Plus Cards (AutoMicrobic system; Vitek Systems Inc.) is inadequate for reliable identifications. Thymidine-requiring organisms are routinely resistant to sulfonamides and trimethoprim. Infection or colonization is associated with previous sulfamethoxazole-trimethoprim therapy in most cases. Of 10 patients, 1 had septicemia of urinary tract origin, 5 had urinary tract colonization or infection, 2 had wound colonization, and two had colonization of respiratory secretions. Thymidine-requiring, gram-negative bacilli can be pathogens and present potential problems in diagnosis, identification, and susceptibility testing. PMID:6604070

Applications of wind generation for power system frequency control, inter-area oscillations damping and parameter identification

NASA Astrophysics Data System (ADS)

Wilches-Bernal, Felipe

Power systems around the world are experiencing a continued increase in wind generation as part of their energy mix. Because of its power electronics interface, wind energy conversion systems interact differently with the grid than conventional generation. These facts are changing the traditional dynamics that regulate power system behavior and call for a re-examination of traditional problems encountered in power systems like frequency response, inter-area oscillations and parameter identification. To address this need, realistic models for wind generation are necessary. The dissertation implements such models in a MATLAB-based flexible environment suited for power system research. The dissertation continues with an analysis of the frequency response of a test power system dependent mainly on a mode referred to as the frequency regulation mode. Using this test system it is shown that its frequency regulation capability is reduced with wind penetration levels of 25% and above. A controller for wind generation to restore the frequency response of the system is then presented. The proposed controller requires the WTG to operate in a deloaded mode, a condition that is obtained through pitching the wind turbine blades. Time simulations at wind penetration levels of 25% and 50% are performed to demonstrate the effectiveness of the proposed controller. Next, the dissertation evaluates how the inter-area oscillation of a two-machine power system is affected by wind integration. The assessment is performed based on the positioning of the WTG, the level of wind penetration, and the loading condition of the system. It is determined that integrating wind reduces the damping of the inter-area mode of the system when performed in an area that imports power. For this worst-case scenario, the dissertation proposes two controllers for wind generation to improve the damping of the inter-area mode. The first controller uses frequency as feedback signal for the active power control of the WTG while the second controller manipulates the reactive power control of the WTG using the current magnitude as the feedback signal. Finally, the dissertation proposes a parameter identification method for identifying and verifying the reactive power control parameters of WTGs. Using voltage and current measurements of a wind unit as an input, the proposed method estimates an optimal set of parameters such that the output current of a standalone WTG model better approximates the measured signal. Because WTG are nonlinear systems, the identification method is solved by a Gauss-Newton iteration used to calculate the solution of a nonlinear least-squares problem. The effectiveness of the proposed method is illustrated using a set of simulated data and actual PMU recordings.

A Programming Environment Evaluation Methodology for Object-Oriented Systems. Ph.D Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Moreau, Dennis R.

1987-01-01

The object-oriented design strategy as both a problem decomposition and system development paradigm has made impressive inroads into the various areas of the computing sciences. Substantial development productivity improvements have been demonstrated in areas ranging from artificial intelligence to user interface design. However, there has been very little progress in the formal characterization of these productivity improvements and in the identification of the underlying cognitive mechanisms. The development and validation of models and metrics of this sort require large amounts of systematically-gathered structural and productivity data. There has, however, been a notable lack of systematically-gathered information on these development environments. A large part of this problem is attributable to the lack of a systematic programming environment evaluation methodology that is appropriate to the evaluation of object-oriented systems.

Identification of pilot-vehicle dynamics from simulation and flight test

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1990-01-01

The paper discusses an identification problem in which a basic feedback control structure, or pilot control strategy, is hypothesized. Identification algorithms are employed to determine the particular form of pilot equalization in each feedback loop. It was found that both frequency- and time-domain identification techniques provide useful information.

[Quality assessment in anesthesia].

PubMed

Kupperwasser, B

1996-01-01

Quality assessment (assurance/improvement) is the set of methods used to measure and improve the delivered care and the department's performance against pre-established criteria or standards. The four stages of the self-maintained quality assessment cycle are: problem identification, problem analysis, problem correction and evaluation of corrective actions. Quality assessment is a measurable entity for which it is necessary to define and calibrate measurement parameters (indicators) from available data gathered from the hospital anaesthesia environment. Problem identification comes from the accumulation of indicators. There are four types of quality indicators: structure, process, outcome and sentinel indicators. The latter signal a quality defect, are independent of outcomes, are easier to analyse by statistical methods and closely related to processes and main targets of quality improvement. The three types of methods to analyse the problems (indicators) are: peer review, quantitative methods and risks management techniques. Peer review is performed by qualified anaesthesiologists. To improve its validity, the review process should be explicited and conclusions based on standards of practice and literature references. The quantitative methods are statistical analyses applied to the collected data and presented in a graphic format (histogram, Pareto diagram, control charts). The risks management techniques include: a) critical incident analysis establishing an objective relationship between a 'critical' event and the associated human behaviours; b) system accident analysis, based on the fact that accidents continue to occur despite safety systems and sophisticated technologies, checks of all the process components leading to the impredictable outcome and not just the human factors; c) cause-effect diagrams facilitate the problem analysis in reducing its causes to four fundamental components (persons, regulations, equipment, process). Definition and implementation of corrective measures, based on the findings of the two previous stages, are the third step of the evaluation cycle. The Hawthorne effect is an outcome improvement, before the implementation of any corrective actions. Verification of the implemented actions is the final and mandatory step closing the evaluation cycle.

Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

PubMed Central

Nandola, Naresh N.; Rivera, Daniel E.

2011-01-01

This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

Robust finger vein ROI localization based on flexible segmentation.

PubMed

Lu, Yu; Xie, Shan Juan; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2013-10-24

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system.

Robust Finger Vein ROI Localization Based on Flexible Segmentation

PubMed Central

Lu, Yu; Xie, Shan Juan; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2013-01-01

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system. PMID:24284769

Analysis and identification of subsynchronous vibration for a high pressure parallel flow centrifugal compressor

NASA Technical Reports Server (NTRS)

Kirk, R. G.; Nicholas, J. C.; Donald, G. H.; Murphy, R. C.

1980-01-01

The summary of a complete analytical design evaluation of an existing parallel flow compressor is presented and a field vibration problem that manifested itself as a subsynchronous vibration that tracked at approximately 2/3 of compressor speed is reviewed. The comparison of predicted and observed peak response speeds, frequency spectrum content, and the performance of the bearing-seal systems are presented as the events of the field problem are reviewed. Conclusions and recommendations are made as to the degree of accuracy of the analytical techniques used to evaluate the compressor design.

Modeling human target acquisition in ground-to-air weapon systems

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Mohr, R. L.; Vikmanis, M.; Wei, K. C.

1982-01-01

The problems associated with formulating and validating mathematical models for describing and predicting human target acquisition response are considered. In particular, the extension of the human observer model to include the acquisition phase as well as the tracking segment is presented. Relationship of the Observer model structure to the more complex Standard Optimal Control model formulation and to the simpler Transfer Function/Noise representation is discussed. Problems pertinent to structural identifiability and the form of the parameterization are elucidated. A systematic approach toward the identification of the observer acquisition model parameters from ensemble tracking error data is presented.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

NASA Astrophysics Data System (ADS)

Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

2017-03-01

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

AIRID: an application of the KAS/Prospector expert system builder to airplane identification

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

Aldridge, J.P.

1984-01-01

The Knowledge Acquisition System/Prospector expert system building tool developed by SRI, International, has been used to construct an expert system to identify aircraft on the basis of observables such as wing shape, engine number/location, fuselage shape, and tail assembly shape. Additional detailed features are allowed to influence the identification as other favorable features. Constraints on the observations imposed by bad weather and distant observations have been included as contexts to the models. Models for Soviet and US fighter aircraft have been included. Inclusion of other types of aircraft such as bombers, transports, and reconnaissance craft is straightforward. Two models permitmore » exploration of the interaction of semantic and taxonomic networks with the models. A full set of text data for fluid communication with the user has been included. The use of demons as triggered output responses to enhance utility to the user has been explored. This paper presents discussion of the ease of building the expert system using this powerful tool and problems encountered in the construction process.« less

Mathematical Techniques for System Realization and Identification.

DTIC Science & Technology

1986-02-26

OZGULER, P. KHARGCNEKAR, J. RIBERA , and T. GEORGIOU. Also supported was the Principal Investigator (partial sumier support only) and various short-term...1982] "Skew-primeness in the regulator problem with internal stability", Ph.D. dissertation, University of Florida, 63 pages. J. RIBERA [1982...Research Institute, Kocaeli, TURKEY) Dr. J. Ribera , doctoral student (now on faculty of I. E. S. E., Barcelona, SPAIN) Dr. A. Tannenbaum, Visiting

The Stigma of Mental Illness as a Barrier to Self Labeling as Having a Mental Illness.

PubMed

Stolzenburg, Susanne; Freitag, Simone; Evans-Lacko, Sara; Muehlan, Holger; Schmidt, Silke; Schomerus, Georg

2017-12-01

The aim of this study was to investigate whether personal stigma decreases self-identification as having a mental illness in individuals with untreated mental health problems. We interviewed 207 persons with a currently untreated mental health problem as confirmed by a structured diagnostic interview. Measures included symptom appraisal, self-identification as having a mental illness (SELFI), self-labeling (open-ended question on the nature of their problem) stigma-related variables (explicit and implicit), as well as sociodemographics, current symptom severity, and previous treatment. Support for discrimination and implicit stigmatizing attitude were both associated with lower likelihood of self-identification. More social distance and support for discrimination were associated with less self-labeling. Previous treatment was the strongest predictor of symptom appraisal, SELFI, and self-labeling. Destigmatizing mental illness could increase awareness of personal mental health problems, potentially leading to lower rates of untreated mental illness.

Fastidious Gram-Negatives: Identification by the Vitek 2 Neisseria-Haemophilus Card and by Partial 16S rRNA Gene Sequencing Analysis.

PubMed

Sönksen, Ute Wolff; Christensen, Jens Jørgen; Nielsen, Lisbeth; Hesselbjerg, Annemarie; Hansen, Dennis Schrøder; Bruun, Brita

2010-12-31

Taxonomy and identification of fastidious Gram negatives are evolving and challenging. We compared identifications achieved with the Vitek 2 Neisseria-Haemophilus (NH) card and partial 16S rRNA gene sequence (526 bp stretch) analysis with identifications obtained with extensive phenotypic characterization using 100 fastidious Gram negative bacteria. Seventy-five strains represented 21 of the 26 taxa included in the Vitek 2 NH database and 25 strains represented related species not included in the database. Of the 100 strains, 31 were the type strains of the species. Vitek 2 NH identification results: 48 of 75 database strains were correctly identified, 11 strains gave `low discrimination´, seven strains were unidentified, and nine strains were misidentified. Identification of 25 non-database strains resulted in 14 strains incorrectly identified as belonging to species in the database. Partial 16S rRNA gene sequence analysis results: For 76 strains phenotypic and sequencing identifications were identical, for 23 strains the sequencing identifications were either probable or possible, and for one strain only the genus was confirmed. Thus, the Vitek 2 NH system identifies most of the commonly occurring species included in the database. Some strains of rarely occurring species and strains of non-database species closely related to database species cause problems. Partial 16S rRNA gene sequence analysis performs well, but does not always suffice, additional phenotypical characterization being useful for final identification.

Fastidious Gram-Negatives: Identification by the Vitek 2 Neisseria-Haemophilus Card and by Partial 16S rRNA Gene Sequencing Analysis

PubMed Central

Sönksen, Ute Wolff; Christensen, Jens Jørgen; Nielsen, Lisbeth; Hesselbjerg, Annemarie; Hansen, Dennis Schrøder; Bruun, Brita

2010-01-01

Taxonomy and identification of fastidious Gram negatives are evolving and challenging. We compared identifications achieved with the Vitek 2 Neisseria-Haemophilus (NH) card and partial 16S rRNA gene sequence (526 bp stretch) analysis with identifications obtained with extensive phenotypic characterization using 100 fastidious Gram negative bacteria. Seventy-five strains represented 21 of the 26 taxa included in the Vitek 2 NH database and 25 strains represented related species not included in the database. Of the 100 strains, 31 were the type strains of the species. Vitek 2 NH identification results: 48 of 75 database strains were correctly identified, 11 strains gave `low discrimination´, seven strains were unidentified, and nine strains were misidentified. Identification of 25 non-database strains resulted in 14 strains incorrectly identified as belonging to species in the database. Partial 16S rRNA gene sequence analysis results: For 76 strains phenotypic and sequencing identifications were identical, for 23 strains the sequencing identifications were either probable or possible, and for one strain only the genus was confirmed. Thus, the Vitek 2 NH system identifies most of the commonly occurring species included in the database. Some strains of rarely occurring species and strains of non-database species closely related to database species cause problems. Partial 16S rRNA gene sequence analysis performs well, but does not always suffice, additional phenotypical characterization being useful for final identification. PMID:21347215

Factors Affecting the Identification of Research Problems in Educational Administration Studies

ERIC Educational Resources Information Center

Yalçin, Mikail; Bektas, Fatih; Öztekin, Özge; Karadag, Engin

2016-01-01

The purpose of this study is to reveal the factors that affect the identification of research problems in educational administration studies. The study was designed using the case study method. Criterion sampling was used to determine the work group; the criterion used to select the participants was that of having a study in the field of…

Model Identification in Time-Series Analysis: Some Empirical Results.

ERIC Educational Resources Information Center

Padia, William L.

Model identification of time-series data is essential to valid statistical tests of intervention effects. Model identification is, at best, inexact in the social and behavioral sciences where one is often confronted with small numbers of observations. These problems are discussed, and the results of independent identifications of 130 social and…

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Systematic technology transfer from biology to engineering.

PubMed

Vincent, Julian F V; Mann, Darrell L

2002-02-15

Solutions to problems move only very slowly between different disciplines. Transfer can be greatly speeded up with suitable abstraction and classification of problems. Russian researchers working on the TRIZ (Teoriya Resheniya Izobretatelskikh Zadatch) method for inventive problem solving have identified systematic means of transferring knowledge between different scientific and engineering disciplines. With over 1500 person years of effort behind it, TRIZ represents the biggest study of human creativity ever conducted, whose aim has been to establish a system into which all known solutions can be placed, classified in terms of function. At present, the functional classification structure covers nearly 3 000 000 of the world's successful patents and large proportions of the known physical, chemical and mathematical knowledge-base. Additional tools are the identification of factors which prevent the attainment of new technology, leading directly to a system of inventive principles which will resolve the impasse, a series of evolutionary trends of development, and to a system of methods for effecting change in a system (Su-fields). As yet, the database contains little biological knowledge despite early recognition by the instigator of TRIZ (Genrich Altshuller) that one day it should. This is illustrated by natural systems evolved for thermal stability and the maintenance of cleanliness.

Neural network for intelligent query of an FBI forensic database

NASA Astrophysics Data System (ADS)

Uvanni, Lee A.; Rainey, Timothy G.; Balasubramanian, Uma; Brettle, Dean W.; Weingard, Fred; Sibert, Robert W.; Birnbaum, Eric

1997-02-01

Examiner is an automated fired cartridge case identification system utilizing a dual-use neural network pattern recognition technology, called the statistical-multiple object detection and location system (S-MODALS) developed by Booz(DOT)Allen & Hamilton, Inc. in conjunction with Rome Laboratory. S-MODALS was originally designed for automatic target recognition (ATR) of tactical and strategic military targets using multisensor fusion [electro-optical (EO), infrared (IR), and synthetic aperture radar (SAR)] sensors. Since S-MODALS is a learning system readily adaptable to problem domains other than automatic target recognition, the pattern matching problem of microscopic marks for firearms evidence was analyzed using S-MODALS. The physics; phenomenology; discrimination and search strategies; robustness requirements; error level and confidence level propagation that apply to the pattern matching problem of military targets were found to be applicable to the ballistic domain as well. The Examiner system uses S-MODALS to rank a set of queried cartridge case images from the most similar to the least similar image in reference to an investigative fired cartridge case image. The paper presents three independent tests and evaluation studies of the Examiner system utilizing the S-MODALS technology for the Federal Bureau of Investigation.

Theoretic aspects of the identification of the parameters in the optimal control model

NASA Technical Reports Server (NTRS)

Vanwijk, R. A.; Kok, J. J.

1977-01-01

The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.

Integrated system of occupational safety and health and fire protection of the fire rescue brigades members.

PubMed

Božović, Marijola; Živković, Snežana; Mihajlović, Emina

2018-06-01

The objective of the conducted research is the identification and determination of requirements of members of fire rescue brigades during operations in the conditions of high risk in order to minimize the possibilities for injury incidence during the intervention. The research is focused on examination, determination and identification of factors affecting the increasing number of occupational injuries of members of fire rescue brigades during interventions. Hypothetical framework of the research problem consists of general hypothesis and six special hypotheses. Results suggest that almost all respondents believe that their skills and abilities are applicable in the intervention phase, but less than a half believe that their skills are applicable in prevention phase. Two-thirds of respondents stated that in their organization they have support for further education and upgrading while a half of respondents stated that they need education concerning identification, assessment and management of risks that can lead to emergency situations.

Private content identification based on soft fingerprinting

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav; Holotyak, Taras; Koval, Oleksiy; Beekhof, Fokko; Farhadzadeh, Farzad

2011-02-01

In many problems such as biometrics, multimedia search, retrieval, recommendation systems requiring privacypreserving similarity computations and identification, some binary features are stored in the public domain or outsourced to third parties that might raise certain privacy concerns about the original data. To avoid this privacy leak, privacy protection is used. In most cases, privacy protection is uniformly applied to all binary features resulting in data degradation and corresponding loss of performance. To avoid this undesirable effect we propose a new privacy amplification technique that is based on data hiding principles and benefits from side information about bit reliability a.k.a. soft fingerprinting. In this paper, we investigate the identification-rate vs privacy-leak trade-off. The analysis is performed for the case of a perfect match between side information shared between the encoder and decoder as well as for the case of partial side information.

Unsupervised real-time speaker identification for daily movies

NASA Astrophysics Data System (ADS)

Li, Ying; Kuo, C.-C. Jay

2002-07-01

The problem of identifying speakers for movie content analysis is addressed in this paper. While most previous work on speaker identification was carried out in a supervised mode using pure audio data, more robust results can be obtained in real-time by integrating knowledge from multiple media sources in an unsupervised mode. In this work, both audio and visual cues will be employed and subsequently combined in a probabilistic framework to identify speakers. Particularly, audio information is used to identify speakers with a maximum likelihood (ML)-based approach while visual information is adopted to distinguish speakers by detecting and recognizing their talking faces based on face detection/recognition and mouth tracking techniques. Moreover, to accommodate for speakers' acoustic variations along time, we update their models on the fly by adapting to their newly contributed speech data. Encouraging results have been achieved through extensive experiments, which shows a promising future of the proposed audiovisual-based unsupervised speaker identification system.

Disproportionality and Learning Disabilities: Parsing Apart Race, Socioeconomic Status, and Language

PubMed Central

Shifrer, Dara; Muller, Chandra; Callahan, Rebecca

2014-01-01

The disproportionate identification of learning disabilities among certain socio-demographic subgroups, typically groups who are already disadvantaged, is perceived as a persistent problem within the education system. The academic and social experiences of students who are misidentified with a learning disability may be severely restricted, while students with a learning disability who are never identified are less likely to receive the accommodations and modifications necessary to learn at their maximum potential. We use the Education Longitudinal Study of 2002 to describe national patterns in learning disability identification. Results indicate that socio-demographic characteristics are predictive of identification with a learning disability. While some conventional areas of disproportionality are confirmed (males and language minorities), differences in SES entirely account for African-American and Hispanic disproportionality. Discrepancy between the results of bivariate and multivariate analyses confirms the importance of employing multivariate multilevel models in investigation of disproportionality. PMID:20587753

A secure RFID mutual authentication protocol for healthcare environments using elliptic curve cryptography.

PubMed

Jin, Chunhua; Xu, Chunxiang; Zhang, Xiaojun; Zhao, Jining

2015-03-01

Radio Frequency Identification(RFID) is an automatic identification technology, which can be widely used in healthcare environments to locate and track staff, equipment and patients. However, potential security and privacy problems in RFID system remain a challenge. In this paper, we design a mutual authentication protocol for RFID based on elliptic curve cryptography(ECC). We use pre-computing method within tag's communication, so that our protocol can get better efficiency. In terms of security, our protocol can achieve confidentiality, unforgeability, mutual authentication, tag's anonymity, availability and forward security. Our protocol also can overcome the weakness in the existing protocols. Therefore, our protocol is suitable for healthcare environments.

Applying a Geospatial Visualization Based on USSD Messages to Real Time Identification of Epidemiological Risk Areas in Developing Countries: A Case of Study of Paraguay.

PubMed

Ochoa, Silvia; Talavera, Julia; Paciello, Julio

2015-01-01

The identification of epidemiological risk areas is one of the major problems in public health. Information management strategies are needed to facilitate prevention and control of disease in the affected areas. This paper presents a model to optimize geographical data collection of suspected or confirmed disease occurrences using the Unstructured Supplementary Service Data (USSD) mobile technology, considering its wide adoption even in developing countries such as Paraguay. A Geographic Information System (GIS) is proposed for visualizing potential epidemiological risk areas in real time, that aims to support decision making and to implement prevention or contingency programs for public health.

Precision pointing and control of flexible spacecraft

NASA Technical Reports Server (NTRS)

Bantell, M. H., Jr.

1987-01-01

The problem and long term objectives for the precision pointing and control of flexible spacecraft are given. The four basic objectives are stated in terms of two principle tasks. Under Task 1, robust low order controllers, improved structural modeling methods for control applications and identification methods for structural dynamics are being developed. Under Task 2, a lab test experiment for verification of control laws and system identification algorithms is being developed. For Task 1, work has focused on robust low order controller design and some initial considerations for structural modeling in control applications. For Task 2, work has focused on experiment design and fabrication, along with sensor selection and initial digital controller implementation. Conclusions are given.

Biomimetics: determining engineering opportunities from nature

NASA Astrophysics Data System (ADS)

Fish, Frank E.

2009-08-01

The biomimetic approach seeks to incorporate designs based on biological organisms into engineered technologies. Biomimetics can be used to engineer machines that emulate the performance of organisms, particularly in instances where the organism's performance exceeds current mechanical technology or provides new directions to solve existing problems. For biologists, an adaptationist program has allowed for the identification of novel features of organisms based on engineering principles; whereas for engineers, identification of such novel features is necessary to exploit them for biomimetic development. Adaptations (leading edge tubercles to passively modify flow and high efficiency oscillatory propulsive systems) from marine animals demonstrate potential utility in the development of biomimetic products. Nature retains a store of untouched knowledge, which would be beneficial in advancing technology.

Tagging of Test Tubes with Electronic p-Chips for Use in Biorepositories.

PubMed

Mandecki, Wlodek; Kopacka, Wesley M; Qian, Ziye; Ertwine, Von; Gedzberg, Katie; Gruda, Maryann; Reinhardt, David; Rodriguez, Efrain

2017-08-01

A system has been developed to electronically tag and track test tubes used in biorepositories. The system is based on a light-activated microtransponder, also known as a "p-Chip." One of the pressing problems with storing and retrieving biological samples at low temperatures is the difficulty of reliably reading the identification (ID) number that links each storage tube with the database containing sample details. Commonly used barcodes are not always reliable at low temperatures because of poor adhesion of the label to the test tube and problems with reading under conditions of frost and ice accumulation. Traditional radio frequency identification (RFID) tags are not cost effective and are too large for this application. The system described herein consists of the p-Chip, p-Chip-tagged test tubes, two ID readers (for single tubes or for racks of tubes), and software. We also describe a robot that is configured for retrofitting legacy test tubes in biorepositories with p-Chips while maintaining the temperature of the sample below -50°C at all times. The main benefits of the p-Chip over other RFID devices are its small size (600 × 600 × 100 μm) that allows even very small tubes or vials to be tagged, low cost due to the chip's unitary construction, durability, and the ability to read the ID through frost and ice.

A hierarchical anatomical classification schema for prediction of phenotypic side effects

PubMed Central

Kanji, Rakesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects. PMID:29494708

A hierarchical anatomical classification schema for prediction of phenotypic side effects.

PubMed

Wadhwa, Somin; Gupta, Aishwarya; Dokania, Shubham; Kanji, Rakesh; Bagler, Ganesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a 'hierarchical anatomical classification schema' which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.

Medical benefits from the NASA biomedical applications program

NASA Technical Reports Server (NTRS)

Sigmon, J. L.

1974-01-01

To achieve its goals the NASA Biomedical Applications Program performs four basic tasks: (1) identification of major medical problems which lend themselves to solution by relevant aerospace technology; (2) identification of relevant aerospace technology which can be applied to those problems; (3) application of that technology to demonstrate the feasibility as real solutions to the identified problems; and, (4) motivation of the industrial community to manufacture and market the identified solution to maximize the utilization of aerospace solutions to the biomedical community.

A structural model decomposition framework for systems health management

NASA Astrophysics Data System (ADS)

Roychoudhury, I.; Daigle, M.; Bregon, A.; Pulido, B.

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

A Structural Model Decomposition Framework for Systems Health Management

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Daigle, Matthew J.; Bregon, Anibal; Pulido, Belamino

2013-01-01

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

Distributed photovoltaic systems - Addressing the utility interface issues

NASA Astrophysics Data System (ADS)

Firstman, S. I.; Vachtsevanos, G. J.

This paper reviews work conducted in the United States on the impact of dispersed photovoltaic sources upon utility operations. The photovoltaic (PV) arrays are roof-mounted on residential houses and connected, via appropriate power conditioning equipment, to the utility grid. The presence of such small (4-6 Kw) dispersed generators on the distribution network raises questions of a technical, economic and institutional nature. After a brief identification of utility interface issues, the paper addresses such technical concerns as protection of equipment and personnel safety, power quality and utility operational stability. A combination of experimental and analytical approaches has been adopted to arrive at solutions to these problems. Problem areas, under various PV system penetration scenarios, are identified and conceptual designs of protection and control equipment and operating policies are developed so that system reliability is maintained while minimizing capital costs. It is hoped that the resolution of balance-of-system and grid interface questions will ascertain the economic viability of photovoltaic systems and assist in their widespread utilization in the future.

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.

An ultrasonic sensor system based on a two-dimensional state method for highway vehicle violation detection applications.

PubMed

Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing

2015-04-16

With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%.

An Ultrasonic Sensor System Based on a Two-Dimensional State Method for Highway Vehicle Violation Detection Applications

PubMed Central

Liu, Jun; Han, Jiuqiang; Lv, Hongqiang; Li, Bing

2015-01-01

With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%. PMID:25894940

Development and program implementation of elements for identification of the electromagnet condition for movable element position control

NASA Astrophysics Data System (ADS)

Leukhin, R. I.; Shaykhutdinov, D. V.; Shirokov, K. M.; Narakidze, N. D.; Vlasov, A. S.

2017-02-01

Developing the experimental design of new electromagnetic constructions types in engineering industry enterprises requires solutions of two major problems: regulator’s parameters setup and comprehensive testing of electromagnets. A weber-ampere characteristic as a data source for electromagnet condition identification was selected. Present article focuses on development and implementation of the software for electromagnetic drive control system based on the weber-ampere characteristic measuring. The software for weber-ampere characteristic data processing based on artificial neural network is developed. Results of the design have been integrated into the program code in LabVIEW environment. The license package of LabVIEW graphic programming was used. The hardware is chosen and possibility of its use for control system implementation was proved. The trained artificial neural network defines electromagnetic drive effector position with minimal error. Developed system allows to control the electromagnetic drive powered by the voltage source, the current source and hybrid sources.

Laser speckle decorrelation for fingerprint acquisition

NASA Astrophysics Data System (ADS)

Schirripa Spagnolo, Giuseppe; Cozzella, Lorenzo

2012-09-01

Biometry is gaining popularity as a physical security approach in situations where a high level of security is necessary. Currently, biometric solutions are embedded in a very large and heterogeneous group of applications. One of the most sensible is for airport security access to boarding gates. More airports are introducing biometric solutions based on face, fingerprint or iris recognition for passenger identification. In particular, fingerprints are the most widely used biometric, and they are mandatorily included in electronic identification documents. One important issue, which is difficult to address in traditional fingerprint acquisition systems, is preventing contact between subsequent users; sebum, which can be a potential vector for contagious diseases. Currently, non-contact devices are used to overcome this problem. In this paper, a new contact device based on laser speckle decorrelation is presented. Our system has the advantage of being compact and low-cost compared with an actual contactless system, allowing enhancement of the sebum pattern imaging contrast in a simple and low-cost way. Furthermore, it avoids the spreading of contagious diseases.

Behavioral pattern identification for structural health monitoring in complex systems

NASA Astrophysics Data System (ADS)

Gupta, Shalabh

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

Research and design on system of asset management based on RFID

NASA Astrophysics Data System (ADS)

Guan, Peng; Du, HuaiChang; Jing, Hua; Zhang, MengYue; Zhang, Meng; Xu, GuiXian

2011-10-01

By analyzing the problems in the current assets management, this thesis proposing RFID technology will be applied to asset management in order to improve the management level of automation and information. This paper designed the equipment identification based on 433MHz RFID tag and reader which was deeply studied on the basis of RFID tag and card reader circuits, and this paper also illustrates the system of asset management. The RS232 converts Ethernet is a innovative technology to transfer data to PC monitor software, and implement system of asset management based on WEB techniques (PHP and MySQL).

Development of a Test Facility for Air Revitalization Technology Evaluation

NASA Technical Reports Server (NTRS)

Lu, Sao-Dung; Lin, Amy; Campbell, Melissa; Smith, Frederick

2006-01-01

An active fault tolerant control (FTC) law is generally sensitive to false identification since the control gain is reconfigured for fault occurrence. In the conventional FTC law design procedure, dynamic variations due to false identification are not considered. In this paper, an FTC synthesis method is developed in order to consider possible variations of closed-loop dynamics under false identification into the control design procedure. An active FTC synthesis problem is formulated into an LMI optimization problem to minimize the upper bound of the induced-L2 norm which can represent the worst-case performance degradation due to false identification. The developed synthesis method is applied for control of the longitudinal motions of FASER (Free-flying Airplane for Subscale Experimental Research). The designed FTC law of the airplane is simulated for pitch angle command tracking under a false identification case.

On-orbit identifying the inertia parameters of space robotic systems using simple equivalent dynamics

NASA Astrophysics Data System (ADS)

Xu, Wenfu; Hu, Zhonghua; Zhang, Yu; Liang, Bin

2017-03-01

After being launched into space to perform some tasks, the inertia parameters of a space robotic system may change due to fuel consumption, hardware reconfiguration, target capturing, and so on. For precision control and simulation, it is required to identify these parameters on orbit. This paper proposes an effective method for identifying the complete inertia parameters (including the mass, inertia tensor and center of mass position) of a space robotic system. The key to the method is to identify two types of simple dynamics systems: equivalent single-body and two-body systems. For the former, all of the joints are locked into a designed configuration and the thrusters are used for orbital maneuvering. The object function for optimization is defined in terms of acceleration and velocity of the equivalent single body. For the latter, only one joint is unlocked and driven to move along a planned (exiting) trajectory in free-floating mode. The object function is defined based on the linear and angular momentum equations. Then, the parameter identification problems are transformed into non-linear optimization problems. The Particle Swarm Optimization (PSO) algorithm is applied to determine the optimal parameters, i.e. the complete dynamic parameters of the two equivalent systems. By sequentially unlocking the 1st to nth joints (or unlocking the nth to 1st joints), the mass properties of body 0 to n (or n to 0) are completely identified. For the proposed method, only simple dynamics equations are needed for identification. The excitation motion (orbit maneuvering and joint motion) is also easily realized. Moreover, the method does not require prior knowledge of the mass properties of any body. It is general and practical for identifying a space robotic system on-orbit.

Lidar and Dial application for detection and identification: a proposal to improve safety and security

NASA Astrophysics Data System (ADS)

Gaudio, P.; Malizia, A.; Gelfusa, M.; Murari, A.; Parracino, S.; Poggi, L. A.; Lungaroni, M.; Ciparisse, J. F.; Di Giovanni, D.; Cenciarelli, O.; Carestia, M.; Peluso, E.; Gabbarini, V.; Talebzadeh, S.; Bellecci, C.

2017-01-01

Nowadays the intentional diffusion in air (both in open and confined environments) of chemical contaminants is a dramatic source of risk for the public health worldwide. The needs of a high-tech networks composed by software, diagnostics, decision support systems and cyber security tools are urging all the stakeholders (military, public, research & academic entities) to create innovative solutions to face this problem and improve both safety and security. The Quantum Electronics and Plasma Physics (QEP) Research Group of the University of Rome Tor Vergata is working since the 1960s on the development of laser-based technologies for the stand-off detection of contaminants in the air. Up to now, four demonstrators have been developed (two LIDAR-based and two DIAL-based) and have been used in experimental campaigns during all 2015. These systems and technologies can be used together to create an innovative solution to the problem of public safety and security: the creation of a network composed by detection systems: A low cost LIDAR based system has been tested in an urban area to detect pollutants coming from urban traffic, in this paper the authors show the results obtained in the city of Crotone (south of Italy). This system can be used as a first alarm and can be coupled with an identification system to investigate the nature of the threat. A laboratory dial based system has been used in order to create a database of absorption spectra of chemical substances that could be release in atmosphere, these spectra can be considered as the fingerprints of the substances that have to be identified. In order to create the database absorption measurements in cell, at different conditions, are in progress and the first results are presented in this paper.

Intelligent systems for the autonomous exploration of Titan and Enceladus

NASA Astrophysics Data System (ADS)

Furfaro, Roberto; Lunine, Jonathan I.; Kargel, Jeffrey S.; Fink, Wolfgang

2008-04-01

Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi- and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination; and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected data and capable of providing the inference required to autonomously optimize future outer satellites explorations.

Cost-constrained optimal sampling for system identification in pharmacokinetics applications with population priors and nuisance parameters.

PubMed

Sorzano, Carlos Oscars S; Pérez-De-La-Cruz Moreno, Maria Angeles; Burguet-Castell, Jordi; Montejo, Consuelo; Ros, Antonio Aguilar

2015-06-01

Pharmacokinetics (PK) applications can be seen as a special case of nonlinear, causal systems with memory. There are cases in which prior knowledge exists about the distribution of the system parameters in a population. However, for a specific patient in a clinical setting, we need to determine her system parameters so that the therapy can be personalized. This system identification is performed many times by measuring drug concentrations in plasma. The objective of this work is to provide an irregular sampling strategy that minimizes the uncertainty about the system parameters with a fixed amount of samples (cost constrained). We use Monte Carlo simulations to estimate the average Fisher's information matrix associated to the PK problem, and then estimate the sampling points that minimize the maximum uncertainty associated to system parameters (a minimax criterion). The minimization is performed employing a genetic algorithm. We show that such a sampling scheme can be designed in a way that is adapted to a particular patient and that it can accommodate any dosing regimen as well as it allows flexible therapeutic strategies. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Smart intimation and location of faults in distribution system

NASA Astrophysics Data System (ADS)

Hari Krishna, K.; Srinivasa Rao, B.

2018-04-01

Location of faults in the distribution system is one of the most complicated problems that we are facing today. Identification of fault location and severity of fault within a short time is required to provide continuous power supply but fault identification and information transfer to the operator is the biggest challenge in the distribution network. This paper proposes a fault location method in the distribution system based on Arduino nano and GSM module with flame sensor. The main idea is to locate the fault in the distribution transformer by sensing the arc coming out from the fuse element. The biggest challenge in the distribution network is to identify the location and the severity of faults under different conditions. Well operated transmission and distribution systems will play a key role for uninterrupted power supply. Whenever fault occurs in the distribution system the time taken to locate and eliminate the fault has to be reduced. The proposed design was achieved with flame sensor and GSM module. Under faulty condition, the system will automatically send an alert message to the operator in the distribution system, about the abnormal conditions near the transformer, site code and its exact location for possible power restoration.

Protocols development for security and privacy of radio frequency identification systems

NASA Astrophysics Data System (ADS)

Sabbagha, Fatin

There are benefits to adopting radio frequency identification (RFID) technology, although there are methods of attack that can compromise the system. This research determined how that may happen and what possible solutions can keep that from happening. Protocols were developed to implement better security. In addition, new topologies were developed to handle the problems of the key management. Previously proposed protocols focused on providing mutual authentication and privacy between readers and tags. However, those protocols are still vulnerable to be attacked. These protocols were analyzed and the disadvantages shown for each one. Previous works assumed that the channels between readers and the servers were secure. In the proposed protocols, a compromised reader is considered along with how to prevent tags from being read by that reader. The new protocols provide mutual authentication between readers and tags and, at the same time, remove the compromised reader from the system. Three protocols are proposed. In the first protocol, a mutual authentication is achieved and a compromised reader is not allowed in the network. In the second protocol, the number of times a reader contacts the server is reduced. The third protocol provides authentication and privacy between tags and readers using a trusted third party. The developed topology is implemented using python language and simulates work to check the efficiency regarding the processing time. The three protocols are implemented by writing codes in C language and then compiling them in MSP430. IAR Embedded workbench is used, which is an integrated development environment with the C/C++ compiler to generate a faster code and to debug the microcontroller. In summary, the goal of this research is to find solutions for the problems on previously proposed protocols, handle a compromised reader, and solve key management problems.

[The application and evaluation of the system theory for community health assessment in a rural village].

PubMed

Wu, Guey-Hau; Liou, Yiing-Mei; Huang, Lian-Hua

2004-10-01

In assessing the health of a community is important to select tools appropriate to the community's characteristics. The framework for this paper is the system framework for community assessment developed by Trotter, Smith and Maurer (2000); the data were collected by windshield survey, literature review, interview, and observation. Through data analysis and the identification of the community's problem, the authors prioritize those problems in accordance with Goeppinger and Schuste's (1992) criteria. They illustrate the practicality and local applicability of this method by means of a local case. Finally, the authors evaluate the framework in terms of concept clearance, variable classification, and indicator measurement. In addition, they propose concrete suggestions for community workers to consider in the selection of assessment tools, and to enrich nursing knowledge.

REIS: phase II, report I. An overview of the REIS system. [State of Minnesota

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

Chervany, N.L.; Naumann, J.D.; Visness, R.D.

1975-07-01

The Regional Energy Information System (REIS) is being designed and implemented to collect, organize, store, and report data from the energy supply/distribution/consumption chain in the state of Minnesota. This system will contain: identification data, energy flow data, and end-use data. The REIS system will allow users to have access to the data base in a variety of ways (i.e., periodic reporting, special request reporting, direct access/browsing capabilities, and the creation of machine readable files). The self-contained language feature of SYSTEM 2000 gives the REIS system the flexibility and evolvability necessary to meet the changing data needs of energy management problems.more » (GRA)« less

A Facile and Sensitive Method for Quantification of Cyclic Nucleotide Monophosphates in Mammalian Organs: Basal Levels of Eight cNMPs and Identification of 2',3'-cIMP

PubMed Central

Jia, Xin; Fontaine, Benjamin M.; Strobel, Fred; Weinert, Emily E.

2014-01-01

A sensitive, versatile and economical method to extract and quantify cyclic nucleotide monophosphates (cNMPs) using LC-MS/MS, including both 3',5'-cNMPs and 2',3'-cNMPs, in mammalian tissues and cellular systems has been developed. Problems, such as matrix effects from complex biological samples, are addressed and have been optimized. This protocol allows for comparison of multiple cNMPs in the same system and was used to examine the relationship between tissue levels of cNMPs in a panel of rat organs. In addition, the study reports the first identification and quantification of 2',3'-cIMP. The developed method will allow for quantification of cNMPs levels in cells and tissues with varying disease states, which will provide insight into the role(s) and interplay of cNMP signalling pathways. PMID:25513747

Identification of coupling direction: Application to cardiorespiratory interaction

NASA Astrophysics Data System (ADS)

Rosenblum, Michael G.; Cimponeriu, Laura; Bezerianos, Anastasios; Patzak, Andreas; Mrowka, Ralf

2002-04-01

We consider the problem of experimental detection of directionality of weak coupling between two self-sustained oscillators from bivariate data. We further develop the method introduced by Rosenblum and Pikovsky [Phys. Rev. E 64, 045202 (2001)], suggesting an alternative approach. Next, we consider another framework for identification of directionality, based on the idea of mutual predictability. Our algorithms provide directionality index that shows whether the coupling between the oscillators is unidirectional or bidirectional, and quantifies the asymmetry of bidirectional coupling. We demonstrate the efficiency of three different algorithms in determination of directionality index from short and noisy data. These techniques are then applied to analysis of cardiorespiratory interaction in healthy infants. The results reveal that the direction of coupling between cardiovascular and respiratory systems varies with the age within the first 6 months of life. We find a tendency to change from nearly symmetric bidirectional interaction to nearly unidirectional one (from respiration to the cardiovascular system).

Design and Implementation of User-Created Information Systems with Mobile RFID

NASA Astrophysics Data System (ADS)

Lee, Jae Kwoen; Chin, Sungho; Kim, Hee Cheon; Chung, Kwang Sik

RFID (Radio Frequency Identification) has been usually applied at physical distribution field. The Mobile RFID can be the only technology that we can lead the market. In our country, ETRI standardizes MOBION (MOBile Identification ON), and the mobile-telecommunication companies provide the trial-mobile RFID service from 2006. In the trial-mobile RFID services, the Broker model is used to decode the mobile RFID code. However, the Broker model has some problems, such as communication overhead caused by the frequent ODS query, service performance, and various services for users. In this paper, we developed device application that is capable for filtering unrelated code from RFID service to improve the decoding performance. We also improve the performance through simplifying connection process between device application and the broker. Finally, we propose and develop the user-created information system to widely distribute the Mobile RFID service.

A facile and sensitive method for quantification of cyclic nucleotide monophosphates in mammalian organs: basal levels of eight cNMPs and identification of 2',3'-cIMP.

PubMed

Jia, Xin; Fontaine, Benjamin M; Strobel, Fred; Weinert, Emily E

2014-12-12

A sensitive, versatile and economical method to extract and quantify cyclic nucleotide monophosphates (cNMPs) using LC-MS/MS, including both 3',5'-cNMPs and 2',3'-cNMPs, in mammalian tissues and cellular systems has been developed. Problems, such as matrix effects from complex biological samples, are addressed and have been optimized. This protocol allows for comparison of multiple cNMPs in the same system and was used to examine the relationship between tissue levels of cNMPs in a panel of rat organs. In addition, the study reports the first identification and quantification of 2',3'-cIMP. The developed method will allow for quantification of cNMPs levels in cells and tissues with varying disease states, which will provide insight into the role(s) and interplay of cNMP signalling pathways.

Identification of Patient Safety Risks Associated with Electronic Health Records: A Software Quality Perspective.

PubMed

Virginio, Luiz A; Ricarte, Ivan Luiz Marques

2015-01-01

Although Electronic Health Records (EHR) can offer benefits to the health care process, there is a growing body of evidence that these systems can also incur risks to patient safety when developed or used improperly. This work is a literature review to identify these risks from a software quality perspective. Therefore, the risks were classified based on the ISO/IEC 25010 software quality model. The risks identified were related mainly to the characteristics of "functional suitability" (i.e., software bugs) and "usability" (i.e., interface prone to user error). This work elucidates the fact that EHR quality problems can adversely affect patient safety, resulting in errors such as incorrect patient identification, incorrect calculation of medication dosages, and lack of access to patient data. Therefore, the risks presented here provide the basis for developers and EHR regulating bodies to pay attention to the quality aspects of these systems that can result in patient harm.

Page segmentation using script identification vectors: A first look

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

Hochberg, J.; Cannon, M.; Kelly, P.

1997-07-01

Document images in which different scripts, such as Chinese and Roman, appear on a single page pose a problem for optical character recognition (OCR) systems. This paper explores the use of script identification vectors in the analysis of multilingual document images. A script identification vector is calculated for each connected component in a document. The vector expresses the closest distance between the component and templates developed for each of thirteen scripts, including Arabic, Chinese, Cyrillic, and Roman. The authors calculate the first three principal components within the resulting thirteen-dimensional space for each image. By mapping these components to red, green,more » and blue, they can visualize the information contained in the script identification vectors. The visualization of several multilingual images suggests that the script identification vectors can be used to segment images into script-specific regions as large as several paragraphs or as small as a few characters. The visualized vectors also reveal distinctions within scripts, such as font in Roman documents, and kanji vs. kana in Japanese. Results are best for documents containing highly dissimilar scripts such as Roman and Japanese. Documents containing similar scripts, such as Roman and Cyrillic will require further investigation.« less

FPGA implementation of neuro-fuzzy system with improved PSO learning.

PubMed

Karakuzu, Cihan; Karakaya, Fuat; Çavuşlu, Mehmet Ali

2016-07-01

This paper presents the first hardware implementation of neuro-fuzzy system (NFS) with its metaheuristic learning ability on field programmable gate array (FPGA). Metaheuristic learning of NFS for all of its parameters is accomplished by using the improved particle swarm optimization (iPSO). As a second novelty, a new functional approach, which does not require any memory and multiplier usage, is proposed for the Gaussian membership functions of NFS. NFS and its learning using iPSO are implemented on Xilinx Virtex5 xc5vlx110-3ff1153 and efficiency of the proposed implementation tested on two dynamic system identification problems and licence plate detection problem as a practical application. Results indicate that proposed NFS implementation and membership function approximation is as effective as the other approaches available in the literature but requires less hardware resources. Copyright © 2016 Elsevier Ltd. All rights reserved.

Numerical method for solution of systems of non-stationary spatially one-dimensional nonlinear differential equations

NASA Technical Reports Server (NTRS)

Morozov, S. K.; Krasitskiy, O. P.

1978-01-01

A computational scheme and a standard program is proposed for solving systems of nonstationary spatially one-dimensional nonlinear differential equations using Newton's method. The proposed scheme is universal in its applicability and its reduces to a minimum the work of programming. The program is written in the FORTRAN language and can be used without change on electronic computers of type YeS and BESM-6. The standard program described permits the identification of nonstationary (or stationary) solutions to systems of spatially one-dimensional nonlinear (or linear) partial differential equations. The proposed method may be used to solve a series of geophysical problems which take chemical reactions, diffusion, and heat conductivity into account, to evaluate nonstationary thermal fields in two-dimensional structures when in one of the geometrical directions it can take a small number of discrete levels, and to solve problems in nonstationary gas dynamics.

[Tacit and explicit knowledge: comparative analysis of the prioritization of maternal health problems in Mexico].

PubMed

Moreno Zegbe, Estephania; Becerril Montekio, Víctor; Alcalde Rabanal, Jacqueline

To identify coincidences and differences in the identification and prioritization of maternal healthcare service problems in Mexico based on the perspective of tacit knowledge and explicit knowledge that may offer evidence that can contribute to attaining the Sustainable Development Goals. Mixed study performed in three stages: 1) systematization of maternal healthcare service problems identified by tacit knowledge (derived from professional experience); 2) identification of maternal healthcare service problems in Latin America addressed by explicit knowledge (scientific publications); 3) comparison between the problems identified by tacit and explicit knowledge. The main problems of maternal health services identified by tacit knowledge are related to poor quality of care, while the predominant problems studied in the scientific literature are related to access barriers to health services. Approximately, 70% of the problems identified by tacit knowledge are also mentioned in the explicit knowledge. Conversely, 70% of the problems identified in the literature are also considered by tacit knowledge. Nevertheless, when looking at the problems taken one by one, no statistically significant similarities were found. The study discovered that the identification of maternal health service problems by tacit knowledge and explicit knowledge is fairly comparable, according to the comparability index used in the study, and highlights the interest of integrating both approaches in order to improve prioritization and decision making towards the Sustainable Development Goals. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

A quasi-spectral method for Cauchy problem of 2/D Laplace equation on an annulus

NASA Astrophysics Data System (ADS)

Saito, Katsuyoshi; Nakada, Manabu; Iijima, Kentaro; Onishi, Kazuei

2005-01-01

Real numbers are usually represented in the computer as a finite number of digits hexa-decimal floating point numbers. Accordingly the numerical analysis is often suffered from rounding errors. The rounding errors particularly deteriorate the precision of numerical solution in inverse and ill-posed problems. We attempt to use a multi-precision arithmetic for reducing the rounding error evil. The use of the multi-precision arithmetic system is by the courtesy of Dr Fujiwara of Kyoto University. In this paper we try to show effectiveness of the multi-precision arithmetic by taking two typical examples; the Cauchy problem of the Laplace equation in two dimensions and the shape identification problem by inverse scattering in three dimensions. It is concluded from a few numerical examples that the multi-precision arithmetic works well on the resolution of those numerical solutions, as it is combined with the high order finite difference method for the Cauchy problem and with the eigenfunction expansion method for the inverse scattering problem.

Proficiency Testing for Evaluating Aerospace Materials Test Anomalies

NASA Technical Reports Server (NTRS)

Hirsch, D.; Motto, S.; Peyton, S.; Beeson, H.

2006-01-01

ASTM G 86 and ASTM G 74 are commonly used to evaluate materials susceptibility to ignition in liquid and gaseous oxygen systems. However, the methods have been known for their lack of repeatability. The inherent problems identified with the test logic would either not allow precise identification or the magnitude of problems related to running the tests, such as lack of consistency of systems performance, lack of adherence to procedures, etc. Excessive variability leads to increasing instances of accepting the null hypothesis erroneously, and so to the false logical deduction that problems are nonexistent when they really do exist. This paper attempts to develop and recommend an approach that could lead to increased accuracy in problem diagnostics by using the 50% reactivity point, which has been shown to be more repeatable. The initial tests conducted indicate that PTFE and Viton A (for pneumatic impact) and Buna S (for mechanical impact) would be good choices for additional testing and consideration for inter-laboratory evaluations. The approach presented could also be used to evaluate variable effects with increased confidence and tolerance optimization.

Results of a Demonstration Assessment of Passive System Reliability Utilizing the Reliability Method for Passive Systems (RMPS)

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

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia

2015-04-26

Advanced small modular reactor designs include many advantageous design features such as passively driven safety systems that are arguably more reliable and cost effective relative to conventional active systems. Despite their attractiveness, a reliability assessment of passive systems can be difficult using conventional reliability methods due to the nature of passive systems. Simple deviations in boundary conditions can induce functional failures in a passive system, and intermediate or unexpected operating modes can also occur. As part of an ongoing project, Argonne National Laboratory is investigating various methodologies to address passive system reliability. The Reliability Method for Passive Systems (RMPS), amore » systematic approach for examining reliability, is one technique chosen for this analysis. This methodology is combined with the Risk-Informed Safety Margin Characterization (RISMC) approach to assess the reliability of a passive system and the impact of its associated uncertainties. For this demonstration problem, an integrated plant model of an advanced small modular pool-type sodium fast reactor with a passive reactor cavity cooling system is subjected to a station blackout using RELAP5-3D. This paper discusses important aspects of the reliability assessment, including deployment of the methodology, the uncertainty identification and quantification process, and identification of key risk metrics.« less

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

Ferrada, J.J.; Osborne-Lee, I.W.; Grizzaffi, P.A.

Expert systems are known to be useful in capturing expertise and applying knowledge to chemical engineering problems such as diagnosis, process control, process simulation, and process advisory. However, expert system applications are traditionally limited to knowledge domains that are heuristic and involve only simple mathematics. Neural networks, on the other hand, represent an emerging technology capable of rapid recognition of patterned behavior without regard to mathematical complexity. Although useful in problem identification, neural networks are not very efficient in providing in-depth solutions and typically do not promote full understanding of the problem or the reasoning behind its solutions. Hence, applicationsmore » of neural networks have certain limitations. This paper explores the potential for expanding the scope of chemical engineering areas where neural networks might be utilized by incorporating expert systems and neural networks into the same application, a process called hybridization. In addition, hybrid applications are compared with those using more traditional approaches, the results of the different applications are analyzed, and the feasibility of converting the preliminary prototypes described herein into useful final products is evaluated. 12 refs., 8 figs.« less

Implantation of radio frequency identification device (RFID) microchip in disaster victim identification (DVI).

PubMed

Meyer, Harald J; Chansue, Nantarika; Monticelli, Fabio

2006-03-10

The tsunami catastrophe of December 2004 left more than 200,000 dead. Disaster victim identification (DVI) teams were presented with the unprecedented challenge of identifying thousands of mostly markedly putrefied and partially skeletised bodies. To this end, an adequate body tagging method is essential. Conventional body bag tagging in terms of writing on body bags and placing of tags inside body bags proved unsatisfactory and problem prone due to consequences of cold storage, formalin (formaldehyde) embalming and body numbers inside storage facilities. The placement of radio frequency identification device (RFID) microchips inside victim bodies provided a practical solution to problems of body tagging and attribution in the DVI setting encountered by the Austrian DVI team in Thailand in early 2005.

Rotor systems research aircraft predesign study. Volume 3: Predesign report

NASA Technical Reports Server (NTRS)

Schmidt, S. A.; Linden, A. W.

1972-01-01

The features of two aircraft designs were selected to be included in the single RSRA configuration. A study was conducted for further preliminary design and a more detailed analysis of development plans and costs. An analysis was also made of foreseeable technical problems and risks, identification of parallel research which would reduce risks and/or add to the basic capability of the aircraft, and a draft aircraft specification.

Computational Methods for Identification, Optimization and Control of PDE Systems

DTIC Science & Technology

2010-04-30

focused on the development of numerical methods and software specifically for the purpose of solving control, design, and optimization prob- lems where...that provide the foundations of simulation software must play an important role in any research of this type, the demands placed on numerical methods...y sus Aplicaciones , Ciudad de Cor- doba - Argentina, October 2007. 3. Inverse Problems in Deployable Space Structures, Fourth Conference on Inverse

Research in Applied Mathematics Related to Nonlinear System Theory.

DTIC Science & Technology

1985-08-01

This list includes A. OZGULER, P. KHARGONEKAR, J. RIBERA , and T. GEORGIOU. Also supported was the Principal Investigator (partial summer support only...regulator problem with internal stability", Ph.D. dissertation, University of Florida, 63 pages. J. RIBERA [1982] "Identification of linear relations... Ribera , doctoral student (now on faculty of I. E. S. E., Barcelona, SPAIN) Dr. A. Tannenbaum, Visiting Professor (partial summer support only, now

Electrical conduction in polymer dielectrics

NASA Technical Reports Server (NTRS)

Cotts, D. B.

1985-01-01

The use of polymer dielectrics with moderate resistivities could reduce or eliminate problems associated with spacecraft charging. The processes responsible for conduction and the properties of electroactive polymers are reviewed, and correlations drawn between molecular structure and electrical conductivity. These structure-property relationships led to the development of several new electroactive polymer compositions and the identification of several systems that have the requisite thermal, mechanical, environmental and electrical properties for use in spacecraft.

Policies and Procedures To Develop Effective School-Wide Discipline Practices at the Elementary School Level. CASE/CCBD Mini-Library Series on Safe, Drug-Free, and Effective Schools.

ERIC Educational Resources Information Center

Newcomer, Lori L.; Lewis, Timothy J.; Powers, Lisa J.

Elementary schools can play an important role in early identification of and intervention for children with problem behavior by creating the infrastructure to provide preventive, proactive supports for all students. This monograph provides an overview of key features of effective school-wide systems of positive behavior support (PBS) at the…

Defining ’Anonymity’ in Networked Communication, Version 1

DTIC Science & Technology

2011-12-01

conference that features many current works on anonymity [5]. 7. References [1] D . Chaum , “Security without Identification: Transaction Systems...to make Big Brother Obsolete,” Communications of the ACM 28:10 (1985), pp. 1030-1044. [2] D . Chaum , “The Dining Cryptographers Problem: Unconditional...Sender and Recipient Untraceability,” Journal of Cryptology 1:1 (1988), pp. 65-75. [3] D . Chaum , “Untraceable Electronic Mail, Return Addresses

Research of future network with multi-layer IP address

NASA Astrophysics Data System (ADS)

Li, Guoling; Long, Zhaohua; Wei, Ziqiang

2018-04-01

The shortage of IP addresses and the scalability of routing systems [1] are challenges for the Internet. The idea of dividing existing IP addresses between identities and locations is one of the important research directions. This paper proposed a new decimal network architecture based on IPv9 [11], and decimal network IP address from E.164 principle of traditional telecommunication network, the IP address level, which helps to achieve separation and identification and location of IP address, IP address form a multilayer network structure, routing scalability problem in remission at the same time, to solve the problem of IPv4 address depletion. On the basis of IPv9, a new decimal network architecture is proposed, and the IP address of the decimal network draws on the E.164 principle of the traditional telecommunication network, and the IP addresses are hierarchically divided, which helps to realize the identification and location separation of IP addresses, the formation of multi-layer IP address network structure, while easing the scalability of the routing system to find a way out of IPv4 address exhausted. In addition to modifying DNS [10] simply and adding the function of digital domain, a DDNS [12] is formed. At the same time, a gateway device is added, that is, IPV9 gateway. The original backbone network and user network are unchanged.

Enabling Microscopic Simulators to Perform System Level Tasks: A System-Identification Based, Closure-on-Demand Toolkit for Multiscale Simulation Stability/Bifurcation Analysis, Optimization and Control

DTIC Science & Technology

2006-10-01

The objective was to construct a bridge between existing and future microscopic simulation codes ( kMC , MD, MC, BD, LB etc.) and traditional, continuum...kinetic Monte Carlo, kMC , equilibrium MC, Lattice-Boltzmann, LB, Brownian Dynamics, BD, or general agent-based, AB) simulators. It also, fortuitously...cond-mat/0310460 at arXiv.org. 27. Coarse Projective kMC Integration: Forward/Reverse Initial and Boundary Value Problems", R. Rico-Martinez, C. W

Integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control for Lead-Wing close formation systems

NASA Astrophysics Data System (ADS)

Liu, Chun; Jiang, Bin; Zhang, Ke

2018-03-01

This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.

Fuzzy cognitive maps for issue identification in a water resources conflict resolution system

NASA Astrophysics Data System (ADS)

Giordano, R.; Passarella, G.; Uricchio, V. F.; Vurro, M.

In water management, conflicts of interests are inevitable due to the variety in quality demands and the number of stakeholders, which are affected in different ways by decisions concerning the use of the resources. Ignoring the differences among interests involved in water resources management and not resolving the emerging conflicts could lead to controversial strategies. In such cases, proposed solutions could generate strong opposition, making these solutions unfeasible. In our contribution, a Community Decision Support System is proposed. Such a system is able to support discussion and collaboration. The system helps participants to structure their problem, to help them learn about possible alternatives, their constraints and implications and to support the participants in the specification of their own preferences. More in detail, the proposed system helps each user in representing and communicating problem perspectives. To reach this aim, cognitive maps are used to capture parts of the stakeholders’ point of view and to enhance negotiation among individuals and organizations. The aim of the negotiation process is to define a shared cognitive map with regard to water management problems. Such a map can be called a water community cognitive map. The system performance has been tested by simulating a real conflict on water resources management that occurred some years ago in a river basin in the south of Italy.

Soft Biometrics; Human Identification Using Comparative Descriptions.

PubMed

Reid, Daniel A; Nixon, Mark S; Stevenage, Sarah V

2014-06-01

Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.

A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

PubMed Central

Xie, Jin; Zhang, Lei; You, Jane; Zhang, David; Qu, Xiaofeng

2012-01-01

Human hand back skin texture (HBST) is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands). An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the l1 -minimization based sparse representation (SR) technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification. PMID:23012512

Using Pareto points for model identification in predictive toxicology

PubMed Central

2013-01-01

Predictive toxicology is concerned with the development of models that are able to predict the toxicity of chemicals. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in cosmetics, drug design or food protection to speed up the process of chemical compound discovery while reducing the need for lab tests. There is an extensive literature associated with the best practice of model generation and data integration but management and automated identification of relevant models from available collections of models is still an open problem. Currently, the decision on which model should be used for a new chemical compound is left to users. This paper intends to initiate the discussion on automated model identification. We present an algorithm, based on Pareto optimality, which mines model collections and identifies a model that offers a reliable prediction for a new chemical compound. The performance of this new approach is verified for two endpoints: IGC50 and LogP. The results show a great potential for automated model identification methods in predictive toxicology. PMID:23517649

Cumulative reports and publications through December 31, 1989

NASA Technical Reports Server (NTRS)

1990-01-01

A complete list of reports from the Institute for Computer Applications in Science and Engineering (ICASE) is presented. The major categories of the current ICASE research program are: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effectual numerical methods; computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, structural analysis, and chemistry; computer systems and software, especially vector and parallel computers, microcomputers, and data management. Since ICASE reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when it is available.

Software support environment design knowledge capture

NASA Technical Reports Server (NTRS)

Dollman, Tom

1990-01-01

The objective of this task is to assess the potential for using the software support environment (SSE) workstations and associated software for design knowledge capture (DKC) tasks. This assessment will include the identification of required capabilities for DKC and hardware/software modifications needed to support DKC. Several approaches to achieving this objective are discussed and interim results are provided: (1) research into the problem of knowledge engineering in a traditional computer-aided software engineering (CASE) environment, like the SSE; (2) research into the problem of applying SSE CASE tools to develop knowledge based systems; and (3) direct utilization of SSE workstations to support a DKC activity.

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

Tokola, Ryan A; Mikkilineni, Aravind K; Boehnen, Chris Bensing

Despite being increasingly easy to acquire, 3D data is rarely used for face-based biometrics applications beyond identification. Recent work in image-based demographic biometrics has enjoyed much success, but these approaches suffer from the well-known limitations of 2D representations, particularly variations in illumination, texture, and pose, as well as a fundamental inability to describe 3D shape. This paper shows that simple 3D shape features in a face-based coordinate system are capable of representing many biometric attributes without problem-specific models or specialized domain knowledge. The same feature vector achieves impressive results for problems as diverse as age estimation, gender classification, and racemore » classification.« less

Identification of groundwater flow parameters using reciprocal data from hydraulic interference tests

NASA Astrophysics Data System (ADS)

Marinoni, Marianna; Delay, Frederick; Ackerer, Philippe; Riva, Monica; Guadagnini, Alberto

2016-08-01

We investigate the effect of considering reciprocal drawdown curves for the characterization of hydraulic properties of aquifer systems through inverse modeling based on interference well testing. Reciprocity implies that drawdown observed in a well B when pumping takes place from well A should strictly coincide with the drawdown observed in A when pumping in B with the same flow rate as in A. In this context, a critical point related to applications of hydraulic tomography is the assessment of the number of available independent drawdown data and their impact on the solution of the inverse problem. The issue arises when inverse modeling relies upon mathematical formulations of the classical single-continuum approach to flow in porous media grounded on Darcy's law. In these cases, introducing reciprocal drawdown curves in the database of an inverse problem is equivalent to duplicate some information, to a certain extent. We present a theoretical analysis of the way a Least-Square objective function and a Levenberg-Marquardt minimization algorithm are affected by the introduction of reciprocal information in the inverse problem. We also investigate the way these reciprocal data, eventually corrupted by measurement errors, influence model parameter identification in terms of: (a) the convergence of the inverse model, (b) the optimal values of parameter estimates, and (c) the associated estimation uncertainty. Our theoretical findings are exemplified through a suite of computational examples focused on block-heterogeneous systems with increased complexity level. We find that the introduction of noisy reciprocal information in the objective function of the inverse problem has a very limited influence on the optimal parameter estimates. Convergence of the inverse problem improves when adding diverse (nonreciprocal) drawdown series, but does not improve when reciprocal information is added to condition the flow model. The uncertainty on optimal parameter estimates is influenced by the strength of measurement errors and it is not significantly diminished or increased by adding noisy reciprocal information.

Extended GTST-MLD for aerospace system safety analysis.

PubMed

Guo, Chiming; Gong, Shiyu; Tan, Lin; Guo, Bo

2012-06-01

The hazards caused by complex interactions in the aerospace system have become a problem that urgently needs to be settled. This article introduces a method for aerospace system hazard interaction identification based on extended GTST-MLD (goal tree-success tree-master logic diagram) during the design stage. GTST-MLD is a functional modeling framework with a simple architecture. Ontology is used to extend the ability of system interaction description in GTST-MLD by adding the system design knowledge and the past accident experience. From the level of functionality and equipment, respectively, this approach can help the technician detect potential hazard interactions. Finally, a case is used to show the method. © 2011 Society for Risk Analysis.

Experiments in structural dynamics and control using a grid

NASA Technical Reports Server (NTRS)

Montgomery, R. C.

1985-01-01

Future spacecraft are being conceived that are highly flexible and of extreme size. The two features of flexibility and size pose new problems in control system design. Since large scale structures are not testable in ground based facilities, the decision on component placement must be made prior to full-scale tests on the spacecraft. Control law research is directed at solving problems of inadequate modelling knowledge prior to operation required to achieve peak performance. Another crucial problem addressed is accommodating failures in systems with smart components that are physically distributed on highly flexible structures. Parameter adaptive control is a method of promise that provides on-orbit tuning of the control system to improve performance by upgrading the mathematical model of the spacecraft during operation. Two specific questions are answered in this work. They are: What limits does on-line parameter identification with realistic sensors and actuators place on the ultimate achievable performance of a system in the highly flexible environment? Also, how well must the mathematical model used in on-board analytic redundancy be known and what are the reasonable expectations for advanced redundancy management schemes in the highly flexible and distributed component environment?

Problem and Dilemma Identification and Formulation As the Most Critical Element of the Decision-Making Process: Behavioral Biases and Characteristics.

ERIC Educational Resources Information Center

Pashiardis, Petros

This paper presents an overview of research in the field of decision theory, with a focus on problem and identification. The goal is to make the decision-making process as rational as possible in order to maximize the rational administration of the organization. The decisions associated with educational administration can be categorized as…

Identification of time-varying structural dynamic systems - An artificial intelligence approach

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1992-01-01

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Detection and identification of human targets in radar data

NASA Astrophysics Data System (ADS)

Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

2007-04-01

Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

ICASE semiannual report, April 1 - September 30, 1989

NASA Technical Reports Server (NTRS)

1990-01-01

The Institute conducts unclassified basic research in applied mathematics, numerical analysis, and computer science in order to extend and improve problem-solving capabilities in science and engineering, particularly in aeronautics and space. The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers. ICASE reports are considered to be primarily preprints of manuscripts that have been submitted to appropriate research journals or that are to appear in conference proceedings.

A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

PubMed Central

Ahmad, Noor Atinah

2014-01-01

An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs. PMID:24688412

REIMR: A Process for Utilizing Propulsion-Oriented 'Lessons-Learned' to Mitigate Development Risk

NASA Technical Reports Server (NTRS)

Ballard, Richard O.; Brown, Kendall K.

2005-01-01

This paper is a summary overview of a study conducted a t the NASA Marshall Space Flight Center (MSFC) during the initial phases of the Space Launch Initiative (SLI) program to evaluate a large number of technical problems associated with the design, development, test, evaluation and operation of several major liquid propellant rocket engine systems (i.e., SSME, Fastrac, J-2, F-1). The results of this study was the identification of the "Fundamental Root Causes" that enabled the technical problems to manifest, and practices that can be implemented to prevent them from recurring in future engine development efforts. This paper will discus the Fundamental Root Causes, cite some examples of how the technical problems arose from them, and provide a discussion of how they can be mitigated or avoided.

Neural network identification of aircraft nonlinear aerodynamic characteristics

NASA Astrophysics Data System (ADS)

Egorchev, M. V.; Tiumentsev, Yu V.

2018-02-01

The simulation problem for the controlled aircraft motion is considered in the case of imperfect knowledge of the modeling object and its operating conditions. The work aims to develop a class of modular semi-empirical dynamic models that combine the capabilities of theoretical and neural network modeling. We consider the use of semi-empirical neural network models for solving the problem of identifying aerodynamic characteristics of an aircraft. We also discuss the formation problem for a representative set of data characterizing the behavior of a simulated dynamic system, which is one of the critical tasks in the synthesis of ANN-models. The effectiveness of the proposed approach is demonstrated using a simulation example of the aircraft angular motion and identifying the corresponding coefficients of aerodynamic forces and moments.

Documenting the decision structure in software development

NASA Technical Reports Server (NTRS)

Wild, J. Christian; Maly, Kurt; Shen, Stewart N.

1990-01-01

Current software development paradigms focus on the products of the development process. Much of the decision making process which produces these products is outside the scope of these paradigms. The Decision-Based Software Development (DBSD) paradigm views the design process as a series of interrelated decisions which involve the identification and articulation of problems, alternates, solutions and justifications. Decisions made by programmers and analysts are recorded in a project data base. Unresolved problems are also recorded and resources for their resolution are allocated by management according to the overall development strategy. This decision structure is linked to the products affected by the relevant decision and provides a process oriented view of the resulted system. Software maintenance uses this decision view of the system to understand the rationale behind the decisions affecting the part of the system to be modified. D-HyperCase, a prototype Decision-Based Hypermedia System is described and results of applying the DBSD approach during its development are presented.

Anticipating the Chaotic Behaviour of Industrial Systems Based on Stochastic, Event-Driven Simulations

NASA Astrophysics Data System (ADS)

Bruzzone, Agostino G.; Revetria, Roberto; Simeoni, Simone; Viazzo, Simone; Orsoni, Alessandra

2004-08-01

In logistics and industrial production managers must deal with the impact of stochastic events to improve performances and reduce costs. In fact, production and logistics systems are generally designed considering some parameters as deterministically distributed. While this assumption is mostly used for preliminary prototyping, it is sometimes also retained during the final design stage, and especially for estimated parameters (i.e. Market Request). The proposed methodology can determine the impact of stochastic events in the system by evaluating the chaotic threshold level. Such an approach, based on the application of a new and innovative methodology, can be implemented to find the condition under which chaos makes the system become uncontrollable. Starting from problem identification and risk assessment, several classification techniques are used to carry out an effect analysis and contingency plan estimation. In this paper the authors illustrate the methodology with respect to a real industrial case: a production problem related to the logistics of distributed chemical processing.

Problem behaviors of low-income children with language delays: an observation study.

PubMed

Qi, Cathy Huaqing; Kaiser, Ann P

2004-06-01

Children from low-income families are at increased risk for significant behavioral and language problems. Early identification of these problems is essential for effective intervention. The purpose of the present study was to use multiple behavioral assessments to examine the behavioral profiles of sixty 3- and 4-year-old children from low-income families enrolled in Head Start programs and to compare the behavior characteristics of 32 children with language delays with those of 28 children with typical language development. Teachers completed the Child Behavior Checklist/Caregiver-Teacher Report Form/2-5 (CTRF; T. M. Achenbach, 1997) and the Social Skills Rating System (SSRS; F. M. Gresham and S. N. Elliott, 1990), and children were observed in the classrooms during structured and unstructured activities. Children with language delays exhibited more problem behaviors and poorer social skills on some of the observational measures than did children with typical language development, as predicted, but not on all.

Efficacy of the alcohol use disorders identification test as a screening tool for hazardous alcohol intake and related disorders in primary care: a validity study.

PubMed Central

Piccinelli, M.; Tessari, E.; Bortolomasi, M.; Piasere, O.; Semenzin, M.; Garzotto, N.; Tansella, M.

1997-01-01

OBJECTIVE: To determine the properties of the alcohol use disorders identification test in screening primary care attenders for alcohol problems. DESIGN: A validity study among consecutive primary care attenders aged 18-65 years. Every third subject completed the alcohol use disorders identification test (a 10 item self report questionnaire on alcohol intake and related problems) and was interviewed by an investigator with the composite international diagnostic interview alcohol use module (a standardised interview for the independent assessment of alcohol intake and related disorders). SETTING: 10 primary care clinics in Verona, north eastern Italy. PATIENTS: 500 subjects were approached and 482 (96.4%) completed evaluation. RESULTS: When the alcohol use disorders identification test was used to detect subjects with alcohol problems the area under the receiver operating characteristic curve was 0.95. The cut off score of 5 was associated with a sensitivity of 0.84, a specificity of 0.90, and a positive predictive value of 0.60. The screening ability of the total score derived from summing the responses to the five items minimising the probability of misclassification between subjects with and without alcohol problems provided an area under the receiver operating characteristic curve of 0.93. A score of 5 or more on the five items was associated with a sensitivity of 0.79, a specificity of 0.95, and a positive predictive value of 0.73. CONCLUSIONS: The alcohol use disorders identification test performs well in detecting subjects with formal alcohol disorders and those with hazardous alcohol intake. Using five of the 10 items on the questionnaire gives reasonable accuracy, and these are recommended as questions of choice to screen patients for alcohol problems. PMID:9040389

Target identification using Zernike moments and neural networks

NASA Astrophysics Data System (ADS)

Azimi-Sadjadi, Mahmood R.; Jamshidi, Arta A.; Nevis, Andrew J.

2001-10-01

The development of an underwater target identification algorithm capable of identifying various types of underwater targets, such as mines, under different environmental conditions pose many technical problems. Some of the contributing factors are: targets have diverse sizes, shapes and reflectivity properties. Target emplacement environment is variable; targets may be proud or partially buried. Environmental properties vary significantly from one location to another. Bottom features such as sand, rocks, corals, and vegetation can conceal a target whether it is partially buried or proud. Competing clutter with responses that closely resemble those of the targets may lead to false positives. All the problems mentioned above contribute to overly difficult and challenging conditions that could lead to unreliable algorithm performance with existing methods. In this paper, we developed and tested a shape-dependent feature extraction scheme that provides features invariant to rotation, size scaling and translation; properties that are extremely useful for any target classification problem. The developed schemes were tested on an electro-optical imagery data set collected under different environmental conditions with variable background, range and target types. The electro-optic data set was collected using a Laser Line Scan (LLS) sensor by the Coastal Systems Station (CSS), located in Panama City, Florida. The performance of the developed scheme and its robustness to distortion, rotation, scaling and translation was also studied.

A De-Identification Pipeline for Ultrasound Medical Images in DICOM Format.

PubMed

Monteiro, Eriksson; Costa, Carlos; Oliveira, José Luís

2017-05-01

Clinical data sharing between healthcare institutions, and between practitioners is often hindered by privacy protection requirements. This problem is critical in collaborative scenarios where data sharing is fundamental for establishing a workflow among parties. The anonymization of patient information burned in DICOM images requires elaborate processes somewhat more complex than simple de-identification of textual information. Usually, before sharing, there is a need for manual removal of specific areas containing sensitive information in the images. In this paper, we present a pipeline for ultrasound medical image de-identification, provided as a free anonymization REST service for medical image applications, and a Software-as-a-Service to streamline automatic de-identification of medical images, which is freely available for end-users. The proposed approach applies image processing functions and machine-learning models to bring about an automatic system to anonymize medical images. To perform character recognition, we evaluated several machine-learning models, being Convolutional Neural Networks (CNN) selected as the best approach. For accessing the system quality, 500 processed images were manually inspected showing an anonymization rate of 89.2%. The tool can be accessed at https://bioinformatics.ua.pt/dicom/anonymizer and it is available with the most recent version of Google Chrome, Mozilla Firefox and Safari. A Docker image containing the proposed service is also publicly available for the community.

An efficient identification approach for stable and unstable nonlinear systems using Colliding Bodies Optimization algorithm.

PubMed

Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P

2015-11-01

This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Portable bacterial identification system based on elastic light scatter patterns.

PubMed

Bae, Euiwon; Ying, Dawei; Kramer, Donald; Patsekin, Valery; Rajwa, Bartek; Holdman, Cheryl; Sturgis, Jennifer; Davisson, V Jo; Robinson, J Paul

2012-08-28

Conventional diagnosis and identification of bacteria requires shipment of samples to a laboratory for genetic and biochemical analysis. This process can take days and imposes significant delay to action in situations where timely intervention can save lives and reduce associated costs. To enable faster response to an outbreak, a low-cost, small-footprint, portable microbial-identification instrument using forward scatterometry has been developed. This device, weighing 9 lb and measuring 12 × 6 × 10.5 in., utilizes elastic light scatter (ELS) patterns to accurately capture bacterial colony characteristics and delivers the classification results via wireless access. The overall system consists of two CCD cameras, one rotational and one translational stage, and a 635-nm laser diode. Various software algorithms such as Hough transform, 2-D geometric moments, and the traveling salesman problem (TSP) have been implemented to provide colony count and circularity, centering process, and minimized travel time among colonies. Experiments were conducted with four bacteria genera using pure and mixed plate and as proof of principle a field test was conducted in four different locations where the average classification rate ranged between 95 and 100%.

Genome-scale identification of Legionella pneumophila effectors using a machine learning approach.

PubMed

Burstein, David; Zusman, Tal; Degtyar, Elena; Viner, Ram; Segal, Gil; Pupko, Tal

2009-07-01

A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF) was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine learning algorithms for the identification and characterization of bacterial pathogenesis determinants.

Identification of Handicapped Students (Ages 12-17) Using Data from Teachers, Parents and Tests.

ERIC Educational Resources Information Center

Malgoire, Mary A.; And Others

The report examines the identification of potentially handicapping conditions in an adolescent population using data from the National Center for Health Statistics' survey (approximatey 8,000 adolescents selected in 1968). Identification of the following disabilities were examined: hearing impairment, vision problems, orthopedic handicaps, mental…

Linking Complex Problem Solving to Opportunity Identification Competence within the Context of Entrepreneurship

ERIC Educational Resources Information Center

Baggen, Yvette; Mainert, Jakob; Lans, Thomas; Biemans, Harm J. A.; Greiff, Samuel; Mulder, Martin

2015-01-01

Today's working life is increasingly characterized by entrepreneurial challenges. Entrepreneurial challenges start at an individual level with the identification of entrepreneurial opportunities, which is acknowledged as one of the key competencies for lifelong learning. Since the identification of entrepreneurial opportunities relies heavily on…

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

PubMed Central

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-01-01

Background We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems. PMID:17081289

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.

PubMed

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-11-02

We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.

Detection, Identification, Location, and Remote Sensing Using SAW RFID Sensor Tags

NASA Technical Reports Server (NTRS)

Barton, Richard J.; Kennedy, Timothy F.; Williams, Robert M.; Fink, Patrick W.; Ngo, Phong H.

2009-01-01

The Electromagnetic Systems Branch (EV4) of the Avionic Systems Division at NASA Johnson Space Center in Houston, TX is studying the utility of surface acoustic wave (SAW) radiofrequency identification (RFID) tags for multiple wireless applications including detection, identification, tracking, and remote sensing of objects on the lunar surface, monitoring of environmental test facilities, structural shape and health monitoring, and nondestructive test and evaluation of assets. For all of these applications, it is anticipated that the system utilized to interrogate the SAW RFID tags may need to operate at fairly long range and in the presence of considerable multipath and multiple-access interference. Towards that end, EV4 is developing a prototype SAW RFID wireless interrogation system for use in such environments called the Passive Adaptive RFID Sensor Equipment (PARSED) system. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In this paper, we will consider the application of the PARSEQ system to the problem of simultaneous detection, identification, localization, and temperature estimation for multiple objects. We will summarize the overall design of the PARSEQ system and present a detailed description of the design and performance of the signal detection and estimation algorithms incorporated in the system. The system is currently configured only to measure temperature (jointly with range and tag ID), but future versions will be revised to measure parameters other than temperature as SAW tags capable of interfacing with external sensors become available. It is anticipated that the estimation of arbitrary parameters measured using SAW-based sensors will be based on techniques very similar to the joint range and temperature estimation techniques described in this paper.

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

PubMed Central

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. PMID:24489748

Introduction to the IWA task group on biofilm modeling.

PubMed

Noguera, D R; Morgenroth, E

2004-01-01

An International Water Association (IWA) Task Group on Biofilm Modeling was created with the purpose of comparatively evaluating different biofilm modeling approaches. The task group developed three benchmark problems for this comparison, and used a diversity of modeling techniques that included analytical, pseudo-analytical, and numerical solutions to the biofilm problems. Models in one, two, and three dimensional domains were also compared. The first benchmark problem (BM1) described a monospecies biofilm growing in a completely mixed reactor environment and had the purpose of comparing the ability of the models to predict substrate fluxes and concentrations for a biofilm system of fixed total biomass and fixed biomass density. The second problem (BM2) represented a situation in which substrate mass transport by convection was influenced by the hydrodynamic conditions of the liquid in contact with the biofilm. The third problem (BM3) was designed to compare the ability of the models to simulate multispecies and multisubstrate biofilms. These three benchmark problems allowed identification of the specific advantages and disadvantages of each modeling approach. A detailed presentation of the comparative analyses for each problem is provided elsewhere in these proceedings.

Identifying problem and compulsive gamblers.

PubMed Central

van Es, R.

2000-01-01

OBJECTIVE: To present a meta-analysis of current research on the prevalence, identification, and treatment of problem and compulsive gamblers. QUALITY OF EVIDENCE: Problem and compulsive gambling was not a socio-scientific concern until the last two decades. Hence research on this topic is limited. The summary and analysis for this paper relied on computer searches of journal and news abstracts in addition to direct contact with organizations addressing the identification and treatment of compulsive gamblers. MAIN MESSAGE: An estimated 5% of those who gamble run into problems. About 1% of those who gamble are predicted to experience serious problems. Successful treatment of problem and compulsive gambling continues to be a challenge. Although cognitive therapy has been the favoured approach, a combination of several therapeutic approaches is advocated. CONCLUSIONS: Problem and compulsive gambling can present a real health threat. As with other addictions, treatment strategies continue to be a baffling social problem. Aware and informed physicians can have a pivotal role in the difficult process of identifying, acknowledging, and remediating problem and compulsive gambling. PMID:10907572

Linear and non-linear systems identification for adaptive control in mechanical applications vibration suppression

NASA Astrophysics Data System (ADS)

Cazzulani, Gabriele; Resta, Ferruccio; Ripamonti, Francesco

2012-04-01

During the last years, more and more mechanical applications saw the introduction of active control strategies. In particular, the need of improving the performances and/or the system health is very often associated to vibration suppression. This goal can be achieved considering both passive and active solutions. In this sense, many active control strategies have been developed, such as the Independent Modal Space Control (IMSC) or the resonant controllers (PPF, IRC, . . .). In all these cases, in order to tune and optimize the control strategy, the knowledge of the system dynamic behaviour is very important and it can be achieved both considering a numerical model of the system or through an experimental identification process. Anyway, dealing with non-linear or time-varying systems, a tool able to online identify the system parameters becomes a key-point for the control logic synthesis. The aim of the present work is the definition of a real-time technique, based on ARMAX models, that estimates the system parameters starting from the measurements of piezoelectric sensors. These parameters are returned to the control logic, that automatically adapts itself to the system dynamics. The problem is numerically investigated considering a carbon-fiber plate model forced through a piezoelectric patch.

The role of compositionality in standardized problem list generation.

PubMed

Elkin, P L; Tuttle, M; Keck, K; Campbell, K; Atkin, G; Chute, C G

1998-01-01

Compositionality is the ability of a Vocabulary System to record non-atomic strings. In this manuscript we define the types of composition, which can occur. We will then propose methods for both server based and client-based composition. We will differentiate the terms Pre-Coordination, Post-Coordination, and User-Directed Coordination. A simple grammar for the recording of terms with concept level identification will be presented, with examples from the Unified Medical Language System's (UMLS) Metathesaurus. We present an implementation of a Window's NT based client application and a remote Internet Based Vocabulary Server, which makes use of this method of compositionality. Finally we will suggest a research agenda which we believe is necessary to move forward toward a more complete understanding of compositionality. This work has the promise of paving the way toward a robust and complete Problem List Entry Tool.

Agriculture and forestry: Identification, vigor, and disease

NASA Technical Reports Server (NTRS)

Jenkins, D. W.

1972-01-01

The agricultural and forestry areas which comprise the watershed of the Chesapeake Bay are described. Major problems of watershed creation and management with emphasis on the erosion problem are discussed. Remote sensing as it relates to the identification of plant species and vigor, pollution, disease, and insect infestation are examined. The application of infrared photography, multispectral sensing, and sequential survey is recommended to identify ecological changes and improve resources management.

Detection, Identification, Location, and Remote Sensing using SAW RFID Sensor Tags

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2009-01-01

In this presentation, we will consider the problem of simultaneous detection, identification, location estimation, and remote sensing for multiple objects. In particular, we will describe the design and testing of a wireless system capable of simultaneously detecting the presence of multiple objects, identifying each object, and acquiring both a low-resolution estimate of location and a high-resolution estimate of temperature for each object based on wireless interrogation of passive surface acoustic wave (SAW) radiofrequency identification (RFID) sensor tags affixed to each object. The system is being studied for application on the lunar surface as well as for terrestrial remote sensing applications such as pre-launch monitoring and testing of spacecraft on the launch pad and monitoring of test facilities. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In the presentation, we will summarize the system design and illustrate several aspects of the operational characteristics and signal structure. We will examine the theoretical performance characteristics of the system and compare the theoretical results with results obtained from experiments in both controlled laboratory environments and in the field.

Biometric identification

NASA Astrophysics Data System (ADS)

Syryamkim, V. I.; Kuznetsov, D. N.; Kuznetsova, A. S.

2018-05-01

Image recognition is an information process implemented by some information converter (intelligent information channel, recognition system) having input and output. The input of the system is fed with information about the characteristics of the objects being presented. The output of the system displays information about which classes (generalized images) the recognized objects are assigned to. When creating and operating an automated system for pattern recognition, a number of problems are solved, while for different authors the formulations of these tasks, and the set itself, do not coincide, since it depends to a certain extent on the specific mathematical model on which this or that recognition system is based. This is the task of formalizing the domain, forming a training sample, learning the recognition system, reducing the dimensionality of space.

UAS Integration into the NAS: Unmanned Aircraft System (UAS) Delegation of Separation

NASA Technical Reports Server (NTRS)

Fern, Lisa Carolynn; Kenny, Caitlin Ailis

2012-01-01

FAA Modernization and Reform Act of 2012 mandates UAS integration in the NAS by 2015. Operators must be able to safely maneuver UAS to maintain separation and collision avoidance. Delegated Separation is defined as the transfer of responsibility for maintaining separation between aircraft or vehicles from the air navigation service provider to the relevant flight operator, and will likely begin in sparsely trafficked areas before moving to more heavily populated airspace. As UAS operate primarily in areas with lower traffic density and perform maneuvers routinely that are currently managed through special handling, they have the advantage of becoming an early adopter of delegated separation. This experiment will examine if UAS are capable of performing delegated separation in 5 nm horizontal and 1000 ft vertical distances under two delegation conditions. In Extended Delegation, ATC are in charge of identifying problems and delegating to pilot identification and implementation of the solution and monitoring. In Full Delegation, the pilots are responsible for all tasks related to separation assurance: identification of problems and solutions, implementation and monitoring.

Extended Kalman filtering for the detection of damage in linear mechanical structures

NASA Astrophysics Data System (ADS)

Liu, X.; Escamilla-Ambrosio, P. J.; Lieven, N. A. J.

2009-09-01

This paper addresses the problem of assessing the location and extent of damage in a vibrating structure by means of vibration measurements. Frequency domain identification methods (e.g. finite element model updating) have been widely used in this area while time domain methods such as the extended Kalman filter (EKF) method, are more sparsely represented. The difficulty of applying EKF in mechanical system damage identification and localisation lies in: the high computational cost, the dependence of estimation results on the initial estimation error covariance matrix P(0), the initial value of parameters to be estimated, and on the statistics of measurement noise R and process noise Q. To resolve these problems in the EKF, a multiple model adaptive estimator consisting of a bank of EKF in modal domain was designed, each filter in the bank is based on different P(0). The algorithm was iterated by using the weighted global iteration method. A fuzzy logic model was incorporated in each filter to estimate the variance of the measurement noise R. The application of the method is illustrated by simulated and real examples.

OGDD (Olive Genetic Diversity Database): a microsatellite markers' genotypes database of worldwide olive trees for cultivar identification and virgin olive oil traceability

PubMed Central

Ben Ayed, Rayda; Ben Hassen, Hanen; Ennouri, Karim; Ben Marzoug, Riadh; Rebai, Ahmed

2016-01-01

Olive (Olea europaea), whose importance is mainly due to nutritional and health features, is one of the most economically significant oil-producing trees in the Mediterranean region. Unfortunately, the increasing market demand towards virgin olive oil could often result in its adulteration with less expensive oils, which is a serious problem for the public and quality control evaluators of virgin olive oil. Therefore, to avoid frauds, olive cultivar identification and virgin olive oil authentication have become a major issue for the producers and consumers of quality control in the olive chain. Presently, genetic traceability using SSR is the cost effective and powerful marker technique that can be employed to resolve such problems. However, to identify an unknown monovarietal virgin olive oil cultivar, a reference system has become necessary. Thus, an Olive Genetic Diversity Database (OGDD) (http://www.bioinfo-cbs.org/ogdd/) is presented in this work. It is a genetic, morphologic and chemical database of worldwide olive tree and oil having a double function. In fact, besides being a reference system generated for the identification of unkown olive or virgin olive oil cultivars based on their microsatellite allele size(s), it provides users additional morphological and chemical information for each identified cultivar. Currently, OGDD is designed to enable users to easily retrieve and visualize biologically important information (SSR markers, and olive tree and oil characteristics of about 200 cultivars worldwide) using a set of efficient query interfaces and analysis tools. It can be accessed through a web service from any modern programming language using a simple hypertext transfer protocol call. The web site is implemented in java, JavaScript, PHP, HTML and Apache with all major browsers supported. Database URL: http://www.bioinfo-cbs.org/ogdd/ PMID:26827236

Benefits of Enterprise Ontology for the Development of ICT-Based Value Networks

NASA Astrophysics Data System (ADS)

Albani, Antonia; Dietz, Jan L. G.

The competitiveness of value networks is highly dependent on the cooperation between business partners and the interoperability of their information systems. Innovations in information and communication technology (ICT), primarily the emergence of the Internet, offer possibilities to increase the interoperability of information systems and therefore enable inter-enterprise cooperation. For the design of inter-enterprise information systems, the concept of business component appears to be very promising. However, the identification of business components is strongly dependent on the appropriateness and the quality of the underlying business domain model. The ontological model of an enterprise - or an enterprise network - as presented in this article, is a high-quality and very adequate business domain model. It provides all essential information that is necessary for the design of the supporting information systems, and at a level of abstraction that makes it also understandable for business people. The application of enterprise ontology for the identification of business components is clarified. To exemplify our approach, a practical case is taken from the domain of strategic supply network development. By doing this, a widespread problem of the practical application of inter-enterprise information systems is being addressed.

Improving the Flexibility of Optimization-Based Decision Aiding Frameworks for Integrated Water Resource Management

NASA Astrophysics Data System (ADS)

Guillaume, J. H.; Kasprzyk, J. R.

2013-12-01

Deep uncertainty refers to situations in which stakeholders cannot agree on the full suite of risks for their system or their probabilities. Additionally, systems are often managed for multiple, conflicting objectives such as minimizing cost, maximizing environmental quality, and maximizing hydropower revenues. Many objective analysis (MOA) uses a quantitative model combined with evolutionary optimization to provide a tradeoff set of potential solutions to a planning problem. However, MOA is often performed using a single, fixed problem conceptualization. Focus on development of a single formulation can introduce an "inertia" into the problem solution, such that issues outside the initial formulation are less likely to ever be addressed. This study uses the Iterative Closed Question Methodology (ICQM) to continuously reframe the optimization problem, providing iterative definition and reflection for stakeholders. By using a series of directed questions to look beyond a problem's existing modeling representation, ICQM seeks to provide a working environment within which it is easy to modify the motivating question, assumptions, and model identification in optimization problems. The new approach helps identify and reduce bottle-necks introduced by properties of both the simulation model and optimization approach that reduce flexibility in generation and evaluation of alternatives. It can therefore help introduce new perspectives on the resolution of conflicts between objectives. The Lower Rio Grande Valley portfolio planning problem is used as a case study.

The role of precise time in IFF

NASA Technical Reports Server (NTRS)

Bridge, W. M.

1982-01-01

The application of precise time to the identification of friend or foe (IFF) problem is discussed. The simple concept of knowing when to expect each signal is exploited in a variety of ways to achieve an IFF system which is hard to detect, minimally exploitable and difficult to jam. Precise clocks are the backbone of the concept and the various candidates for this role are discussed. The compact rubidium-controlled oscillator is the only practical candidate.

Fiber Optic Chemical Sensors

DTIC Science & Technology

1993-10-01

patent rights. A major problem was identification of the property of ST&E vs LLNL ST&E was formed to manage the activities of Dr. Hirschfeld and Dr...positions of the fields defined in a fixed format to allow its importation into file management programs both in the microcomputer and the minicomputer...Systems Inc., Perry, Florida. askSam is a free-form information manager . A few basic elements of structure can be used to create a highly structured

Identification and feedback control in structures with piezoceramic actuators

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.; Wang, Y.

1992-01-01

In this lecture we give fundamental well-posedness results for a variational formulation of a class of damped second order partial differential equations with unbounded input or control coefficients. Included as special cases in this class are structures with piezoceramic actuators. We consider approximation techniques leading to computational methods in the context of both parameter estimation and feedback control problems for these systems. Rigorous convergence results for parameter estimates and feedback gains are discussed.

An Infrastructure for Multi-Level Secure Service-Oriented Architecture (MLS-SOA) Using the Multiple Single-Level Approach

DTIC Science & Technology

2009-12-17

IEEE TDKE, 1996. 8( 1). 14. Garvey, T.D., The inference Problem for Computer Security. 1992, SRI International. 15. Chaum , D ., Blind Signatures for...Pervasive Computing Environments. IEEE Transactions on Vehicular Technology, 2006. 55(4). 17. Chaum , D ., Security without Identification: Transaction...Systems to make Big Brother Obsolete. Communications of the ACM 1985. 28(10). 18. Chaum , D ., Untraceable Electronic Mail, Return Addresses, and Digital

Comparison and Association of Intellectual Capital: An Investigation and Measurement of the Value of Intellectual Capital Assets and Their Contribution to Stakeholder Perception within the Framework of Higher Education

ERIC Educational Resources Information Center

Helm Stevens, Roxanne

2011-01-01

PROBLEM: Many of the preliminary approaches to strategic management of intellectual capital or knowledge assets have not been attempted in the not-for-profit arena. Additionally, because there is no marketplace value for not-for-profit firms or a valuation system for intangible assets, the identification and measurement necessary for efficient and…

On multi-site damage identification using single-site training data

NASA Astrophysics Data System (ADS)

Barthorpe, R. J.; Manson, G.; Worden, K.

2017-11-01

This paper proposes a methodology for developing multi-site damage location systems for engineering structures that can be trained using single-site damaged state data only. The methodology involves training a sequence of binary classifiers based upon single-site damage data and combining the developed classifiers into a robust multi-class damage locator. In this way, the multi-site damage identification problem may be decomposed into a sequence of binary decisions. In this paper Support Vector Classifiers are adopted as the means of making these binary decisions. The proposed methodology represents an advancement on the state of the art in the field of multi-site damage identification which require either: (1) full damaged state data from single- and multi-site damage cases or (2) the development of a physics-based model to make multi-site model predictions. The potential benefit of the proposed methodology is that a significantly reduced number of recorded damage states may be required in order to train a multi-site damage locator without recourse to physics-based model predictions. In this paper it is first demonstrated that Support Vector Classification represents an appropriate approach to the multi-site damage location problem, with methods for combining binary classifiers discussed. Next, the proposed methodology is demonstrated and evaluated through application to a real engineering structure - a Piper Tomahawk trainer aircraft wing - with its performance compared to classifiers trained using the full damaged-state dataset.

Tackling 'wicked' health promotion problems: a New Zealand case study.

PubMed

Signal, Louise N; Walton, Mat D; Ni Mhurchu, Cliona; Maddison, Ralph; Bowers, Sharron G; Carter, Kristie N; Gorton, Delvina; Heta, Craig; Lanumata, Tolotea S; McKerchar, Christina W; O'Dea, Des; Pearce, Jamie

2013-03-01

This paper reports on a complex environmental approach to addressing 'wicked' health promotion problems devised to inform policy for enhancing food security and physical activity among Māori, Pacific and low-income people in New Zealand. This multi-phase research utilized literature reviews, focus groups, stakeholder workshops and key informant interviews. Participants included members of affected communities, policy-makers and academics. Results suggest that food security and physical activity 'emerge' from complex systems. Key areas for intervention include availability of money within households; the cost of food; improvements in urban design and culturally specific physical activity programmes. Seventeen prioritized intervention areas were explored in-depth and recommendations for action identified. These include healthy food subsidies, increasing the statutory minimum wage rate and enhancing open space and connectivity in communities. This approach has moved away from seeking individual solutions to complex social problems. In doing so, it has enabled the mapping of the relevant systems and the identification of a range of interventions while taking account of the views of affected communities and the concerns of policy-makers. The complex environmental approach used in this research provides a method to identify how to intervene in complex systems that may be relevant to other 'wicked' health promotion problems.

Twelfth Annual Conference on Manual Control

NASA Technical Reports Server (NTRS)

Wempe, T. E.

1976-01-01

Main topics discussed cover multi-task decision making, attention allocation and workload measurement, displays and controls, nonvisual displays, tracking and other psychomotor tasks, automobile driving, handling qualities and pilot ratings, remote manipulation, system identification, control models, and motion and visual cues. Sixty-five papers are included with presentations on results of analytical studies to develop and evaluate human operator models for a range of control task, vehicle dynamics and display situations; results of tests of physiological control systems and applications to medical problems; and on results of simulator and flight tests to determine display, control and dynamics effects on operator performance and workload for aircraft, automobile, and remote control systems.

The Zero-Degree Detector System for Fragmentation Studies

NASA Technical Reports Server (NTRS)

Adams, J. H., Jr.; Christl, M. J.; Howell, L. W.; Kuznetsov, E.

2006-01-01

The measurement of nuclear fragmentation cross sections requires the detection and identification of individual projectile fragments. If light and heavy fragments are recorded in 'ne same detector, it may be impossible distinguish the signal from the light fragment. To overcome this problem, we have developed the Zero-Degree Detector System. The ZDDS enables the measurement of cross sections for light fragment production by using pixelated detectors to separately measure the signals of each fragment. The system has been used to measure the fragmentation of beams as heavy as Fe at the NASA Space Radiation Laboratory at Brookhaven National Laboratory and the Heavy Ion Medical Accelerator in Chiba, Japan.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

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

[Applications of DNA identification technology in protection of wild animals].

PubMed

Ni, Ping-Ya; Pei, Li; Ge, Wen-Dong; Zhang, Ying; Yang, Xue-Ying; Xu, Xiao-Yu; Tu, Zheng

2011-12-01

With the development of biotechnology, forensic DNA identification technology in protection of wild animals has been used more and more widely. This review introduces the global status of wildlife crime and the relevant protection to wildlife, outlines the practical applications of forensic DNA identification technology with regard to species identification, determination of geographic origin, individual identification and paternity identification. It focus on the techniques commonly used in DNA typing and their merits and demerits, as well as the problems and prospects of forensic DNA technology for wildlife conservation.

Study on Material Parameters Identification of Brain Tissue Considering Uncertainty of Friction Coefficient

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu; Zhu, Feng

2017-10-01

Accurate material parameters are critical to construct the high biofidelity finite element (FE) models. However, it is hard to obtain the brain tissue parameters accurately because of the effects of irregular geometry and uncertain boundary conditions. Considering the complexity of material test and the uncertainty of friction coefficient, a computational inverse method for viscoelastic material parameters identification of brain tissue is presented based on the interval analysis method. Firstly, the intervals are used to quantify the friction coefficient in the boundary condition. And then the inverse problem of material parameters identification under uncertain friction coefficient is transformed into two types of deterministic inverse problem. Finally the intelligent optimization algorithm is used to solve the two types of deterministic inverse problems quickly and accurately, and the range of material parameters can be easily acquired with no need of a variety of samples. The efficiency and convergence of this method are demonstrated by the material parameters identification of thalamus. The proposed method provides a potential effective tool for building high biofidelity human finite element model in the study of traffic accident injury.

Differential referral of women and men to employee assistance programs: the role of supervisory attitudes.

PubMed

Young, D W; Reichman, W R; Levy, M F

1987-01-01

Potential factors underlying sex differences in the referral of problem-drinking subordinates to employee assistance programs (EAPs) were explored in interviews with 120 supervisors in four organizations. Analyses of data obtained in these interviews assessed the relative ability of eight variables to predict supervisor's actual identification and referral of female and male problem drinkers. In addition to numbers of employees supervised, the supervisors' judgment of the EAP's effectiveness was the best predictor of referral and identification, regardless of the sex of the referred subordinate. Knowledge and training in the EAP was a secondary contributor to referral of men, but played no role in female referrals. When controlling for all other variables, the extent to which supervisors held an egalitarian attitude toward women's rights and roles was found to be marginally positively related to identification of female drinkers. Similarly, a less stigmatized, stereotyped view of women's use and abuse of alcohol was marginally associated with a greater likelihood of referral of a female drinker to the EAP. Neither of these attitudinal variables was related to identification or referral of male problem drinkers.

Integrated structural control design of large space structures

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

Allen, J.J.; Lauffer, J.P.

1995-01-01

Active control of structures has been under intensive development for the last ten years. Reference 2 reviews much of the identification and control technology for structural control developed during this time. The technology was initially focused on space structure and weapon applications; however, recently the technology is also being directed toward applications in manufacturing and transportation. Much of this technology focused on multiple-input/multiple-output (MIMO) identification and control methodology because many of the applications require a coordinated control involving multiple disturbances and control objectives where multiple actuators and sensors are necessary for high performance. There have been many optimal robust controlmore » methods developed for the design of MIMO robust control laws; however, there appears to be a significant gap between the theoretical development and experimental evaluation of control and identification methods to address structural control applications. Many methods have been developed for MIMO identification and control of structures, such as the Eigensystem Realization Algorithm (ERA), Q-Markov Covariance Equivalent Realization (Q-Markov COVER) for identification; and, Linear Quadratic Gaussian (LQG), Frequency Weighted LQG and H-/ii-synthesis methods for control. Upon implementation, many of the identification and control methods have shown limitations such as the excitation of unmodelled dynamics and sensitivity to system parameter variations. As a result, research on methods which address these problems have been conducted.« less

Dynamic identification of axial force and boundary restraints in tie rods and cables with uncertainty quantification using Set Inversion Via Interval Analysis

NASA Astrophysics Data System (ADS)

Kernicky, Timothy; Whelan, Matthew; Al-Shaer, Ehab

2018-06-01

A methodology is developed for the estimation of internal axial force and boundary restraints within in-service, prismatic axial force members of structural systems using interval arithmetic and contractor programming. The determination of the internal axial force and end restraints in tie rods and cables using vibration-based methods has been a long standing problem in the area of structural health monitoring and performance assessment. However, for structural members with low slenderness where the dynamics are significantly affected by the boundary conditions, few existing approaches allow for simultaneous identification of internal axial force and end restraints and none permit for quantifying the uncertainties in the parameter estimates due to measurement uncertainties. This paper proposes a new technique for approaching this challenging inverse problem that leverages the Set Inversion Via Interval Analysis algorithm to solve for the unknown axial forces and end restraints using natural frequency measurements. The framework developed offers the ability to completely enclose the feasible solutions to the parameter identification problem, given specified measurement uncertainties for the natural frequencies. This ability to propagate measurement uncertainty into the parameter space is critical towards quantifying the confidence in the individual parameter estimates to inform decision-making within structural health diagnosis and prognostication applications. The methodology is first verified with simulated data for a case with unknown rotational end restraints and then extended to a case with unknown translational and rotational end restraints. A laboratory experiment is then presented to demonstrate the application of the methodology to an axially loaded rod with progressively increased end restraint at one end.

Statistical and operational considerations for designs for x-ray tomographic spectrophotometry to detect, localize, and classify foreign objects in various systems

NASA Astrophysics Data System (ADS)

Fennelly, Alphonsus J.; Fry, Edward L.; Zukic, Muamer; Wilson, Michele M.; Janik, Tadeusz J.; Torr, Douglas G.

1994-11-01

In six companion papers we discuss a capability for x-ray tomographic spectrophotometry at three energy ranges to observe foreign objects in various systems using a novel x-ray optical and photometric approach. We describe new types of thin-film x-ray reflecting filters to provide energy-specific optical trains, inserted into existing x-ray interrogation systems. That is complemented by performing topographic imaging at a few, to several, energies in each case. That provides a full topographic and spectrophotometric analysis. Foreign objects can then be detected, localized, discriminated, and classified, so that they may be dealt with by excision, and replacement with benign system elements. We analyze statistical and operational concerns leading to the design of three systems: The first operates at x-ray energies of 1 - 10 keV; it deals with defects in microelectronic integrated circuits. The second operates at x-ray energies of 10 - 30 keV; it deals with the defects in human tissue. The chemical specificity and image resolution of the system will allow identification, localization, and mensuration of tumors without the need of biopsy. The system which we concentrate this discussion on, the third, operates at x- ray energies of 30 - 70 keV; it deals with the presence in transportation systems of explosive devices, and contraband materials and objects in luggage and cargo. We present the analysis of the statistical features of the detection problem in these types of systems, discussing the operational constraints which limits system performance. After considering the multivariate, multisignature, approach to the problem, we discuss the tomographic and spectrophotometric approach to the problem which yields a better solution to the detection problem within the operational constraints.

Role of Referrals in Mental Health Service Disparities for Racial and Ethnic Minority Youth

ERIC Educational Resources Information Center

Alegria, Margarita; Lin, Julia Y.; Green, Jennifer Greif; Sampson, Nancy A.; Gruber, Michael J.; Kessler, Ronald C.

2012-01-01

Objective: To investigate racial/ethnic differences in teachers' and other adults' identification and/or encouragement of parents to seek treatment for psychiatric problems in their children and to evaluate if and whether identification/encouragement is associated with service use. Method: Data on identification/encouragement to seek treatment for…

The Role of Problem Construction in Creative Production

ERIC Educational Resources Information Center

Reiter-Palmon, Roni

2017-01-01

This paper provides an overview of theory and research regarding problem construction and identification. Specifically, the paper reviews a theoretical model of processes associated with problem construction and empirical evidence in relation to the model. Finally, the paper reviews the literature on team problem construction.

On decoupling of volatility smile and term structure in inverse option pricing

NASA Astrophysics Data System (ADS)

Egger, Herbert; Hein, Torsten; Hofmann, Bernd

2006-08-01

Correct pricing of options and other financial derivatives is of great importance to financial markets and one of the key subjects of mathematical finance. Usually, parameters specifying the underlying stochastic model are not directly observable, but have to be determined indirectly from observable quantities. The identification of local volatility surfaces from market data of European vanilla options is one very important example of this type. As with many other parameter identification problems, the reconstruction of local volatility surfaces is ill-posed, and reasonable results can only be achieved via regularization methods. Moreover, due to the sparsity of data, the local volatility is not uniquely determined, but depends strongly on the kind of regularization norm used and a good a priori guess for the parameter. By assuming a multiplicative structure for the local volatility, which is motivated by the specific data situation, the inverse problem can be decomposed into two separate sub-problems. This removes part of the non-uniqueness and allows us to establish convergence and convergence rates under weak assumptions. Additionally, a numerical solution of the two sub-problems is much cheaper than that of the overall identification problem. The theoretical results are illustrated by numerical tests.

PubMed Central

CICIRIELLO, E.

2016-01-01

SUMMARY Non-uniform, late, or inappropriate care of childhood with permanent hearing impairment (PHI) predisposes many children to develop communicative- behaviour problems and impaired psychosocial adjustment that can persist in adolescence and adulthood.In March 2014, the CCM (Centro Controllo Malattie or Disease Control Centre) of the Italian Ministry of Health funded a project entitled " Preventing Communication Disorders: a Regional Program for Early Identification, Intervention and Care of Hearing Impaired Children". The project involved 5 tertiary centres with UNHS programs formally approved by the Region. The main purpose of the project is to define and launch an integrated regionally-based public health model for identification, diagnosis and intervention of childhood PHI. The first phase of the project investigated the state of art and produced recommendations for positive changes in identification, diagnosis, therapy and care of childhood PHI in Italy, taking into account diagnostic and treatment innovations, family empowerment, treatment alliance and an interdisciplinary approach. Recommendations drawn from this initial phase will represent the basis for a regional system for early intervention that is validated, integrated and shared between the five regions. PMID:27054384

A touch probe method of operating an implantable RFID tag for orthopedic implant identification.

PubMed

Liu, Xiaoyu; Berger, J Lee; Ogirala, Ajay; Mickle, Marlin H

2013-06-01

The major problem in operating an implantable radio-frequency identification (RFID) tag embedded on an orthopedic implant is low efficiency because of metallic interference. To improve the efficiency, this paper proposes a method of operating an implantable passive RFID tag using a touch probe at 13.56 MHz. This technology relies on the electric field interaction between two pairs of electrodes, one being a part of the touch probe placed on the surface of tissue and the other being a part of the tag installed under the tissue. Compared with using a conventional RFID antenna such as a loop antenna, this method has a better performance in the near field operation range to reduce interference with the orthopedic implant. Properly matching the touch probe and the tag to the tissue and the implant reduces signal attenuation and increases the overall system efficiency. The experiments have shown that this method has a great performance in the near field transcutaneous operation and can be used for orthopedic implant identification.

Open Globe Injury Patient Identification in Warfare Clinical Notes1

PubMed Central

Apostolova, Emilia; White, Helen A.; Morris, Patty A.; Eliason, David A.; Velez, Tom

2017-01-01

The aim of this study is to utilize the Defense and Veterans Eye Injury and Vision Registry clinical data derived from DoD and VA medical systems which include documentation of care while in combat, and develop methods for comprehensive and reliable Open Globe Injury (OGI) patient identification. In particular, we focus on the use of free-form clinical notes, since structured data, such as diagnoses or procedure codes, as found in early post-trauma clinical records, may not be a comprehensive and reliable indicator of OGIs. The challenges of the task include low incidence rate (few positive examples), idiosyncratic military ophthalmology vocabulary, extreme brevity of notes, specialized abbreviations, typos and misspellings. We modeled the problem as a text classification task and utilized a combination of supervised learning (SVMs) and word embeddings learnt in a unsupervised manner, achieving a precision of 92.50% and a recall of89.83%o. The described techniques are applicable to patient cohort identification with limited training data and low incidence rate. PMID:29854104