Societal and ethical implications of anti-spoofing technologies in biometrics.

PubMed

Rebera, Andrew P; Bonfanti, Matteo E; Venier, Silvia

2014-03-01

Biometric identification is thought to be less vulnerable to fraud and forgery than are traditional forms of identification. However biometric identification is not without vulnerabilities. In a 'spoofing attack' an artificial replica of an individual's biometric trait is used to induce a system to falsely infer that individual's presence. Techniques such as liveness-detection and multi-modality, as well as the development of new and emerging modalities, are intended to secure biometric identification systems against such threats. Unlike biometrics in general, the societal and ethical issues raised by spoofing and anti-spoofing techniques have not received much attention. This paper examines these issues.

Neutron Detection With Ultra-Fast Digitizer and Pulse Identification Techniques on DIII-D

NASA Astrophysics Data System (ADS)

Zhu, Y. B.; Heidbrink, W. W.; Piglowski, D. A.

2013-10-01

A prototype system for neutron detection with an ultra-fast digitizer and pulse identification techniques has been implemented on the DIII-D tokamak. The system consists of a cylindrical neutron fission chamber, a charge sensitive amplifier, and a GaGe Octopus 12-bit CompuScope digitizer card installed in a Linux computer. Digital pulse identification techniques have been successfully performed at maximum data acquisition rate of 50 MSPS with on-board memory of 2 GS. Compared to the traditional approach with fast nuclear electronics for pulse counting, this straightforward digital solution has many advantages, including reduced expense, improved accuracy, higher counting rate, and easier maintenance. The system also provides the capability of neutron-gamma pulse shape discrimination and pulse height analysis. Plans for the upgrade of the old DIII-D neutron counting system with these techniques will be presented. Work supported by the US Department of Energy under SC-G903402, and DE-FC02-04ER54698.

Decentralized system identification using stochastic subspace identification on wireless smart sensor networks

NASA Astrophysics Data System (ADS)

Sim, Sung-Han; Spencer, Billie F., Jr.; Park, Jongwoong; Jung, Hyungjo

2012-04-01

Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventional monitoring systems based on wired sensors and centralized data acquisition and processing have been considered to be challenging and costly due to cabling and expensive equipment and maintenance costs. WSSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. Thus, several system identification methods have been implemented to process sensor data and extract essential information, including Natural Excitation Technique with Eigensystem Realization Algorithm, Frequency Domain Decomposition (FDD), and Random Decrement Technique (RDT); however, Stochastic Subspace Identification (SSI) has not been fully utilized in WSSNs, while SSI has the strong potential to enhance the system identification. This study presents a decentralized system identification using SSI in WSSNs. The approach is implemented on MEMSIC's Imote2 sensor platform and experimentally verified using a 5-story shear building model.

Boundary shape identification problems in two-dimensional domains related to thermal testing of materials

NASA Technical Reports Server (NTRS)

Banks, H. T.; Kojima, Fumio

1988-01-01

The identification of the geometrical structure of the system boundary for a two-dimensional diffusion system is reported. The domain identification problem treated here is converted into an optimization problem based on a fit-to-data criterion and theoretical convergence results for approximate identification techniques are discussed. Results of numerical experiments to demonstrate the efficacy of the theoretical ideas are reported.

Reliability of System Identification Techniques to Assess Standing Balance in Healthy Elderly

PubMed Central

Maier, Andrea B.; Aarts, Ronald G. K. M.; van Gerven, Joop M. A.; Arendzen, J. Hans; Schouten, Alfred C.; Meskers, Carel G. M.; van der Kooij, Herman

2016-01-01

Objectives System identification techniques have the potential to assess the contribution of the underlying systems involved in standing balance by applying well-known disturbances. We investigated the reliability of standing balance parameters obtained with multivariate closed loop system identification techniques. Methods In twelve healthy elderly balance tests were performed twice a day during three days. Body sway was measured during two minutes of standing with eyes closed and the Balance test Room (BalRoom) was used to apply four disturbances simultaneously: two sensory disturbances, to the proprioceptive and the visual system, and two mechanical disturbances applied at the leg and trunk segment. Using system identification techniques, sensitivity functions of the sensory disturbances and the neuromuscular controller were estimated. Based on the generalizability theory (G theory), systematic errors and sources of variability were assessed using linear mixed models and reliability was assessed by computing indexes of dependability (ID), standard error of measurement (SEM) and minimal detectable change (MDC). Results A systematic error was found between the first and second trial in the sensitivity functions. No systematic error was found in the neuromuscular controller and body sway. The reliability of 15 of 25 parameters and body sway were moderate to excellent when the results of two trials on three days were averaged. To reach an excellent reliability on one day in 7 out of 25 parameters, it was predicted that at least seven trials must be averaged. Conclusion This study shows that system identification techniques are a promising method to assess the underlying systems involved in standing balance in elderly. However, most of the parameters do not appear to be reliable unless a large number of trials are collected across multiple days. To reach an excellent reliability in one third of the parameters, a training session for participants is needed and at least seven trials of two minutes must be performed on one day. PMID:26953694

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.

Reliable dual-redundant sensor failure detection and identification for the NASA F-8 DFBW aircraft

NASA Technical Reports Server (NTRS)

Deckert, J. C.; Desai, M. N.; Deyst, J. J., Jr.; Willsky, A. S.

1978-01-01

A technique was developed which provides reliable failure detection and identification (FDI) for a dual redundant subset of the flight control sensors onboard the NASA F-8 digital fly by wire (DFBW) aircraft. The technique was successfully applied to simulated sensor failures on the real time F-8 digital simulator and to sensor failures injected on telemetry data from a test flight of the F-8 DFBW aircraft. For failure identification the technique utilized the analytic redundancy which exists as functional and kinematic relationships among the various quantities being measured by the different control sensor types. The technique can be used not only in a dual redundant sensor system, but also in a more highly redundant system after FDI by conventional voting techniques reduced to two the number of unfailed sensors of a particular type. In addition the technique can be easily extended to the case in which only one sensor of a particular type is available.

Detection, identification, and quantification techniques for spills of hazardous chemicals

NASA Technical Reports Server (NTRS)

Washburn, J. F.; Sandness, G. A.

1977-01-01

The first 400 chemicals listed in the Coast Guard's Chemical Hazards Response Information System were evaluated with respect to their detectability, identifiability, and quantifiability by 12 generalized remote and in situ sensing techniques. Identification was also attempted for some key areas in water pollution sensing technology.

An experimental study of nonlinear dynamic system identification

NASA Technical Reports Server (NTRS)

Stry, Greselda I.; Mook, D. Joseph

1990-01-01

A technique for robust identification of nonlinear dynamic systems is developed and illustrated using both simulations and analog experiments. The technique is based on the Minimum Model Error 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 of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in constrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. 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.

Comments on Frequency Swept Rotating Input Perturbation Techniques and Identification of the Fluid Force Models in Rotor/bearing/seal Systems and Fluid Handling Machines

NASA Technical Reports Server (NTRS)

Muszynska, Agnes; Bently, Donald E.

1991-01-01

Perturbation techniques used for identification of rotating system dynamic characteristics are described. A comparison between two periodic frequency-swept perturbation methods applied in identification of fluid forces of rotating machines is presented. The description of the fluid force model identified by inputting circular periodic frequency-swept force is given. This model is based on the existence and strength of the circumferential flow, most often generated by the shaft rotation. The application of the fluid force model in rotor dynamic analysis is presented. It is shown that the rotor stability is an entire rotating system property. Some areas for further research are discussed.

Fourth NASA Inter-Center Control Systems Conference

NASA Technical Reports Server (NTRS)

1978-01-01

Space vehicle control applications are discussed, along with aircraft guidance, control, and handling qualities. System simulation and identification, engine control, advanced propulsion techniques, and advanced control techniques are also included.

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.

The application of a biometric identification technique for linking community and hospital data in rural Ghana

PubMed Central

Odei-Lartey, Eliezer Ofori; Boateng, Dennis; Danso, Samuel; Kwarteng, Anthony; Abokyi, Livesy; Amenga-Etego, Seeba; Gyaase, Stephaney; Asante, Kwaku Poku; Owusu-Agyei, Seth

2016-01-01

Background The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Objective Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. Design A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. Results A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Conclusions Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information. PMID:26993473

The application of a biometric identification technique for linking community and hospital data in rural Ghana.

PubMed

Odei-Lartey, Eliezer Ofori; Boateng, Dennis; Danso, Samuel; Kwarteng, Anthony; Abokyi, Livesy; Amenga-Etego, Seeba; Gyaase, Stephaney; Asante, Kwaku Poku; Owusu-Agyei, Seth

2016-01-01

The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information.

Identification of piecewise affine systems based on fuzzy PCA-guided robust clustering technique

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA-guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.

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.

System/observer/controller identification toolbox

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

1992-01-01

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

Charge Identification of Highly Ionizing Particles in Desensitized Nuclear Emulsion Using High Speed Read-Out System

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

Toshito, T.; Kodama, K.; Yusa, K.

2006-05-10

We performed an experimental study of charge identification of heavy ions from helium to carbon having energy of about 290 MeV/u using an emulsion chamber. Emulsion was desensitized by means of forced fading (refreshing) to expand a dynamic range of response to highly charged particles. For the track reconstruction and charge identification, the fully automated high speed emulsion read-out system, which was originally developed for identifying minimum ionizing particles, was used without any modification. Clear track by track charge identification up to Z=6 was demonstrated. The refreshing technique has proved to be a powerful technique to expand response of emulsionmore » film to highly ionizing particles.« less

Vision-based system identification technique for building structures using a motion capture system

NASA Astrophysics Data System (ADS)

Oh, Byung Kwan; Hwang, Jin Woo; Kim, Yousok; Cho, Tongjun; Park, Hyo Seon

2015-11-01

This paper presents a new vision-based system identification (SI) technique for building structures by using a motion capture system (MCS). The MCS with outstanding capabilities for dynamic response measurements can provide gage-free measurements of vibrations through the convenient installation of multiple markers. In this technique, from the dynamic displacement responses measured by MCS, the dynamic characteristics (natural frequency, mode shape, and damping ratio) of building structures are extracted after the processes of converting the displacement from MCS to acceleration and conducting SI by frequency domain decomposition. A free vibration experiment on a three-story shear frame was conducted to validate the proposed technique. The SI results from the conventional accelerometer-based method were compared with those from the proposed technique and showed good agreement, which confirms the validity and applicability of the proposed vision-based SI technique for building structures. Furthermore, SI directly employing MCS measured displacements to FDD was performed and showed identical results to those of conventional SI method.

Stochastic subspace identification for operational modal analysis of an arch bridge

NASA Astrophysics Data System (ADS)

Loh, Chin-Hsiung; Chen, Ming-Che; Chao, Shu-Hsien

2012-04-01

In this paer the application of output-only system identification technique, known as Stochastic Subspace Identification (SSI) algorithms, for civil infrastructures is carried out. The ability of covariance driven stochastic subspace identification (SSI-COV) was proved through the analysis of the ambient data of an arch bridge under operational condition. A newly developed signal processing technique, Singular Spectrum analysis (SSA), capable to smooth noisy signals, is adopted for pre-processing the recorded data before the SSI. The conjunction of SSA and SSICOV provides a useful criterion for the system order determination. With the aim of estimating accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data Hankel matrix. Identification task of a real structure, Guandu Bridge, is carried out to identify the system natural frequencies and mode shapes. The uncertainty of the identified model parameters from output-only measurement of the bridge under operation condition, such as temperature and traffic loading conditions, is discussed.

An Adaptive Technique for a Redundant-Sensor Navigation System. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chien, T. T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.

Application of star identification using pattern matching to space ground systems at GSFC

NASA Technical Reports Server (NTRS)

Fink, D.; Shoup, D.

1994-01-01

This paper reports the application of pattern recognition techniques for star identification based on those proposed by Van Bezooijen to space ground systems for near-real-time attitude determination. A prototype was developed using these algorithms, which was used to assess the suitability of these techniques for support of the X-Ray Timing Explorer (XTE), Submillimeter Wave Astronomy Satellite (SWAS), and the Solar and Heliospheric Observatory (SOHO) missions. Experience with the prototype was used to refine specifications for the operational system. Different geometry tests appropriate to the mission requirements of XTE, SWAS, and SOHO were adopted. The applications of these techniques to upcoming mission support of XTE, SWAS, and SOHO are discussed.

A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Rizzi, Egidio

2016-08-01

This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

Active Vibration damping of Smart composite beams based on system identification technique

NASA Astrophysics Data System (ADS)

Bendine, Kouider; Satla, Zouaoui; Boukhoulda, Farouk Benallel; Nouari, Mohammed

2018-03-01

In the present paper, the active vibration control of a composite beam using piezoelectric actuator is investigated. The space state equation is determined using system identification technique based on the structure input output response provided by ANSYS APDL finite element package. The Linear Quadratic (LQG) control law is designed and integrated into ANSYS APDL to perform closed loop simulations. Numerical examples for different types of excitation loads are presented to test the efficiency and the accuracy of the proposed model.

Development of neural network techniques for finger-vein pattern classification

NASA Astrophysics Data System (ADS)

Wu, Jian-Da; Liu, Chiung-Tsiung; Tsai, Yi-Jang; Liu, Jun-Ching; Chang, Ya-Wen

2010-02-01

A personal identification system using finger-vein patterns and neural network techniques is proposed in the present study. In the proposed system, the finger-vein patterns are captured by a device that can transmit near infrared through the finger and record the patterns for signal analysis and classification. The biometric system for verification consists of a combination of feature extraction using principal component analysis and pattern classification using both back-propagation network and adaptive neuro-fuzzy inference systems. Finger-vein features are first extracted by principal component analysis method to reduce the computational burden and removes noise residing in the discarded dimensions. The features are then used in pattern classification and identification. To verify the effect of the proposed adaptive neuro-fuzzy inference system in the pattern classification, the back-propagation network is compared with the proposed system. The experimental results indicated the proposed system using adaptive neuro-fuzzy inference system demonstrated a better performance than the back-propagation network for personal identification using the finger-vein patterns.

Projective Identification in Common Couple Dances.

ERIC Educational Resources Information Center

Middelberg, Carol V.

2001-01-01

Integrates the object relations concept of projective identification and the systemic concept of marital dances to develop a more powerful model for working with more difficult and distressed couples. Suggests how object relations techniques can be used to interrupt projective identifications and resolve conflict on intrapsychic level so the…

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.

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

Five-way smoking status classification using text hot-spot identification and error-correcting output codes.

PubMed

Cohen, Aaron M

2008-01-01

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using micro- and macro-averaged F1 as the primary performance metric. Our best performing system achieved a micro-F1 of 0.9000 on the test collection, equivalent to the best performing system submitted to the i2b2 challenge. Hot-spot identification, zero-vector filtering, classifier weighting, and error correcting output coding contributed additively to increased performance, with hot-spot identification having by far the largest positive effect. High performance on automatic identification of patient smoking status from discharge summaries is achievable with the efficient and straightforward machine learning techniques studied here.

Note: Design of FPGA based system identification module with application to atomic force microscopy

NASA Astrophysics Data System (ADS)

Ghosal, Sayan; Pradhan, Sourav; Salapaka, Murti

2018-05-01

The science of system identification is widely utilized in modeling input-output relationships of diverse systems. In this article, we report field programmable gate array (FPGA) based implementation of a real-time system identification algorithm which employs forgetting factors and bias compensation techniques. The FPGA module is employed to estimate the mechanical properties of surfaces of materials at the nano-scale with an atomic force microscope (AFM). The FPGA module is user friendly which can be interfaced with commercially available AFMs. Extensive simulation and experimental results validate the design.

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.

System identification through nonstationary data using Time-Frequency Blind Source Separation

NASA Astrophysics Data System (ADS)

Guo, Yanlin; Kareem, Ahsan

2016-06-01

Classical output-only system identification (SI) methods are based on the assumption of stationarity of the system response. However, measured response of buildings and bridges is usually non-stationary due to strong winds (e.g. typhoon, and thunder storm etc.), earthquakes and time-varying vehicle motions. Accordingly, the response data may have time-varying frequency contents and/or overlapping of modal frequencies due to non-stationary colored excitation. This renders traditional methods problematic for modal separation and identification. To address these challenges, a new SI technique based on Time-Frequency Blind Source Separation (TFBSS) is proposed. By selectively utilizing "effective" information in local regions of the time-frequency plane, where only one mode contributes to energy, the proposed technique can successfully identify mode shapes and recover modal responses from the non-stationary response where the traditional SI methods often encounter difficulties. This technique can also handle response with closely spaced modes which is a well-known challenge for the identification of large-scale structures. Based on the separated modal responses, frequency and damping can be easily identified using SI methods based on a single degree of freedom (SDOF) system. In addition to the exclusive advantage of handling non-stationary data and closely spaced modes, the proposed technique also benefits from the absence of the end effects and low sensitivity to noise in modal separation. The efficacy of the proposed technique is demonstrated using several simulation based studies, and compared to the popular Second-Order Blind Identification (SOBI) scheme. It is also noted that even some non-stationary response data can be analyzed by the stationary method SOBI. This paper also delineates non-stationary cases where SOBI and the proposed scheme perform comparably and highlights cases where the proposed approach is more advantageous. Finally, the performance of the proposed method is evaluated using a full-scale non-stationary response of a tall building during an earthquake and found it to perform satisfactorily.

Performance Assessment of the CapitalBio Mycobacterium Identification Array System for Identification of Mycobacteria

PubMed Central

Liu, Jingbo; Yan, Zihe; Han, Min; Han, Zhijun; Jin, Lingjie; Zhao, Yanlin

2012-01-01

The CapitalBio Mycobacterium identification microarray system is a rapid system for the detection of Mycobacterium tuberculosis. The performance of this system was assessed with 24 reference strains, 486 Mycobacterium tuberculosis clinical isolates, and 40 clinical samples and then compared to the “gold standard” of DNA sequencing. The CapitalBio Mycobacterium identification microarray system showed highly concordant identification results of 100% and 98.4% for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), respectively. The sensitivity and specificity of the CapitalBio Mycobacterium identification array for identification of Mycobacterium tuberculosis isolates were 99.6% and 100%, respectively, for direct detection and identification of clinical samples, and the overall sensitivity was 52.5%. It was 100% for sputum, 16.7% for pleural fluid, and 10% for bronchoalveolar lavage fluid, respectively. The total assay was completed in 6 h, including DNA extraction, PCR, and hybridization. The results of this study confirm the utility of this system for the rapid identification of mycobacteria and suggest that the CapitalBio Mycobacterium identification array is a molecular diagnostic technique with high sensitivity and specificity that has the capacity to quickly identify most mycobacteria. PMID:22090408

Comparison of modal identification techniques using a hybrid-data approach

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1986-01-01

Modal identification of seemingly simple structures, such as the generic truss is often surprisingly difficult in practice due to high modal density, nonlinearities, and other nonideal factors. Under these circumstances, different data analysis techniques can generate substantially different results. The initial application of a new hybrid-data method for studying the performance characteristics of various identification techniques with such data is summarized. This approach offers new pieces of information for the system identification researcher. First, it allows actual experimental data to be used in the studies, while maintaining the traditional advantage of using simulated data. That is, the identification technique under study is forced to cope with the complexities of real data, yet the performance can be measured unquestionably for the artificial modes because their true parameters are known. Secondly, the accuracy achieved for the true structural modes in the data can be estimated from the accuracy achieved for the artificial modes if the results show similar characteristics. This similarity occurred in the study, for example, for a weak structural mode near 56 Hz. It may even be possible--eventually--to use the error information from the artificial modes to improve the identification accuracy for the structural modes.

Control-based method to identify underlying delays of a nonlinear dynamical system.

PubMed

Yu, Dongchuan; Frasca, Mattia; Liu, Fang

2008-10-01

We suggest several stationary state control-based delay identification methods which do not require any structural information about the controlled systems and are applicable to systems described by delayed ordinary differential equations. This proposed technique includes three steps: (i) driving a system to a steady state; (ii) perturbing the control signal for shifting the steady state; and (iii) identifying all delays by detecting the time that the system is abruptly drawn out of stationarity. Some aspects especially important for applications are discussed as well, including interaction delay identification, stationary state convergence speed, performance comparison, and the influence of noise on delay identification. Several examples are presented to illustrate the reliability and robustness of all delay identification methods suggested.

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.

Heart Sound Biometric System Based on Marginal Spectrum Analysis

PubMed Central

Zhao, Zhidong; Shen, Qinqin; Ren, Fangqin

2013-01-01

This work presents a heart sound biometric system based on marginal spectrum analysis, which is a new feature extraction technique for identification purposes. This heart sound identification system is comprised of signal acquisition, pre-processing, feature extraction, training, and identification. Experiments on the selection of the optimal values for the system parameters are conducted. The results indicate that the new spectrum coefficients result in a significant increase in the recognition rate of 94.40% compared with that of the traditional Fourier spectrum (84.32%) based on a database of 280 heart sounds from 40 participants. PMID:23429515

Stable adaptive PI control for permanent magnet synchronous motor drive based on improved JITL technique.

PubMed

Zheng, Shiqi; Tang, Xiaoqi; Song, Bao; Lu, Shaowu; Ye, Bosheng

2013-07-01

In this paper, a stable adaptive PI control strategy based on the improved just-in-time learning (IJITL) technique is proposed for permanent magnet synchronous motor (PMSM) drive. Firstly, the traditional JITL technique is improved. The new IJITL technique has less computational burden and is more suitable for online identification of the PMSM drive system which is highly real-time compared to traditional JITL. In this way, the PMSM drive system is identified by IJITL technique, which provides information to an adaptive PI controller. Secondly, the adaptive PI controller is designed in discrete time domain which is composed of a PI controller and a supervisory controller. The PI controller is capable of automatically online tuning the control gains based on the gradient descent method and the supervisory controller is developed to eliminate the effect of the approximation error introduced by the PI controller upon the system stability in the Lyapunov sense. Finally, experimental results on the PMSM drive system show accurate identification and favorable tracking performance. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Application of MALDI-TOF MS Systems in the Rapid Identification of Campylobacter spp. of Public Health Importance.

PubMed

Hsieh, Ying-Hsin; Wang, Yun F; Moura, Hercules; Miranda, Nancy; Simpson, Steven; Gowrishankar, Ramnath; Barr, John; Kerdahi, Khalil; Sulaiman, Irshad M

2018-05-01

Campylobacteriosis is an infectious gastrointestinal disease caused by Campylobacter spp. In most cases, it is either underdiagnosed or underreported due to poor diagnostics and limited databases. Several DNA-based molecular diagnostic techniques, including 16S ribosomal RNA (rRNA) sequence typing, have been widely used in the species identification of Campylobacter. Nevertheless, these assays are time-consuming and require a high quality of bacterial DNA. Matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) MS is an emerging diagnostic technology that can provide the rapid identification of microorganisms by using their intact cells without extraction or purification. In this study, we analyzed 24 American Type Culture Collection reference isolates of 16 Campylobacter spp. and five unknown clinical bacterial isolates for rapid identification utilizing two commercially available MADI-TOF MS platforms, namely the bioMérieux VITEK® MS and Bruker Biotyper systems. In addition, 16S rRNA sequencing was performed to confirm the species-level identification of the unknown clinical isolates. Both MALDI-TOF MS systems identified the isolates of C. jejuni, C. coli, C. lari, and C. fetus. The results of this study suggest that the MALDI-TOF MS technique can be used in the identification of Campylobacter spp. of public health importance.

An Interactive Computer-Aided Instructional Strategy and Assessment Methods for System Identification and Adaptive Control Laboratory

ERIC Educational Resources Information Center

Özbek, Necdet Sinan; Eker, Ilyas

2015-01-01

This study describes a set of real-time interactive experiments that address system identification and model reference adaptive control (MRAC) techniques. In constructing laboratory experiments that contribute to efficient teaching, experimental design and instructional strategy are crucial, but a process for doing this has yet to be defined. This…

Validation of photo-identification as a mark-recapture method in the spotted eagle ray Aetobatus narinari.

PubMed

González-Ramos, M S; Santos-Moreno, A; Rosas-Alquicira, E F; Fuentes-Mascorro, G

2017-03-01

The spotted eagle ray Aetobatus narinari is characterized by pigmentation patterns that are retained for up to 3·5 years. These pigmentations can be used to identify individuals through photo-identification. Only one study has validated this technique, but no study has estimated the percentage of correct identification of the rays using this technique. In order to carry out demographic research, a reliable photographic identification technique is needed. To achieve this validation for A. narinari, a double-mark system was established over 11 months and photographs of the dorsal surface of 191 rays were taken. Three body parts with distinctive natural patterns were analysed (dorsal surface of the cephalic region, dorsal surface of the pectoral fins and dorsal surface of the pelvic fins) in order to determine the body part that could be used to give the highest percentage of correct identification. The dorsal surface of the pectoral fins of A. narinari provides the most accurate photo-identification to distinguish individuals (88·2%). © 2016 The Fisheries Society of the British Isles.

In-Flight System Identification

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1998-01-01

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

An adaptive technique for a redundant-sensor navigation system.

NASA Technical Reports Server (NTRS)

Chien, T.-T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.

Routine identification of medical fungi by the new Vitek MS matrix-assisted laser desorption ionization-time of flight system with a new time-effective strategy.

PubMed

Iriart, Xavier; Lavergne, Rose-Anne; Fillaux, Judith; Valentin, Alexis; Magnaval, Jean-François; Berry, Antoine; Cassaing, Sophie

2012-06-01

We report here a clinical evaluation of the Vitek MS system for rapid fungal identification. A strategy that uses a single deposit without prior protein extraction was utilized to save time and money. Clinical isolates from the Toulouse University hospital were used to evaluate the performance of the Vitek MS compared to that of both routine laboratory techniques and Vitek2. The Vitek MS performed well in the identification of yeasts and Aspergillus fungi (93.2% of correct identifications).

Inverse problems and optimal experiment design in unsteady heat transfer processes identification

NASA Technical Reports Server (NTRS)

Artyukhin, Eugene A.

1991-01-01

Experimental-computational methods for estimating characteristics of unsteady heat transfer processes are analyzed. The methods are based on the principles of distributed parameter system identification. The theoretical basis of such methods is the numerical solution of nonlinear ill-posed inverse heat transfer problems and optimal experiment design problems. Numerical techniques for solving problems are briefly reviewed. The results of the practical application of identification methods are demonstrated when estimating effective thermophysical characteristics of composite materials and thermal contact resistance in two-layer systems.

Enhanced Learning Methodologies and the Implementation of an Identification Course

NASA Astrophysics Data System (ADS)

Guidorzi, Roberto

This paper proposes some considerations on the role played by information and communication technologies in the evolution of educational systems and describes the design philosophy and the realization of a basic course on dynamic system identification that relies on constructivist methodologies and on the use of e-learning environments. It reports also some of the opinions formulated by the students on the effectiveness of the available tools and on their role in acquiring proficiency in the application of identification techniques in modeling real processes.

Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks

PubMed Central

Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

2015-01-01

Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. PMID:25856325

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.

The 32nd CDC: System identification using interval dynamic models

NASA Technical Reports Server (NTRS)

Keel, L. H.; Lew, J. S.; Bhattacharyya, S. P.

1992-01-01

Motivated by the recent explosive development of results in the area of parametric robust control, a new technique to identify a family of uncertain systems is identified. The new technique takes the frequency domain input and output data obtained from experimental test signals and produces an 'interval transfer function' that contains the complete frequency domain behavior with respect to the test signals. This interval transfer function is one of the key concepts in the parametric robust control approach and identification with such an interval model allows one to predict the worst case performance and stability margins using recent results on interval systems. The algorithm is illustrated by applying it to an 18 bay Mini-Mast truss structure.

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.

On-Orbit System Identification

NASA Technical Reports Server (NTRS)

Mettler, E.; Milman, M. H.; Bayard, D.; Eldred, D. B.

1987-01-01

Information derived from accelerometer readings benefits important engineering and control functions. Report discusses methodology for detection, identification, and analysis of motions within space station. Techniques of vibration and rotation analyses, control theory, statistics, filter theory, and transform methods integrated to form system for generating models and model parameters that characterize total motion of complicated space station, with respect to both control-induced and random mechanical disturbances.

Dynamic Identification for Control of Large Space Structures

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.

1985-01-01

This is a compilation of reports by the one author on one subject. It consists of the following five journal articles: (1) A Parametric Study of the Ibrahim Time Domain Modal Identification Algorithm; (2) Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique; (3) Computation of Normal Modes from Identified Complex Modes; (4) Dynamic Modeling of Structural from Measured Complex Modes; and (5) Time Domain Quasi-Linear Identification of Nonlinear Dynamic Systems.

Damage location and quantification of a pretensioned concrete beam using stochastic subspace identification

NASA Astrophysics Data System (ADS)

Cancelli, Alessandro; Micheli, Laura; Laflamme, Simon; Alipour, Alice; Sritharan, Sri; Ubertini, Filippo

2017-04-01

Stochastic subspace identification (SSID) is a first-order linear system identification technique enabling modal analysis through the time domain. Research in the field of structural health monitoring has demonstrated that SSID can be used to successfully retrieve modal properties, including modal damping ratios, using output-only measurements. In this paper, the utilization of SSID for indirectly retrieving structures' stiffness matrix was investigated, through the study of a simply supported reinforced concrete beam subjected to dynamic loads. Hence, by introducing a physical model of the structure, a second-order identification method is achieved. The reconstruction is based on system condensation methods, which enables calculation of reduced order stiffness, damping, and mass matrices for the structural system. The methods compute the reduced order matrices directly from the modal properties, obtained through the use of SSID. Lastly, the reduced properties of the system are used to reconstruct the stiffness matrix of the beam. The proposed approach is first verified through numerical simulations and then validated using experimental data obtained from a full-scale reinforced concrete beam that experienced progressive damage. Results show that the SSID technique can be used to diagnose, locate, and quantify damage through the reconstruction of the stiffness matrix.

Privacy-protected biometric templates: acoustic ear identification

NASA Astrophysics Data System (ADS)

Tuyls, Pim T.; Verbitskiy, Evgeny; Ignatenko, Tanya; Schobben, Daniel; Akkermans, Ton H.

2004-08-01

Unique Biometric Identifiers offer a very convenient way for human identification and authentication. In contrast to passwords they have hence the advantage that they can not be forgotten or lost. In order to set-up a biometric identification/authentication system, reference data have to be stored in a central database. As biometric identifiers are unique for a human being, the derived templates comprise unique, sensitive and therefore private information about a person. This is why many people are reluctant to accept a system based on biometric identification. Consequently, the stored templates have to be handled with care and protected against misuse [1, 2, 3, 4, 5, 6]. It is clear that techniques from cryptography can be used to achieve privacy. However, as biometric data are noisy, and cryptographic functions are by construction very sensitive to small changes in their input, and hence one can not apply those crypto techniques straightforwardly. In this paper we show the feasibility of the techniques developed in [5], [6] by applying them to experimental biometric data. As biometric identifier we have choosen the shape of the inner ear-canal, which is obtained by measuring the headphone-to-ear-canal Transfer Functions (HpTFs) which are known to be person dependent [7].

Recursive Deadbeat Controller Design

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh Q.

1997-01-01

This paper presents a recursive algorithm for a deadbeat predictive controller design. The method combines together the concepts of system identification and deadbeat controller designs. It starts with the multi-step output prediction equation and derives the control force in terms of past input and output time histories. The formulation thus derived satisfies simultaneously system identification and deadbeat controller design requirements. As soon as the coefficient matrices are identified satisfying the output prediction equation, no further work is required to compute the deadbeat control gain matrices. The method can be implemented recursively just as any typical recursive system identification techniques.

Mass spectrometry applied to the identification of Mycobacterium tuberculosis and biomarker discovery.

PubMed

López-Hernández, Y; Patiño-Rodríguez, O; García-Orta, S T; Pinos-Rodríguez, J M

2016-12-01

An adequate and effective tuberculosis (TB) diagnosis system has been identified by the World Health Organization as a priority in the fight against this disease. Over the years, several methods have been developed to identify the bacillus, but bacterial culture remains one of the most affordable methods for most countries. For rapid and accurate identification, however, it is more feasible to implement molecular techniques, taking advantage of the availability of public databases containing protein sequences. Mass spectrometry (MS) has become an interesting technique for the identification of TB. Here, we review some of the most widely employed methods for identifying Mycobacterium tuberculosis and present an update on MS applied for the identification of mycobacterial species. © 2016 The Society for Applied Microbiology.

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.

Output-only cyclo-stationary linear-parameter time-varying stochastic subspace identification method for rotating machinery and spinning structures

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2015-02-01

Economical maintenance and operation are critical issues for rotating machinery and spinning structures containing blade elements, especially large slender dynamic beams (e.g., wind turbines). Structural health monitoring systems represent promising instruments to assure reliability and good performance from the dynamics of the mechanical systems. However, such devices have not been completely perfected for spinning structures. These sensing technologies are typically informed by both mechanistic models coupled with data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order, especially when overlapping frequency content is present. Instead, time-domain techniques have shown to possess powerful advantages from a practical point of view (i.e. low-order computational effort suitable for real-time or embedded algorithms) and also are more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify this analysis, but such cannot be the case for sinusoidally loaded structures containing spinning multi-bodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system and the interaction of the supporting substructure. Transformations of the cyclic effects on the vibrational data can be applied to isolate inertial quantities that are different from rotation-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated eigensystem realizations. In this paper, an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here for spinning multi-blade systems by means of a modified Eigensystem Realization Algorithm (ERA) via stochastic subspace identification (SSI) and linear parameter time-varying (LPTV) techniques. Structural response is assumed to be stationary ambient excitation produced by a Gaussian (white) noise within the operative range bandwidth of the machinery or structure in study. ERA-OKID analysis is driven by correlation-function matrices from the stationary ambient response aiming to reduce noise effects. Singular value decomposition (SVD) and eigenvalue analysis are computed in a last stage to identify frequencies and complex-valued mode shapes. Proposed assumptions are carefully weighted to account for the uncertainty of the environment. A numerical example is carried out based a spinning finite element (SFE) model, and verified using ANSYS® Ver. 12. Finally, comments and observations are provided on how this subspace realization technique can be extended to the problem of modal-parameter identification using only ambient vibration data.

Applications of integrated human error identification techniques on the chemical cylinder change task.

PubMed

Cheng, Ching-Min; Hwang, Sheue-Ling

2015-03-01

This paper outlines the human error identification (HEI) techniques that currently exist to assess latent human errors. Many formal error identification techniques have existed for years, but few have been validated to cover latent human error analysis in different domains. This study considers many possible error modes and influential factors, including external error modes, internal error modes, psychological error mechanisms, and performance shaping factors, and integrates several execution procedures and frameworks of HEI techniques. The case study in this research was the operational process of changing chemical cylinders in a factory. In addition, the integrated HEI method was used to assess the operational processes and the system's reliability. It was concluded that the integrated method is a valuable aid to develop much safer operational processes and can be used to predict human error rates on critical tasks in the plant. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

NASA Astrophysics Data System (ADS)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

In the aeroelastic analysis of flight vehicles with electromechanical actuators (EMAs), an accurate prediction of flutter requires dynamic stiffness characteristics of the EMA. The dynamic stiffness transfer function of the EMA with brushless direct current (BLDC) motor can be obtained by conducting complicated mathematical calculations of control algorithms and mechanical/electrical nonlinearities using linearization techniques. Thus, system identification approaches using experimental data, as an alternative, have considerable advantages. However, the test setup for system identification is expensive and complex, and experimental procedures for data collection are time-consuming tasks. To obtain the dynamic stiffness transfer function, this paper proposes a linear system identification method that uses information obtained from a reliable dynamic stiffness model with a control algorithm and nonlinearities. The results of this study show that the system identification procedure is compact, and the transfer function is able to describe the dynamic stiffness characteristics of the EMA. In addition, to verify the validity of the system identification method, the simulation results of the dynamic stiffness transfer function and the dynamic stiffness model were compared with the experimental data for various external loads.

Effective techniques for the identification and accommodation of disturbances

NASA Technical Reports Server (NTRS)

Johnson, C. D.

1989-01-01

The successful control of dynamic systems such as space stations, or launch vehicles, requires a controller design methodology that acknowledges and addresses the disruptive effects caused by external and internal disturbances that inevitably act on such systems. These disturbances, technically defined as uncontrollable inputs, typically vary with time in an uncertain manner and usually cannot be directly measured in real time. A relatively new non-statistical technique for modeling, and (on-line) identification, of those complex uncertain disturbances that are not as erratic and capricious as random noise is described. This technique applies to multi-input cases and to many of the practical disturbances associated with the control of space stations, or launch vehicles. Then, a collection of smart controller design techniques that allow controlled dynamic systems, with possible multi-input controls, to accommodate (cope with) such disturbances with extraordinary effectiveness are associated. These new smart controllers are designed by non-statistical techniques and typically turn out to be unconventional forms of dynamic linear controllers (compensators) with constant coefficients. The simplicity and reliability of linear, constant coefficient controllers is well-known in the aerospace field.

Ballistics projectile image analysis for firearm identification.

PubMed

Li, Dongguang

2006-10-01

This paper is based upon the observation that, when a bullet is fired, it creates characteristic markings on the cartridge case and projectile. From these markings, over 30 different features can be distinguished, which, in combination, produce a "fingerprint" for a firearm. By analyzing features within such a set of firearm fingerprints, it will be possible to identify not only the type and model of a firearm, but also each and every individual weapon just as effectively as human fingerprint identification. A new analytic system based on the fast Fourier transform for identifying projectile specimens by the line-scan imaging technique is proposed in this paper. This paper develops optical, photonic, and mechanical techniques to map the topography of the surfaces of forensic projectiles for the purpose of identification. Experiments discussed in this paper are performed on images acquired from 16 various weapons. Experimental results show that the proposed system can be used for firearm identification efficiently and precisely through digitizing and analyzing the fired projectiles specimens.

Generalized approach for identification and evaluation of technology-insertion options for military avionics systems

NASA Astrophysics Data System (ADS)

Harkness, Linda L.; Sjoberg, Eric S.

1996-06-01

The Georgia Tech Research Institute, sponsored by the Warner Robins Air Logistics Center, has developed an approach for efficiently postulating and evaluating methods for extending the life of radars and other avionics systems. The technique identified specific assemblies for potential replacement and evaluates the system level impact, including performance, reliability and life-cycle cost of each action. The initial impetus for this research was the increasing obsolescence of integrated circuits contained in the AN/APG-63 system. The operational life of military electronics is typically in excess of twenty years, which encompasses several generations of IC technology. GTRI has developed a systems approach to inserting modern technology components into older systems based upon identification of those functions which limit the system's performance or reliability and which are cost drivers. The presentation will discuss the above methodology and a technique for evaluating and ranking the different potential system upgrade options.

Occupational Analysis Technology: Expanded Role in Development of Cost-Effective Maintenance Systems. Final Report.

ERIC Educational Resources Information Center

Foley, John P., Jr.

A study was conducted to refine and coordinate occupational analysis, job performance aids, and elements of the instructional systems development process for task specific Air Force maintenance training. Techniques for task identification and analysis (TI & A) and data gathering techniques for occupational analysis were related. While TI &…

Evaluation of the utility of a glycemic pattern identification system.

PubMed

Otto, Erik A; Tannan, Vinay

2014-07-01

With the increasing prevalence of systems allowing automated, real-time transmission of blood glucose data there is a need for pattern recognition techniques that can inform of deleterious patterns in glycemic control when people test. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes. To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows. Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The system was also significantly more predictive of deleterious events than other pattern identification methods evaluated, and was persistently predictive up to 3 months after pattern identification. The system identified patterns that are significantly predictive of deleterious glycemic events, and more so relative to many pattern identification methods used in diabetes management today. Further study will inform how improved pattern identification can lead to improved glycemic control. © 2014 Diabetes Technology Society.

Decoupling Identification for Serial Two-Link Two-Inertia System

NASA Astrophysics Data System (ADS)

Oaki, Junji; Adachi, Shuichi

The purpose of our study is to develop a precise model by applying the technique of system identification for the model-based control of a nonlinear robot arm, under taking joint-elasticity into consideration. We previously proposed a systematic identification method, called “decoupling identification,” for a “SCARA-type” planar two-link robot arm with elastic joints caused by the Harmonic-drive® reduction gears. The proposed method serves as an extension of the conventional rigid-joint-model-based identification. The robot arm is treated as a serial two-link two-inertia system with nonlinearity. The decoupling identification method using link-accelerometer signals enables the serial two-link two-inertia system to be divided into two linear one-link two-inertia systems. The MATLAB®'s commands for state-space model estimation are utilized in the proposed method. Physical parameters such as motor inertias, link inertias, joint-friction coefficients, and joint-spring coefficients are estimated through the identified one-link two-inertia systems using a gray-box approach. This paper describes accuracy evaluations using the two-link arm for the decoupling identification method under introducing closed-loop-controlled elements and varying amplitude-setup of identification-input. Experimental results show that the identification method also works with closed-loop-controlled elements. Therefore, the identification method is applicable to a “PUMA-type” vertical robot arm under gravity.

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.

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Raman scattering spectroscopy for explosives identification

NASA Astrophysics Data System (ADS)

Nagli, L.; Gaft, M.

2007-04-01

Real time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called Improvised Explosive Devices (IED). It is recognized that the only technique, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS technique belongs to trace detection, namely to its micro-particles variety. We applied gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. Raman system was developed and tested by LDS for field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Particle image velocimetry for the Surface Tension Driven Convection Experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Particle image velocimetry for the surface tension driven convection experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

A hybrid LIBS-Raman system combined with chemometrics: an efficient tool for plastic identification and sorting.

PubMed

Shameem, K M Muhammed; Choudhari, Khoobaram S; Bankapur, Aseefhali; Kulkarni, Suresh D; Unnikrishnan, V K; George, Sajan D; Kartha, V B; Santhosh, C

2017-05-01

Classification of plastics is of great importance in the recycling industry as the littering of plastic wastes increases day by day as a result of its extensive use. In this paper, we demonstrate the efficacy of a combined laser-induced breakdown spectroscopy (LIBS)-Raman system for the rapid identification and classification of post-consumer plastics. The atomic information and molecular information of polyethylene terephthalate, polyethylene, polypropylene, and polystyrene were studied using plasma emission spectra and scattered signal obtained in the LIBS and Raman technique, respectively. The collected spectral features of the samples were analyzed using statistical tools (principal component analysis, Mahalanobis distance) to categorize the plastics. The analyses of the data clearly show that elemental information and molecular information obtained from these techniques are efficient for classification of plastics. In addition, the molecular information collected via Raman spectroscopy exhibits clearly distinct features for the transparent plastics (100% discrimination), whereas the LIBS technique shows better spectral feature differences for the colored samples. The study shows that the information obtained from these complementary techniques allows the complete classification of the plastic samples, irrespective of the color or additives. This work further throws some light on the fact that the potential limitations of any of these techniques for sample identification can be overcome by the complementarity of these two techniques. Graphical Abstract ᅟ.

Identification of Low Order Equivalent System Models From Flight Test Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2000-01-01

Identification of low order equivalent system dynamic models from flight test data was studied. Inputs were pilot control deflections, and outputs were aircraft responses, so the models characterized the total aircraft response including bare airframe and flight control system. Theoretical investigations were conducted and related to results found in the literature. Low order equivalent system modeling techniques using output error and equation error parameter estimation in the frequency domain were developed and validated on simulation data. It was found that some common difficulties encountered in identifying closed loop low order equivalent system models from flight test data could be overcome using the developed techniques. Implications for data requirements and experiment design were discussed. The developed methods were demonstrated using realistic simulation cases, then applied to closed loop flight test data from the NASA F-18 High Alpha Research Vehicle.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

Olivari, Mario; Nieuwenhuizen, Frank M; Venrooij, Joost; Bülthoff, Heinrich H; Pollini, Lorenzo

2015-12-01

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

Optical security system for the protection of personal identification information.

PubMed

Doh, Yang-Hoi; Yoon, Jong-Soo; Choi, Kyung-Hyun; Alam, Mohammad S

2005-02-10

A new optical security system for the protection of personal identification information is proposed. First, authentication of the encrypted personal information is carried out by primary recognition of a personal identification number (PIN) with the proposed multiplexed minimum average correlation energy phase-encrypted (MMACE_p) filter. The MMACE_p filter, synthesized with phase-encrypted training images, can increase the discrimination capability and prevent the leak of personal identification information. After the PIN is recognized, speedy authentication of personal information can be achieved through one-to-one optical correlation by means of the optical wavelet filter. The possibility of information counterfeiting can be significantly decreased with the double-identification process. Simulation results demonstrate the effectiveness of the proposed technique.

Eigensystem realization algorithm user's guide forVAX/VMS computers: Version 931216

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1994-01-01

The eigensystem realization algorithm (ERA) is a multiple-input, multiple-output, time domain technique for structural modal identification and minimum-order system realization. Modal identification is the process of calculating structural eigenvalues and eigenvectors (natural vibration frequencies, damping, mode shapes, and modal masses) from experimental data. System realization is the process of constructing state-space dynamic models for modern control design. This user's guide documents VAX/VMS-based FORTRAN software developed by the author since 1984 in conjunction with many applications. It consists of a main ERA program and 66 pre- and post-processors. The software provides complete modal identification capabilities and most system realization capabilities.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1992-01-01

Continuing work on frequency analysis for transfer function identification is discussed. A new study was initiated into a 'weighted' least squares algorithm within the context of the Fourier modulating function approach. The first phase of applying these techniques to the F-18 flight data is nearing completion, and these results are summarized.

Modeling and Model Identification of Autonomous Underwater Vehicles

DTIC Science & Technology

2015-06-01

setup, based on a quadrifilar pendulum , is developed to measure the moments of inertia of the vehicle. System identification techniques, based on...parametric models of the platforms: an individual channel excitation approach and a free decay pendulum test. The former is applied to THAUS, which can...excite the system in individual channels in four degrees of freedom. These results are verified in the free decay pendulum setup, which has the

An experimental approach to identify dynamical models of transcriptional regulation in living cells

NASA Astrophysics Data System (ADS)

Fiore, G.; Menolascina, F.; di Bernardo, M.; di Bernardo, D.

2013-06-01

We describe an innovative experimental approach, and a proof of principle investigation, for the application of System Identification techniques to derive quantitative dynamical models of transcriptional regulation in living cells. Specifically, we constructed an experimental platform for System Identification based on a microfluidic device, a time-lapse microscope, and a set of automated syringes all controlled by a computer. The platform allows delivering a time-varying concentration of any molecule of interest to the cells trapped in the microfluidics device (input) and real-time monitoring of a fluorescent reporter protein (output) at a high sampling rate. We tested this platform on the GAL1 promoter in the yeast Saccharomyces cerevisiae driving expression of a green fluorescent protein (Gfp) fused to the GAL1 gene. We demonstrated that the System Identification platform enables accurate measurements of the input (sugars concentrations in the medium) and output (Gfp fluorescence intensity) signals, thus making it possible to apply System Identification techniques to obtain a quantitative dynamical model of the promoter. We explored and compared linear and nonlinear model structures in order to select the most appropriate to derive a quantitative model of the promoter dynamics. Our platform can be used to quickly obtain quantitative models of eukaryotic promoters, currently a complex and time-consuming process.

Comparison of frequency-domain and time-domain rotorcraft vibration control methods

NASA Technical Reports Server (NTRS)

Gupta, N. K.

1984-01-01

Active control of rotor-induced vibration in rotorcraft has received significant attention recently. Two classes of techniques have been proposed. The more developed approach works with harmonic analysis of measured time histories and is called the frequency-domain approach. The more recent approach computes the control input directly using the measured time history data and is called the time-domain approach. The report summarizes the results of a theoretical investigation to compare the two approaches. Five specific areas were addressed: (1) techniques to derive models needed for control design (system identification methods), (2) robustness with respect to errors, (3) transient response, (4) susceptibility to noise, and (5) implementation difficulties. The system identification methods are more difficult for the time-domain models. The time-domain approach is more robust (e.g., has higher gain and phase margins) than the frequency-domain approach. It might thus be possible to avoid doing real-time system identification in the time-domain approach by storing models at a number of flight conditions. The most significant error source is the variation in open-loop vibrations caused by pilot inputs, maneuvers or gusts. The implementation requirements are similar except that the time-domain approach can be much simpler to implement if real-time system identification were not necessary.

MALDI-TOF MS versus VITEK 2 ANC card for identification of anaerobic bacteria.

PubMed

Li, Yang; Gu, Bing; Liu, Genyan; Xia, Wenying; Fan, Kun; Mei, Yaning; Huang, Peijun; Pan, Shiyang

2014-05-01

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an accurate, rapid and inexpensive technique that has initiated a revolution in the clinical microbiology laboratory for identification of pathogens. The Vitek 2 anaerobe and Corynebacterium (ANC) identification card is a newly developed method for identification of corynebacteria and anaerobic species. The aim of this study was to evaluate the effectiveness of the ANC card and MALDI-TOF MS techniques for identification of clinical anaerobic isolates. Five reference strains and a total of 50 anaerobic bacteria clinical isolates comprising ten different genera and 14 species were identified and analyzed by the ANC card together with Vitek 2 identification system and Vitek MS together with version 2.0 database respectively. 16S rRNA gene sequencing was used as reference method for accuracy in the identification. Vitek 2 ANC card and Vitek MS provided comparable results at species level for the five reference strains. Of 50 clinical strains, the Vitek MS provided identification for 46 strains (92%) to the species level, 47 (94%) to genus level, one (2%) low discrimination, two (4%) no identification and one (2%) misidentification. The Vitek 2 ANC card provided identification for 43 strains (86%) correct to the species level, 47 (94%) correct to the genus level, three (6%) low discrimination, three (6%) no identification and one (2%) misidentification. Both Vitek MS and Vitek 2 ANC card can be used for accurate routine clinical anaerobe identification. Comparing to the Vitek 2 ANC card, Vitek MS is easier, faster and more economic for each test. The databases currently available for both systems should be updated and further developed to enhance performance.

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

Identification of visual evoked response parameters sensitive to pilot mental state

NASA Technical Reports Server (NTRS)

Zacharias, G. L.

1988-01-01

Systems analysis techniques were developed and demonstrated for modeling the electroencephalographic (EEG) steady state visual evoked response (ssVER), for use in EEG data compression and as an indicator of mental workload. The study focused on steady state frequency domain stimulation and response analysis, implemented with a sum-of-sines (SOS) stimulus generator and an off-line describing function response analyzer. Three major tasks were conducted: (1) VER related systems identification material was reviewed; (2) Software for experiment control and data analysis was developed and implemented; and (3) ssVER identification and modeling was demonstrated, via a mental loading experiment. It was found that a systems approach to ssVER functional modeling can serve as the basis for eventual development of a mental workload indicator. The review showed how transient visual evoked response (tVER) and ssVER research are related at the functional level, the software development showed how systems techniques can be used for ssVER characterization, and the pilot experiment showed how a simple model can be used to capture the basic dynamic response of the ssVER, under varying loads.

Rotorcraft system identification techniques for handling qualities and stability and control evaluation

NASA Technical Reports Server (NTRS)

Hall, W. E., Jr.; Gupta, N. K.; Hansen, R. S.

1978-01-01

An integrated approach to rotorcraft system identification is described. This approach consists of sequential application of (1) data filtering to estimate states of the system and sensor errors, (2) model structure estimation to isolate significant model effects, and (3) parameter identification to quantify the coefficient of the model. An input design algorithm is described which can be used to design control inputs which maximize parameter estimation accuracy. Details of each aspect of the rotorcraft identification approach are given. Examples of both simulated and actual flight data processing are given to illustrate each phase of processing. The procedure is shown to provide means of calibrating sensor errors in flight data, quantifying high order state variable models from the flight data, and consequently computing related stability and control design models.

Search-based model identification of smart-structure damage

NASA Technical Reports Server (NTRS)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

21 CFR 866.5640 - Infectious mononucleosis immunological test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Infectious mononucleosis immunological test system....5640 Infectious mononucleosis immunological test system. (a) Identification. An infectious... immunochemical techniques heterophile antibodies frequently associated with infectious mononucleosis in serum...

21 CFR 866.5640 - Infectious mononucleosis immunological test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Infectious mononucleosis immunological test system....5640 Infectious mononucleosis immunological test system. (a) Identification. An infectious... immunochemical techniques heterophile antibodies frequently associated with infectious mononucleosis in serum...

21 CFR 866.5640 - Infectious mononucleosis immunological test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Infectious mononucleosis immunological test system....5640 Infectious mononucleosis immunological test system. (a) Identification. An infectious... immunochemical techniques heterophile antibodies frequently associated with infectious mononucleosis in serum...

21 CFR 866.5640 - Infectious mononucleosis immunological test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Infectious mononucleosis immunological test system....5640 Infectious mononucleosis immunological test system. (a) Identification. An infectious... immunochemical techniques heterophile antibodies frequently associated with infectious mononucleosis in serum...

21 CFR 866.5640 - Infectious mononucleosis immunological test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Infectious mononucleosis immunological test system....5640 Infectious mononucleosis immunological test system. (a) Identification. An infectious... immunochemical techniques heterophile antibodies frequently associated with infectious mononucleosis in serum...

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

Recent developments in learning control and system identification for robots and structures

NASA Technical Reports Server (NTRS)

Phan, M.; Juang, J.-N.; Longman, R. W.

1990-01-01

This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1991-01-01

A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Utilization of volume correlation filters for underwater mine identification in LIDAR imagery

NASA Astrophysics Data System (ADS)

Walls, Bradley

2008-04-01

Underwater mine identification persists as a critical technology pursued aggressively by the Navy for fleet protection. As such, new and improved techniques must continue to be developed in order to provide measurable increases in mine identification performance and noticeable reductions in false alarm rates. In this paper we show how recent advances in the Volume Correlation Filter (VCF) developed for ground based LIDAR systems can be adapted to identify targets in underwater LIDAR imagery. Current automated target recognition (ATR) algorithms for underwater mine identification employ spatial based three-dimensional (3D) shape fitting of models to LIDAR data to identify common mine shapes consisting of the box, cylinder, hemisphere, truncated cone, wedge, and annulus. VCFs provide a promising alternative to these spatial techniques by correlating 3D models against the 3D rendered LIDAR data.

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.

Compressed ECG biometric: a fast, secured and efficient method for identification of CVD patient.

PubMed

Sufi, Fahim; Khalil, Ibrahim; Mahmood, Abdun

2011-12-01

Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of Electrocardiography (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional step of decompression creates a significant processing delay for identification task. This becomes an obvious burden on a system, if this needs to be done for a trillion of compressed ECG per hour by the hospital. Even though the hospital might be able to come up with an expensive infrastructure to tame the exuberant processing, for small intermediate nodes in a multihop network identification preceded by decompression is confronting. In this paper, we report a technique by which a person can be identified directly from his / her compressed ECG. This technique completely obviates the step of decompression and therefore upholds biometric identification less intimidating for the smaller nodes in a multihop network. The biometric template created by this new technique is lower in size compared to the existing ECG based biometrics as well as other forms of biometrics like face, finger, retina etc. (up to 8302 times lower than face template and 9 times lower than existing ECG based biometric template). Lower size of the template substantially reduces the one-to-many matching time for biometric recognition, resulting in a faster biometric authentication mechanism.

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

Nonlinear and Digital Man-machine Control Systems Modeling

NASA Technical Reports Server (NTRS)

Mekel, R.

1972-01-01

An adaptive modeling technique is examined by which controllers can be synthesized to provide corrective dynamics to a human operator's mathematical model in closed loop control systems. The technique utilizes a class of Liapunov functions formulated for this purpose, Liapunov's stability criterion and a model-reference system configuration. The Liapunov function is formulated to posses variable characteristics to take into consideration the identification dynamics. The time derivative of the Liapunov function generate the identification and control laws for the mathematical model system. These laws permit the realization of a controller which updates the human operator's mathematical model parameters so that model and human operator produce the same response when subjected to the same stimulus. A very useful feature is the development of a digital computer program which is easily implemented and modified concurrent with experimentation. The program permits the modeling process to interact with the experimentation process in a mutually beneficial way.

Chemical and microbiological experimentation for development of environmental control and life support systems

NASA Technical Reports Server (NTRS)

Whitman, G. A.; Wilson, M. E.; Cole, H. E.; Traweek, M.

1992-01-01

Microbiological techniques are under study with a view to the identification of viable microorganisms in liquid cultures, improve the identification of stressed organisms, and determine the biocidal activity of iodine and other chemicals on isolates from recycled water. A quality-assurance program has been implemented to validate data employed in making decisions concerning engineering and human health and safety. Analytical laboratory refinements will strongly aid the development of environmental control and life-support systems.

A Demonstration of Techniques in the Identification, Diagnosis, and Treatment of Children with Learning Disabilities. Final Report.

ERIC Educational Resources Information Center

Skokie School District 68, IL.

A Chicago suburban public school with approximately 450 children per grade level demonstrated a system-wide program for identification, diagnosis, and educational treatment of children with learning disabilities in grades 2 through 6. Children were judged to underachieve when achievement measures in language or mathematics fell more than 10% below…

Spectral identification of a 90Sr source in the presence of masking nuclides using Maximum-Likelihood deconvolution

NASA Astrophysics Data System (ADS)

Neuer, Marcus J.

2013-11-01

A technique for the spectral identification of strontium-90 is shown, utilising a Maximum-Likelihood deconvolution. Different deconvolution approaches are discussed and summarised. Based on the intensity distribution of the beta emission and Geant4 simulations, a combined response matrix is derived, tailored to the β- detection process in sodium iodide detectors. It includes scattering effects and attenuation by applying a base material decomposition extracted from Geant4 simulations with a CAD model for a realistic detector system. Inversion results of measurements show the agreement between deconvolution and reconstruction. A detailed investigation with additional masking sources like 40K, 226Ra and 131I shows that a contamination of strontium can be found in the presence of these nuisance sources. Identification algorithms for strontium are presented based on the derived technique. For the implementation of blind identification, an exemplary masking ratio is calculated.

Application of Raman spectroscopy to identification and sorting of post-consumer plastics for recycling

DOEpatents

Sommer, Edward J.; Rich, John T.

2001-01-01

A high accuracy rapid system for sorting a plurality of waste products by polymer type. The invention involves the application of Raman spectroscopy and complex identification techniques to identify and sort post-consumer plastics for recycling. The invention reads information unique to the molecular structure of the materials to be sorted to identify their chemical compositions and uses rapid high volume sorting techniques to sort them into product streams at commercially viable throughput rates. The system employs a laser diode (20) for irradiating the material sample (10), a spectrograph (50) is used to determine the Raman spectrum of the material sample (10) and a microprocessor based controller (70) is employed to identify the polymer type of the material sample (10).

21 CFR 866.5170 - Breast milk immunological test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Breast milk immunological test system. 866.5170... milk immunological test system. (a) Identification. A breast milk immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the breast milk proteins. (b...

21 CFR 866.5170 - Breast milk immunological test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Breast milk immunological test system. 866.5170... milk immunological test system. (a) Identification. A breast milk immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the breast milk proteins. (b...

21 CFR 866.5170 - Breast milk immunological test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Breast milk immunological test system. 866.5170... milk immunological test system. (a) Identification. A breast milk immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the breast milk proteins. (b...

21 CFR 866.5170 - Breast milk immunological test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Breast milk immunological test system. 866.5170... milk immunological test system. (a) Identification. A breast milk immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the breast milk proteins. (b...

Radar studies of arctic ice and development of a real-time Arctic ice type identification system

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr.; Schell, J. A.; Permenter, J. A.

1973-01-01

Studies were conducted to develop a real-time Arctic ice type identification system. Data obtained by NASA Mission 126, conducted at Pt. Barrow, Alaska (Site 93) in April 1970 was analyzed in detail to more clearly define the major mechanisms at work affecting the radar energy illuminating a terrain cell of sea ice. General techniques for reduction of the scatterometer data to a form suitable for application of ice type decision criteria were investigated, and the electronic circuit requirements for implementation of these techniques were determined. Also, consideration of circuit requirements are extended to include the electronics necessary for analog programming of ice type decision algorithms. After completing the basic circuit designs a laboratory model was constructed and a preliminary evaluation performed. Several system modifications for improved performance are suggested. (Modified author abstract)

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1993-01-01

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study

PubMed Central

Chen, Zengshun; Zhou, Xiao; Wang, Xu; Dong, Lili; Qian, Yuanhao

2017-01-01

Structural health monitoring (SHM) technology for surveillance and evaluation of existing and newly built long-span bridges has been widely developed, and the significance of the technique has been recognized by many administrative authorities. The paper reviews the recent progress of the SHM technology that has been applied to long-span bridges. The deployment of a SHM system is introduced. Subsequently, the data analysis and condition assessment including techniques on modal identification, methods on signal processing, and damage identification were reviewed and summarized. A case study about a SHM system of a long-span arch bridge (the Jiubao bridge in China) was systematically incorporated in each part to advance our understanding of deployment and investigation of a SHM system for long-span arch bridges. The applications of SHM systems of long-span arch bridge were also introduced. From the illustrations, the challenges and future trends for development a SHM system were concluded. PMID:28925943

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

NASA Technical Reports Server (NTRS)

Juang, J. N.; Pappa, R. S.

1985-01-01

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

A Galerkin method for the estimation of parameters in hybrid systems governing the vibration of flexible beams with tip bodies

NASA Technical Reports Server (NTRS)

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

1985-01-01

An approximation scheme is developed for the identification of hybrid systems describing the transverse vibrations of flexible beams with attached tip bodies. In particular, problems involving the estimation of functional parameters are considered. The identification problem is formulated as a least squares fit to data subject to the coupled system of partial and ordinary differential equations describing the transverse displacement of the beam and the motion of the tip bodies respectively. A cubic spline-based Galerkin method applied to the state equations in weak form and the discretization of the admissible parameter space yield a sequence of approximating finite dimensional identification problems. It is shown that each of the approximating problems admits a solution and that from the resulting sequence of optimal solutions a convergent subsequence can be extracted, the limit of which is a solution to the original identification problem. The approximating identification problems can be solved using standard techniques and readily available software.

Advanced driver assistance system: Road sign identification using VIAPIX system and a correlation technique

NASA Astrophysics Data System (ADS)

Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.

2017-02-01

We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.

System identification of jet engines

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

Sugiyama, N.

2000-01-01

System identification plays an important role in advanced control systems for jet engines, in which controls are performed adaptively using data from the actual engine and the identified engine. An identification technique for jet engine using the Constant Gain Extended Kalman Filter (CGEKF) is described. The filter is constructed for a two-spool turbofan engine. The CGEKF filter developed here can recognize parameter change in engine components and estimate unmeasurable variables over whole flight conditions. These capabilities are useful for an advanced Full Authority Digital Electric Control (FADEC). Effects of measurement noise and bias, effects of operating point and unpredicted performancemore » change are discussed. Some experimental results using the actual engine are shown to evaluate the effectiveness of CGEKF filter.« less

Optical/digital identification/verification system based on digital watermarking technology

NASA Astrophysics Data System (ADS)

Herrigel, Alexander; Voloshynovskiy, Sviatoslav V.; Hrytskiv, Zenon D.

2000-06-01

This paper presents a new approach for the secure integrity verification of driver licenses, passports or other analogue identification documents. The system embeds (detects) the reference number of the identification document with the DCT watermark technology in (from) the owner photo of the identification document holder. During verification the reference number is extracted and compared with the reference number printed in the identification document. The approach combines optical and digital image processing techniques. The detection system must be able to scan an analogue driver license or passport, convert the image of this document into a digital representation and then apply the watermark verification algorithm to check the payload of the embedded watermark. If the payload of the watermark is identical with the printed visual reference number of the issuer, the verification was successful and the passport or driver license has not been modified. This approach constitutes a new class of application for the watermark technology, which was originally targeted for the copyright protection of digital multimedia data. The presented approach substantially increases the security of the analogue identification documents applied in many European countries.

Hybrid neuro-fuzzy approach for automatic vehicle license plate recognition

NASA Astrophysics Data System (ADS)

Lee, Hsi-Chieh; Jong, Chung-Shi

1998-03-01

Most currently available vehicle identification systems use techniques such as R.F., microwave, or infrared to help identifying the vehicle. Transponders are usually installed in the vehicle in order to transmit the corresponding information to the sensory system. It is considered expensive to install a transponder in each vehicle and the malfunction of the transponder will result in the failure of the vehicle identification system. In this study, novel hybrid approach is proposed for automatic vehicle license plate recognition. A system prototype is built which can be used independently or cooperating with current vehicle identification system in identifying a vehicle. The prototype consists of four major modules including the module for license plate region identification, the module for character extraction from the license plate, the module for character recognition, and the module for the SimNet neuro-fuzzy system. To test the performance of the proposed system, three hundred and eighty vehicle image samples are taken by a digital camera. The license plate recognition success rate of the prototype is approximately 91% while the character recognition success rate of the prototype is approximately 97%.

Control Law Design in a Computational Aeroelasticity Environment

NASA Technical Reports Server (NTRS)

Newsom, Jerry R.; Robertshaw, Harry H.; Kapania, Rakesh K.

2003-01-01

A methodology for designing active control laws in a computational aeroelasticity environment is given. The methodology involves employing a systems identification technique to develop an explicit state-space model for control law design from the output of a computational aeroelasticity code. The particular computational aeroelasticity code employed in this paper solves the transonic small disturbance aerodynamic equation using a time-accurate, finite-difference scheme. Linear structural dynamics equations are integrated simultaneously with the computational fluid dynamics equations to determine the time responses of the structure. These structural responses are employed as the input to a modern systems identification technique that determines the Markov parameters of an "equivalent linear system". The Eigensystem Realization Algorithm is then employed to develop an explicit state-space model of the equivalent linear system. The Linear Quadratic Guassian control law design technique is employed to design a control law. The computational aeroelasticity code is modified to accept control laws and perform closed-loop simulations. Flutter control of a rectangular wing model is chosen to demonstrate the methodology. Various cases are used to illustrate the usefulness of the methodology as the nonlinearity of the aeroelastic system is increased through increased angle-of-attack changes.

Mass spectrometry techniques for studying the ubiquitin system.

PubMed

Heap, Rachel E; Gant, Megan S; Lamoliatte, Frederic; Peltier, Julien; Trost, Matthias

2017-10-15

Post-translational control of proteins through covalent attachment of ubiquitin plays important roles in all eukaryotic cell functions. The ubiquitin system in humans consists of 2 E1, 35 E2 and >600 E3 ubiquitin ligases as well as hundreds of deubiquitylases, which reverse ubiquitin attachment. Moreover, there are hundreds of proteins with ubiquitin-binding domains that bind one of the eight possible polyubiquitin chains. Dysfunction of the ubiquitin system is associated with many diseases such as cancer, autoimmunity and neurodegeneration, demonstrating the importance of ubiquitylation. Therefore, enzymes of the ubiquitin system are considered highly attractive drug targets. In recent years, mass spectrometry (MS)-based techniques have become increasingly important in the deciphering of the ubiquitin system. This short review addresses the state-of-the-art MS techniques for the identification of ubiquitylated proteins and their ubiquitylation sites. We also discuss the identification and quantitation of ubiquitin chain topologies and highlight how the activity of enzymes in the ubiquitin pathway can be measured. Finally, we present current MS tools that can be used for drug discovery in the ubiquitin space. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Mechanical system diagnostics using vibration testing techniques

NASA Technical Reports Server (NTRS)

Mcleod, Catherine D.; Raju, P. K.; Crocker, M. J.

1990-01-01

The 'Cepstrum' technique of vibration-path identification allows the recovery of the transfer function of a system with little knowledge as to its excitation force, by means of a mathematical manipulation of the system output in conjunction with subtraction of part of the output and suitable signal processing. An experimental program has been conducted to evaluate the usefulness of this technique in the cases of simple, cantilever-beam and free-free plate structures as well as in that of a complex mechanical system. On the basis of the transfer functions thus recovered, it was possible to evaluate the shifts in the resonance frequencies of a structure due to the presence of defects.

[A study of culture-based easy identification system for Malassezia].

PubMed

Kaneko, Takamasa

2011-01-01

Most species of this genus are lipid-dependent yeasts, which colonize the seborrheic part of the skin, and they have been reported to be associated with pityriasis versicolor, Malassezia folliculitis, seborrheic dermatitis, and atopic dermatitis. Malassezia have been re-classified into 7 species based on molecular biological analysis of nuclear ribosomal DNA/RNA and new Malassezia species were reported. As members of the genus Malassezia share similar morphological and biochemical characteristics, it was thought to be difficult to differentiate between them based on phenotypic features. While molecular biological techniques are the most reliable methods for identification of Malassezia, they are not available in most clinical laboratories. We studied ( i ) development of an efficient isolation media and culture based easy identification system, ( ii ) the incidence of atypical biochemical features in Malassezia species and propose a culture-based easy identification system for clinically important Malassezia species, M. globosa, M. restricta, and M. furfur.

Robotic Low Ligation of the Inferior Mesenteric Artery for Rectal Cancer Using the Firefly Technique.

PubMed

Bae, Sung Uk; Min, Byung Soh; Kim, Nam Kyu

2015-07-01

By integrating intraoperative near infrared fluorescence imaging into a robotic system, surgeons can identify the vascular anatomy in real-time with the technical advantages of robotics that is useful for meticulous lymphovascular dissection. Herein, we report our initial experience of robotic low ligation of the inferior mesenteric artery (IMA) with real-time identification of the vascular system for rectal cancer using the Firefly technique. The study group included 11 patients who underwent a robotic total mesorectal excision with preservation of the left colic artery for rectal cancer using the Firefly technique between July 2013 and December 2013. The procedures included five low anterior resections and six ultra-low anterior resections with loop ileostomy. The median total operation time was 327 min (226-490). The low ligation time was 10 min (6-20), and the time interval between indocyanine green injection and division of the sigmoid artery was 5 min (2-8). The estimated blood loss was 200 mL (100-500). The median time to soft diet was 4 days (4-5), and the median length of stay was 7 days (5-9). Three patients developed postoperative complications; one patients developed anal stricture, one developed ileus, and one developed non-complicated intraabdominal fluid collection. The median total number of lymph nodes harvested was 17 (9-29). Robotic low ligation of the IMA with real-time identification of the vascular system for rectal cancer using the Firefly technique is safe and feasible. This technique can allow for precise lymph node dissection along the IMA and facilitate the identification of the left colic branch of the IMA.

Parametric Robust Control and System Identification: Unified Approach

NASA Technical Reports Server (NTRS)

Keel, L. H.

1996-01-01

During the period of this support, a new control system design and analysis method has been studied. This approach deals with control systems containing uncertainties that are represented in terms of its transfer function parameters. Such a representation of the control system is common and many physical parameter variations fall into this type of uncertainty. Techniques developed here are capable of providing nonconservative analysis of such control systems with parameter variations. We have also developed techniques to deal with control systems when their state space representations are given rather than transfer functions. In this case, the plant parameters will appear as entries of state space matrices. Finally, a system modeling technique to construct such systems from the raw input - output frequency domain data has been developed.

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.

The Shock and Vibration Bulletin. Part 3. Machinery Dynamics, System Identification and Structural Analysis

DTIC Science & Technology

1985-06-01

purposes. 55 15 525 + 2 225L L53 + L3 ) + 2G3(L 2 + L35L4 + L45)" For the present system identification + 2G(L45 2 + L45L5 + L5 "L 1 technique, the...orbital model is comprised of 257 nodes and 819 dynamic:"DOF’s. k; were compared to ITD results for a wide variety of TD input parameters. Overall, the

An automated method of quantifying ferrite microstructures using electron backscatter diffraction (EBSD) data.

PubMed

Shrestha, Sachin L; Breen, Andrew J; Trimby, Patrick; Proust, Gwénaëlle; Ringer, Simon P; Cairney, Julie M

2014-02-01

The identification and quantification of the different ferrite microconstituents in steels has long been a major challenge for metallurgists. Manual point counting from images obtained by optical and scanning electron microscopy (SEM) is commonly used for this purpose. While classification systems exist, the complexity of steel microstructures means that identifying and quantifying these phases is still a great challenge. Moreover, point counting is extremely tedious, time consuming, and subject to operator bias. This paper presents a new automated identification and quantification technique for the characterisation of complex ferrite microstructures by electron backscatter diffraction (EBSD). This technique takes advantage of the fact that different classes of ferrite exhibit preferential grain boundary misorientations, aspect ratios and mean misorientation, all of which can be detected using current EBSD software. These characteristics are set as criteria for identification and linked to grain size to determine the area fractions. The results of this method were evaluated by comparing the new automated technique with point counting results. The technique could easily be applied to a range of other steel microstructures. © 2013 Published by Elsevier B.V.

[Toxoplasmosis. Anatomo clinical characteristics and morphological indentification of the parasite using the silver-impregnation technic].

PubMed

Villegas González, J; Fastag de Shor, A; Villegas Silva, R

1977-01-01

The clinical and anatomicopathological characteristics of acute and chronic toxoplasmosis are described as they affect different structures and systems. The lesion to adrenal glands is compared to that seen in disseminated herpes simplex; however, the question remains as to why in both congenital infections, necrosis of adrenal glands appears without inflammatory reaction. The investigation of special techniques for localization and identification of Toxoplasma gondii "groups" or cysts, leads to the conclusion that Grocott's silver impregnation technique used for the identification of Entamoeba histolytica is also useful to discover Toxoplasma in tissues.

Reduced-Order Models Based on Linear and Nonlinear Aerodynamic Impulse Responses

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1999-01-01

This paper discusses a method for the identification and application of reduced-order models based on linear and nonlinear aerodynamic impulse responses. The Volterra theory of nonlinear systems and an appropriate kernel identification technique are described. Insight into the nature of kernels is provided by applying the method to the nonlinear Riccati equation in a non-aerodynamic application. The method is then applied to a nonlinear aerodynamic model of RAE 2822 supercritical airfoil undergoing plunge motions using the CFL3D Navier-Stokes flow solver with the Spalart-Allmaras turbulence model. Results demonstrate the computational efficiency of the technique.

Reduced Order Models Based on Linear and Nonlinear Aerodynamic Impulse Responses

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1999-01-01

This paper discusses a method for the identification and application of reduced-order models based on linear and nonlinear aerodynamic impulse responses. The Volterra theory of nonlinear systems and an appropriate kernel identification technique are described. Insight into the nature of kernels is provided by applying the method to the nonlinear Riccati equation in a non-aerodynamic application. The method is then applied to a nonlinear aerodynamic model of an RAE 2822 supercritical airfoil undergoing plunge motions using the CFL3D Navier-Stokes flow solver with the Spalart-Allmaras turbulence model. Results demonstrate the computational efficiency of the technique.

Nonparametric identification of nonlinear dynamic systems using a synchronisation-based method

NASA Astrophysics Data System (ADS)

Kenderi, Gábor; Fidlin, Alexander

2014-12-01

The present study proposes an identification method for highly nonlinear mechanical systems that does not require a priori knowledge of the underlying nonlinearities to reconstruct arbitrary restoring force surfaces between degrees of freedom. This approach is based on the master-slave synchronisation between a dynamic model of the system as the slave and the real system as the master using measurements of the latter. As the model synchronises to the measurements, it becomes an observer of the real system. The optimal observer algorithm in a least-squares sense is given by the Kalman filter. Using the well-known state augmentation technique, the Kalman filter can be turned into a dual state and parameter estimator to identify parameters of a priori characterised nonlinearities. The paper proposes an extension of this technique towards nonparametric identification. A general system model is introduced by describing the restoring forces as bilateral spring-dampers with time-variant coefficients, which are estimated as augmented states. The estimation procedure is followed by an a posteriori statistical analysis to reconstruct noise-free restoring force characteristics using the estimated states and their estimated variances. Observability is provided using only one measured mechanical quantity per degree of freedom, which makes this approach less demanding in the number of necessary measurement signals compared with truly nonparametric solutions, which typically require displacement, velocity and acceleration signals. Additionally, due to the statistical rigour of the procedure, it successfully addresses signals corrupted by significant measurement noise. In the present paper, the method is described in detail, which is followed by numerical examples of one degree of freedom (1DoF) and 2DoF mechanical systems with strong nonlinearities of vibro-impact type to demonstrate the effectiveness of the proposed technique.

A New Position Location System Using DTV Transmitter Identification Watermark Signals

NASA Astrophysics Data System (ADS)

Wang, Xianbin; Wu, Yiyan; Chouinard, Jean-Yves

2006-12-01

A new position location technique using the transmitter identification (TxID) RF watermark in the digital TV (DTV) signals is proposed in this paper. Conventional global positioning system (GPS) usually does not work well inside buildings due to the high frequency and weak field strength of the signal. In contrast to the GPS, the DTV signals are received from transmitters at relatively short distance, while the broadcast transmitters operate at levels up to the megawatts effective radiated power (ERP). Also the RF frequency of the DTV signal is much lower than the GPS, which makes it easier for the signal to penetrate buildings and other objects. The proposed position location system based on DTV TxID signal is presented in this paper. Practical receiver implementation issues including nonideal correlation and synchronization are analyzed and discussed. Performance of the proposed technique is evaluated through Monte Carlo simulations and compared with other existing position location systems. Possible ways to improve the accuracy of the new position location system is discussed.

Performance of wavelet analysis and neural networks for pathological voices identification

NASA Astrophysics Data System (ADS)

Salhi, Lotfi; Talbi, Mourad; Abid, Sabeur; Cherif, Adnane

2011-09-01

Within the medical environment, diverse techniques exist to assess the state of the voice of the patient. The inspection technique is inconvenient for a number of reasons, such as its high cost, the duration of the inspection, and above all, the fact that it is an invasive technique. This study focuses on a robust, rapid and accurate system for automatic identification of pathological voices. This system employs non-invasive, non-expensive and fully automated method based on hybrid approach: wavelet transform analysis and neural network classifier. First, we present the results obtained in our previous study while using classic feature parameters. These results allow visual identification of pathological voices. Second, quantified parameters drifting from the wavelet analysis are proposed to characterise the speech sample. On the other hand, a system of multilayer neural networks (MNNs) has been developed which carries out the automatic detection of pathological voices. The developed method was evaluated using voice database composed of recorded voice samples (continuous speech) from normophonic or dysphonic speakers. The dysphonic speakers were patients of a National Hospital 'RABTA' of Tunis Tunisia and a University Hospital in Brussels, Belgium. Experimental results indicate a success rate ranging between 75% and 98.61% for discrimination of normal and pathological voices using the proposed parameters and neural network classifier. We also compared the average classification rate based on the MNN, Gaussian mixture model and support vector machines.

How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems.

PubMed

Malin, Bradley; Sweeney, Latanya

2004-06-01

The increasing integration of patient-specific genomic data into clinical practice and research raises serious privacy concerns. Various systems have been proposed that protect privacy by removing or encrypting explicitly identifying information, such as name or social security number, into pseudonyms. Though these systems claim to protect identity from being disclosed, they lack formal proofs. In this paper, we study the erosion of privacy when genomic data, either pseudonymous or data believed to be anonymous, are released into a distributed healthcare environment. Several algorithms are introduced, collectively called RE-Identification of Data In Trails (REIDIT), which link genomic data to named individuals in publicly available records by leveraging unique features in patient-location visit patterns. Algorithmic proofs of re-identification are developed and we demonstrate, with experiments on real-world data, that susceptibility to re-identification is neither trivial nor the result of bizarre isolated occurrences. We propose that such techniques can be applied as system tests of privacy protection capabilities.

21 CFR 866.5590 - Lipoprotein X immunolog-ical test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Lipoprotein X immunolog-ical test system. 866.5590... Lipoprotein X immunolog-ical test system. (a) Identification. A lipoprotein X immunological test system is a device that consists of the reagents used to measure by immunochemical techniques lipoprotein X (a high...

21 CFR 866.5590 - Lipoprotein X immunolog-ical test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Lipoprotein X immunolog-ical test system. 866.5590... Lipoprotein X immunolog-ical test system. (a) Identification. A lipoprotein X immunological test system is a device that consists of the reagents used to measure by immunochemical techniques lipoprotein X (a high...

21 CFR 866.5590 - Lipoprotein X immunolog-ical test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Lipoprotein X immunolog-ical test system. 866.5590... Lipoprotein X immunolog-ical test system. (a) Identification. A lipoprotein X immunological test system is a device that consists of the reagents used to measure by immunochemical techniques lipoprotein X (a high...

21 CFR 866.5590 - Lipoprotein X immunolog-ical test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Lipoprotein X immunolog-ical test system. 866.5590... Lipoprotein X immunolog-ical test system. (a) Identification. A lipoprotein X immunological test system is a device that consists of the reagents used to measure by immunochemical techniques lipoprotein X (a high...

21 CFR 866.5590 - Lipoprotein X immunolog-ical test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Lipoprotein X immunolog-ical test system. 866.5590... Lipoprotein X immunolog-ical test system. (a) Identification. A lipoprotein X immunological test system is a device that consists of the reagents used to measure by immunochemical techniques lipoprotein X (a high...

21 CFR 866.5080 - Alpha-1-antichymotrypsin immunological test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Alpha-1-antichymotrypsin immunological test system....5080 Alpha-1-antichymotrypsin immunological test system. (a) Identification. An alpha-1... immunochemical techniques alpha-1-antichymotrypsin (a protein) in serum, other body fluids, and tissues. Alpha-1...

21 CFR 866.5080 - Alpha-1-antichymotrypsin immunological test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Alpha-1-antichymotrypsin immunological test system....5080 Alpha-1-antichymotrypsin immunological test system. (a) Identification. An alpha-1... immunochemical techniques alpha-1-antichymotrypsin (a protein) in serum, other body fluids, and tissues. Alpha-1...

21 CFR 866.5080 - Alpha-1-antichymotrypsin immunological test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Alpha-1-antichymotrypsin immunological test system....5080 Alpha-1-antichymotrypsin immunological test system. (a) Identification. An alpha-1... immunochemical techniques alpha-1-antichymotrypsin (a protein) in serum, other body fluids, and tissues. Alpha-1...

Analytical techniques for the study of some parameters of multispectral scanner systems for remote sensing

NASA Technical Reports Server (NTRS)

Wiswell, E. R.; Cooper, G. R. (Principal Investigator)

1978-01-01

The author has identified the following significant results. The concept of average mutual information in the received spectral random process about the spectral scene was developed. Techniques amenable to implementation on a digital computer were also developed to make the required average mutual information calculations. These techniques required identification of models for the spectral response process of scenes. Stochastic modeling techniques were adapted for use. These techniques were demonstrated on empirical data from wheat and vegetation scenes.

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.

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Guillaume, Alexandre

2009-01-01

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

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.

Experimental and theoretical identification of a four- acoustic-inputs/two-vibration-outputs hearing system

NASA Astrophysics Data System (ADS)

Balaji, P. A.

1999-07-01

A cricket's ear is a directional acoustic sensor. It has a remarkable level of sensitivity to the direction of sound propagation in a narrow frequency bandwidth of 4-5 KHz. Because of its complexity, the directional sensitivity has long intrigued researchers. The cricket's ear is a four-acoustic-inputs/two-vibration-outputs system. In this dissertation, this system is examined in depth, both experimentally and theoretically, with a primary goal to understand the mechanics involved in directional hearing. Experimental identification of the system is done by using random signal processing techniques. Theoretical identification of the system is accomplished by analyzing sound transmission through complex trachea of the ear. Finally, a description of how the cricket achieves directional hearing sensitivity is proposed. The fundamental principle involved in directional heating of the cricket has been utilized to design a device to obtain a directional signal from non- directional inputs.

Spatial and functional characterization, identification and assessment of isolated wetlands in Alachua County, Florida, USA - GIS and remote sensing techniques

EPA Science Inventory

In this study, Geographic Information Systems (GIS) and remote sensing mapping techniques were developed to identify the locations of isolated wetlands in Alachua County, FL, a 2510 sq km area in north-central Florida with diverse geology and numerous isolated wetlands. The resul...

Rapid Detection and Identification of Streptococcus Iniae Using a Monoclonal Antibody-Based Indirect Fluorescent Antibody Technique

USDA-ARS?s Scientific Manuscript database

Streptococcus iniae is among the major pathogens of a large number of fish species cultured in fresh and marine recirculating and net pen production systems . The traditional plate culture technique to detect and identify S. iniae is time consuming and may be problematic due to phenotypic variations...

Classification of coordination polygons and polyhedra according to their mode of self-assembly.

PubMed

Swiegers, G F; Malefetse, T J

2001-09-03

This work extends techniques for the controlled formation of synthetic molecular containers by metal-mediated self-assembly. A new classification system based on the self-assembly of such species is proposed. The system: 1) allows a systematic identification of suitable acceptor-donor combinations, 2) widens the variety of design possibilities available, 3) allows a ready comparison of the self-assembly of different compounds, 4) reveals useful commonalities between different compounds, 5) aids in the development of novel architectures, and 6) permits identification of systems capable of being switched back-and-forth between architectures.

A Concealed Barcode Identification System Using Terahertz Time-domain Spectroscopy

NASA Astrophysics Data System (ADS)

Guan, Yu; Yamamoto, Manabu; Kitazawa, Toshiyuki; Tripathi, Saroj R.; Takeya, Kei; Kawase, Kodo

2015-03-01

We present a concealed terahertz barcode/chipless tag to achieve remote identification through an obstructing material using terahertz radiation. We show scanned terahertz reflection spectral images of barcodes concealed by a thick obstacle. A concealed and double- side printed terahertz barcode structure is proposed, and we demonstrate that our design has better performance in definition than a single-side printed barcode using terahertz time-domain spectroscopy. This technique combines the benefits of a chipless tag to read encoded information covered by an optically opaque material with low cost and a simple fabrication process. Simulations are also described, along with an explanation of the principle of the terahertz barcode identification system.

Rapid identification of Prototheca species by the API 20C system.

PubMed Central

Padhye, A A; Baker, J G; D'Amato, R F

1979-01-01

The conventional auxanographic method of testing for the assimilation of carbohydrates and alcohols by the various species of Prototheca requires at least 2 weeks of incubation at 25 to 30 degrees C before definitive results are obtained. Even though Prototheca spp., in culture as well as in fixed tissues, can be identified more rapidly by fluorescent-antibody techniques in which species-specific reagents are used, such diagnostic facilities and reagents are not available in most diagnostic laboratories. The API 20C clinical yeast identification system, a commercially available ready-to-use micromethod, was found to permit the definitive identification of P. stagnora, P. wickerhamii, and P. zopfii within 4 days. Images PMID:393722

Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.

PubMed

Yousef Kalafi, Elham; Tan, Wooi Boon; Town, Christopher; Dhillon, Sarinder Kaur

2016-12-22

Monogeneans are flatworms (Platyhelminthes) that are primarily found on gills and skin of fishes. Monogenean parasites have attachment appendages at their haptoral regions that help them to move about the body surface and feed on skin and gill debris. Haptoral attachment organs consist of sclerotized hard parts such as hooks, anchors and marginal hooks. Monogenean species are differentiated based on their haptoral bars, anchors, marginal hooks, reproductive parts' (male and female copulatory organs) morphological characters and soft anatomical parts. The complex structure of these diagnostic organs and also their overlapping in microscopic digital images are impediments for developing fully automated identification system for monogeneans (LNCS 7666:256-263, 2012), (ISDA; 457-462, 2011), (J Zoolog Syst Evol Res 52(2): 95-99. 2013;). In this study images of hard parts of the haptoral organs such as bars and anchors are used to develop a fully automated identification technique for monogenean species identification by implementing image processing techniques and machine learning methods. Images of four monogenean species namely Sinodiplectanotrema malayanus, Trianchoratus pahangensis, Metahaliotrema mizellei and Metahaliotrema sp. (undescribed) were used to develop an automated technique for identification. K-nearest neighbour (KNN) was applied to classify the monogenean specimens based on the extracted features. 50% of the dataset was used for training and the other 50% was used as testing for system evaluation. Our approach demonstrated overall classification accuracy of 90%. In this study Leave One Out (LOO) cross validation is used for validation of our system and the accuracy is 91.25%. The methods presented in this study facilitate fast and accurate fully automated classification of monogeneans at the species level. In future studies more classes will be included in the model, the time to capture the monogenean images will be reduced and improvements in extraction and selection of features will be implemented.

Explicit least squares system parameter identification for exact differential input/output models

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1993-01-01

The equation error for a class of systems modeled by input/output differential operator equations has the potential to be integrated exactly, given the input/output data on a finite time interval, thereby opening up the possibility of using an explicit least squares estimation technique for system parameter identification. The paper delineates the class of models for which this is possible and shows how the explicit least squares cost function can be obtained in a way that obviates dealing with unknown initial and boundary conditions. The approach is illustrated by two examples: a second order chemical kinetics model and a third order system of Lorenz equations.

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.

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.

Module encapsulation technology

NASA Technical Reports Server (NTRS)

Willis, P.

1986-01-01

The identification and development techniques for low-cost module encapsulation materials were reviewed. Test results were displayed for a variety of materials. The improved prospects for modeling encapsulation systems for life prediction were reported.

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

Statistical analysis of texture in trunk images for biometric identification of tree species.

PubMed

Bressane, Adriano; Roveda, José A F; Martins, Antônio C G

2015-04-01

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year. Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

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

Using a tracer technique to identify the extent of non-ideal flows in the continuous mixing of non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Patel, D.; Ein-Mozaffari, F.; Mehrvar, M.

2013-05-01

The identification of non-ideal flows in a continuous-flow mixing of non-Newtonian fluids is a challenging task for various chemical industries: plastic manufacturing, water and wastewater treatment, and pulp and paper manufacturing. Non-ideal flows such as channelling, recirculation, and dead zones significantly affect the performance of continuous-flow mixing systems. Therefore, the main objective of this paper was to develop an identification protocol to measure non-ideal flows in the continuous-flow mixing system. The extent of non-ideal flows was quantified using a dynamic model that incorporated channelling, recirculation, and dead volume in the mixing vessel. To estimate the dynamic model parameters, the system was excited using a frequency-modulated random binary input by injecting the saline solution (as a tracer) into the fresh feed stream prior to being pumped into the mixing vessel. The injection of the tracer was controlled by a computer-controlled on-off solenoid valve. Using the trace technique, the extent of channelling and the effective mixed volume were successfully determined and used as mixing quality criteria. Such identification procedures can be applied at various areas of chemical engineering in order to improve the mixing quality.

Applying face identification to detecting hijacking of airplane

NASA Astrophysics Data System (ADS)

Luo, Xuanwen; Cheng, Qiang

2004-09-01

That terrorists hijacked the airplanes and crashed the World Trade Center is disaster to civilization. To avoid the happening of hijack is critical to homeland security. To report the hijacking in time, limit the terrorist to operate the plane if happened and land the plane to the nearest airport could be an efficient way to avoid the misery. Image processing technique in human face recognition or identification could be used for this task. Before the plane take off, the face images of pilots are input into a face identification system installed in the airplane. The camera in front of pilot seat keeps taking the pilot face image during the flight and comparing it with pre-input pilot face images. If a different face is detected, a warning signal is sent to ground automatically. At the same time, the automatic cruise system is started or the plane is controlled by the ground. The terrorists will have no control over the plane. The plane will be landed to a nearest or appropriate airport under the control of the ground or cruise system. This technique could also be used in automobile industry as an image key to avoid car stealth.

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.

System Identification and POD Method Applied to Unsteady Aerodynamics

NASA Technical Reports Server (NTRS)

Tang, Deman; Kholodar, Denis; Juang, Jer-Nan; Dowell, Earl H.

2001-01-01

The representation of unsteady aerodynamic flow fields in terms of global aerodynamic modes has proven to be a useful method for reducing the size of the aerodynamic model over those representations that use local variables at discrete grid points in the flow field. Eigenmodes and Proper Orthogonal Decomposition (POD) modes have been used for this purpose with good effect. This suggests that system identification models may also be used to represent the aerodynamic flow field. Implicit in the use of a systems identification technique is the notion that a relative small state space model can be useful in describing a dynamical system. The POD model is first used to show that indeed a reduced order model can be obtained from a much larger numerical aerodynamical model (the vortex lattice method is used for illustrative purposes) and the results from the POD and the system identification methods are then compared. For the example considered, the two methods are shown to give comparable results in terms of accuracy and reduced model size. The advantages and limitations of each approach are briefly discussed. Both appear promising and complementary in their characteristics.

Cyclo-stationary linear parameter time-varying subspace realization method applied for identification of horizontal-axis wind turbines

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2013-04-01

Wind energy is becoming increasingly important worldwide as an alternative renewable energy source. Economical, maintenance and operation are critical issues for large slender dynamic structures, especially for remote offshore wind farms. Health monitoring systems are very promising instruments to assure reliability and good performance of the structure. These sensing and control technologies are typically informed by models based on mechanics or data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order and having overlapping frequency content. Instead, time-domain techniques have shown powerful advantages from a practical point of view (e.g. embedded algorithms in wireless-sensor networks), being more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify the analysis, but such is not the case for wind loaded structures with spinning multibodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system, and the wind tower substructure interaction. Transformations of the cyclic effects on the vibration data can be applied to isolate inertia quantities different from rotating-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated Eigensystem realizations. In this paper an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here by means of a modified Eigensystem Realization Algorithm (ERA) via Stochastic Subspace Identification (SSI) and Linear Parameter Time-Varying (LPTV) techniques. Structural response is assumed under stationary ambient excitation produced by a Gaussian (white) noise assembled in the operative range bandwidth of horizontal-axis wind turbines. ERA-OKID analysis is driven by correlation-function matrices from the stationary ambient response aiming to reduce noise effects. Singular value decomposition (SVD) and eigenvalue analysis are computed in a last stage to get frequencies and mode shapes. Proposed assumptions are carefully weighted to account for the uncertainty of the environment the wind turbines are subjected to. A numerical example is presented based on data acquisition carried out in a BWC XL.1 low power wind turbine device installed in University of California at Davis. Finally, comments and observations are provided on how this subspace realization technique can be extended for modal-parameter identification using exclusively ambient vibration data.

Continuum of Medical Education in Obstetrics and Gynecology.

ERIC Educational Resources Information Center

Dohner, Charles W.; Hunter, Charles A., Jr.

1980-01-01

Over the past eight years the obstetric and gynecology specialty has applied a system model of instructional planning to the continuum of medical education. The systems model of needs identification, preassessment, instructional objectives, instructional materials, learning experiences; and evaluation techniques directly related to objectives was…

Interactive visual optimization and analysis for RFID benchmarking.

PubMed

Wu, Yingcai; Chung, Ka-Kei; Qu, Huamin; Yuan, Xiaoru; Cheung, S C

2009-01-01

Radio frequency identification (RFID) is a powerful automatic remote identification technique that has wide applications. To facilitate RFID deployment, an RFID benchmarking instrument called aGate has been invented to identify the strengths and weaknesses of different RFID technologies in various environments. However, the data acquired by aGate are usually complex time varying multidimensional 3D volumetric data, which are extremely challenging for engineers to analyze. In this paper, we introduce a set of visualization techniques, namely, parallel coordinate plots, orientation plots, a visual history mechanism, and a 3D spatial viewer, to help RFID engineers analyze benchmark data visually and intuitively. With the techniques, we further introduce two workflow procedures (a visual optimization procedure for finding the optimum reader antenna configuration and a visual analysis procedure for comparing the performance and identifying the flaws of RFID devices) for the RFID benchmarking, with focus on the performance analysis of the aGate system. The usefulness and usability of the system are demonstrated in the user evaluation.

Real-time color image processing for forensic fiber investigations

NASA Astrophysics Data System (ADS)

Paulsson, Nils

1995-09-01

This paper describes a system for automatic fiber debris detection based on color identification. The properties of the system are fast analysis and high selectivity, a necessity when analyzing forensic fiber samples. An ordinary investigation separates the material into well above 100,000 video images to analyze. The system is based on standard techniques such as CCD-camera, motorized sample table, and IBM-compatible PC/AT with add-on-boards for video frame digitalization and stepping motor control as the main parts. It is possible to operate the instrument at full video rate (25 image/s) with aid of the HSI-color system (hue- saturation-intensity) and software optimization. High selectivity is achieved by separating the analysis into several steps. The first step is fast direct color identification of objects in the analyzed video images and the second step analyzes detected objects with a more complex and time consuming stage of the investigation to identify single fiber fragments for subsequent analysis with more selective techniques.

Evaluation of the automatic optical authentication technologies for control systems of objects

NASA Astrophysics Data System (ADS)

Averkin, Vladimir V.; Volegov, Peter L.; Podgornov, Vladimir A.

2000-03-01

The report considers the evaluation of the automatic optical authentication technologies for the automated integrated system of physical protection, control and accounting of nuclear materials at RFNC-VNIITF, and for providing of the nuclear materials nonproliferation regime. The report presents the nuclear object authentication objectives and strategies, the methodology of the automatic optical authentication and results of the development of pattern recognition techniques carried out under the ISTC project #772 with the purpose of identification of unique features of surface structure of a controlled object and effects of its random treatment. The current decision of following functional control tasks is described in the report: confirmation of the item authenticity (proof of the absence of its substitution by an item of similar shape), control over unforeseen change of item state, control over unauthorized access to the item. The most important distinctive feature of all techniques is not comprehensive description of some properties of controlled item, but unique identification of item using minimum necessary set of parameters, properly comprising identification attribute of the item. The main emphasis in the technical approach is made on the development of rather simple technological methods for the first time intended for use in the systems of physical protection, control and accounting of nuclear materials. The developed authentication devices and system are described.

System Identification for Nonlinear Control Using Neural Networks

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Linse, Dennis J.

1990-01-01

An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.

Earth resources sensor data handling system: NASA JSC version

NASA Technical Reports Server (NTRS)

1974-01-01

The design of the NASA JSC data handling system is presented. Data acquisition parameters and computer display formats and the flow of image data through the system, with recommendations for improving system efficiency are discussed along with modifications to existing data handling procedures which will allow utilization of data duplication techniques and the accurate identification of imagery.

Identification of clinical yeasts by Vitek MS system compared with API ID 32 C.

PubMed

Durán-Valle, M Teresa; Sanz-Rodríguez, Nuria; Muñoz-Paraíso, Carmen; Almagro-Moltó, María; Gómez-Garcés, José Luis

2014-05-01

We performed a clinical evaluation of the Vitek MS matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) system with the commercial database version 2.0 for rapid identification of medically important yeasts as compared with the conventional phenotypic method API ID 32 C. We tested 161 clinical isolates, nine isolates from culture collections and five reference strains. In case of discrepant results or no identification with one or both methods, molecular identification techniques were employed. Concordance between both methods was observed with 160/175 isolates (91.42%) and misidentifications by both systems occurred only when taxa were not included in the respective databases, i.e., one isolate of Candida etchellsii was identified as C. globosa by Vitek MS and two isolates of C. orthopsilosis were identified as C. parapsilosis by API ID 32 C. Vitek MS could not identify nine strains (5.14%) and API ID 32 C did not identify 13 (7.42%). Vitek MS was more reliable than API ID 32 C and reduced the time required for the identification of clinical isolates to only a few minutes.

Microscopic optical path length difference and polarization measurement system for cell analysis

NASA Astrophysics Data System (ADS)

Satake, H.; Ikeda, K.; Kowa, H.; Hoshiba, T.; Watanabe, E.

2018-03-01

In recent years, noninvasive, nonstaining, and nondestructive quantitative cell measurement techniques have become increasingly important in the medical field. These cell measurement techniques enable the quantitative analysis of living cells, and are therefore applied to various cell identification processes, such as those determining the passage number limit during cell culturing in regenerative medicine. To enable cell measurement, we developed a quantitative microscopic phase imaging system based on a Mach-Zehnder interferometer that measures the optical path length difference distribution without phase unwrapping using optical phase locking. The applicability of our phase imaging system was demonstrated by successful identification of breast cancer cells amongst normal cells. However, the cell identification method using this phase imaging system exhibited a false identification rate of approximately 7%. In this study, we implemented a polarimetric imaging system by introducing a polarimetric module to one arm of the Mach-Zehnder interferometer of our conventional phase imaging system. This module was comprised of a quarter wave plate and a rotational polarizer on the illumination side of the sample, and a linear polarizer on the optical detector side. In addition, we developed correction methods for the measurement errors of the optical path length and birefringence phase differences that arose through the influence of elements other than cells, such as the Petri dish. As the Petri dish holding the fluid specimens was transparent, it did not affect the amplitude information; however, the optical path length and birefringence phase differences were affected. Therefore, we proposed correction of the optical path length and birefringence phase for the influence of elements other than cells, as a prerequisite for obtaining highly precise phase and polarimetric images.

Development of an advanced system identification technique for comparing ADAMS analytical results with modal test data for a MICON 65/13 wind turbine

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

Bialasiewicz, J.T.

1995-07-01

This work uses the theory developed in NREL/TP--442-7110 to analyze simulated data from an ADAMS (Automated Dynamic Analysis of Mechanical Systems) model of the MICON 65/13 wind turbine. The Observer/Kalman Filter identification approach is expanded to use input-output time histories from ADAMS simulations or structural test data. A step by step outline is offered on how the tools developed in this research, can be used for validation of the ADAMS model.

A facial reconstruction and identification technique for seriously devastating head wounds.

PubMed

Joukal, Marek; Frišhons, Jan

2015-07-01

Many authors have focused on facial identification techniques, and facial reconstructions for cases when skulls have been found are especially well known. However, a standardized facial identification technique for an unknown body with seriously devastating head injuries has not yet been developed. A reconstruction and identification technique was used in 7 cases of accidents involving trains striking pedestrians. This identification technique is based on the removal of skull bone fragments, subsequent fixation of soft tissue onto a universal commercial polystyrene head model, precise suture of dermatomuscular flaps, and definitive adjustment using cosmetic treatments. After reconstruction, identifying marks such as scars, eyebrows, facial lines, facial hair and partly hairstyle become evident. It is then possible to present a modified picture of the reconstructed face to relatives. After comparing the results with photos of the person before death, this technique has proven to be very useful for identifying unknown bodies when other identification techniques are not available. This technique is useful for its being rather quick and especially for its results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modeling global vector fields of chaotic systems from noisy time series with the aid of structure-selection techniques.

PubMed

Xu, Daolin; Lu, Fangfang

2006-12-01

We address the problem of reconstructing a set of nonlinear differential equations from chaotic time series. A method that combines the implicit Adams integration and the structure-selection technique of an error reduction ratio is proposed for system identification and corresponding parameter estimation of the model. The structure-selection technique identifies the significant terms from a pool of candidates of functional basis and determines the optimal model through orthogonal characteristics on data. The technique with the Adams integration algorithm makes the reconstruction available to data sampled with large time intervals. Numerical experiment on Lorenz and Rossler systems shows that the proposed strategy is effective in global vector field reconstruction from noisy time series.

New X-Ray Technique to Characterize Nanoscale Precipitates in Aged Aluminum Alloys

NASA Astrophysics Data System (ADS)

Sitdikov, V. D.; Murashkin, M. Yu.; Valiev, R. Z.

2017-10-01

This paper puts forward a new technique for measurement of x-ray patterns, which enables to solve the problem of identification and determination of precipitates (nanoscale phases) in metallic alloys of the matrix type. The minimum detection limit of precipitates in the matrix of the base material provided by this technique constitutes as little as 1%. The identification of precipitates in x-ray patterns and their analysis are implemented through a transmission mode with a larger radiation area, longer holding time and higher diffractometer resolution as compared to the conventional reflection mode. The presented technique has been successfully employed to identify and quantitatively describe precipitates formed in the Al alloy of the Al-Mg-Si system as a result of artificial aging. For the first time, the x-ray phase analysis has been used to identify and measure precipitates formed during the alloy artificial aging.

Real-Time Continuous Identification of Greenhouse Plant Pathogens Based on Recyclable Microfluidic Bioassay System.

PubMed

Qu, Xiangmeng; Li, Min; Zhang, Hongbo; Lin, Chenglie; Wang, Fei; Xiao, Mingshu; Zhou, Yi; Shi, Jiye; Aldalbahi, Ali; Pei, Hao; Chen, Hong; Li, Li

2017-09-20

The development of a real-time continuous analytical platform for the pathogen detection is of great scientific importance for achieving better disease control and prevention. In this work, we report a rapid and recyclable microfluidic bioassay system constructed from oligonucleotide arrays for selective and sensitive continuous identification of DNA targets of fungal pathogens. We employ the thermal denaturation method to effectively regenerate the oligonucleotide arrays for multiple sample detection, which could considerably reduce the screening effort and costs. The combination of thermal denaturation and laser-induced fluorescence detection technique enables real-time continuous identification of multiple samples (<10 min per sample). As a proof of concept, we have demonstrated that two DNA targets of fungal pathogens (Botrytis cinerea and Didymella bryoniae) can be sequentially analyzed using our rapid microfluidic bioassay system, which provides a new paradigm in the design of microfluidic bioassay system and will be valuable for chemical and biomedical analysis.

Aircraft applications of fault detection and isolation techniques

NASA Astrophysics Data System (ADS)

Marcos Esteban, Andres

In this thesis the problems of fault detection & isolation and fault tolerant systems are studied from the perspective of LTI frequency-domain, model-based techniques. Emphasis is placed on the applicability of these LTI techniques to nonlinear models, especially to aerospace systems. Two applications of Hinfinity LTI fault diagnosis are given using an open-loop (no controller) design approach: one for the longitudinal motion of a Boeing 747-100/200 aircraft, the other for a turbofan jet engine. An algorithm formalizing a robust identification approach based on model validation ideas is also given and applied to the previous jet engine. A general linear fractional transformation formulation is given in terms of the Youla and Dual Youla parameterizations for the integrated (control and diagnosis filter) approach. This formulation provides better insight into the trade-off between the control and the diagnosis objectives. It also provides the basic groundwork towards the development of nested schemes for the integrated approach. These nested structures allow iterative improvements on the control/filter Youla parameters based on successive identification of the system uncertainty (as given by the Dual Youla parameter). The thesis concludes with an application of Hinfinity LTI techniques to the integrated design for the longitudinal motion of the previous Boeing 747-100/200 model.

Consistent detection and identification of individuals in a large camera network

NASA Astrophysics Data System (ADS)

Colombo, Alberto; Leung, Valerie; Orwell, James; Velastin, Sergio A.

2007-10-01

In the wake of an increasing number of terrorist attacks, counter-terrorism measures are now a main focus of many research programmes. An important issue for the police is the ability to track individuals and groups reliably through underground stations, and in the case of post-event analysis, to be able to ascertain whether specific individuals have been at the station previously. While there exist many motion detection and tracking algorithms, the reliable deployment of them in a large network is still ongoing research. Specifically, to track individuals through multiple views, on multiple levels and between levels, consistent detection and labelling of individuals is crucial. In view of these issues, we have developed a change detection algorithm to work reliably in the presence of periodic movements, e.g. escalators and scrolling advertisements, as well as a content-based retrieval technique for identification. The change detection technique automatically extracts periodically varying elements in the scene using Fourier analysis, and constructs a Markov model for the process. Training is performed online, and no manual intervention is required, making this system suitable for deployment in large networks. Experiments on real data shows significant improvement over existing techniques. The content-based retrieval technique uses MPEG-7 descriptors to identify individuals. Given the environment under which the system operates, i.e. at relatively low resolution, this approach is suitable for short timescales. For longer timescales, other forms of identification such as gait, or if the resolution allows, face recognition, will be required.

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.

Modeling, estimation and identification methods for static shape determination of flexible structures. [for large space structure design

NASA Technical Reports Server (NTRS)

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

1986-01-01

This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

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.

Recent literature on structural modeling, identification, and analysis

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1990-01-01

The literature on the mathematical modeling of large space structures is first reviewed, with attention given to continuum models, model order reduction, substructuring, and computational techniques. System identification and mode verification are then discussed with reference to the verification of mathematical models of large space structures. In connection with analysis, the paper surveys recent research on eigensolvers and dynamic response solvers for large-order finite-element-based models.

MIMO model of an interacting series process for Robust MPC via System Identification.

PubMed

Wibowo, Tri Chandra S; Saad, Nordin

2010-07-01

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Modal Parameter Identification of a Flexible Arm System

NASA Technical Reports Server (NTRS)

Barrington, Jason; Lew, Jiann-Shiun; Korbieh, Edward; Wade, Montanez; Tantaris, Richard

1998-01-01

In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.

Automated colour identification in melanocytic lesions.

PubMed

Sabbaghi, S; Aldeen, M; Garnavi, R; Varigos, G; Doliantis, C; Nicolopoulos, J

2015-08-01

Colour information plays an important role in classifying skin lesion. However, colour identification by dermatologists can be very subjective, leading to cases of misdiagnosis. Therefore, a computer-assisted system for quantitative colour identification is highly desirable for dermatologists to use. Although numerous colour detection systems have been developed, few studies have focused on imitating the human visual perception of colours in melanoma application. In this paper we propose a new methodology based on QuadTree decomposition technique for automatic colour identification in dermoscopy images. Our approach mimics the human perception of lesion colours. The proposed method is trained on a set of 47 images from NIH dataset and applied to a test set of 190 skin lesions obtained from PH2 dataset. The results of our proposed method are compared with a recently reported colour identification method using the same dataset. The effectiveness of our method in detecting colours in dermoscopy images is vindicated by obtaining approximately 93% accuracy when the CIELab1 colour space is used.

40 CFR 142.62 - Variances and exemptions from the maximum contaminant levels for organic and inorganic chemicals.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Identification of Best Technology, Treatment Techniques or Other Means... community water systems and non-transient, non-community water systems to install and/or use any treatment...

System identification principles in studies of forest dynamics.

Treesearch

Rolfe A. Leary

1970-01-01

Shows how it is possible to obtain governing equation parameter estimates on the basis of observed system states. The approach used represents a constructive alternative to regression techniques for models expressed as differential equations. This approach allows scientists to more completely quantify knowledge of forest development processes, to express theories in...

Reducing Error Rates for Iris Image using higher Contrast in Normalization process

NASA Astrophysics Data System (ADS)

Aminu Ghali, Abdulrahman; Jamel, Sapiee; Abubakar Pindar, Zahraddeen; Hasssan Disina, Abdulkadir; Mat Daris, Mustafa

2017-08-01

Iris recognition system is the most secured, and faster means of identification and authentication. However, iris recognition system suffers a setback from blurring, low contrast and illumination due to low quality image which compromises the accuracy of the system. The acceptance or rejection rates of verified user depend solely on the quality of the image. In many cases, iris recognition system with low image contrast could falsely accept or reject user. Therefore this paper adopts Histogram Equalization Technique to address the problem of False Rejection Rate (FRR) and False Acceptance Rate (FAR) by enhancing the contrast of the iris image. A histogram equalization technique enhances the image quality and neutralizes the low contrast of the image at normalization stage. The experimental result shows that Histogram Equalization Technique has reduced FRR and FAR compared to the existing techniques.

Infrasound from the 2009 and 2017 DPRK rocket launches

NASA Astrophysics Data System (ADS)

Evers, L. G.; Assink, J. D.; Smets, P. SM

2018-06-01

Supersonic rockets generate low-frequency acoustic waves, that is, infrasound, during the launch and re-entry. Infrasound is routinely observed at infrasound arrays from the International Monitoring System, in place for the verification of the Comprehensive Nuclear-Test-Ban Treaty. Association and source identification are key elements of the verification system. The moving nature of a rocket is a defining criterion in order to distinguish it from an isolated explosion. Here, it is shown how infrasound recordings can be associated, which leads to identification of the rocket. Propagation modelling is included to further constrain the source identification. Four rocket launches by the Democratic People's Republic of Korea in 2009 and 2017 are analysed in which multiple arrays detected the infrasound. Source identification in this region is important for verification purposes. It is concluded that with a passive monitoring technique such as infrasound, characteristics can be remotely obtained on sources of interest, that is, infrasonic intelligence, over 4500+ km.

Multisource information fusion applied to ship identification for the recognized maritime picture

NASA Astrophysics Data System (ADS)

Simard, Marc-Alain; Lefebvre, Eric; Helleur, Christopher

2000-04-01

The Recognized Maritime Picture (RMP) is defined as a composite picture of activity over a maritime area of interest. In simplistic terms, building an RAMP comes down to finding if an object of interest, a ship in our case, is there or not, determining what it is, determining what it is doing and determining if some type of follow-on action is required. The Canadian Department of National Defence currently has access to or may, in the near future, have access to a number of civilians, military and allied information or sensor systems to accomplish these purposes. These systems include automatic self-reporting positional systems, air patrol surveillance systems, high frequency surface radars, electronic intelligence systems, radar space systems and high frequency direction finding sensors. The ability to make full use of these systems is limited by the existing capability to fuse data from all sources in a timely, accurate and complete manner. This paper presents an information fusion systems under development that correlates and fuses these information and sensor data sources. This fusion system, named Adaptive Fuzzy Logic Correlator, correlates the information in batch but fuses and constructs ship tracks sequentially. It applies standard Kalman filter techniques and fuzzy logic correlation techniques. We propose a set of recommendations that should improve the ship identification process. Particularly it is proposed to utilize as many non-redundant sources of information as possible that address specific vessel attributes. Another important recommendation states that the information fusion and data association techniques should be capable of dealing with incomplete and imprecise information. Some fuzzy logic techniques capable of tolerating imprecise and dissimilar data are proposed.

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1984-01-01

A unified control synthesis methodology for complex and/or non-conventional flight vehicles are developed. Prediction techniques for the handling characteristics of such vehicles and pilot parameter identification from experimental data are addressed.

Tracking and Ability Grouping in Education.

ERIC Educational Resources Information Center

Drowatzky, John N.

1981-01-01

A look at identification, grouping, and instruction techniques, followed by an assessment of the legality of a properly administered tracking system and an enumeration of guidelines and due process procedures that must be followed. (Author/MLF)

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Modal parameter identification using the log decrement method and band-pass filters

NASA Astrophysics Data System (ADS)

Liao, Yabin; Wells, Valana

2011-10-01

This paper presents a time-domain technique for identifying modal parameters of test specimens based on the log-decrement method. For lightly damped multidegree-of-freedom or continuous systems, the conventional method is usually restricted to identification of fundamental-mode parameters only. Implementation of band-pass filters makes it possible for the proposed technique to extract modal information of higher modes. The method has been applied to a polymethyl methacrylate (PMMA) beam for complex modulus identification in the frequency range 10-1100 Hz. Results compare well with those obtained using the Least Squares method, and with those previously published in literature. Then the accuracy of the proposed method has been further verified by experiments performed on a QuietSteel specimen with very low damping. The method is simple and fast. It can be used for a quick estimation of the modal parameters, or as a complementary approach for validation purposes.

Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.

PubMed

Baran Pouyan, Maziyar; Birjandtalab, Javad; Nourani, Mehrdad; Matthew Pompeo, M D

2016-08-01

Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data mining and visualization techniques

DOEpatents

Wong, Pak Chung [Richland, WA; Whitney, Paul [Richland, WA; Thomas, Jim [Richland, WA

2004-03-23

Disclosed are association rule identification and visualization methods, systems, and apparatus. An association rule in data mining is an implication of the form X.fwdarw.Y where X is a set of antecedent items and Y is the consequent item. A unique visualization technique that provides multiple antecedent, consequent, confidence, and support information is disclosed to facilitate better presentation of large quantities of complex association rules.

A two-thermocouple probe technique for estimating thermocouple time constants in flows with combustion: In situ parameter identification of a first-order lag system

NASA Astrophysics Data System (ADS)

Tagawa, M.; Shimoji, T.; Ohta, Y.

1998-09-01

A two-thermocouple probe, composed of two fine-wire thermocouples of unequal diameters, is a novel technique for estimating thermocouple time constants without any dynamic calibration of the thermocouple response. This technique is most suitable for measuring fluctuating temperatures in turbulent combustion. In the present study, the reliability and applicability of this technique are appraised in a turbulent wake of a heated cylinder (without combustion). A fine-wire resistance thermometer (cold wire) of fast response is simultaneously used to provide a reference temperature. A quantitative and detailed comparison between the cold-wire measurement and the compensated thermocouple ones shows that a previous estimation scheme gives thermocouple time constants smaller than appropriate values, unless the noise in the thermocouple signals is negligible and/or the spatial resolution of the two-thermocouple probe is sufficiently high. The scheme has been improved so as to maximize the correlation coefficient between the two compensated-thermocouple outputs. The improved scheme offers better compensation of the thermocouple response. The present approach is generally applicable to in situ parameter identification of a first-order lag system.

OPERATIONS RESEARCH IN THE DESIGN OF MANAGEMENT INFORMATION SYSTEMS

DTIC Science & Technology

management information systems is concerned with the identification and detailed specification of the information and data processing...of advanced data processing techniques in management information systems today, the close coordination of operations research and data systems activities has become a practical necessity for the modern business firm.... information systems in which mathematical models are employed as the basis for analysis and systems design. Operations research provides a

Near-infrared imaging spectroscopy for counterfeit drug detection

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Evaluation of the Andromas Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry System for Identification of Aerobically Growing Gram-Positive Bacilli

PubMed Central

Farfour, E.; Leto, J.; Barritault, M.; Barberis, C.; Meyer, J.; Dauphin, B.; Le Guern, A.-S.; Leflèche, A.; Badell, E.; Guiso, N.; Leclercq, A.; Le Monnier, A.; Lecuit, M.; Rodriguez-Nava, V.; Bergeron, E.; Raymond, J.; Vimont, S.; Bille, E.; Carbonnelle, E.; Guet-Revillet, H.; Lécuyer, H.; Beretti, J.-L.; Vay, C.; Berche, P.; Ferroni, A.; Nassif, X.

2012-01-01

Matrix-associated laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) is a rapid and simple microbial identification method. Previous reports using the Biotyper system suggested that this technique requires a preliminary extraction step to identify Gram-positive rods (GPRs), a technical issue that may limit the routine use of this technique to identify pathogenic GPRs in the clinical setting. We tested the accuracy of the MALDI-TOF MS Andromas strategy to identify a set of 659 GPR isolates representing 16 bacterial genera and 72 species by the direct colony method. This bacterial collection included 40 C. diphtheriae, 13 C. pseudotuberculosis, 19 C. ulcerans, and 270 other Corynebacterium isolates, 32 L. monocytogenes and 24 other Listeria isolates, 46 Nocardia, 75 Actinomyces, 18 Actinobaculum, 11 Propionibacterium acnes, 18 Propionibacterium avidum, 30 Lactobacillus, 21 Bacillus, 2 Rhodococcus equi, 2 Erysipelothrix rhusiopathiae, and 38 other GPR isolates, all identified by reference techniques. Totals of 98.5% and 1.2% of non-Listeria GPR isolates were identified to the species or genus level, respectively. Except for L. grayi isolates that were identified to the species level, all other Listeria isolates were identified to the genus level because of highly similar spectra. These data demonstrate that rapid identification of pathogenic GPRs can be obtained without an extraction step by MALDI-TOF mass spectrometry. PMID:22692743

High-throughput screening of hybridoma supernatants using multiplexed fluorescent cell barcoding on live cells.

PubMed

Lu, Mei; Chan, Brian M; Schow, Peter W; Chang, Wesley S; King, Chadwick T

2017-12-01

With current available assay formats using either immobilized protein (ELISA, enzyme-linked immunosorbent assay) or immunostaining of fixed cells for primary monoclonal antibody (mAb) screening, researchers often fail to identify and characterize antibodies that recognize the native conformation of cell-surface antigens. Therefore, screening using live cells has become an integral and important step contributing to the successful identification of therapeutic antibody candidates. Thus the need for developing high-throughput screening (HTS) technologies using live cells has become a major priority for therapeutic mAb discovery and development. We have developed a novel technique called Multiplexed Fluorescent Cell Barcoding (MFCB), a flow cytometry-based method based upon the Fluorescent Cell Barcoding (FCB) technique and the Luminex fluorescent bead array system, but is applicable to high-through mAb screens on live cells. Using this technique in our system, we can simultaneously identify or characterize the antibody-antigen binding of up to nine unique fluorescent labeled cell populations in the time that it would normally take to process a single population. This has significantly reduced the amount of time needed for the identification of potential lead candidates. This new technology enables investigators to conduct large-scale primary hybridoma screens using flow cytometry. This in turn has allowed us to screen antibodies more efficiently than before and streamline identification and characterization of lead molecules. Copyright © 2017 Elsevier B.V. All rights reserved.

Thin-Layer and Paper Chromatography.

ERIC Educational Resources Information Center

Sherma, Joseph; Fried, Bernard

1984-01-01

Reviews literature on chromatography examining: books, reviews, student experiments; chromatographic systems, techniques, apparatus; detecting and identification of separated zones; preparative chromatography and radiochromatography; and applications related to specific materials (such as acids, alcohols, amino acids, antibiotics, enzymes, dyes,…

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.; Vicroy, Dan D.

2011-01-01

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Multi-Innovation Gradient Iterative Locally Weighted Learning Identification for A Nonlinear Ship Maneuvering System

NASA Astrophysics Data System (ADS)

Bai, Wei-wei; Ren, Jun-sheng; Li, Tie-shan

2018-06-01

This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative (MIGI) approach is proposed to optimize the distance metric of locally weighted learning (LWL), and a novel non-parametric modeling technique is developed for a nonlinear ship maneuvering system. This proposed method's advantages are as follows: first, it can avoid the unmodeled dynamics and multicollinearity inherent to the conventional parametric model; second, it eliminates the over-learning or underlearning and obtains the optimal distance metric; and third, the MIGI is not sensitive to the initial parameter value and requires less time during the training phase. These advantages result in a highly accurate mathematical modeling technique that can be conveniently implemented in applications. To verify the characteristics of this mathematical model, two examples are used as the model platforms to study the ship maneuvering.

High Accuracy Evaluation of the Finite Fourier Transform Using Sampled Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1997-01-01

Many system identification and signal processing procedures can be done advantageously in the frequency domain. A required preliminary step for this approach is the transformation of sampled time domain data into the frequency domain. The analytical tool used for this transformation is the finite Fourier transform. Inaccuracy in the transformation can degrade system identification and signal processing results. This work presents a method for evaluating the finite Fourier transform using cubic interpolation of sampled time domain data for high accuracy, and the chirp Zeta-transform for arbitrary frequency resolution. The accuracy of the technique is demonstrated in example cases where the transformation can be evaluated analytically. Arbitrary frequency resolution is shown to be important for capturing details of the data in the frequency domain. The technique is demonstrated using flight test data from a longitudinal maneuver of the F-18 High Alpha Research Vehicle.

Comparison of sonochemiluminescence images using image analysis techniques and identification of acoustic pressure fields via simulation.

PubMed

Tiong, T Joyce; Chandesa, Tissa; Yap, Yeow Hong

2017-05-01

One common method to determine the existence of cavitational activity in power ultrasonics systems is by capturing images of sonoluminescence (SL) or sonochemiluminescence (SCL) in a dark environment. Conventionally, the light emitted from SL or SCL was detected based on the number of photons. Though this method is effective, it could not identify the sonochemical zones of an ultrasonic systems. SL/SCL images, on the other hand, enable identification of 'active' sonochemical zones. However, these images often provide just qualitative data as the harvesting of light intensity data from the images is tedious and require high resolution images. In this work, we propose a new image analysis technique using pseudo-colouring images to quantify the SCL zones based on the intensities of the SCL images and followed by comparison of the active SCL zones with COMSOL simulated acoustic pressure zones. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of a parametric, discrete-time model of ankle stiffness.

PubMed

Guarin, Diego L; Jalaleddini, Kian; Kearney, Robert E

2013-01-01

Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the torque acting about it and can be separated into intrinsic and reflex components. Under stationary conditions, intrinsic stiffness can described by a linear second order system while reflex stiffness is described by Hammerstein system whose input is delayed velocity. Given that reflex and intrinsic torque cannot be measured separately, there has been much interest in the development of system identification techniques to separate them analytically. To date, most methods have been nonparametric and as a result there is no direct link between the estimated parameters and those of the stiffness model. This paper presents a novel algorithm for identification of a discrete-time model of ankle stiffness. Through simulations we show that the algorithm gives unbiased results even in the presence of large, non-white noise. Application of the method to experimental data demonstrates that it produces results consistent with previous findings.

A random PCR screening system for the identification of type 1 human herpes simplex virus.

PubMed

Yu, Xuelian; Shi, Bisheng; Gong, Yan; Zhang, Xiaonan; Shen, Silan; Qian, Fangxing; Gu, Shimin; Hu, Yunwen; Yuan, Zhenghong

2009-10-01

Several viral diseases exhibit measles-like symptoms. Differentiation of suspected cases of measles with molecular epidemiological techniques in the laboratory is useful for measles surveillance. In this study, a random PCR screening system was undertaken for the identification of isolates from patients with measles-like symptoms who exhibited cytopathic effects, but who had negative results for measles virus-specific reverse transcription (RT)-PCR and indirect immunofluorescence assays. Sequence analysis of random amplified PCR products showed that they were highly homologous to type 1 human herpes simplex virus (HSV-1). The results were further confirmed by an HSV-1-specific TaqMan real-time PCR assay. The random PCR screening system described in this study provides an efficient procedure for the identification of unknown viral pathogens. Measles-like symptoms can also be caused by HSV-1, suggesting the need to include HSV-1 in differential diagnoses of measles-like diseases.

Identification of dynamic load for prosthetic structures.

PubMed

Zhang, Dequan; Han, Xu; Zhang, Zhongpu; Liu, Jie; Jiang, Chao; Yoda, Nobuhiro; Meng, Xianghua; Li, Qing

2017-12-01

Dynamic load exists in numerous biomechanical systems, and its identification signifies a critical issue for characterizing dynamic behaviors and studying biomechanical consequence of the systems. This study aims to identify dynamic load in the dental prosthetic structures, namely, 3-unit implant-supported fixed partial denture (I-FPD) and teeth-supported fixed partial denture. The 3-dimensional finite element models were constructed through specific patient's computerized tomography images. A forward algorithm and regularization technique were developed for identifying dynamic load. To verify the effectiveness of the identification method proposed, the I-FPD and teeth-supported fixed partial denture structures were investigated to determine the dynamic loads. For validating the results of inverse identification, an experimental force-measuring system was developed by using a 3-dimensional piezoelectric transducer to measure the dynamic load in the I-FPD structure in vivo. The computationally identified loads were presented with different noise levels to determine their influence on the identification accuracy. The errors between the measured load and identified counterpart were calculated for evaluating the practical applicability of the proposed procedure in biomechanical engineering. This study is expected to serve as a demonstrative role in identifying dynamic loading in biomedical systems, where a direct in vivo measurement may be rather demanding in some areas of interest clinically. Copyright © 2017 John Wiley & Sons, Ltd.

Estimation et validation des derivees de stabilite et controle du modele dynamique non-lineaire d'un drone a voilure fixe

NASA Astrophysics Data System (ADS)

Courchesne, Samuel

Knowledge of the dynamic characteristics of a fixed-wing UAV is necessary to design flight control laws and to conceive a high quality flight simulator. The basic features of a flight mechanic model include the properties of mass, inertia and major aerodynamic terms. They respond to a complex process involving various numerical analysis techniques and experimental procedures. This thesis focuses on the analysis of estimation techniques applied to estimate problems of stability and control derivatives from flight test data provided by an experimental UAV. To achieve this objective, a modern identification methodology (Quad-M) is used to coordinate the processing tasks from multidisciplinary fields, such as parameter estimation modeling, instrumentation, the definition of flight maneuvers and validation. The system under study is a non-linear model with six degrees of freedom with a linear aerodynamic model. The time domain techniques are used for identification of the drone. The first technique, the equation error method is used to determine the structure of the aerodynamic model. Thereafter, the output error method and filter error method are used to estimate the aerodynamic coefficients values. The Matlab scripts for estimating the parameters obtained from the American Institute of Aeronautics and Astronautics (AIAA) are used and modified as necessary to achieve the desired results. A commendable effort in this part of research is devoted to the design of experiments. This includes an awareness of the system data acquisition onboard and the definition of flight maneuvers. The flight tests were conducted under stable flight conditions and with low atmospheric disturbance. Nevertheless, the identification results showed that the filter error method is most effective for estimating the parameters of the drone due to the presence of process noise and measurement. The aerodynamic coefficients are validated using a numerical analysis of the vortex method. In addition, a simulation model incorporating the estimated parameters is used to compare the behavior of states measured. Finally, a good correspondence between the results is demonstrated despite a limited number of flight data. Keywords: drone, identification, estimation, nonlinear, flight test, system, aerodynamic coefficient.

System identification for modeling for control of flexible structures

NASA Technical Reports Server (NTRS)

Mettler, Edward; Milman, Mark

1986-01-01

The major components of a design and operational flight strategy for flexible structure control systems are presented. In this strategy an initial distributed parameter control design is developed and implemented from available ground test data and on-orbit identification using sophisticated modeling and synthesis techniques. The reliability of this high performance controller is directly linked to the accuracy of the parameters on which the design is based. Because uncertainties inevitably grow without system monitoring, maintaining the control system requires an active on-line system identification function to supply parameter updates and covariance information. Control laws can then be modified to improve performance when the error envelopes are decreased. In terms of system safety and stability the covariance information is of equal importance as the parameter values themselves. If the on-line system ID function detects an increase in parameter error covariances, then corresponding adjustments must be made in the control laws to increase robustness. If the error covariances exceed some threshold, an autonomous calibration sequence could be initiated to restore the error enveloped to an acceptable level.

User's manual for a parameter identification technique. [with options for model simulation for fixed input forcing functions and identification from wind tunnel and flight measurements

NASA Technical Reports Server (NTRS)

Kanning, G.

1975-01-01

A digital computer program written in FORTRAN is presented that implements the system identification theory for deterministic systems using input-output measurements. The user supplies programs simulating the mathematical model of the physical plant whose parameters are to be identified. The user may choose any one of three options. The first option allows for a complete model simulation for fixed input forcing functions. The second option identifies up to 36 parameters of the model from wind tunnel or flight measurements. The third option performs a sensitivity analysis for up to 36 parameters. The use of each option is illustrated with an example using input-output measurements for a helicopter rotor tested in a wind tunnel.

E-Learning Personalization Based on Hybrid Recommendation Strategy and Learning Style Identification

ERIC Educational Resources Information Center

Klasnja-Milicevic, Aleksandra; Vesin, Boban; Ivanovic, Mirjana; Budimac, Zoran

2011-01-01

Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper, we describe a recommendation module of a…

[Identification of proteins interacting with the circadian clock protein PER1 in tumors using bacterial two-hybrid system technique].

PubMed

Zhang, Yu; Yao, Youlin; Jiang, Siyuan; Lu, Yilu; Liu, Yunqiang; Tao, Dachang; Zhang, Sizhong; Ma, Yongxin

2015-04-01

To identify protein-protein interaction partners of PER1 (period circadian protein homolog 1), key component of the molecular oscillation system of the circadian rhythm in tumors using bacterial two-hybrid system technique. Human cervical carcinoma cell Hela library was adopted. Recombinant bait plasmid pBT-PER1 and pTRG cDNA plasmid library were cotransformed into the two-hybrid system reporter strain cultured in a special selective medium. Target clones were screened. After isolating the positive clones, the target clones were sequenced and analyzed. Fourteen protein coding genes were identified, 4 of which were found to contain whole coding regions of genes, which included optic atrophy 3 protein (OPA3) associated with mitochondrial dynamics and homo sapiens cutA divalent cation tolerance homolog of E. coli (CUTA) associated with copper metabolism. There were also cellular events related proteins and proteins which are involved in biochemical reaction and signal transduction-related proteins. Identification of potential interacting proteins with PER1 in tumors may provide us new insights into the functions of the circadian clock protein PER1 during tumorigenesis.

Improving Our Odds: Success through Continuous Risk Management

NASA Technical Reports Server (NTRS)

Greenhalgh, Phillip O.

2009-01-01

Launching a rocket, running a business, driving to work and even day-to-day living all involve some degree of risk. Risk is ever present yet not always recognized, adequately assessed and appropriately mitigated. Identification, assessment and mitigation of risk are elements of the risk management component of the "continuous improvement" way of life that has become a hallmark of successful and progressive enterprises. While the application of risk management techniques to provide continuous improvement may be detailed and extensive, the philosophy, ideals and tools can be beneficially applied to all situations. Experiences with the use of risk identification, assessment and mitigation techniques for complex systems and processes are described. System safety efforts and tools used to examine potential risks of the Ares I First Stage of NASA s new Constellation Crew Launch Vehicle (CLV) presently being designed are noted as examples. Recommendations from lessons learned are provided for the application of risk management during the development of new systems as well as for the improvement of existing systems. Lessons learned and suggestions given are also examined for applicability to simple systems, uncomplicated processes and routine personal daily tasks. This paper informs the reader of varied uses of risk management efforts and techniques to identify, assess and mitigate risk for improvement of products, success of business, protection of people and enhancement of personal life.

Optical rangefinding applications using communications modulation technique

NASA Astrophysics Data System (ADS)

Caplan, William D.; Morcom, Christopher John

2010-10-01

A novel range detection technique combines optical pulse modulation patterns with signal cross-correlation to produce an accurate range estimate from low power signals. The cross-correlation peak is analyzed by a post-processing algorithm such that the phase delay is proportional to the range to target. This technique produces a stable range estimate from noisy signals. The advantage is higher accuracy obtained with relatively low optical power transmitted. The technique is useful for low cost, low power and low mass sensors suitable for tactical use. The signal coding technique allows applications including IFF and battlefield identification systems.

P19-S Managing Proteomics Data from Data Generation and Data Warehousing to Central Data Repository and Journal Reviewing Processes

PubMed Central

Thiele, H.; Glandorf, J.; Koerting, G.; Reidegeld, K.; Blüggel, M.; Meyer, H.; Stephan, C.

2007-01-01

In today’s proteomics research, various techniques and instrumentation bioinformatics tools are necessary to manage the large amount of heterogeneous data with an automatic quality control to produce reliable and comparable results. Therefore a data-processing pipeline is mandatory for data validation and comparison in a data-warehousing system. The proteome bioinformatics platform ProteinScape has been proven to cover these needs. The reprocessing of HUPO BPP participants’ MS data was done within ProteinScape. The reprocessed information was transferred into the global data repository PRIDE. ProteinScape as a data-warehousing system covers two main aspects: archiving relevant data of the proteomics workflow and information extraction functionality (protein identification, quantification and generation of biological knowledge). As a strategy for automatic data validation, different protein search engines are integrated. Result analysis is performed using a decoy database search strategy, which allows the measurement of the false-positive identification rate. Peptide identifications across different workflows, different MS techniques, and different search engines are merged to obtain a quality-controlled protein list. The proteomics identifications database (PRIDE), as a public data repository, is an archiving system where data are finally stored and no longer changed by further processing steps. Data submission to PRIDE is open to proteomics laboratories generating protein and peptide identifications. An export tool has been developed for transferring all relevant HUPO BPP data from ProteinScape into PRIDE using the PRIDE.xml format. The EU-funded ProDac project will coordinate the development of software tools covering international standards for the representation of proteomics data. The implementation of data submission pipelines and systematic data collection in public standards–compliant repositories will cover all aspects, from the generation of MS data in each laboratory to the conversion of all the annotating information and identifications to a standardized format. Such datasets can be used in the course of publishing in scientific journals.

Simple and fast multiplex PCR method for detection of species origin in meat products.

PubMed

Izadpanah, Mehrnaz; Mohebali, Nazanin; Elyasi Gorji, Zahra; Farzaneh, Parvaneh; Vakhshiteh, Faezeh; Shahzadeh Fazeli, Seyed Abolhassan

2018-02-01

Identification of animal species is one of the major concerns in food regulatory control and quality assurance system. Different approaches have been used for species identification in animal origin of feedstuff. This study aimed to develop a multiplex PCR approach to detect the origin of meat and meat products. Specific primers were designed based on the conserved region of mitochondrial Cytochrome C Oxidase subunit I ( COX1 ) gene. This method could successfully distinguish the origin of the pig, camel, sheep, donkey, goat, cow, and chicken in one single reaction. Since PCR products derived from each species represent unique molecular weight, the amplified products could be identified by electrophoresis and analyzed based on their size. Due to the synchronized amplification of segments within a single PCR reaction, multiplex PCR is considered to be a simple, fast, and inexpensive technique that can be applied for identification of meat products in food industries. Nowadays, this technique has been considered as a practical method to identify the species origin, which could further applied for animal feedstuffs identification.

Development of automated optical verification technologies for control systems

NASA Astrophysics Data System (ADS)

Volegov, Peter L.; Podgornov, Vladimir A.

1999-08-01

The report considers optical techniques for automated verification of object's identity designed for control system of nuclear objects. There are presented results of experimental researches and results of development of pattern recognition techniques carried out under the ISTC project number 772 with the purpose of identification of unique feature of surface structure of a controlled object and effects of its random treatment. Possibilities of industrial introduction of the developed technologies in frames of USA and Russia laboratories' lab-to-lab cooperation, including development of up-to-date systems for nuclear material control and accounting are examined.

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.

Intergration of system identification and robust controller designs for flexible structures in space

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Lew, Jiann-Shiun

1990-01-01

An approach is developed using experimental data to identify a reduced-order model and its model error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the Eigensystem Realization Algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole placement technique in combination with a H(infinity) control method is applied to design a controller for the considered system. A set experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach.

Outside-In Systems Pharmacology Combines Innovative Computational Methods With High-Throughput Whole Vertebrate Studies.

PubMed

Schulthess, Pascal; van Wijk, Rob C; Krekels, Elke H J; Yates, James W T; Spaink, Herman P; van der Graaf, Piet H

2018-04-25

To advance the systems approach in pharmacology, experimental models and computational methods need to be integrated from early drug discovery onward. Here, we propose outside-in model development, a model identification technique to understand and predict the dynamics of a system without requiring prior biological and/or pharmacological knowledge. The advanced data required could be obtained by whole vertebrate, high-throughput, low-resource dose-exposure-effect experimentation with the zebrafish larva. Combinations of these innovative techniques could improve early drug discovery. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

Laser Scanning Systems and Techniques in Rockfall Source Identification and Risk Assessment: A Critical Review

NASA Astrophysics Data System (ADS)

Fanos, Ali Mutar; Pradhan, Biswajeet

2018-04-01

Rockfall poses risk to people, their properties and to transportation ways in mountainous and hilly regions. This catastrophe shows various characteristics such as vast distribution, sudden occurrence, variable magnitude, strong fatalness and randomicity. Therefore, prediction of rockfall phenomenon both spatially and temporally is a challenging task. Digital Terrain model (DTM) is one of the most significant elements in rockfall source identification and risk assessment. Light detection and ranging (LiDAR) is the most advanced effective technique to derive high-resolution and accurate DTM. This paper presents a critical overview of rockfall phenomenon (definition, triggering factors, motion modes and modeling) and LiDAR technique in terms of data pre-processing, DTM generation and the factors that can be obtained from this technique for rockfall source identification and risk assessment. It also reviews the existing methods that are utilized for the evaluation of the rockfall trajectories and their characteristics (frequency, velocity, bouncing height and kinetic energy), probability, susceptibility, hazard and risk. Detail consideration is given on quantitative methodologies in addition to the qualitative ones. Various methods are demonstrated with respect to their application scales (local and regional). Additionally, attention is given to the latest improvement, particularly including the consideration of the intensity of the phenomena and the magnitude of the events at chosen sites.

Developing an Automated Method for Detection of Operationally Relevant Ocean Fronts and Eddies

NASA Astrophysics Data System (ADS)

Rogers-Cotrone, J. D.; Cadden, D. D. H.; Rivera, P.; Wynn, L. L.

2016-02-01

Since the early 90's, the U.S. Navy has utilized an observation-based process for identification of frontal systems and eddies. These Ocean Feature Assessments (OFA) rely on trained analysts to identify and position ocean features using satellite-observed sea surface temperatures. Meanwhile, as enhancements and expansion of the navy's Hybrid Coastal Ocean Model (HYCOM) and Regional Navy Coastal Ocean Model (RNCOM) domains have proceeded, the Naval Oceanographic Office (NAVO) has provided Tactical Oceanographic Feature Assessments (TOFA) that are based on data-validated model output but also rely on analyst identification of significant features. A recently completed project has migrated OFA production to the ArcGIS-based Acoustic Reach-back Cell Ocean Analysis Suite (ARCOAS), enabling use of additional observational datasets and significantly decreasing production time; however, it has highlighted inconsistencies inherent to this analyst-based identification process. Current efforts are focused on development of an automated method for detecting operationally significant fronts and eddies that integrates model output and observational data on a global scale. Previous attempts to employ techniques from the scientific community have been unable to meet the production tempo at NAVO. Thus, a system that incorporates existing techniques (Marr-Hildreth, Okubo-Weiss, etc.) with internally-developed feature identification methods (from model-derived physical and acoustic properties) is required. Ongoing expansions to the ARCOAS toolset have shown promising early results.

[Advances of studies on new technology and method for identifying traditional Chinese medicinal materials].

PubMed

Chen, Shilin; Guo, Baolin; Zhang, Guijun; Yan, Zhuyun; Luo, Guangming; Sun, Suqin; Wu, Hezhen; Huang, Linfang; Pang, Xiaohui; Chen, Jianbo

2012-04-01

In this review, the authors summarized the new technologies and methods for identifying traditional Chinese medicinal materials, including molecular identification, chemical identification, morphological identification, microscopic identification and identification based on biological effects. The authors introduced the principle, characteristics, application and prospect on each new technology or method and compared their advantages and disadvantages. In general, new methods make the result more objective and accurate. DNA barcoding technique and spectroscopy identification have their owner obvious strongpoint in universality and digitalization. In the near future, the two techniques are promising to be the main trend for identifying traditional Chinese medicinal materials. The identification techniques based on microscopy, liquid chromatography, PCR, biological effects and DNA chip will be indispensable supplements. However, the bionic identification technology is just placed in the developing stage at present.

Identification of Bearing Failure Using Signal Vibrations

NASA Astrophysics Data System (ADS)

Yani, Irsyadi; Resti, Yulia; Burlian, Firmansyah

2018-04-01

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

Miniature Gas Chromatograph (GC): Penning Ionization Electron Spectroscopy (PIES) Instrument for the Trace Analyses of Extraterrestrial Environments

NASA Technical Reports Server (NTRS)

Kojiro, Daniel R.; Sheverev, Valery A.; Holland, Paul M.; Takeuchi, Norishige

2006-01-01

In situ exploration of the solar system to identify its early chemistry as preserved in icy bodies and to look for compelling evidence of astrobiology will require new technology for chemical analysis. Chemical measurements in space flight environments highlight the need for a high level of positive identification of chemical compounds, since re-measurement by alternative techniques for confirmation will not be feasible. It also may not be possible to anticipate all chemical species that are observed, and important species may be present only at trace levels where they can be masked by complex chemical backgrounds. Up to now, the only techniques providing independent sample identification of GC separated components across a wide range of chemical species have been Mass Spectrometry (MS) and Ion Mobility Spectrometry (IMS). We describe here the development of a versatile and robust miniature GC detector based on Penning Ionization Electron Spectroscopy (PIES), for use with miniature GC systems being developed for planetary missions. PIES identifies the sample molecule through spectra related to its ionization potential. The combination of miniature GC technology with the primary identification capabilities of PIES provides an analytical approach ideal for planetary analyses.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Ares I-X In-Flight Modal Identification

NASA Technical Reports Server (NTRS)

Bartkowicz, Theodore J.; James, George H., III

2011-01-01

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Application of MALDI-TOF mass spectrometry in clinical diagnostic microbiology.

PubMed

De Carolis, Elena; Vella, Antonietta; Vaccaro, Luisa; Torelli, Riccardo; Spanu, Teresa; Fiori, Barbara; Posteraro, Brunella; Sanguinetti, Maurizio

2014-09-12

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently emerged as a powerful technique for identification of microorganisms, changing the workflow of well-established laboratories so that its impact on microbiological diagnostics has been unparalleled. In comparison with conventional identification methods that rely on biochemical tests and require long incubation procedures, MALDI-TOF MS has the advantage of identifying bacteria and fungi directly from colonies grown on culture plates in a few minutes and with simple procedures. Numerous studies on different systems available demonstrate the reliability and accuracy of the method, and new frontiers have been explored besides microbial species level identification, such as direct identification of pathogens from positive blood cultures, subtyping, and drug susceptibility detection.

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.

Standoff laser-based spectroscopy for explosives detection

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2007-10-01

Real time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called Improvised Explosive Devices (IED). It is recognized that the only technique, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS activity is based on a combination of laser-based spectroscopic methods with orthogonal capabilities. Our technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We has applied optical techniques including gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Technique for laparoscopic autonomic nerve preserving total mesorectal excision.

PubMed

Breukink, S O; Pierie, J P E N; Hoff, C; Wiggers, T; Meijerink, W J H J

2006-05-01

With the introduction of total mesorectal excision (TME) for treatment of rectal cancer, the prognosis of patients with rectal cancer is improved. With this better prognosis, there is a growing awareness about the quality of life of patients after rectal carcinoma. Laparoscopic total mesorectal excision (LTME) for rectal cancer offers several advantages in comparison with open total mesorectal excision (OTME), including greater patient comfort and an earlier return to daily activities while preserving the oncologic radicality of the procedure. Moreover, laparoscopy allows good exposure of the pelvic cavity because of magnification and good illumination. The laparoscope seems to facilitate pelvic dissection including identification and preservation of critical structures such as the autonomic nervous system. The technique for laparoscopic autonomic nerve preserving total mesorectal excision is reported. A three- or four-port technique is used. Vascular ligation, sharp mesorectal dissection and identification and preservation of the autonomic pelvic nerves are described.

High Resolution Ultrasonic Method for 3D Fingerprint Recognizable Characteristics in Biometrics Identification

NASA Astrophysics Data System (ADS)

Maev, R. Gr.; Bakulin, E. Yu.; Maeva, A.; Severin, F.

Biometrics is a rapidly evolving scientific and applied discipline that studies possible ways of personal identification by means of unique biological characteristics. Such identification is important in various situations requiring restricted access to certain areas, information and personal data and for cases of medical emergencies. A number of automated biometric techniques have been developed, including fingerprint, hand shape, eye and facial recognition, thermographic imaging, etc. All these techniques differ in the recognizable parameters, usability, accuracy and cost. Among these, fingerprint recognition stands alone since a very large database of fingerprints has already been acquired. Also, fingerprints are key evidence left at a crime scene and can be used to indentify suspects. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. We introduce a newer development of the ultrasonic fingerprint imaging. The proposed method obtains a scan only once and then varies the C-scan gate position and width to visualize acoustic reflections from any appropriate depth inside the skin. Also, B-scans and A-scans can be recreated from any position using such data array, which gives the control over the visualization options. By setting the C-scan gate deeper inside the skin, distribution of the sweat pores (which are located along the ridges) can be easily visualized. This distribution should be unique for each individual so this provides a means of personal identification, which is not affected by any changes (accidental or intentional) of the fingers' surface conditions. This paper discusses different setups, acoustic parameters of the system, signal and image processing options and possible ways of 3-dimentional visualization that could be used as a recognizable characteristic in biometric identification.

System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

DOE PAGES

Bacelli, Giorgio; Coe, Ryan; Patterson, David; ...

2017-04-01

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less

System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

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

Bacelli, Giorgio; Coe, Ryan; Patterson, David

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less

Personal identification based on blood vessels of retinal fundus images

NASA Astrophysics Data System (ADS)

Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

Secure method for biometric-based recognition with integrated cryptographic functions.

PubMed

Chiou, Shin-Yan

2013-01-01

Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

NASA Technical Reports Server (NTRS)

Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

2003-01-01

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.

PubMed

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-02-23

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements

PubMed Central

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-01-01

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation. PMID:28241472

Ultrasonic flowmeters offer oil line leak-detection potential

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

Hettrich, U.

1995-04-01

Ultrasonic flowmeters (USFM) installed on Transalpine Pipeline Co.`s (TAL) crude-oil system have proven to be a cost-effective flow measurement technique and beneficial in batch identification and leak detection. Through close examination, TAL has determined that clamp-on USFMs offer cost-saving advantages in installation, maintenance and operation. USFMs do not disturb pig passage. The technique also provides sound velocity capabilities, which can be used for liquid identification and batch tracking. The instruments have a repeatability of better than 0.25% and achieve an accuracy of better than 1%, depending on the flow profiles predictability. Using USFMs with multiple beams probably will improve accuracymore » further and it should be possible to find leaks even smaller than 1% of flow.« less

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

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

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.

What Is New in Clinical Microbiology—Microbial Identification by MALDI-TOF Mass Spectrometry

PubMed Central

Murray, Patrick R.

2012-01-01

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) offers the possibility of accurate, rapid, inexpensive identification of bacteria, fungi, and mycobacteria isolated in clinical microbiology laboratories. The procedures for preanalytic processing of organisms and analysis by MALDI-TOF MS are technically simple and reproducible, and commercial databases and interpretive algorithms are available for the identification of a wide spectrum of clinically significant organisms. Although only limited work has been reported on the use of this technique to identify molds, perform strain typing, or determine antibiotic susceptibility results, these are fruitful areas of promising research. As experience is gained with MALDI-TOF MS, it is expected that the databases will be expanded to resolve many of the current inadequate identifications (eg, no identification, genus-level identification) and algorithms for potential misidentification will be developed. The current lack of Food and Drug Administration approval of any MALDI-TOF MS system for organism identification limits widespread use in the United States. PMID:22795961

A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

Airway and tissue loading in postinterrupter response of the respiratory system - an identification algorithm construction.

PubMed

Jablonski, Ireneusz; Mroczka, Janusz

2010-01-01

The paper offers an enhancement of the classical interrupter technique algorithm dedicated to respiratory mechanics measurements. Idea consists in exploitation of information contained in postocclusional transient states during indirect measurement of parameter characteristics by model identification. It needs the adequacy of an inverse analogue to general behavior of the real system and a reliable algorithm of parameter estimation. The second one was a subject of reported works, which finally showed the potential of the approach to separation of airway and tissue response in a case of short-term excitation by interrupter valve operation. Investigations were conducted in a regime of forward-inverse computer experiment.

Identification and robust control of an experimental servo motor.

PubMed

Adam, E J; Guestrin, E D

2002-04-01

In this work, the design of a robust controller for an experimental laboratory-scale position control system based on a dc motor drive as well as the corresponding identification and robust stability analysis are presented. In order to carry out the robust design procedure, first, a classic closed-loop identification technique is applied and then, the parametrization by internal model control is used. The model uncertainty is evaluated under both parametric and global representation. For the latter case, an interesting discussion about the conservativeness of this description is presented by means of a comparison between the uncertainty disk and the critical perturbation radius approaches. Finally, conclusions about the performance of the experimental system with the robust controller are discussed using comparative graphics of the controlled variable and the Nyquist stability margin as a robustness measurement.

Novel Pseudomonas fluorescens Septic Sacroiliitis in a Healthy Soldier

DTIC Science & Technology

2013-08-01

Clin Microbiol 2007; 45(11): 3774–6. 8. Zbinden A, Böttger EC, Bosshard PP, Zbinden R: Evaluation of the colorimetric VITEK 2 card for identification...Böddinghaus B, Altwegg M, Böttger EC: 16S rRNA gene sequencing versus the API 20 NE system and the VITEK 2 ID-GNB card for identification of...techniques beyond routine culture and susceptibility testing should also be considered to account for less commonly seen pathogens. Although optimal

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 Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

NASA Technical Reports Server (NTRS)

Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji

2013-01-01

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

Identification Of Cells With A Compact Microscope Imaging System With Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark (Inventor)

2006-01-01

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking mic?oscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

An animal tracking system for behavior analysis using radio frequency identification.

PubMed

Catarinucci, Luca; Colella, Riccardo; Mainetti, Luca; Patrono, Luigi; Pieretti, Stefano; Secco, Andrea; Sergi, Ilaria

2014-09-01

Evaluating the behavior of mice and rats has substantially contributed to the progress of research in many scientific fields. Researchers commonly observe recorded video of animal behavior and manually record their observations for later analysis, but this approach has several limitations. The authors developed an automated system for tracking and analyzing the behavior of rodents that is based on radio frequency identification (RFID) in an ultra-high-frequency bandwidth. They provide an overview of the system's hardware and software components as well as describe their technique for surgically implanting passive RFID tags in mice. Finally, the authors present the findings of two validation studies to compare the accuracy of the RFID system versus commonly used approaches for evaluating the locomotor activity and object exploration of mice.

Videogrammetric Model Deformation Measurement Technique

NASA Technical Reports Server (NTRS)

Burner, A. W.; Liu, Tian-Shu

2001-01-01

The theory, methods, and applications of the videogrammetric model deformation (VMD) measurement technique used at NASA for wind tunnel testing are presented. The VMD technique, based on non-topographic photogrammetry, can determine static and dynamic aeroelastic deformation and attitude of a wind-tunnel model. Hardware of the system includes a video-rate CCD camera, a computer with an image acquisition frame grabber board, illumination lights, and retroreflective or painted targets on a wind tunnel model. Custom software includes routines for image acquisition, target-tracking/identification, target centroid calculation, camera calibration, and deformation calculations. Applications of the VMD technique at five large NASA wind tunnels are discussed.

Simultaneous Intrinsic and Extrinsic Parameter Identification of a Hand-Mounted Laser-Vision Sensor

PubMed Central

Lee, Jong Kwang; Kim, Kiho; Lee, Yongseok; Jeong, Taikyeong

2011-01-01

In this paper, we propose a simultaneous intrinsic and extrinsic parameter identification of a hand-mounted laser-vision sensor (HMLVS). A laser-vision sensor (LVS), consisting of a camera and a laser stripe projector, is used as a sensor component of the robotic measurement system, and it measures the range data with respect to the robot base frame using the robot forward kinematics and the optical triangulation principle. For the optimal estimation of the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. Best-fit parameters, including both the intrinsic and extrinsic parameters of the HMLVS, are simultaneously obtained based on the least-squares criterion. From the simulation and experimental results, it is shown that the parameter identification problem considered was characterized by a highly multimodal landscape; thus, the global optimization technique such as a particle swarm optimization can be a promising tool to identify the model parameters for a HMLVS, while the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum. The proposed optimization method does not require good initial guesses of the system parameters to converge at a very stable solution and it could be applied to a kinematically dissimilar robot system without loss of generality. PMID:22164104

21 CFR 864.1860 - Immunohistochemistry reagents and kits.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Immunohistochemistry reagents and kits. (a) Identification. Immunohistochemistry test systems (IHC's) are in vitro... performance claims, which may be packaged with ancillary reagents in kits. Their intended use is to identify, by immunological techniques, antigens in tissues or cytologic specimens. Similar devices intended for...

21 CFR 864.1860 - Immunohistochemistry reagents and kits.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Immunohistochemistry reagents and kits. (a) Identification. Immunohistochemistry test systems (IHC's) are in vitro... performance claims, which may be packaged with ancillary reagents in kits. Their intended use is to identify, by immunological techniques, antigens in tissues or cytologic specimens. Similar devices intended for...

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

PubMed

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

2015-02-01

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

Chemical Detection and Identification Techniques for Exobiology Flight Experiments

NASA Technical Reports Server (NTRS)

Kojiro, Daniel R.; Sheverev, Valery A.; Khromov, Nikolai A.

2002-01-01

Exobiology flight experiments require highly sensitive instrumentation for in situ analysis of the volatile chemical species that occur in the atmospheres and surfaces of various bodies within the solar system. The complex mixtures encountered place a heavy burden on the analytical Instrumentation to detect and identify all species present. The minimal resources available onboard for such missions mandate that the instruments provide maximum analytical capabilities with minimal requirements of volume, weight and consumables. Advances in technology may be achieved by increasing the amount of information acquired by a given technique with greater analytical capabilities and miniaturization of proven terrestrial technology. We describe here methods to develop analytical instruments for the detection and identification of a wide range of chemical species using Gas Chromatography. These efforts to expand the analytical capabilities of GC technology are focused on the development of detectors for the GC which provide sample identification independent of the GC retention time data. A novel new approach employs Penning Ionization Electron Spectroscopy (PIES).

Review of methods used for identification of biothreat agents in environmental protection and human health aspects.

PubMed

Mirski, Tomasz; Bartoszcze, Michał; Bielawska-Drózd, Agata; Cieślik, Piotr; Michalski, Aleksander J; Niemcewicz, Marcin; Kocik, Janusz; Chomiczewski, Krzysztof

2014-01-01

Modern threats of bioterrorism force the need to develop methods for rapid and accurate identification of dangerous biological agents. Currently, there are many types of methods used in this field of studies that are based on immunological or genetic techniques, or constitute a combination of both methods (immuno-genetic). There are also methods that have been developed on the basis of physical and chemical properties of the analytes. Each group of these analytical assays can be further divided into conventional methods (e.g. simple antigen-antibody reactions, classical PCR, real-time PCR), and modern technologies (e.g. microarray technology, aptamers, phosphors, etc.). Nanodiagnostics constitute another group of methods that utilize the objects at a nanoscale (below 100 nm). There are also integrated and automated diagnostic systems, which combine different methods and allow simultaneous sampling, extraction of genetic material and detection and identification of the analyte using genetic, as well as immunological techniques.

Parametric system identification of catamaran for improving controller design

NASA Astrophysics Data System (ADS)

Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

2018-01-01

This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

Linear control of oscillator and amplifier flows*

NASA Astrophysics Data System (ADS)

Schmid, Peter J.; Sipp, Denis

2016-08-01

Linear control applied to fluid systems near an equilibrium point has important applications for many flows of industrial or fundamental interest. In this article we give an exposition of tools and approaches for the design of control strategies for globally stable or unstable flows. For unstable oscillator flows a feedback configuration and a model-based approach is proposed, while for stable noise-amplifier flows a feedforward setup and an approach based on system identification is advocated. Model reduction and robustness issues are addressed for the oscillator case; statistical learning techniques are emphasized for the amplifier case. Effective suppression of global and convective instabilities could be demonstrated for either case, even though the system-identification approach results in a superior robustness to off-design conditions.

New techniques for the analysis of manual control systems. [mathematical models of human operator behavior

NASA Technical Reports Server (NTRS)

Bekey, G. A.

1971-01-01

Studies are summarized on the application of advanced analytical and computational methods to the development of mathematical models of human controllers in multiaxis manual control systems. Specific accomplishments include the following: (1) The development of analytical and computer methods for the measurement of random parameters in linear models of human operators. (2) Discrete models of human operator behavior in a multiple display situation were developed. (3) Sensitivity techniques were developed which make possible the identification of unknown sampling intervals in linear systems. (4) The adaptive behavior of human operators following particular classes of vehicle failures was studied and a model structure proposed.

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.

The Monitoring and Affinity Purification of Proteins Using Dual Tags with Tetracysteine Motifs

NASA Astrophysics Data System (ADS)

Giannone, Richard J.; Liu, Yie; Wang, Yisong

Identification and characterization of protein-protein interaction networks is essential for the elucidation of biochemical mechanisms and cellular function. Affinity purification in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as a very powerful tactic for the identification of specific protein-protein interactions. In this chapter, we describe a comprehensive methodology that uses our recently developed dual-tag affinity purification system for the enrichment and identification of mammalian protein complexes. The protocol covers a series of separate but sequentially related techniques focused on the facile monitoring and purification of a dual-tagged protein of interest and its interacting partners via a system built with tetracysteine motifs and various combinations of affinity tags. Using human telomeric repeat binding factor 2 (TRF2) as an example, we demonstrate the power of the system in terms of bait protein recovery after dual-tag affinity purification, detection of bait protein subcellular localization and expression, and successful identification of known and potentially novel TRF2 interacting proteins. Although the protocol described here has been optimized for the identification and characterization of TRF2-associated proteins, it is, in principle, applicable to the study of any other mammalian protein complexes that may be of interest to the research community.

Designing and benchmarking the MULTICOM protein structure prediction system

PubMed Central

2013-01-01

Background Predicting protein structure from sequence is one of the most significant and challenging problems in bioinformatics. Numerous bioinformatics techniques and tools have been developed to tackle almost every aspect of protein structure prediction ranging from structural feature prediction, template identification and query-template alignment to structure sampling, model quality assessment, and model refinement. How to synergistically select, integrate and improve the strengths of the complementary techniques at each prediction stage and build a high-performance system is becoming a critical issue for constructing a successful, competitive protein structure predictor. Results Over the past several years, we have constructed a standalone protein structure prediction system MULTICOM that combines multiple sources of information and complementary methods at all five stages of the protein structure prediction process including template identification, template combination, model generation, model assessment, and model refinement. The system was blindly tested during the ninth Critical Assessment of Techniques for Protein Structure Prediction (CASP9) in 2010 and yielded very good performance. In addition to studying the overall performance on the CASP9 benchmark, we thoroughly investigated the performance and contributions of each component at each stage of prediction. Conclusions Our comprehensive and comparative study not only provides useful and practical insights about how to select, improve, and integrate complementary methods to build a cutting-edge protein structure prediction system but also identifies a few new sources of information that may help improve the design of a protein structure prediction system. Several components used in the MULTICOM system are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:23442819

Three-Dimensional Aeroelastic and Aerothermoelastic Behavior in Hypersonic Flow

NASA Technical Reports Server (NTRS)

McNamara, Jack J.; Friedmann, Peretz P.; Powell, Kenneth G.; Thuruthimattam, Biju J.; Bartels, Robert E.

2005-01-01

The aeroelastic and aerothermoelastic behavior of three-dimensional configurations in hypersonic flow regime are studied. The aeroelastic behavior of a low aspect ratio wing, representative of a fin or control surface on a generic hypersonic vehicle, is examined using third order piston theory, Euler and Navier-Stokes aerodynamics. The sensitivity of the aeroelastic behavior generated using Euler and Navier-Stokes aerodynamics to parameters governing temporal accuracy is also examined. Also, a refined aerothermoelastic model, which incorporates the heat transfer between the fluid and structure using CFD generated aerodynamic heating, is used to examine the aerothermoelastic behavior of the low aspect ratio wing in the hypersonic regime. Finally, the hypersonic aeroelastic behavior of a generic hypersonic vehicle with a lifting-body type fuselage and canted fins is studied using piston theory and Euler aerodynamics for the range of 2.5 less than or equal to M less than or equal to 28, at altitudes ranging from 10,000 feet to 80,000 feet. This analysis includes a study on optimal mesh selection for use with Euler aerodynamics. In addition to the aeroelastic and aerothermoelastic results presented, three time domain flutter identification techniques are compared, namely the moving block approach, the least squares curve fitting method, and a system identification technique using an Auto-Regressive model of the aeroelastic system. In general, the three methods agree well. The system identification technique, however, provided quick damping and frequency estimations with minimal response record length, and therefore o ers significant reductions in computational cost. In the present case, the computational cost was reduced by 75%. The aeroelastic and aerothermoelastic results presented illustrate the applicability of the CFL3D code for the hypersonic flight regime.

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.

Short Term Load Forecasting with Fuzzy Logic Systems for power system planning and reliability-A Review

NASA Astrophysics Data System (ADS)

Holmukhe, R. M.; Dhumale, Mrs. Sunita; Chaudhari, Mr. P. S.; Kulkarni, Mr. P. P.

2010-10-01

Load forecasting is very essential to the operation of Electricity companies. It enhances the energy efficient and reliable operation of power system. Forecasting of load demand data forms an important component in planning generation schedules in a power system. The purpose of this paper is to identify issues and better method for load foecasting. In this paper we focus on fuzzy logic system based short term load forecasting. It serves as overview of the state of the art in the intelligent techniques employed for load forecasting in power system planning and reliability. Literature review has been conducted and fuzzy logic method has been summarized to highlight advantages and disadvantages of this technique. The proposed technique for implementing fuzzy logic based forecasting is by Identification of the specific day and by using maximum and minimum temperature for that day and finally listing the maximum temperature and peak load for that day. The results show that Load forecasting where there are considerable changes in temperature parameter is better dealt with Fuzzy Logic system method as compared to other short term forecasting techniques.

Stability and control flight test results of the space transportation system's orbiter

NASA Technical Reports Server (NTRS)

Culp, M. A.; Cooke, D. R.

1982-01-01

Flight testing of the Space Shuttle Orbiter is in progress and current results of the post-flight aerodynamic analyses are discussed. The purpose of these analyses is to reduce the pre-flight aerodynamic uncertainties, thereby leading to operational certification of the Orbiter flight envelope relative to the integrated airframe and flight control system. Primary data reduction is accomplished with a well documented maximum likelihood system identification techniques.

Comparison of the techniques for the identification of the epidural space using the loss-of-resistance technique or an automated syringe - results of a randomized double-blind study.

PubMed

Duniec, Larysa; Nowakowski, Piotr; Sieczko, Jakub; Chlebus, Marcin; Łazowski, Tomasz

2016-01-01

The conventional, loss of resistance technique for identification of the epidural space is highly dependent on the anaesthetist's personal experience and is susceptible to technical errors. Therefore, an alternative, automated technique was devised to overcome the drawbacks of the traditional method. The aim of the study was to compare the efficacy of epidural space identification and the complication rate between the two groups - the automatic syringe and conventional loss of resistance methods. 47 patients scheduled for orthopaedic and gynaecology procedures under epidural anaesthesia were enrolled into the study. The number of attempts, ease of epidural space identification, complication rate and the patients' acceptance regarding the two techniques were evaluated. The majority of blocks were performed by trainee anaesthetists (91.5%). No statistical difference was found between the number of needle insertion attempts (1 vs. 2), the efficacy of epidural anaesthesia or the number of complications between the groups. The ease of epidural space identification, as assessed by an anaesthetist, was significantly better (P = 0.011) in the automated group (87.5% vs. 52.4%). A similar number of patients (92% vs. 94%) in both groups stated they would accept epidural anaesthesia in the future. The automated and loss of resistance methods of epidural space identification were proved to be equivalent in terms of efficacy and safety. Since the use of the automated technique may facilitate epidural space identification, it may be regarded as useful technique for anaesthetists inexperienced in epidural anaesthesia, or for trainees.

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.

A program to form a multidisciplinary data base and analysis for dynamic systems

NASA Technical Reports Server (NTRS)

Taylor, L. W.; Suit, W. T.; Mayo, M. H.

1984-01-01

Diverse sets of experimental data and analysis programs have been assembled for the purpose of facilitating research in systems identification, parameter estimation and state estimation techniques. The data base analysis programs are organized to make it easy to compare alternative approaches. Additional data and alternative forms of analysis will be included as they become available.

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.

The influence of and the identification of nonlinearity in flexible structures

NASA Technical Reports Server (NTRS)

Zavodney, Lawrence D.

1988-01-01

Several models were built at NASA Langley and used to demonstrate the following nonlinear behavior: internal resonance in a free response, principal parametric resonance and subcritical instability in a cantilever beam-lumped mass structure, combination resonance in a parametrically excited flexible beam, autoparametric interaction in a two-degree-of-freedom system, instability of the linear solution, saturation of the excited mode, subharmonic bifurcation, and chaotic responses. A video tape documenting these phenomena was made. An attempt to identify a simple structure consisting of two light-weight beams and two lumped masses using the Eigensystem Realization Algorithm showed the inherent difficulty of using a linear based theory to identify a particular nonlinearity. Preliminary results show the technique requires novel interpretation, and hence may not be useful for structural modes that are coupled by a guadratic nonlinearity. A literature survey was also completed on recent work in parametrically excited nonlinear system. In summary, nonlinear systems may possess unique behaviors that require nonlinear identification techniques based on an understanding of how nonlinearity affects the dynamic response of structures. In this was, the unique behaviors of nonlinear systems may be properly identified. Moreover, more accutate quantifiable estimates can be made once the qualitative model has been determined.

Methodologies for Adaptive Flight Envelope Estimation and Protection

NASA Technical Reports Server (NTRS)

Tang, Liang; Roemer, Michael; Ge, Jianhua; Crassidis, Agamemnon; Prasad, J. V. R.; Belcastro, Christine

2009-01-01

This paper reports the latest development of several techniques for adaptive flight envelope estimation and protection system for aircraft under damage upset conditions. Through the integration of advanced fault detection algorithms, real-time system identification of the damage/faulted aircraft and flight envelop estimation, real-time decision support can be executed autonomously for improving damage tolerance and flight recoverability. Particularly, a bank of adaptive nonlinear fault detection and isolation estimators were developed for flight control actuator faults; a real-time system identification method was developed for assessing the dynamics and performance limitation of impaired aircraft; online learning neural networks were used to approximate selected aircraft dynamics which were then inverted to estimate command margins. As off-line training of network weights is not required, the method has the advantage of adapting to varying flight conditions and different vehicle configurations. The key benefit of the envelope estimation and protection system is that it allows the aircraft to fly close to its limit boundary by constantly updating the controller command limits during flight. The developed techniques were demonstrated on NASA s Generic Transport Model (GTM) simulation environments with simulated actuator faults. Simulation results and remarks on future work are presented.

Extending birthday paradox theory to estimate the number of tags in RFID systems.

PubMed

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Extending Birthday Paradox Theory to Estimate the Number of Tags in RFID Systems

PubMed Central

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes. PMID:24752285

Gabor filter based fingerprint image enhancement

NASA Astrophysics Data System (ADS)

Wang, Jin-Xiang

2013-03-01

Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

Simultaneous identification of optical constants and PSD of spherical particles by multi-wavelength scattering-transmittance measurement

NASA Astrophysics Data System (ADS)

Zhang, Jun-You; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2018-04-01

An accurate and stable identification technique is developed to retrieve the optical constants and particle size distributions (PSDs) of particle system simultaneously from the multi-wavelength scattering-transmittance signals by using the improved quantum particle swarm optimization algorithm. The Mie theory are selected to calculate the directional laser intensity scattered by particles and the spectral collimated transmittance. The sensitivity and objective function distribution analysis were conducted to evaluate the mathematical properties (i.e. ill-posedness and multimodality) of the inverse problems under three different optical signals combinations (i.e. the single-wavelength multi-angle light scattering signal, the single-wavelength multi-angle light scattering and spectral transmittance signal, and the multi-angle light scattering and spectral transmittance signal). It was found the best global convergence performance can be obtained by using the multi-wavelength scattering-transmittance signals. Meanwhile, the present technique have been tested under different Gaussian measurement noise to prove its feasibility in a large solution space. All the results show that the inverse technique by using multi-wavelength scattering-transmittance signals is effective and suitable for retrieving the optical complex refractive indices and PSD of particle system simultaneously.

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).

Wavelet Analyses of F/A-18 Aeroelastic and Aeroservoelastic Flight Test Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

1997-01-01

Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique.

Rapid characterisation of Klebsiella oxytoca isolates from contaminated liquid hand soap using mass spectrometry, FTIR and Raman spectroscopy.

PubMed

Dieckmann, Ralf; Hammerl, Jens Andre; Hahmann, Hartmut; Wicke, Amal; Kleta, Sylvia; Dabrowski, Piotr Wojciech; Nitsche, Andreas; Stämmler, Maren; Al Dahouk, Sascha; Lasch, Peter

2016-06-23

Microbiological monitoring of consumer products and the efficiency of early warning systems and outbreak investigations depend on the rapid identification and strain characterisation of pathogens posing risks to the health and safety of consumers. This study evaluates the potential of three rapid analytical techniques for identification and subtyping of bacterial isolates obtained from a liquid hand soap product, which has been recalled and reported through the EU RAPEX system due to its severe bacterial contamination. Ten isolates recovered from two bottles of the product were identified as Klebsiella oxytoca and subtyped using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF MS), near-infrared Fourier transform (NIR FT) Raman spectroscopy and Fourier transform infrared (FTIR) spectroscopy. Comparison of the classification results obtained by these phenotype-based techniques with outcomes of the DNA-based methods pulsed-field gel electrophoresis (PFGE), multi-locus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis of whole-genome sequencing (WGS) data revealed a high level of concordance. In conclusion, a set of analytical techniques might be useful for rapid, reliable and cost-effective microbial typing to ensure safe consumer products and allow source tracking.

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...

EXPERIMENTAL APPROACHES TO EVALUATING THE ROLE OF ENVIRONMENTAL FACTORS IN THE DEVELOPMENT OF CARDIOVASCULAR DISEASE

EPA Science Inventory

Epidemiologic studies have suggested factors in drinking water influence on the human cardiovascular system. A clear identification of the factors involved requires more invasive techniques and more strict experimental controls than can usually be applied in epidemiologic studies...

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

Development of a unified control synthesis methodology for complex and/or non-conventional flight vehicles, and prediction techniques for the handling characteristics of such vehicles are reported. Identification of pilot dynamics and objectives, using time domain and frequency domain methods is proposed.

Prevention of Child Abuse: Possibilities for Educational Systems.

ERIC Educational Resources Information Center

Holmes, Christine P.

1987-01-01

Educators' roles in identification of abused/neglected children, subsequent reporting, and techniques for interviewing suspected abused children are discussed. Educators' expanded role in abuse prevention, involving such activities as offering courses in parenting, child safety/protection, and human sexuality, is examined, followed by a…

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1986-01-01

The topics of research in this program include pilot/vehicle analysis techniques, identification of pilot dynamics, and control and display synthesis techniques for optimizing aircraft handling qualities. The project activities are discussed. The current technical activity is directed at extending and validating the active display synthesis procedure, and the pilot/vehicle analysis of the NLR rate-command flight configurations in the landing task. Two papers published by the researchers are attached as appendices.

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Laser micro-etching of metal prostheses for personal identification

PubMed Central

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

Denture marking techniques play a vital role in establishing personal identification in suitable clinical and forensic situations. The denture marking techniques are categorized broadly into additive and ablative methods. Additive methods involve embedding or impregnation of markers for establishing personal identity. Ablative methods involve partial removal of the denture surface thereby providing a marking for identification. Engraving and etching methods are the commonly used ablative methods. Ablative methods can be of contact and noncontact subtypes. Laser micro-etching is a precise noncontact ablative denture marking technique that could be used for prostheses-guided personal identification. PMID:28584473

Laser micro-etching of metal prostheses for personal identification.

PubMed

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

Denture marking techniques play a vital role in establishing personal identification in suitable clinical and forensic situations. The denture marking techniques are categorized broadly into additive and ablative methods. Additive methods involve embedding or impregnation of markers for establishing personal identity. Ablative methods involve partial removal of the denture surface thereby providing a marking for identification. Engraving and etching methods are the commonly used ablative methods. Ablative methods can be of contact and noncontact subtypes. Laser micro-etching is a precise noncontact ablative denture marking technique that could be used for prostheses-guided personal identification.

Dataset for Testing Contamination Source Identification Methods for Water Distribution Networks

EPA Pesticide Factsheets

This dataset includes the results of a simulation study using the source inversion techniques available in the Water Security Toolkit. The data was created to test the different techniques for accuracy, specificity, false positive rate, and false negative rate. The tests examined different parameters including measurement error, modeling error, injection characteristics, time horizon, network size, and sensor placement. The water distribution system network models that were used in the study are also included in the dataset. This dataset is associated with the following publication:Seth, A., K. Klise, J. Siirola, T. Haxton , and C. Laird. Testing Contamination Source Identification Methods for Water Distribution Networks. Journal of Environmental Division, Proceedings of American Society of Civil Engineers. American Society of Civil Engineers (ASCE), Reston, VA, USA, ., (2016).

Development of advanced techniques for rotorcraft state estimation and parameter identification

NASA Technical Reports Server (NTRS)

Hall, W. E., Jr.; Bohn, J. G.; Vincent, J. H.

1980-01-01

An integrated methodology for rotorcraft system identification consists of rotorcraft mathematical modeling, three distinct data processing steps, and a technique for designing inputs to improve the identifiability of the data. These elements are as follows: (1) a Kalman filter smoother algorithm which estimates states and sensor errors from error corrupted data. Gust time histories and statistics may also be estimated; (2) a model structure estimation algorithm for isolating a model which adequately explains the data; (3) a maximum likelihood algorithm for estimating the parameters and estimates for the variance of these estimates; and (4) an input design algorithm, based on a maximum likelihood approach, which provides inputs to improve the accuracy of parameter estimates. Each step is discussed with examples to both flight and simulated data cases.

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

PubMed

Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

2016-01-01

Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

Determination of the event collision time with the ALICE detector at the LHC

NASA Astrophysics Data System (ADS)

Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; An, M.; Andrei, C.; Andrews, H. A.; Andronic, A.; Anguelov, V.; Anson, C.; Antičić, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V.; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Boldizsár, L.; Bombara, M.; Bonora, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buitron, S. A. I.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crkovská, J.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Deisting, A.; Deloff, A.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Di Ruzza, B.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Duggal, A. K.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Espagnon, B.; Esumi, S.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Gallio, M.; Galvan, C. D.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Garg, P.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Gay Ducati, M. B.; Germain, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, A. S.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Graham, K. L.; Greiner, L.; Grelli, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grosso, R.; Gruber, L.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Guzman, I. B.; Haake, R.; Hadjidakis, C.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbär, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Herrmann, F.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Hladky, J.; Horak, D.; Hosokawa, R.; Hristov, P.; Hughes, C.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Isakov, V.; Islam, M. S.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacak, B.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Khatun, A.; Khuntia, A.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, J.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kundu, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lapidus, K.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lazaridis, L.; Lea, R.; Leardini, L.; Lee, S.; Lehas, F.; Lehner, S.; Lehrbach, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Llope, W.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lupi, M.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Mao, Y.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzilli, M.; Mazzoni, M. A.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Mhlanga, S.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Mishra, T.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Münning, K.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Myers, C. J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Negrao De Oliveira, R. A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Ohlson, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pacik, V.; Pagano, D.; Pagano, P.; Paić, G.; Pal, S. K.; Palni, P.; Pan, J.; Pandey, A. K.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, J.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Peng, X.; Pereira Da Costa, H.; Peresunko, D.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Poppenborg, H.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Pozdniakov, V.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Rana, D. B.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Ratza, V.; Ravasenga, I.; Read, K. F.; Redlich, K.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rodríguez Cahuantzi, M.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarkar, N.; Sarma, P.; Sas, M. H. P.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schmidt, M.; Schukraft, J.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sett, P.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singhal, V.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spiriti, E.; Sputowska, I.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Sumowidagdo, S.; Suzuki, K.; Swain, S.; Szabo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thakur, D.; Thomas, D.; Tieulent, R.; Tikhonov, A.; Timmins, A. R.; Toia, A.; Tripathy, S.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Umaka, E. N.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vázquez Doce, O.; Vechernin, V.; Veen, A. M.; Velure, A.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Vértesi, R.; Vickovic, L.; Vigolo, S.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Virgili, T.; Vislavicius, V.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Voscek, D.; Vranic, D.; Vrláková, J.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Willems, G. A.; Williams, M. C. S.; Windelband, B.; Winn, M.; Witt, W. E.; Yalcin, S.; Yang, P.; Yano, S.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zmeskal, J.

2017-02-01

Particle identification is an important feature of the ALICE detector at the LHC. In particular, for particle identification via the time-of-flight technique, the precise determination of the event collision time represents an important ingredient of the quality of the measurement. In this paper, the different methods used for such a measurement in ALICE by means of the T0 and the TOF detectors are reviewed. Efficiencies, resolution and the improvement of the particle identification separation power of the methods used are presented for the different LHC colliding systems (pp, p-Pb and Pb-Pb) during the first period of data taking of LHC (RUN 1).

[Utility of the direct culture examination (Ziehl-Neelsen) using the Bactec system for the presumptive identification of Mycobacterium tuberculosis complex, Mycobacterium avium complex, Mycobacterium xenopi, and Mycobacterium kansasii].

PubMed

Moreno, C; Garrigó, M; Sánchez, F; Coll, P

1994-05-01

The usefulness of the microscopic examination of Bactec 12B and 13A growth medium as a method for the possible identification of M. tuberculosis complex, M. avium complex, M. xenopi, and M. kansasii was performed out to guide the selection of different genetic identification probes and, in the case of M. xenopi, the selection of the temperature of subcultures incubation. Upon detection of an index of growth greater than 100 in Bactec tubes, staining was performed by the Ziehl-Neelsen technique. On the basis of the morphology observed, the possible identification was performed by genetic probes. Subcultures were used for definitive identification. Three hundred forty-four positive samples were studied by radiometric technique. A total of 190 strains were identified as M. tuberculosis, 88 strains as M. avium-intracellulare (MAI), 33 strains as M. xenopi, 14 strains as M. kansasii and 19 strains were identified as: M. gordonae (10), unpigmented rapid growth microbacteria (7), and M. simiae (2). Sensitivity, specificity, positive predictive value, and negative predictive value were 97.9%, 95.4%, 96.4%, and 97.3%, respectively for M. tuberculosis complex, 84.0%, 99.2%, 97.3% 94.7% for M. avium complex; 63.6%, 98.3%, 80.7%, 96.2% for M. xenopi; 35.7%, 98.1%, 45.5% 97.2% for M. kansasii. The morphology of M. tuberculosis complex examined in the radiometric system in useful to differentiate this species from other microbacteria (MOTT), allowing the selection of specific probe used. Within the MOTT, M. avium complex also has morphological characteristics which are useful for its differentiation, the morphology usually described for the remaining species was frequently not observed.

System identification of timber masonry walls using shaking table test

NASA Astrophysics Data System (ADS)

Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

2017-04-01

Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

[Groundwater organic pollution source identification technology system research and application].

PubMed

Wang, Xiao-Hong; Wei, Jia-Hua; Cheng, Zhi-Neng; Liu, Pei-Bin; Ji, Yi-Qun; Zhang, Gan

2013-02-01

Groundwater organic pollutions are found in large amount of locations, and the pollutions are widely spread once onset; which is hard to identify and control. The key process to control and govern groundwater pollution is how to control the sources of pollution and reduce the danger to groundwater. This paper introduced typical contaminated sites as an example; then carried out the source identification studies and established groundwater organic pollution source identification system, finally applied the system to the identification of typical contaminated sites. First, grasp the basis of the contaminated sites of geological and hydrogeological conditions; determine the contaminated sites characteristics of pollutants as carbon tetrachloride, from the large numbers of groundwater analysis and test data; then find the solute transport model of contaminated sites and compound-specific isotope techniques. At last, through groundwater solute transport model and compound-specific isotope technology, determine the distribution of the typical site of organic sources of pollution and pollution status; invest identified potential sources of pollution and sample the soil to analysis. It turns out that the results of two identified historical pollution sources and pollutant concentration distribution are reliable. The results provided the basis for treatment of groundwater pollution.

Stochastic global identification of a bio-inspired self-sensing composite UAV wing via wind tunnel experiments

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotios; Nardari, Raphael; Li, Yu-Hung; Wang, Pengchuan; Chang, Fu-Kuo

2016-04-01

In this work, the system design, integration, and wind tunnel experimental evaluation are presented for a bioinspired self-sensing intelligent composite unmanned aerial vehicle (UAV) wing. A total of 148 micro-sensors, including piezoelectric, strain, and temperature sensors, in the form of stretchable sensor networks are embedded in the layup of a composite wing in order to enable its self-sensing capabilities. Novel stochastic system identification techniques based on time series models and statistical parameter estimation are employed in order to accurately interpret the sensing data and extract real-time information on the coupled air flow-structural dynamics. Special emphasis is given to the wind tunnel experimental assessment under various flight conditions defined by multiple airspeeds and angles of attack. A novel modeling approach based on the recently introduced Vector-dependent Functionally Pooled (VFP) model structure is employed for the stochastic identification of the "global" coupled airflow-structural dynamics of the wing and their correlation with dynamic utter and stall. The obtained results demonstrate the successful system-level integration and effectiveness of the stochastic identification approach, thus opening new perspectives for the state sensing and awareness capabilities of the next generation of "fly-by-fee" UAVs.

On-site identification of meat species in processed foods by a rapid real-time polymerase chain reaction system.

PubMed

Furutani, Shunsuke; Hagihara, Yoshihisa; Nagai, Hidenori

2017-09-01

Correct labeling of foods is critical for consumers who wish to avoid a specific meat species for religious or cultural reasons. Therefore, gene-based point-of-care food analysis by real-time Polymerase Chain Reaction (PCR) is expected to contribute to the quality control in the food industry. In this study, we perform rapid identification of meat species by our portable rapid real-time PCR system, following a very simple DNA extraction method. Applying these techniques, we correctly identified beef, pork, chicken, rabbit, horse, and mutton in processed foods in 20min. Our system was sensitive enough to detect the interfusion of about 0.1% chicken egg-derived DNA in a processed food sample. Our rapid real-time PCR system is expected to contribute to the quality control in food industries because it can be applied for the identification of meat species, and future applications can expand its functionality to the detection of genetically modified organisms or mutations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Speaker gender identification based on majority vote classifiers

NASA Astrophysics Data System (ADS)

Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

2017-03-01

Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

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.

Integration between terrestrial-based and satellite-based land mobile communications systems

NASA Technical Reports Server (NTRS)

Arcidiancono, Antonio

1990-01-01

A survey is given of several approaches to improving the performance and marketability of mobile satellite systems (MSS). The provision of voice/data services in the future regional European Land Mobile Satellite System (LMSS), network integration between the Digital Cellular Mobile System (GSM) and LMSS, the identification of critical areas for the implementation of integrated GSM/LMSS areas, space segment scenarios, LMSS for digital trunked private mobile radio (PMR) services, and code division multiple access (CDMA) techniques for a terrestrial/satellite system are covered.

Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges

PubMed Central

Zhou, Huaying; Luo, Dehan; GholamHosseini, Hamid; Li, Zhong; He, Jiafeng

2017-01-01

This paper provides a review of the most recent works in machine olfaction as applied to the identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the complexity of growing sources and the diverse specifications of herb components, the quality control of CHMs is a challenging issue. Much research has demonstrated that an electronic nose (E-nose) as an advanced machine olfaction system, can overcome this challenge through identification of the complex odors of CHMs. E-nose technology, with better usability, high sensitivity, real-time detection and non-destructive features has shown better performance in comparison with other analytical techniques such as gas chromatography-mass spectrometry (GC-MS). Although there has been immense development of E-nose techniques in other applications, there are limited reports on the application of E-noses for the quality control of CHMs. The aim of current study is to review practical implementation and advantages of E-noses for robust and effective odor identification of CHMs. It covers the use of E-nose technology to study the effects of growing regions, identification methods, production procedures and storage time on CHMs. Moreover, the challenges and applications of E-nose for CHM identification are investigated. Based on the advancement in E-nose technology, odor may become a new quantitative index for quality control of CHMs and drug discovery. It was also found that more research could be done in the area of odor standardization and odor reproduction for remote sensing. PMID:28486407

Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges.

PubMed

Zhou, Huaying; Luo, Dehan; GholamHosseini, Hamid; Li, Zhong; He, Jiafeng

2017-05-09

This paper provides a review of the most recent works in machine olfaction as applied to the identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the complexity of growing sources and the diverse specifications of herb components, the quality control of CHMs is a challenging issue. Much research has demonstrated that an electronic nose (E-nose) as an advanced machine olfaction system, can overcome this challenge through identification of the complex odors of CHMs. E-nose technology, with better usability, high sensitivity, real-time detection and non-destructive features has shown better performance in comparison with other analytical techniques such as gas chromatography-mass spectrometry (GC-MS). Although there has been immense development of E-nose techniques in other applications, there are limited reports on the application of E-noses for the quality control of CHMs. The aim of current study is to review practical implementation and advantages of E-noses for robust and effective odor identification of CHMs. It covers the use of E-nose technology to study the effects of growing regions, identification methods, production procedures and storage time on CHMs. Moreover, the challenges and applications of E-nose for CHM identification are investigated. Based on the advancement in E-nose technology, odor may become a new quantitative index for quality control of CHMs and drug discovery. It was also found that more research could be done in the area of odor standardization and odor reproduction for remote sensing.

AGARD Flight Test Techniques Series. Volume 3. Identification of Dynamic Systems-Applications to Aircraft. Part 2. Nonlinear Analysis and Manoeuvre Design. (L’Identification des Systemes Dynamiques-Applications aux Aeronefs Titre 2; L’analyse non-lineaire et la Conception de la Manoeuvre)

DTIC Science & Technology

1994-05-01

matrix K(i+1) is calculated from the vector can be reconstructed by simple integration. covariance matrix P(i+1 Ii) by: In reality not all components...is preferable to use a symbolic algebra favorable wheather conditions, for flight tests with package such as Maple or Mathematica, which will large...proved to be virtually A A identical. IZX(r, + (Pro + kp)(q%, + kq)) The actual application of the extended Kalman M AxrPq filter and smoother to

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

76 FR 2011 - High Seas Driftnet Fishing Moratorium Protection Act; Identification and Certification Procedures...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-12

... unauthorized or other IUU catch; Catch and effort monitoring, including licensing and permitting schemes, reporting, and vessel monitoring systems (VMS); Bycatch reduction and mitigation strategies and techniques... effective sanctions and monitoring, control and surveillance (MCS) capacity; and Participation in voluntary...

Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions

PubMed Central

Chiou, Shin-Yan

2013-01-01

Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied. PMID:23762851

Expert system verification and validation study. Phase 2: Requirements Identification. Delivery 2: Current requirements applicability

NASA Technical Reports Server (NTRS)

1991-01-01

The second phase of a task is described which has the ultimate purpose of ensuring that adequate Expert Systems (ESs) Verification and Validation (V and V) tools and techniques are available for Space Station Freedom Program Knowledge Based Systems development. The purpose of this phase is to recommend modifications to current software V and V requirements which will extend the applicability of the requirements to NASA ESs.

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.

A robust star identification algorithm with star shortlisting

NASA Astrophysics Data System (ADS)

Mehta, Deval Samirbhai; Chen, Shoushun; Low, Kay Soon

2018-05-01

A star tracker provides the most accurate attitude solution in terms of arc seconds compared to the other existing attitude sensors. When no prior attitude information is available, it operates in "Lost-In-Space (LIS)" mode. Star pattern recognition, also known as star identification algorithm, forms the most crucial part of a star tracker in the LIS mode. Recognition reliability and speed are the two most important parameters of a star pattern recognition technique. In this paper, a novel star identification algorithm with star ID shortlisting is proposed. Firstly, the star IDs are shortlisted based on worst-case patch mismatch, and later stars are identified in the image by an initial match confirmed with a running sequential angular match technique. The proposed idea is tested on 16,200 simulated star images having magnitude uncertainty, noise stars, positional deviation, and varying size of the field of view. The proposed idea is also benchmarked with the state-of-the-art star pattern recognition techniques. Finally, the real-time performance of the proposed technique is tested on the 3104 real star images captured by a star tracker SST-20S currently mounted on a satellite. The proposed technique can achieve an identification accuracy of 98% and takes only 8.2 ms for identification on real images. Simulation and real-time results depict that the proposed technique is highly robust and achieves a high speed of identification suitable for actual space applications.

Utilization of matrix-assisted laser desorption and ionization time-of-flight mass spectrometry for identification of infantile seborrheic dermatitis-causing Malassezia and incidence of culture-based cutaneous Malassezia microbiota of 1-month-old infants.

PubMed

Yamamoto, Mikachi; Umeda, Yoshiko; Yo, Ayaka; Yamaura, Mariko; Makimura, Koichi

2014-02-01

Matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has been utilized for identification of various microorganisms. Malassezia species, including Malassezia restricta, which is associated with seborrheic dermatitis, has been difficult to identify by traditional means. This study was performed to develop a system for identification of Malassezia species with MALDI-TOF-MS and to investigate the incidence and variety of cutaneous Malassezia microbiota of 1-month-old infants using this technique. A Malassezia species-specific MALDI-TOF-MS database was developed from eight standard strains, and the availability of this system was assessed using 54 clinical strains isolated from the skin of 1-month-old infants. Clinical isolates were cultured initially on CHROMagar Malassezia growth medium, and the 28S ribosomal DNA (D1/D2) sequence was analyzed for confirmatory identification. Using this database, we detected and analyzed Malassezia species in 68% and 44% of infants with and without infantile seborrheic dermatitis, respectively. The results of MALDI-TOF-MS analysis were consistent with those of rDNA sequencing identification (100% accuracy rate). To our knowledge, this is the first report of a MALDI-TOF-MS database for major skin pathogenic Malassezia species. This system is an easy, rapid and reliable method for identification of Malassezia. © 2014 Japanese Dermatological Association.

Identification of granite varieties from colour spectrum data.

PubMed

Araújo, María; Martínez, Javier; Ordóñez, Celestino; Vilán, José Antonio

2010-01-01

The granite processing sector of the northwest of Spain handles many varieties of granite with specific technical and aesthetic properties that command different prices in the natural stone market. Hence, correct granite identification and classification from the outset of processing to the end-product stage optimizes the management and control of stocks of granite slabs and tiles and facilitates the operation of traceability systems. We describe a methodology for automatically identifying granite varieties by processing spectral information captured by a spectrophotometer at various stages of processing using functional machine learning techniques.

Identification of Granite Varieties from Colour Spectrum Data

PubMed Central

Araújo, María; Martínez, Javier; Ordóñez, Celestino; Vilán, José Antonio

2010-01-01

The granite processing sector of the northwest of Spain handles many varieties of granite with specific technical and aesthetic properties that command different prices in the natural stone market. Hence, correct granite identification and classification from the outset of processing to the end-product stage optimizes the management and control of stocks of granite slabs and tiles and facilitates the operation of traceability systems. We describe a methodology for automatically identifying granite varieties by processing spectral information captured by a spectrophotometer at various stages of processing using functional machine learning techniques. PMID:22163673

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Structure identification methods for atomistic simulations of crystalline materials

DOE PAGES

Stukowski, Alexander

2012-05-28

Here, we discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as common neighbor analysis (CNA), centrosymmetry analysis, bond angle analysis, bond order analysis and Voronoi analysis. In addition we propose a simple extension to the CNA method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.

Structure Computation of Quiet Spike[Trademark] Flight-Test Data During Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2008-01-01

System identification or mathematical modeling is used in the aerospace community for development of simulation models for robust control law design. These models are often described as linear time-invariant processes. Nevertheless, it is well known that the underlying process is often nonlinear. The reason for using a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades, the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B Quiet Spike(TradeMark) aeroservoelastic flight-test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description that may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance for the development of robust parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion, which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B Quiet Spike aeroservoelastic flight-test data for several flight conditions that 1) linear models are inefficient for modeling aeroservoelastic data, 2) nonlinear identification provides a parsimonious model description while providing a high percent fit for cross-validated data, and 3) the model structure and parameters vary as the flight condition is altered.

Rapid identification of clinical mycobacterial isolates by protein profiling using matrix assisted laser desorption ionization-time of flight mass spectrometry.

PubMed

Panda, A; Kurapati, S; Samantaray, J C; Myneedu, V P; Verma, A; Srinivasan, A; Ahmad, H; Behera, D; Singh, U B

2013-01-01

The purpose of this study was to evaluate the identification of Mycobacterium tuberculosis which is often plagued with ambiguity. It is a time consuming process requiring 4-8 weeks after culture positivity, thereby delaying therapeutic intervention. For a successful treatment and disease management, timely diagnosis is imperative. We evaluated a rapid, proteomic based technique for identification of clinical mycobacterial isolates by protein profiling using matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Freshly grown mycobacterial isolates were used. Acetonitrile/trifluoroacetic acid extraction procedure was carried out, following which cinnamic acid charged plates were subjected to identification by MALDI-TOF MS. A comparative analysis of 42 clinical mycobacterial isolates using the MALDI-TOF MS and conventional techniques was carried out. Among these, 97.61% were found to corroborate with the standard methods at genus level and 85.36% were accurate till the species level. One out of 42 was not in accord with the conventional assays because MALDI-TOF MS established it as Mycobacterium tuberculosis (log (score)>2.0) and conventional methods established it to be non-tuberculous Mycobacterium. MALDI-TOF MS was found to be an accurate, rapid, cost effective and robust system for identification of mycobacterial species. This innovative approach holds promise for early therapeutic intervention leading to better patient care.

Development of an Effective System Identification and Control Capability for Quad-copter UAVs

NASA Astrophysics Data System (ADS)

Wei, Wei

In recent years, with the promise of extensive commercial applications, the popularity of Unmanned Aerial Vehicles (UAVs) has dramatically increased as witnessed by publications and mushrooming research and educational programs. Over the years, multi-copter aircraft have been chosen as a viable configuration for small-scale VTOL UAVs in the form of quad-copters, hexa-copters and octo-copters. Compared to the single main rotor configuration such as the conventional helicopter, multi-copter airframes require a simpler feedback control system and fewer mechanical parts. These characteristics make these UAV platforms, such as quad-copter which is the main emphasis in this dissertation, a rugged and competitive candidate for many applications in both military and civil areas. Because of its configuration and relative size, the small-scale quad-copter UAV system is inherently very unstable. In order to develop an effective control system through simulation techniques, obtaining an accurate dynamic model of a given quad-copter is imperative. Moreover, given the anticipated stringent safety requirements, fault tolerance will be a crucial component of UAV certification. Accurate dynamic modeling and control of this class of UAV is an enabling technology and is imperative for future commercial applications. In this work, the dynamic model of a quad-copter system in hover flight was identified using frequency-domain system identification techniques. A new and unique experimental system, data acquisition and processing procedure was developed catering specifically to the class of electric powered multi-copter UAV systems. The Comprehensive Identification from FrEquency Responses (CIFER RTM) software package, developed by US Army Aviation Development Directorate -- AFDD, was utilized along with flight tests to develop dynamic models of the quad-copter system. A new set of flight tests were conducted and the predictive capability of the dynamic models were successfully validated. A PID controller and two fuzzy logic controllers were developed based on the validated dynamic models. The controller performances were evaluated and compared in both simulation environment and flight testing. Flight controllers were optimized to comply with US Aeronautical Design Standard Performance Specification Handling Quality Requirements for Military Rotorcraft (ADS-33E-PRF). Results showed a substantial improvement for developed controllers when compared to the nominal controllers based on hand tuning. The scope of this research involves experimental system hardware and software development, flight instrumentation, flight testing, dynamics modeling, system identification, dynamic model validation, control system modeling using PID and fuzzy logic, analysis of handling qualities, flight control optimization and validation. Both closed-loop and open-loop dynamics of the quad-copter system were analyzed. A cost-effective and high quality system identification procedure was applied and results proved in simulations as well as in flight tests.

Combining Raman spectroscopy and digital holographic microscopy for label-free classification of human immune cells (Conference Presentation)

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Cooke, Fiona G. M.; Chen, Mingzhou; Powis, Simon J.; Dholakia, Kishan

2017-02-01

Moving towards label-free techniques for cell identification is essential for many clinical and research applications. Raman spectroscopy and digital holographic microscopy (DHM) are both label-free, non-destructive optical techniques capable of providing complimentary information. We demonstrate a multi-modal system which may simultaneously take Raman spectra and DHM images to provide both a molecular and a morphological description of our sample. In this study we use Raman spectroscopy and DHM to discriminate between three immune cell populations CD4+ T cells, B cells, and monocytes, which together comprise key functional immune cell subsets in immune responses to invading pathogens. Various parameters that may be used to describe the phase images are also examined such as pixel value histograms or texture analysis. Using our system it is possible to consider each technique individually or in combination. Principal component analysis is used on the data set to discriminate between cell types and leave-one-out cross-validation is used to estimate the efficiency of our method. Raman spectroscopy provides specific chemical information but requires relatively long acquisition times, combining this with a faster modality such as DHM could help achieve faster throughput rates. The combination of these two complimentary optical techniques provides a wealth of information for cell characterisation which is a step towards achieving label free technology for the identification of human immune cells.

FEASIBILITY STUDY FOR IDENTIFICATION OF STATIC AND DYNAMIC EXPOSURE USING CCD IMAGING TECHNIQUE FOR Caso4:Dy TL DOSEMETERS.

PubMed

Srivastava, Kshama; Soin, Seepika; Sapra, B K; Ratna, P; Datta, D

2017-11-01

The occupational exposure incurred by the radiation workers due to the external radiation is estimated using personal dosemeter placed on the human body during the monitoring period. In certain situations, it is required to determine whether the dosemeter alone was exposed accidentally/intentionally in radiation field (static exposure) or was exposed while being worn by a worker moving in his workplace (dynamic exposure). The present thermoluminscent (TL) based personnel monitoring systems are not capable of distinguishing between the above stated (static and dynamic) exposure conditions. The feasibility of a new methodology developed using the charge coupled device based imaging technique for identification of the static/dynamic exposure of CaSO4:Dy based TL detectors for low energy photons has been investigated. The techniques for the qualitative and the quantitative assessments of the exposure conditions are presented in this paper. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Leveraging natural dynamical structures to explore multi-body systems

NASA Astrophysics Data System (ADS)

Bosanac, Natasha

Multi-body systems have become the target of an increasing number of mission concepts and observations, supplying further information about the composition, origin and dynamical environment of bodies within the solar system and beyond. In many of these scenarios, identification and characterization of the particular solutions that exist in a circular restricted three-body model is valuable. This insight into the underlying natural dynamical structures is achieved via the application of dynamical systems techniques. One application of such analysis is trajectory design for CubeSats, which are intended to explore cislunar space and other planetary systems. These increasingly complex mission objectives necessitate innovative trajectory design strategies for spacecraft within our solar system, as well as the capability for rapid and well-informed redesign. Accordingly, a trajectory design framework is constructed using dynamical systems techniques and demonstrated for the Lunar IceCube mission. An additional application explored in this investigation involves the motion of an exoplanet near a binary star system. Due to the strong gravitational field near a binary star, physicists have previously leveraged these systems as testbeds for examining the validity of gravitational and relativistic theories. In this investigation, a preliminary analysis into the effect of an additional three-body interaction on the dynamical environment near a large mass ratio binary system is conducted. As demonstrated through both of these sample applications, identification and characterization of the natural particular solutions that exist within a multi-body system supports a well-informed and guided analysis.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Review of the systems biology of the immune system using agent-based models.

PubMed

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

IEEE/AIAA/NASA Digital Avionics Systems Conference, 9th, Virginia Beach, VA, Oct. 15-18, 1990, Proceedings

NASA Technical Reports Server (NTRS)

1990-01-01

The present conference on digital avionics discusses vehicle-management systems, spacecraft avionics, special vehicle avionics, communication/navigation/identification systems, software qualification and quality assurance, launch-vehicle avionics, Ada applications, sensor and signal processing, general aviation avionics, automated software development, design-for-testability techniques, and avionics-software engineering. Also discussed are optical technology and systems, modular avionics, fault-tolerant avionics, commercial avionics, space systems, data buses, crew-station technology, embedded processors and operating systems, AI and expert systems, data links, and pilot/vehicle interfaces.

Oligonucleotide (GTG)5 as a marker for Mycobacterium tuberculosis strain identification.

PubMed Central

Wiid, I J; Werely, C; Beyers, N; Donald, P; van Helden, P D

1994-01-01

Culture of Mycobacterium tuberculosis provides no information on the identity of a strain or the distribution of such a strain in the community. Strain identification of M. tuberculosis can help to address important epidemiological questions, e.g., the origin of an infection in a patient's household or community, whether reactivation of infection is endogenous or exogenous in origin, and the spread and early detection of organisms with acquired antibiotic resistance. To research this problem, strain identification must be reliable and accurate. Although genetic identification techniques already exist, it is valuable to have genetic identification techniques based on a number of genetic markers to improve the accurate identification of M. tuberculosis strains. We show that oligonucleotide (GTG)5 can be successfully applied to the identification of M. tuberculosis strains. This technique may be particularly useful in cases in which M. tuberculosis strains have few or no insertion elements (e.g., IS6110) or in identifying other strains of mycobacteria when informative probes are lacking. Images PMID:7914207

Detection of chemical warfare simulants using Raman excitation at 1064 nm

NASA Astrophysics Data System (ADS)

Dentinger, Claire; Mabry, Mark W.; Roy, Eric G.

2014-05-01

Raman spectroscopy is a powerful technique for material identification. The technique is sensitive to primary and higher ordered molecular structure and can be used to identify unknown materials by comparison with spectral reference libraries. Additionally, miniaturization of opto-electronic components has permitted development of portable Raman analyzers that are field deployable. Raman scattering is a relatively weak effect compared to a competing phenomenon, fluorescence. Even a moderate amount of fluorescence background interference can easily prevent identification of unknown materials. A long wavelength Raman system is less likely to induce fluorescence from a wider variety of materials than a higher energy visible laser system. Compounds such as methyl salicylate (MS), diethyl malonate (DEM), and dimethyl methylphosphonate (DMMP) are used as chemical warfare agent (CWA) simulants for development of analytical detection strategies. Field detection of these simulants however poses unique challenges because threat identification must be made quickly without the turnaround time usually required for a laboratory based analysis. Fortunately, these CWA simulants are good Raman scatterers, and field based detection using portable Raman instruments is promising. Measurements of the CWA simulants were done using a 1064 nm based portable Raman spectrometer. The longer wavelength excitation laser was chosen relative to a visible based laser systems because the 1064 nm based spectrometer is less likely to induce fluorescence and more suitable to a wider range of materials. To more closely mimic real world measurement situations, different sample presentations were investigated.

Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping.

PubMed

Roth, Gary A; Sosa Peña, Maria del Pilar; Neu-Baker, Nicole M; Tahiliani, Sahil; Brenner, Sara A

2015-12-08

Nanomaterials are increasingly prevalent throughout industry, manufacturing, and biomedical research. The need for tools and techniques that aid in the identification, localization, and characterization of nanoscale materials in biological samples is on the rise. Currently available methods, such as electron microscopy, tend to be resource-intensive, making their use prohibitive for much of the research community. Enhanced darkfield microscopy complemented with a hyperspectral imaging system may provide a solution to this bottleneck by enabling rapid and less expensive characterization of nanoparticles in histological samples. This method allows for high-contrast nanoscale imaging as well as nanomaterial identification. For this technique, histological tissue samples are prepared as they would be for light-based microscopy. First, positive control samples are analyzed to generate the reference spectra that will enable the detection of a material of interest in the sample. Negative controls without the material of interest are also analyzed in order to improve specificity (reduce false positives). Samples can then be imaged and analyzed using methods and software for hyperspectral microscopy or matched against these reference spectra in order to provide maps of the location of materials of interest in a sample. The technique is particularly well-suited for materials with highly unique reflectance spectra, such as noble metals, but is also applicable to other materials, such as semi-metallic oxides. This technique provides information that is difficult to acquire from histological samples without the use of electron microscopy techniques, which may provide higher sensitivity and resolution, but are vastly more resource-intensive and time-consuming than light microscopy.

INDES User's guide multistep input design with nonlinear rotorcraft modeling

NASA Technical Reports Server (NTRS)

1979-01-01

The INDES computer program, a multistep input design program used as part of a data processing technique for rotorcraft systems identification, is described. Flight test inputs base on INDES improve the accuracy of parameter estimates. The input design algorithm, program input, and program output are presented.

Determination of relative potencies for chemical inhibition of spontaneous neuronal activity using a four amplifier MEA system.

EPA Science Inventory

Potency determination is important to identify the most promising drug candidates as well as identification of and ranking of compound toxicity. In our laboratory, we have utilized MEA recording techniques to determine the relative potency of 11 insecticidal compounds and rank th...

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.…

Techniques for Improving Spelling Performance.

ERIC Educational Resources Information Center

Saylor, Paul

Improving spelling performance of college students is a question of insuring that the correct information is in long-term memory and readily retrievable. Any system of spelling instruction should recognize the capacity limits of the sensory register and short-term memory; provide for identification of and concentration on the distinctive features…

Electromagnetic image guidance in gynecology: prospective study of a new laparoscopic imaging and targeting technique for the treatment of symptomatic uterine fibroids.

PubMed

Galen, Donald I

2015-10-15

Uterine fibroids occur singly or as multiple benign tumors originating in the myometrium. Because they vary in size and location, the approach and technique for their identification and surgical management vary. Reference images, such as ultrasound images, magnetic resonance images, and sonohystograms, do not provide real-time intraoperative findings. Electromagnetic image guidance, as incorporated in the Acessa Guidance System, has been cleared by the FDA to facilitate targeting and ablation of uterine fibroids during laparoscopic surgery. This is the first feasibility study to verify the features and usefulness of the guidance system in targeting symptomatic uterine fibroids-particularly hard-to-reach intramural fibroids and those abutting the endometrium. One gynecologic surgeon, who had extensive prior experience in laparoscopic ultrasound-guided identification of fibroids, treated five women with symptomatic uterine fibroids using the Acessa Guidance System. The surgeon evaluated the system and its features in terms of responses to prescribed statements; the responses were analyzed prospectively. The surgeon strongly agreed (96 %) or agreed (4 %) with statements describing the helpfulness of the transducer and handpiece's dynamic animation in targeting each fibroid, reaching the fibroid quickly, visualizing the positions of the transducer and handpiece within the pelvic cavity, and providing the surgeon with confidence when targeting the fibroid even during "out-of-plane" positioning of the handpiece. The surgeon's positive user experience was evident in the guidance system's facilitation of accurate handpiece tip placement during targeting and ablation of uterine fibroids. Continued study of electromagnetic image guidance in the laparoscopic identification and treatment of fibroids is warranted. ClinicalTrials.gov Identifier: NCT01842789.

Forensic botany: species identification of botanical trace evidence using a multigene barcoding approach.

PubMed

Ferri, Gianmarco; Alù, Milena; Corradini, Beatrice; Beduschi, Giovanni

2009-09-01

Forensic botany can provide significant supporting evidence during criminal investigations. However, it is still an underutilized field of investigation with its most common application limited to identifying specific as well as suspected illegal plants. The ubiquitous presence of plant species can be useful in forensics, but the absence of an accurate identification system remains the major obstacle to the present inability to routinely and correctly identify trace botanical evidence. Many plant materials cannot be identified and differentiated to the species level by traditional morphological characteristics when botanical specimens are degraded and lack physical features. By taking advantage of a universal barcode system, DNA sequencing, and other biomolecular techniques used routinely in forensic investigations, two chloroplast DNA regions were evaluated for their use as "barcoding" markers for plant identification in the field of forensics. We therefore investigated the forensic use of two non-coding plastid regions, psbA-trnH and trnL-trnF, to create a multimarker system for species identification that could be useful throughout the plant kingdom. The sequences from 63 plants belonging to our local flora were submitted and registered on the GenBank database. Sequence comparison to set up the level of identification (species, genus, or family) through Blast algorithms allowed us to assess the suitability of this method. The results confirmed the effectiveness of our botanic universal multimarker assay in forensic investigations.

A Comparison of Direction Finding Results From an FFT Peak Identification Technique With Those From the Music Algorithm

DTIC Science & Technology

1991-07-01

MUSIC ALGORITHM (U) by L.E. Montbrland go I July 1991 CRC REPORT NO. 1438 Ottawa I* Government of Canada Gouvsrnweient du Canada I o DParunnt of...FINDING RESULTS FROM AN FFT PEAK IDENTIFICATION TECHNIQUE WITH THOSE FROM THE MUSIC ALGORITHM (U) by L.E. Montbhrand CRC REPORT NO. 1438 July 1991...Ottawa A Comparison of Direction Finding Results From an FFT Peak Identification Technique With Those From the Music Algorithm L.E. Montbriand Abstract A

Post-acquisition data mining techniques for LC-MS/MS-acquired data in drug metabolite identification.

PubMed

Dhurjad, Pooja Sukhdev; Marothu, Vamsi Krishna; Rathod, Rajeshwari

2017-08-01

Metabolite identification is a crucial part of the drug discovery process. LC-MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC-MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

Identification Of Natural Dyes On Archaeological Textile Objects Using Laser Induced Fluorescent Technique

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

Abdel-Kareem, O.; Eltokhy, A.; Harith, M. A.

2011-09-22

This study aims to evaluate the use of Laser Fluorescent as a non-destructive technique for identification of natural dyes on archaeological textile objects. In this study wool textile samples were dyed with 10 natural dyes such as cochineal, cutch, henna, indigo, Lac, madder, safflower, saffron, sumac and turmeric. These dyes common present on archaeological textile objects to be used as standard dyed textile samples. These selected natural dyes will be used as known references that can be used a guide to identify unknown archaeological dyes. The dyed textile samples were investigated with laser radiation in different wavelengths to detect themore » best wavelengths for identification each dye. This study confirms that Laser Florescent is very useful and a rapid technique can be used as a non-destructive technique for identification of natural dyes on archaeological textile objects. The results obtained with this study can be a guide for all conservators in identification of natural organic dyes on archaeological textile objects.« less

Identification Of Natural Dyes On Archaeological Textile Objects Using Laser Induced Fluorescent Technique

NASA Astrophysics Data System (ADS)

Abdel-Kareem, O.; Eltokhy, A.; Harith, M. A.

2011-09-01

This study aims to evaluate the use of Laser Fluorescent as a non-destructive technique for identification of natural dyes on archaeological textile objects. In this study wool textile samples were dyed with 10 natural dyes such as cochineal, cutch, henna, indigo, Lac, madder, safflower, saffron, sumac and turmeric. These dyes common present on archaeological textile objects to be used as standard dyed textile samples. These selected natural dyes will be used as known references that can be used a guide to identify unknown archaeological dyes. The dyed textile samples were investigated with laser radiation in different wavelengths to detect the best wavelengths for identification each dye. This study confirms that Laser Florescent is very useful and a rapid technique can be used as a non-destructive technique for identification of natural dyes on archaeological textile objects. The results obtained with this study can be a guide for all conservators in identification of natural organic dyes on archaeological textile objects.

Systems and Techniques for Identifying and Avoiding Ice

NASA Technical Reports Server (NTRS)

Hansman, R. John

1995-01-01

In-flight icing is one of the most difficult aviation weather hazards facing general aviation. Because most aircraft in the general aviation category are not certified for flight into known icing conditions, techniques for identifying and avoiding in-flight ice are important to maintain safety while increasing the utility and dispatch capability which is part of the AGATE vision. This report summarizes a brief study effort which: (1) Reviewed current ice identification, forecasting, and avoidance techniques; (2) Assessed feasibility of improved forecasting and ice avoidance procedures; and (3) Identified key issues for the development of improved capability with regard to in-flight icing.

Time series modeling of human operator dynamics in manual control tasks

NASA Technical Reports Server (NTRS)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

NASA Technical Reports Server (NTRS)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Cloud-based adaptive exon prediction for DNA analysis.

PubMed

Putluri, Srinivasareddy; Zia Ur Rahman, Md; Fathima, Shaik Yasmeen

2018-02-01

Cloud computing offers significant research and economic benefits to healthcare organisations. Cloud services provide a safe place for storing and managing large amounts of such sensitive data. Under conventional flow of gene information, gene sequence laboratories send out raw and inferred information via Internet to several sequence libraries. DNA sequencing storage costs will be minimised by use of cloud service. In this study, the authors put forward a novel genomic informatics system using Amazon Cloud Services, where genomic sequence information is stored and accessed for processing. True identification of exon regions in a DNA sequence is a key task in bioinformatics, which helps in disease identification and design drugs. Three base periodicity property of exons forms the basis of all exon identification techniques. Adaptive signal processing techniques found to be promising in comparison with several other methods. Several adaptive exon predictors (AEPs) are developed using variable normalised least mean square and its maximum normalised variants to reduce computational complexity. Finally, performance evaluation of various AEPs is done based on measures such as sensitivity, specificity and precision using various standard genomic datasets taken from National Center for Biotechnology Information genomic sequence database.

Robust Library Building for Autonomous Classification of Downhole Geophysical Logs Using Gaussian Processes

NASA Astrophysics Data System (ADS)

Silversides, Katherine L.; Melkumyan, Arman

2017-03-01

Machine learning techniques such as Gaussian Processes can be used to identify stratigraphically important features in geophysical logs. The marker shales in the banded iron formation hosted iron ore deposits of the Hamersley Ranges, Western Australia, form distinctive signatures in the natural gamma logs. The identification of these marker shales is important for stratigraphic identification of unit boundaries for the geological modelling of the deposit. Machine learning techniques each have different unique properties that will impact the results. For Gaussian Processes (GPs), the output values are inclined towards the mean value, particularly when there is not sufficient information in the library. The impact that these inclinations have on the classification can vary depending on the parameter values selected by the user. Therefore, when applying machine learning techniques, care must be taken to fit the technique to the problem correctly. This study focuses on optimising the settings and choices for training a GPs system to identify a specific marker shale. We show that the final results converge even when different, but equally valid starting libraries are used for the training. To analyse the impact on feature identification, GP models were trained so that the output was inclined towards a positive, neutral or negative output. For this type of classification, the best results were when the pull was towards a negative output. We also show that the GP output can be adjusted by using a standard deviation coefficient that changes the balance between certainty and accuracy in the results.

Proceedings of the Conference on the Stability and Dynamic Response of Rotors with Squeeze Film Bearings, 8-10 May 79.

DTIC Science & Technology

1979-01-01

oil films, the effects of squeeze film bearings on the dynamic response of rotor-bearing systems , design techniques and methods of analyzing complicated...rotor-bearing systems including squeeze film bearings. The consensus of the participants was that further research is needed to more fully understand...176 BEARING PARAMETER IDENTIFICATION, E. Woomer, W. D. Pilkey .... 189 TRANSIENT DYNAMICS OF SQUEEZE FILM BEARING SYSTEMS , A. J

Portable, real-time alloy identification of metallic wear debris from machinery lubrication systems: laser-induced breakdown spectroscopy versus x-ray fluorescence

NASA Astrophysics Data System (ADS)

Suresh, Pooja

2014-05-01

Alloy identification of oil-borne wear debris captured on chip detectors, filters and magnetic plugs allows the machinery maintainer to assess the health of the engine or gearbox and identify specific component damage. Today, such identification can be achieved in real time using portable, at-line laser-induced breakdown spectroscopy (LIBS) and Xray fluorescence (XRF) instruments. Both techniques can be utilized in various industries including aviation, marine, railways, heavy diesel and other industrial machinery with, however, some substantial differences in application and instrument performance. In this work, the performances of a LIBS and an XRF instrument are compared based on measurements of a wide range of typical aerospace alloys including steels, titanium, aluminum and nickel alloys. Measurement results were analyzed with a staged correlation technique specifically developed for the purposes of this study - identifying the particle alloy composition using a pre-recorded library of spectral signatures. The analysis is performed in two stages: first, the base element of the alloy is determined by correlation with the stored elemental spectra and then, the alloy is identified by matching the particle's spectral signature using parametric correlation against the stored spectra of all alloys that have the same base element. The correlation analysis has achieved highly repeatable discrimination between alloys of similar composition. Portable LIBS demonstrates higher detection accuracy and better identification of alloys comprising lighter elements as compared to that of the portable XRF system, and reveals a significant reduction in the analysis time over XRF.

Order reduction, identification and localization studies of dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Xianghong

In this thesis methods are developed for performing order reduction, system identification and induction of nonlinear localization in complex mechanical dynamic systems. General techniques are proposed for constructing low-order models of linear and nonlinear mechanical systems; in addition, novel mechanical designs are considered for inducing nonlinear localization phenomena for the purpose of enhancing their dynamical performance. The thesis is in three major parts. In the first part, the transient dynamics of an impulsively loaded multi-bay truss is numerically computed by employing the Direct Global Matrix (DGM) approach. The approach is applicable to large-scale flexible structures with periodicity. Karhunen-Loeve (K-L) decomposition is used to discretize the dynamics of the truss and to create the low-order models of the truss. The leading order K-L modes are recovered by an experiment, which shows the feasibility of K-L based order reduction technique. In the second part of the thesis, nonlinear localization in dynamical systems is studied through two applications. In the seismic base isolation study, it is shown that the dynamics are sensitive to the presence of nonlinear elements and that passive motion confinement can be induced under proper design. In the coupled rod system, numerical simulation of the transient dynamics shows that a nonlinear backlash spring can induce either nonlinear localization or delocalization in the form of beat phenomena. K-L decomposition and poincare maps are utilized to study the nonlinear effects. The study shows that nonlinear localization can be induced in complex structures through backlash. In the third and final part of the thesis, a new technique based on Green!s function method is proposed to identify the dynamics of practical bolted joints. By modeling the difference between the dynamics of the bolted structure and the corresponding unbolted one, one constructs a nonparametric model for the joint dynamics. Two applications are given with a bolted beam and a truss joint in order to show the applicability of the technique.

Towards large-scale FAME-based bacterial species identification using machine learning techniques.

PubMed

Slabbinck, Bram; De Baets, Bernard; Dawyndt, Peter; De Vos, Paul

2009-05-01

In the last decade, bacterial taxonomy witnessed a huge expansion. The swift pace of bacterial species (re-)definitions has a serious impact on the accuracy and completeness of first-line identification methods. Consequently, back-end identification libraries need to be synchronized with the List of Prokaryotic names with Standing in Nomenclature. In this study, we focus on bacterial fatty acid methyl ester (FAME) profiling as a broadly used first-line identification method. From the BAME@LMG database, we have selected FAME profiles of individual strains belonging to the genera Bacillus, Paenibacillus and Pseudomonas. Only those profiles resulting from standard growth conditions have been retained. The corresponding data set covers 74, 44 and 95 validly published bacterial species, respectively, represented by 961, 378 and 1673 standard FAME profiles. Through the application of machine learning techniques in a supervised strategy, different computational models have been built for genus and species identification. Three techniques have been considered: artificial neural networks, random forests and support vector machines. Nearly perfect identification has been achieved at genus level. Notwithstanding the known limited discriminative power of FAME analysis for species identification, the computational models have resulted in good species identification results for the three genera. For Bacillus, Paenibacillus and Pseudomonas, random forests have resulted in sensitivity values, respectively, 0.847, 0.901 and 0.708. The random forests models outperform those of the other machine learning techniques. Moreover, our machine learning approach also outperformed the Sherlock MIS (MIDI Inc., Newark, DE, USA). These results show that machine learning proves very useful for FAME-based bacterial species identification. Besides good bacterial identification at species level, speed and ease of taxonomic synchronization are major advantages of this computational species identification strategy.

Evaluation of two matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) systems for the identification of Candida species.

PubMed

Lacroix, C; Gicquel, A; Sendid, B; Meyer, J; Accoceberry, I; François, N; Morio, F; Desoubeaux, G; Chandenier, J; Kauffmann-Lacroix, C; Hennequin, C; Guitard, J; Nassif, X; Bougnoux, M-E

2014-02-01

Candida spp. are responsible for severe infections in immunocompromised patients and those undergoing invasive procedures. The accurate identification of Candida species is important because emerging species can be associated with various antifungal susceptibility spectra. Conventional methods have been developed to identify the most common pathogens, but have often failed to identify uncommon species. Several studies have reported the efficiency of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for the identification of clinically relevant Candida species. In this study, we evaluated two commercially available MALDI-TOF systems, Andromas™ and Bruker Biotyper™, for Candida identification in routine diagnosis. For this purpose, we investigated 1383 Candida isolates prospectively collected in eight hospital laboratories during routine practice. MALDI-TOF MS results were compared with those obtained using conventional phenotypic methods. Analysis of rDNA gene sequences with internal transcribed regions or D1-D2 regions is considered the reference standard for identification. Both MALDI-TOF MS systems could accurately identify 98.3% of the isolates at the species level (1359/1383 for Andromas™; 1360/1383 for Bruker Biotyper™) vs. 96.5% for conventional techniques. Furthermore, whereas conventional methods failed to identify rare or emerging species, these were correctly identified by MALDI-TOF MS. Both MALDI-TOF MS systems are accurate and cost-effective alternatives to conventional methods for mycological identification of clinically relevant Candida species and should improve the diagnosis of fungal infections as well as patient management. © 2013 The Authors Clinical Microbiology and Infection © 2013 European Society of Clinical Microbiology and Infectious Diseases.

Reduced-order model for underwater target identification using proper orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ramesh, Sai Sudha; Lim, Kian Meng

2017-03-01

Research on underwater acoustics has seen major development over the past decade due to its widespread applications in domains such as underwater communication/navigation (SONAR), seismic exploration and oceanography. In particular, acoustic signatures from partially or fully buried targets can be used in the identification of buried mines for mine counter measures (MCM). Although there exist several techniques to identify target properties based on SONAR images and acoustic signatures, these methods first employ a feature extraction method to represent the dominant characteristics of a data set, followed by the use of an appropriate classifier based on neural networks or the relevance vector machine. The aim of the present study is to demonstrate the applications of proper orthogonal decomposition (POD) technique in capturing dominant features of a set of scattered pressure signals, and subsequent use of the POD modes and coefficients in the identification of partially buried underwater target parameters such as its location, size and material density. Several numerical examples are presented to demonstrate the performance of the system identification method based on POD. Although the present study is based on 2D acoustic model, the method can be easily extended to 3D models and thereby enables cost-effective representations of large-scale data.

A highly sensitive quantitative cytosensor technique for the identification of receptor ligands in tissue extracts.

PubMed

Lenkei, Z; Beaudet, A; Chartrel, N; De Mota, N; Irinopoulou, T; Braun, B; Vaudry, H; Llorens-Cortes, C

2000-11-01

Because G-protein-coupled receptors (GPCRs) constitute excellent putative therapeutic targets, functional characterization of orphan GPCRs through identification of their endogenous ligands has great potential for drug discovery. We propose here a novel single cell-based assay for identification of these ligands. This assay involves (a) fluorescent tagging of the GPCR, (b) expression of the tagged receptor in a heterologous expression system, (c) incubation of the transfected cells with fractions purified from tissue extracts, and (d) imaging of ligand-induced receptor internalization by confocal microscopy coupled to digital image quantification. We tested this approach in CHO cells stably expressing the NT1 neurotensin receptor fused to EGFP (enhanced green fluorescent protein), in which neurotensin promoted internalization of the NT1-EGFP receptor in a dose-dependent fashion (EC(50) = 0.98 nM). Similarly, four of 120 consecutive reversed-phase HPLC fractions of frog brain extracts promoted internalization of the NT1-EGFP receptor. The same four fractions selectively contained neurotensin, an endogenous ligand of the NT1 receptor, as detected by radioimmunoassay and inositol phosphate production. The present internalization assay provides a highly specific quantitative cytosensor technique with sensitivity in the nanomolar range that should prove useful for the identification of putative natural and synthetic ligands for GPCRs.

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.

AGARD Flight Test Techniques Series. Volume 14. Introduction to Flight Test Engineering (Introduction a la Technique d’essais en vol)

DTIC Science & Technology

1995-09-01

path and aircraft attitude and other flight or aircraft parameters • Calculations in the frequency domain ( Fast Fourier Transform) • Data analysis...Signal filtering Image processing of video and radar data Parameter identification Statistical analysis Power spectral density Fast Fourier Transform...airspeeds both fast and slow, altitude, load factor both above and below 1g, centers of gravity (fore and aft), and with system/subsystem failures. Whether

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun-Fat

2017-01-01

A new time-domain approach for computing flutter speed is presented. Based on the time-history result of aeroelastic simulation, the unknown unsteady aerodynamics model is estimated using a system identification technique. The full aeroelastic model is generated via coupling the estimated unsteady aerodynamic model with the known linear structure model. The critical dynamic pressure is computed and used in the subsequent simulation until the convergence of the critical dynamic pressure is achieved. The proposed method is applied to a benchmark cantilevered rectangular wing.

Ballistic Signature Identification System Study

NASA Technical Reports Server (NTRS)

1976-01-01

The first phase of a research project directed toward development of a high speed automatic process to be used to match gun barrel signatures imparted to fired bullets was documented. An optical projection technique has been devised to produce and photograph a planar image of the entire signature, and the phototransparency produced is subjected to analysis using digital Fourier transform techniques. The success of this approach appears to be limited primarily by the accuracy of the photographic step since no significant processing limitations have been encountered.

Flight-vehicle materials, structures, and dynamics - Assessment and future directions. Vol. 5 - Structural dynamics and aeroelasticity

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Editor); Venneri, Samuel L. (Editor)

1993-01-01

Various papers on flight vehicle materials, structures, and dynamics are presented. Individual topics addressed include: general modeling methods, component modeling techniques, time-domain computational techniques, dynamics of articulated structures, structural dynamics in rotating systems, structural dynamics in rotorcraft, damping in structures, structural acoustics, structural design for control, structural modeling for control, control strategies for structures, system identification, overall assessment of needs and benefits in structural dynamics and controlled structures. Also discussed are: experimental aeroelasticity in wind tunnels, aeroservoelasticity, nonlinear aeroelasticity, aeroelasticity problems in turbomachines, rotary-wing aeroelasticity with application to VTOL vehicles, computational aeroelasticity, structural dynamic testing and instrumentation.

Applications of data compression techniques in modal analysis for on-orbit system identification

NASA Technical Reports Server (NTRS)

Carlin, Robert A.; Saggio, Frank; Garcia, Ephrahim

1992-01-01

Data compression techniques have been investigated for use with modal analysis applications. A redundancy-reduction algorithm was used to compress frequency response functions (FRFs) in order to reduce the amount of disk space necessary to store the data and/or save time in processing it. Tests were performed for both single- and multiple-degree-of-freedom (SDOF and MDOF, respectively) systems, with varying amounts of noise. Analysis was done on both the compressed and uncompressed FRFs using an SDOF Nyquist curve fit as well as the Eigensystem Realization Algorithm. Significant savings were realized with minimal errors incurred by the compression process.

Broadband Noise Control Using Predictive Techniques

NASA Technical Reports Server (NTRS)

Eure, Kenneth W.; Juang, Jer-Nan

1997-01-01

Predictive controllers have found applications in a wide range of industrial processes. Two types of such controllers are generalized predictive control and deadbeat control. Recently, deadbeat control has been augmented to include an extended horizon. This modification, named deadbeat predictive control, retains the advantage of guaranteed stability and offers a novel way of control weighting. This paper presents an application of both predictive control techniques to vibration suppression of plate modes. Several system identification routines are presented. Both algorithms are outlined and shown to be useful in the suppression of plate vibrations. Experimental results are given and the algorithms are shown to be applicable to non- minimal phase systems.

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

PubMed

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

2014-01-01

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

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

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

1972-01-01

A survey was made of the literature devoted to the synthesis of model-tracking adaptive systems based on application of Liapunov's second method. The basic synthesis procedure is introduced and a critical review of extensions made to the theory since 1966 is made. The extensions relate to design for relative stability, reduction of order techniques, design with disturbance, design with time variable parameters, multivariable systems, identification, and an adaptive observer.

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

A historical overview of flight flutter testing

NASA Technical Reports Server (NTRS)

Kehoe, Michael W.

1995-01-01

This paper reviews the test techniques developed over the last several decades for flight flutter testing of aircraft. Structural excitation systems, instrumentation systems, digital data preprocessing, and parameter identification algorithms (for frequency and damping estimates from the response data) are described. Practical experiences and example test programs illustrate the combined, integrated effectiveness of the various approaches used. Finally, comments regarding the direction of future developments and needs are presented.

Identification and assessment of hazardous compounds in drinking water.

PubMed

Fawell, J K; Fielding, M

1985-12-01

The identification of organic chemicals in drinking water and their assessment in terms of potential hazardous effects are two very different but closely associated tasks. In relation to both continuous low-level background contamination and specific, often high-level, contamination due to pollution incidents, the identification of contaminants is a pre-requisite to evaluation of significant hazards. Even in the case of the rapidly developing short-term bio-assays which are applied to water to indicate a potential genotoxic hazard (for example Ames tests), identification of the active chemicals is becoming a major factor in the further assessment of the response. Techniques for the identification of low concentrations of organic chemicals in drinking water have developed remarkably since the early 1970s and methods based upon gas chromatography-mass spectrometry (GC-MS) have revolutionised qualitative analysis of water. Such techniques are limited to "volatile" chemicals and these usually constitute a small fraction of the total organic material in water. However, in recent years there have been promising developments in techniques for "non-volatile" chemicals in water. Such techniques include combined high-performance liquid chromatography-mass spectrometry (HPLC-MS) and a variety of MS methods, involving, for example, field desorption, fast atom bombardment and thermospray ionisation techniques. In the paper identification techniques in general are reviewed and likely future developments outlined. The assessment of hazards associated with chemicals identified in drinking and related waters usually centres upon toxicology - an applied science which involves numerous disciplines. The paper examines the toxicological information needed, the quality and deployment of such information and discusses future research needs. Application of short-term bio-assays to drinking water is a developing area and one which is closely involved with, and to some extent dependent on, powerful methods of identification. Recent developments are discussed.

Cell-Detection Technique for Automated Patch Clamping

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth

2008-01-01

A unique and customizable machinevision and image-data-processing technique has been developed for use in automated identification of cells that are optimal for patch clamping. [Patch clamping (in which patch electrodes are pressed against cell membranes) is an electrophysiological technique widely applied for the study of ion channels, and of membrane proteins that regulate the flow of ions across the membranes. Patch clamping is used in many biological research fields such as neurobiology, pharmacology, and molecular biology.] While there exist several hardware techniques for automated patch clamping of cells, very few of those techniques incorporate machine vision for locating cells that are ideal subjects for patch clamping. In contrast, the present technique is embodied in a machine-vision algorithm that, in practical application, enables the user to identify good and bad cells for patch clamping in an image captured by a charge-coupled-device (CCD) camera attached to a microscope, within a processing time of one second. Hence, the present technique can save time, thereby increasing efficiency and reducing cost. The present technique involves the utilization of cell-feature metrics to accurately make decisions on the degree to which individual cells are "good" or "bad" candidates for patch clamping. These metrics include position coordinates (x,y) in the image plane, major-axis length, minor-axis length, area, elongation, roundness, smoothness, angle of orientation, and degree of inclusion in the field of view. The present technique does not require any special hardware beyond commercially available, off-the-shelf patch-clamping hardware: A standard patchclamping microscope system with an attached CCD camera, a personal computer with an imagedata- processing board, and some experience in utilizing imagedata- processing software are all that are needed. A cell image is first captured by the microscope CCD camera and image-data-processing board, then the image data are analyzed by software that implements the present machine-vision technique. This analysis results in the identification of cells that are "good" candidates for patch clamping (see figure). Once a "good" cell is identified, a patch clamp can be effected by an automated patchclamping apparatus or by a human operator. This technique has been shown to enable reliable identification of "good" and "bad" candidate cells for patch clamping. The ultimate goal in further development of this technique is to combine artificial-intelligence processing with instrumentation and controls in order to produce a complete "turnkey" automated patch-clamping system capable of accurately and reliably patch clamping cells with a minimum intervention by a human operator. Moreover, this technique can be adapted to virtually any cellular-analysis procedure that includes repetitive operation of microscope hardware by a human.

Combination of microautoradiography and fluorescence in situ hybridization for identification of microorganisms degrading xenobiotic contaminants.

PubMed

Yang, Yanru; Zarda, Annatina; Zeyer, Josef

2003-12-01

One of the central topics in environmental bioremediation research is to identify microorganisms that are capable of degrading the contaminants of interest. Here we report application of combined microautoradiography (MAR) and fluorescence in situ hybridization (FISH). The method has previously been used in a number of systems; however, here we demonstrate its feasibility in studying the degradation of xenobiotic compounds. With a model system (coculture of Pseudomonas putida B2 and Sphingomonas stygia incubated with [14C] o-nitrophenol), combination of MAR and FISH was shown to be able to successfully identify the microorganisms degrading o-nitrophenol. Compared with the conventional techniques, MAR-FISH allows fast and accurate identification of the microorganisms involved in environmental contaminant degradation.

Eigensystem realization algorithm modal identification experiences with mini-mast

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Schenk, Axel; Noll, Christopher

1992-01-01

This paper summarizes work performed under a collaborative research effort between the National Aeronautics and Space Administration (NASA) and the German Aerospace Research Establishment (DLR, Deutsche Forschungsanstalt fur Luft- und Raumfahrt). The objective is to develop and demonstrate system identification technology for future large space structures. Recent experiences using the Eigensystem Realization Algorithm (ERA), for modal identification of Mini-Mast, are reported. Mini-Mast is a 20 m long deployable space truss used for structural dynamics and active vibration-control research at the Langley Research Center. A comprehensive analysis of 306 frequency response functions (3 excitation forces and 102 displacement responses) was performed. Emphasis is placed on two topics of current research: (1) gaining an improved understanding of ERA performance characteristics (theory vs. practice); and (2) developing reliable techniques to improve identification results for complex experimental data. Because of nonlinearities and numerous local modes, modal identification of Mini-Mast proved to be surprisingly difficult. Methods were available, ERA, for obtaining detailed, high-confidence results.

Ultrabroadband phased-array radio frequency (RF) receivers based on optical techniques

NASA Astrophysics Data System (ADS)

Overmiller, Brock M.; Schuetz, Christopher A.; Schneider, Garrett; Murakowski, Janusz; Prather, Dennis W.

2014-03-01

Military operations require the ability to locate and identify electronic emissions in the battlefield environment. However, recent developments in radio detection and ranging (RADAR) and communications technology are making it harder to effectively identify such emissions. Phased array systems aid in discriminating emitters in the scene by virtue of their relatively high-gain beam steering and nulling capabilities. For the purpose of locating emitters, we present an approach realize a broadband receiver based on optical processing techniques applied to the response of detectors in conformal antenna arrays. This approach utilizes photonic techniques that enable us to capture, route, and process the incoming signals. Optical modulators convert the incoming signals up to and exceeding 110 GHz with appreciable conversion efficiency and route these signals via fiber optics to a central processing location. This central processor consists of a closed loop phase control system which compensates for phase fluctuations induced on the fibers due to thermal or acoustic vibrations as well as an optical heterodyne approach for signal conversion down to baseband. Our optical heterodyne approach uses injection-locked paired optical sources to perform heterodyne downconversion/frequency identification of the detected emission. Preliminary geolocation and frequency identification testing of electronic emissions has been performed demonstrating the capabilities of our RF receiver.

Evaluation of partial 16S ribosomal DNA sequencing for identification of nocardia species by using the MicroSeq 500 system with an expanded database.

PubMed

Cloud, Joann L; Conville, Patricia S; Croft, Ann; Harmsen, Dag; Witebsky, Frank G; Carroll, Karen C

2004-02-01

Identification of clinically significant nocardiae to the species level is important in patient diagnosis and treatment. A study was performed to evaluate Nocardia species identification obtained by partial 16S ribosomal DNA (rDNA) sequencing by the MicroSeq 500 system with an expanded database. The expanded portion of the database was developed from partial 5' 16S rDNA sequences derived from 28 reference strains (from the American Type Culture Collection and the Japanese Collection of Microorganisms). The expanded MicroSeq 500 system was compared to (i). conventional identification obtained from a combination of growth characteristics with biochemical and drug susceptibility tests; (ii). molecular techniques involving restriction enzyme analysis (REA) of portions of the 16S rRNA and 65-kDa heat shock protein genes; and (iii). when necessary, sequencing of a 999-bp fragment of the 16S rRNA gene. An unknown isolate was identified as a particular species if the sequence obtained by partial 16S rDNA sequencing by the expanded MicroSeq 500 system was 99.0% similar to that of the reference strain. Ninety-four nocardiae representing 10 separate species were isolated from patient specimens and examined by using the three different methods. Sequencing of partial 16S rDNA by the expanded MicroSeq 500 system resulted in only 72% agreement with conventional methods for species identification and 90% agreement with the alternative molecular methods. Molecular methods for identification of Nocardia species provide more accurate and rapid results than the conventional methods using biochemical and susceptibility testing. With an expanded database, the MicroSeq 500 system for partial 16S rDNA was able to correctly identify the human pathogens N. brasiliensis, N. cyriacigeorgica, N. farcinica, N. nova, N. otitidiscaviarum, and N. veterana.

A Program for the Identification of the Enterobacteriaceae for Use in Teaching the Principles of Computer Identification of Bacteria.

ERIC Educational Resources Information Center

Hammonds, S. J.

1990-01-01

A technique for the numerical identification of bacteria using normalized likelihoods calculated from a probabilistic database is described, and the principles of the technique are explained. The listing of the computer program is included. Specimen results from the program, and examples of how they should be interpreted, are given. (KR)

Method of joint bit rate/modulation format identification and optical performance monitoring using asynchronous delay-tap sampling for radio-over-fiber systems

NASA Astrophysics Data System (ADS)

Guesmi, Latifa; Menif, Mourad

2016-08-01

In the context of carrying a wide variety of modulation formats and data rates for home networks, the study covers the radio-over-fiber (RoF) technology, where the need for an alternative way of management, automated fault diagnosis, and formats identification is expressed. Also, RoF signals in an optical link are impaired by various linear and nonlinear effects including chromatic dispersion, polarization mode dispersion, amplified spontaneous emission noise, and so on. Hence, for this purpose, we investigated the sampling method based on asynchronous delay-tap sampling in conjunction with a cross-correlation function for the joint bit rate/modulation format identification and optical performance monitoring. Three modulation formats with different data rates are used to demonstrate the validity of this technique, where the identification accuracy and the monitoring ranges reached high values.

System identification of closed-loop cardiovascular control: effects of posture and autonomic blockade

NASA Technical Reports Server (NTRS)

Mullen, T. J.; Appel, M. L.; Mukkamala, R.; Mathias, J. M.; Cohen, R. J.

1997-01-01

We applied system identification to the analysis of fluctuations in heart rate (HR), arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize quantitatively the physiological mechanisms responsible for the couplings between these variables. We characterized two autonomically mediated coupling mechanisms [the heart rate baroreflex (HR baroreflex) and respiratory sinus arrhythmia (ILV-HR)] and two mechanically mediated coupling mechanisms [the blood pressure wavelet generated with each cardiac contraction (circulatory mechanics) and the direct mechanical effects of respiration on blood pressure (ILV-->ABP)]. We evaluated the method in humans studied in the supine and standing postures under control conditions and under conditions of beta-sympathetic and parasympathetic pharmacological blockades. Combined beta-sympathetic and parasympathetic blockade abolished the autonomically mediated couplings while preserving the mechanically mediated coupling. Selective autonomic blockade and postural changes also altered the couplings in a manner consistent with known physiological mechanisms. System identification is an "inverse-modeling" technique that provides a means for creating a closed-loop model of cardiovascular regulation for an individual subject without altering the underlying physiological control mechanisms.

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

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.

F-15B Quiet Spike(TradeMark) Aeroservoelastic Flight-Test Data Analysis

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

System identification is utilized in the aerospace community for development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlin ear systems. In this report, we show the application of one such nonlinear system identification technique, structure detection, for the an alysis of Quiet Spike(TradeMark)(Gulfstream Aerospace Corporation, Savannah, Georgia) aeroservoelastic flight-test data. Structure detectio n is concerned with the selection of a subset of candidate terms that best describe the observed output. Structure computation as a tool fo r black-box modeling may be of critical importance for the development of robust, parsimonious models for the flight-test community. The ob jectives of this study are to demonstrate via analysis of Quiet Spike(TradeMark) aeroservoelastic flight-test data for several flight conditions that: linear models are inefficient for modelling aeroservoelast ic data, nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data an d the model structure and parameters vary as the flight condition is altered.

Microearthquake Studies at the Salton Sea Geothermal Field

DOE Data Explorer

Templeton, Dennise

2013-10-01

The objective of this project is to detect and locate microearthquakes to aid in the characterization of reservoir fracture networks. Accurate identification and mapping of the large numbers of microearthquakes induced in EGS is one technique that provides diagnostic information when determining the location, orientation and length of underground crack systems for use in reservoir development and management applications. Conventional earthquake location techniques often are employed to locate microearthquakes. However, these techniques require labor-intensive picking of individual seismic phase onsets across a network of sensors. For this project we adapt the Matched Field Processing (MFP) technique to the elastic propagation problem in geothermal reservoirs to identify more and smaller events than traditional methods alone.

Molecular identification of Malassezia species isolated from dermatitis affections.

PubMed

Affes, M; Ben Salah, S; Makni, F; Sellami, H; Ayadi, A

2009-05-01

The lipophilic yeast of the genus Malassezia are opportunistic microorganisms of the skin microflora but they can be agents of various dermatomycoses. The aim of this study was to perform molecular identification of the commonly isolated Malassezia species from various dermatomycoses in our region. Thirty strains of Malassezia were isolated from different dermatologic affections: pityriasis versicolor (17), dandruff (5), seborrheic dermatitis (4), onyxis (2), folliculitis (1) and blepharitis (1). These species were identified by their morphological features and biochemical characterisation. The molecular identification was achieved by amplification of the internal transcribed spacer region by simple PCR. PCR technique was used for molecular characterisation of four Malassezia species: Malassezia globosa (270 bp), Malassezia furfur (230 bp), Malassezia sympodialis (190 bp) and Malassezia restricta (320 bp). We have detected the association between M. furfur and M. sympodialis in 16% and confirmed presumptive identification in 70% of the cases. The phenotypic identification based on microscopic and physiological method is difficult and time consuming. The application of a simple PCR method provides a sensitive and rapid identification system for Malassezia species, which may be applied in epidemiological surveys and routine practice.

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.

Rocket Engine Health Management: Early Definition of Critical Flight Measurements

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

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…

Application of the System Identification Technique to Goal-Directed Saccades.

DTIC Science & Technology

1985-07-01

Saccadic eye movements are among the fastest voluntary muscle movements the human body is capable of producing and are characterized by a rapid shift of gaze ...moving the target the same distance the eyeball moves. Collewijn and Van der Mark (9), in their study of the slow phase of optokinetic nystagmus , used

Candida infections among neutropenic patients

PubMed Central

Mohammadi, Rasoul; Foroughifar, Elham

2016-01-01

Background: Systemic candidiasis is a major complication in neutropenic cancer patients undergoing treatment. Most systemic fungal infections emerge from endogenous microflora so the aim of the present study was to identify Candida species isolated from the different regions of body in neutropenic patients in compare with the control group. Methods: A total of 309 neutropenic cancer patients and 584 patients without cancer (control group) entered in the study. Molecular identification of clinical isolates was performed by PCR-RFLP technique. Results: Twenty-two out of 309 patients had candidiasis (7.1%). Male to female ratio was 1/1 and age ranged from 23 to 66 years. Colorectal cancer and acute myeloid leukemia (AML) were the most common cancers. Candida albicans was the most prevalent Candida species among neutropenic patients (50%) and control group (57.9%). Mortality rate in cancer patients was 13.6% in comparison with control group (5.2%). Conclusion: Since candidiasis is an important cause of morbidity and mortality in neutropenic patients, precise identification of Candida species by molecular techniques can be useful for the appropriate selection of antifungal drugs particularly in high risk patients. PMID:27386056

A Passive System Reliability Analysis for a Station Blackout

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

Brunett, Acacia; Bucknor, Matthew; Grabaskas, David

2015-05-03

The latest iterations of advanced reactor designs have included increased reliance on passive safety systems to maintain plant integrity during unplanned sequences. While these systems are advantageous in reducing the reliance on human intervention and availability of power, the phenomenological foundations on which these systems are built require a novel approach to a reliability assessment. Passive systems possess the unique ability to fail functionally without failing physically, a result of their explicit dependency on existing boundary conditions that drive their operating mode and capacity. Argonne National Laboratory is performing ongoing analyses that demonstrate various methodologies for the characterization of passivemore » system reliability within a probabilistic framework. Two reliability analysis techniques are utilized in this work. The first approach, the Reliability Method for Passive Systems, provides a mechanistic technique employing deterministic models and conventional static event trees. The second approach, a simulation-based technique, utilizes discrete dynamic event trees to treat time- dependent phenomena during scenario evolution. For this demonstration analysis, both reliability assessment techniques are used to analyze an extended station blackout in a pool-type sodium fast reactor (SFR) coupled with a reactor cavity cooling system (RCCS). This work demonstrates the entire process of a passive system reliability analysis, including identification of important parameters and failure metrics, treatment of uncertainties and analysis of results.« less

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.

Interior Noise Reduction by Adaptive Feedback Vibration Control

NASA Technical Reports Server (NTRS)

Lim, Tae W.

1998-01-01

The objective of this project is to investigate the possible use of adaptive digital filtering techniques in simultaneous, multiple-mode identification of the modal parameters of a vibrating structure in real-time. It is intended that the results obtained from this project will be used for state estimation needed in adaptive structural acoustics control. The work done in this project is basically an extension of the work on real-time single mode identification, which was performed successfully using a digital signal processor (DSP) at NASA, Langley. Initially, in this investigation the single mode identification work was duplicated on a different processor, namely the Texas Instruments TMS32OC40 DSP. The system identification results for the single mode case were very good. Then an algorithm for simultaneous two mode identification was developed and tested using analytical simulation. When it successfully performed the expected tasks, it was implemented in real-time on the DSP system to identify the first two modes of vibration of a cantilever aluminum beam. The results of the simultaneous two mode case were good but some problems were identified related to frequency warping and spurious mode identification. The frequency warping problem was found to be due to the bilinear transformation used in the algorithm to convert the system transfer function from the continuous-time domain to the discrete-time domain. An alternative approach was developed to rectify the problem. The spurious mode identification problem was found to be associated with high sampling rates. Noise in the signal is suspected to be the cause of this problem but further investigation will be needed to clarify the cause. For simultaneous identification of more than two modes, it was found that theoretically an adaptive digital filter can be designed to identify the required number of modes, but the algebra became very complex which made it impossible to implement in the DSP system used in this study. The on-line identification algorithm developed in this research will be useful in constructing a state estimator for feedback vibration control.

Time domain nonlinear SMA damper force identification approach and its numerical validation

NASA Astrophysics Data System (ADS)

Xin, Lulu; Xu, Bin; He, Jia

2012-04-01

Most of the currently available vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from vibration measurements and, strictly speaking, are only suitable for linear system. However, the initiation and development of damage in engineering structures under severe dynamic loadings are typical nonlinear procedure. Studies on the identification of restoring force which is a direct indicator of the extent of the nonlinearity have received increasing attention in recent years. In this study, a date-based time domain identification approach for general nonlinear system was developed. The applied excitation and the corresponding response time series of the structure were used for identification by means of standard least-square techniques and a power series polynomial model (PSPM) which was utilized to model the nonlinear restoring force (NRF). The feasibility and robustness of the proposed approach was verified by a 2 degree-of-freedoms (DOFs) lumped mass numerical model equipped with a shape memory ally (SMA) damper mimicking nonlinear behavior. The results show that the proposed data-based time domain method is capable of identifying the NRF in engineering structures without any assumptions on the mass distribution and the topology of the structure, and provides a promising way for damage detection in the presence of structural nonlinearities.

Technical management techniques for identification and control of industrial safety and pollution hazards

NASA Technical Reports Server (NTRS)

Campbell, R.; Dyer, M. K.; Hoard, E. G.; Little, D. G.; Taylor, A. C.

1972-01-01

Constructive recommendations are suggested for pollution problems from offshore energy resources industries on outer continental shelf. Technical management techniques for pollution identification and control offer possible applications to space engineering and management.

Neural networks for function approximation in nonlinear control

NASA Technical Reports Server (NTRS)

Linse, Dennis J.; Stengel, Robert F.

1990-01-01

Two neural network architectures are compared with a classical spline interpolation technique for the approximation of functions useful in a nonlinear control system. A standard back-propagation feedforward neural network and a cerebellar model articulation controller (CMAC) neural network are presented, and their results are compared with a B-spline interpolation procedure that is updated using recursive least-squares parameter identification. Each method is able to accurately represent a one-dimensional test function. Tradeoffs between size requirements, speed of operation, and speed of learning indicate that neural networks may be practical for identification and adaptation in a nonlinear control environment.

Tag-to-Tag Interference Suppression Technique Based on Time Division for RFID.

PubMed

Khadka, Grishma; Hwang, Suk-Seung

2017-01-01

Radio-frequency identification (RFID) is a tracking technology that enables immediate automatic object identification and rapid data sharing for a wide variety of modern applications using radio waves for data transmission from a tag to a reader. RFID is already well established in technical areas, and many companies have developed corresponding standards and measurement techniques. In the construction industry, effective monitoring of materials and equipment is an important task, and RFID helps to improve monitoring and controlling capabilities, in addition to enabling automation for construction projects. However, on construction sites, there are many tagged objects and multiple RFID tags that may interfere with each other's communications. This reduces the reliability and efficiency of the RFID system. In this paper, we propose an anti-collision algorithm for communication between multiple tags and a reader. In order to suppress interference signals from multiple neighboring tags, the proposed algorithm employs the time-division (TD) technique, where tags in the interrogation zone are assigned a specific time slot so that at every instance in time, a reader communicates with tags using the specific time slot. We present representative computer simulation examples to illustrate the performance of the proposed anti-collision technique for multiple RFID tags.

Identification of integrated airframe: Propulsion effects on an F-15 aircraft for application to drag minimization

NASA Technical Reports Server (NTRS)

Schkolnik, Gerard S.

1993-01-01

The application of an adaptive real-time measurement-based performance optimization technique is being explored for a future flight research program. The key technical challenge of the approach is parameter identification, which uses a perturbation-search technique to identify changes in performance caused by forced oscillations of the controls. The controls on the NASA F-15 highly integrated digital electronic control (HIDEC) aircraft were perturbed using inlet cowl rotation steps at various subsonic and supersonic flight conditions to determine the effect on aircraft performance. The feasibility of the perturbation-search technique for identifying integrated airframe-propulsion system performance effects was successfully shown through flight experiments and postflight data analysis. Aircraft response and control data were analyzed postflight to identify gradients and to determine the minimum drag point. Changes in longitudinal acceleration as small as 0.004 g were measured, and absolute resolution was estimated to be 0.002 g or approximately 50 lbf of drag. Two techniques for identifying performance gradients were compared: a least-squares estimation algorithm and a modified maximum likelihood estimator algorithm. A complementary filter algorithm was used with the least squares estimator.

Identification of integrated airframe-propulsion effects on an F-15 aircraft for application to drag minimization

NASA Technical Reports Server (NTRS)

Schkolnik, Gerald S.

1993-01-01

The application of an adaptive real-time measurement-based performance optimization technique is being explored for a future flight research program. The key technical challenge of the approach is parameter identification, which uses a perturbation-search technique to identify changes in performance caused by forced oscillations of the controls. The controls on the NASA F-15 highly integrated digital electronic control (HIDEC) aircraft were perturbed using inlet cowl rotation steps at various subsonic and supersonic flight conditions to determine the effect on aircraft performance. The feasibility of the perturbation-search technique for identifying integrated airframe-propulsion system performance effects was successfully shown through flight experiments and postflight data analysis. Aircraft response and control data were analyzed postflight to identify gradients and to determine the minimum drag point. Changes in longitudinal acceleration as small as 0.004 g were measured, and absolute resolution was estimated to be 0.002 g or approximately 50 lbf of drag. Two techniques for identifying performance gradients were compared: a least-squares estimation algorithm and a modified maximum likelihood estimator algorithm. A complementary filter algorithm was used with the least squares estimator.

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

PubMed Central

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

PubMed

Illias, Hazlee Azil; Zhao Liang, Wee

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

Automated Solid Phase Extraction (SPE) LC/NMR Applied to the Structural Analysis of Extractable Compounds from a Pharmaceutical Packaging Material of Construction.

PubMed

Norwood, Daniel L; Mullis, James O; Davis, Mark; Pennino, Scott; Egert, Thomas; Gonnella, Nina C

2013-01-01

The structural analysis (i.e., identification) of organic chemical entities leached into drug product formulations has traditionally been accomplished with techniques involving the combination of chromatography with mass spectrometry. These include gas chromatography/mass spectrometry (GC/MS) for volatile and semi-volatile compounds, and various forms of liquid chromatography/mass spectrometry (LC/MS or HPLC/MS) for semi-volatile and relatively non-volatile compounds. GC/MS and LC/MS techniques are complementary for structural analysis of leachables and potentially leachable organic compounds produced via laboratory extraction of pharmaceutical container closure/delivery system components and corresponding materials of construction. Both hyphenated analytical techniques possess the separating capability, compound specific detection attributes, and sensitivity required to effectively analyze complex mixtures of trace level organic compounds. However, hyphenated techniques based on mass spectrometry are limited by the inability to determine complete bond connectivity, the inability to distinguish between many types of structural isomers, and the inability to unambiguously determine aromatic substitution patterns. Nuclear magnetic resonance spectroscopy (NMR) does not have these limitations; hence it can serve as a complement to mass spectrometry. However, NMR technology is inherently insensitive and its ability to interface with chromatography has been historically challenging. This article describes the application of NMR coupled with liquid chromatography and automated solid phase extraction (SPE-LC/NMR) to the structural analysis of extractable organic compounds from a pharmaceutical packaging material of construction. The SPE-LC/NMR technology combined with micro-cryoprobe technology afforded the sensitivity and sample mass required for full structure elucidation. Optimization of the SPE-LC/NMR analytical method was achieved using a series of model compounds representing the chemical diversity of extractables. This study demonstrates the complementary nature of SPE-LC/NMR with LC/MS for this particular pharmaceutical application. The identification of impurities leached into drugs from the components and materials associated with pharmaceutical containers, packaging components, and materials has historically been done using laboratory techniques based on the combination of chromatography with mass spectrometry. Such analytical techniques are widely recognized as having the selectivity and sensitivity required to separate the complex mixtures of impurities often encountered in such identification studies, including both the identification of leachable impurities as well as potential leachable impurities produced by laboratory extraction of packaging components and materials. However, while mass spectrometry-based analytical techniques have limitations for this application, newer analytical techniques based on the combination of chromatography with nuclear magnetic resonance spectroscopy provide an added dimension of structural definition. This article describes the development, optimization, and application of an analytical technique based on the combination of chromatography and nuclear magnetic resonance spectroscopy to the identification of potential leachable impurities from a pharmaceutical packaging material. The complementary nature of the analytical techniques for this particular pharmaceutical application is demonstrated.

Experimental validation of a new heterogeneous mechanical test design

NASA Astrophysics Data System (ADS)

Aquino, J.; Campos, A. Andrade; Souto, N.; Thuillier, S.

2018-05-01

Standard material parameters identification strategies generally use an extensive number of classical tests for collecting the required experimental data. However, a great effort has been made recently by the scientific and industrial communities to support this experimental database on heterogeneous tests. These tests can provide richer information on the material behavior allowing the identification of a more complete set of material parameters. This is a result of the recent development of full-field measurements techniques, like digital image correlation (DIC), that can capture the heterogeneous deformation fields on the specimen surface during the test. Recently, new specimen geometries were designed to enhance the richness of the strain field and capture supplementary strain states. The butterfly specimen is an example of these new geometries, designed through a numerical optimization procedure where an indicator capable of evaluating the heterogeneity and the richness of strain information. However, no experimental validation was yet performed. The aim of this work is to experimentally validate the heterogeneous butterfly mechanical test in the parameter identification framework. For this aim, DIC technique and a Finite Element Model Up-date inverse strategy are used together for the parameter identification of a DC04 steel, as well as the calculation of the indicator. The experimental tests are carried out in a universal testing machine with the ARAMIS measuring system to provide the strain states on the specimen surface. The identification strategy is accomplished with the data obtained from the experimental tests and the results are compared to a reference numerical solution.

Identification and tracking of vertebrae in ultrasound using deep networks with unsupervised feature learning

NASA Astrophysics Data System (ADS)

Hetherington, Jorden; Pesteie, Mehran; Lessoway, Victoria A.; Abolmaesumi, Purang; Rohling, Robert N.

2017-03-01

Percutaneous needle insertion procedures on the spine often require proper identification of the vertebral level in order to effectively deliver anesthetics and analgesic agents to achieve adequate block. For example, in obstetric epidurals, the target is at the L3-L4 intervertebral space. The current clinical method involves "blind" identification of the vertebral level through manual palpation of the spine, which has only 30% accuracy. This implies the need for better anatomical identification prior to needle insertion. A system is proposed to identify the vertebrae, assigning them to their respective levels, and track them in a standard sequence of ultrasound images, when imaged in the paramedian plane. Machine learning techniques are developed to identify discriminative features of the laminae. In particular, a deep network is trained to automatically learn the anatomical features of the lamina peaks, and classify image patches, for pixel-level classification. The chosen network utilizes multiple connected auto-encoders to learn the anatomy. Pre-processing with ultrasound bone enhancement techniques is done to aid the pixel-level classification performance. Once the lamina are identified, vertebrae are assigned levels and tracked in sequential frames. Experimental results were evaluated against an expert sonographer. Based on data acquired from 15 subjects, vertebrae identification with sensitivity of 95% and precision of 95% was achieved within each frame. Between pairs of subsequently analyzed frames, matches of predicted vertebral level labels were correct in 94% of cases, when compared to matches of manually selected labels

Optical Security System Based on the Biometrics Using Holographic Storage Technique with a Simple Data Format

NASA Astrophysics Data System (ADS)

Jun, An Won

2006-01-01

We implement a first practical holographic security system using electrical biometrics that combines optical encryption and digital holographic memory technologies. Optical information for identification includes a picture of face, a name, and a fingerprint, which has been spatially multiplexed by random phase mask used for a decryption key. For decryption in our biometric security system, a bit-error-detection method that compares the digital bit of live fingerprint with of fingerprint information extracted from hologram is used.

A Novel Augmented Reality-Based Navigation System in Perforator Flap Transplantation - A Feasibility Study.

PubMed

Jiang, Taoran; Zhu, Ming; Zan, Tao; Gu, Bin; Li, Qingfeng

2017-08-01

In perforator flap transplantation, dissection of the perforator is an important but difficult procedure because of the high variability in vascular anatomy. Preoperative imaging techniques could provide substantial information about vascular anatomy; however, it cannot provide direct guidance for surgeons during the operation. In this study, a navigation system (NS) was established to overlie a vascular map on surgical sites to further provide a direct guide for perforator flap transplantation. The NS was established based on computed tomographic angiography and augmented reality techniques. A virtual vascular map was reconstructed according to computed tomographic angiography data and projected onto real patient images using ARToolKit software. Additionally, a screw-fixation marker holder was created to facilitate registration. With the use of a tracking and display system, we conducted the NS on an animal model and measured the system error on a rapid prototyping model. The NS assistance allowed for correct identification, as well as a safe and precise dissection of the perforator. The mean value of the system error was determined to be 3.474 ± 1.546 mm. Augmented reality-based NS can provide precise navigation information by directly displaying a 3-dimensional individual anatomical virtual model onto the operative field in real time. It will allow rapid identification and safe dissection of a perforator in free flap transplantation surgery.

A computational approach to real-time image processing for serial time-encoded amplified microscopy

NASA Astrophysics Data System (ADS)

Oikawa, Minoru; Hiyama, Daisuke; Hirayama, Ryuji; Hasegawa, Satoki; Endo, Yutaka; Sugie, Takahisa; Tsumura, Norimichi; Kuroshima, Mai; Maki, Masanori; Okada, Genki; Lei, Cheng; Ozeki, Yasuyuki; Goda, Keisuke; Shimobaba, Tomoyoshi

2016-03-01

High-speed imaging is an indispensable technique, particularly for identifying or analyzing fast-moving objects. The serial time-encoded amplified microscopy (STEAM) technique was proposed to enable us to capture images with a frame rate 1,000 times faster than using conventional methods such as CCD (charge-coupled device) cameras. The application of this high-speed STEAM imaging technique to a real-time system, such as flow cytometry for a cell-sorting system, requires successively processing a large number of captured images with high throughput in real time. We are now developing a high-speed flow cytometer system including a STEAM camera. In this paper, we describe our approach to processing these large amounts of image data in real time. We use an analog-to-digital converter that has up to 7.0G samples/s and 8-bit resolution for capturing the output voltage signal that involves grayscale images from the STEAM camera. Therefore the direct data output from the STEAM camera generates 7.0G byte/s continuously. We provided a field-programmable gate array (FPGA) device as a digital signal pre-processor for image reconstruction and finding objects in a microfluidic channel with high data rates in real time. We also utilized graphics processing unit (GPU) devices for accelerating the calculation speed of identification of the reconstructed images. We built our prototype system, which including a STEAM camera, a FPGA device and a GPU device, and evaluated its performance in real-time identification of small particles (beads), as virtual biological cells, owing through a microfluidic channel.

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.

Low-cost real-time automatic wheel classification system

NASA Astrophysics Data System (ADS)

Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

1992-11-01

This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

TOXICITY IDENTIFICATION EVALUATION (TIE) RESULTS FOR METAL CONTAMINATED SEDIMENTS

EPA Science Inventory

Identification of contaminants in sediment is necessary for sound management decisions on sediment disposal, remediation, determination of ecological risk, and source identification. We have been developing sediment toxicity identification evaluation (TIE) techniques that allow ...

Vibrio parahaemolyticus: a review on the pathogenesis, prevalence, and advance molecular identification techniques

PubMed Central

Letchumanan, Vengadesh; Chan, Kok-Gan; Lee, Learn-Han

2014-01-01

Vibrio parahaemolyticus is a Gram-negative halophilic bacterium that is found in estuarine, marine and coastal environments. V. parahaemolyticus is the leading causal agent of human acute gastroenteritis following the consumption of raw, undercooked, or mishandled marine products. In rare cases, V. parahaemolyticus causes wound infection, ear infection or septicaemia in individuals with pre-existing medical conditions. V. parahaemolyticus has two hemolysins virulence factors that are thermostable direct hemolysin (tdh)-a pore-forming protein that contributes to the invasiveness of the bacterium in humans, and TDH-related hemolysin (trh), which plays a similar role as tdh in the disease pathogenesis. In addition, the bacterium is also encodes for adhesions and type III secretion systems (T3SS1 and T3SS2) to ensure its survival in the environment. This review aims at discussing the V. parahaemolyticus growth and characteristics, pathogenesis, prevalence and advances in molecular identification techniques. PMID:25566219

Crop Identification Technolgy Assessment for Remote Sensing (CITARS). Volume 1: Task design plan

NASA Technical Reports Server (NTRS)

Hall, F. G.; Bizzell, R. M.

1975-01-01

A plan for quantifying the crop identification performances resulting from the remote identification of corn, soybeans, and wheat is described. Steps for the conversion of multispectral data tapes to classification results are specified. The crop identification performances resulting from the use of several basic types of automatic data processing techniques are compared and examined for significant differences. The techniques are evaluated also for changes in geographic location, time of the year, management practices, and other physical factors. The results of the Crop Identification Technology Assessment for Remote Sensing task will be applied extensively in the Large Area Crop Inventory Experiment.

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.

Theoretical Models for Aircraft Availability: Classical Approach to Identification of Trends, Seasonality, and System Constraints in the Development of Realized Models

DTIC Science & Technology

2004-03-01

predicting future events ( Heizer and Render , 1999). Forecasting techniques fall into two major categories, qualitative and quantitative methods...Globemaster III.” Excerpt from website. www.globalsecurity.org/military /systems/ aircraft/c-17-history.htm. 2003. Heizer , Jay, and Barry Render ...of the past data used to make the forecast ( Heizer , et. al., 1999). Explanatory forecasting models assume that the variable being forecasted

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1997-01-01

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

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

Pierre, John W.; Wies, Richard; Trudnowski, Daniel

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacificmore » Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements.« less

Advanced Health Management of a Brushless Direct Current Motor/Controller

NASA Technical Reports Server (NTRS)

Pickett, R. D.

2003-01-01

This effort demonstrates that health management can be taken to the component level for electromechanical systems. The same techniques can be applied to take any health management system to the component level, based on the practicality of the implementation for that particular system. This effort allows various logic schemes to be implemented for the identification and management of failures. By taking health management to the component level, integrated vehicle health management systems can be enhanced by protecting box-level avionics from being shut down in order to isolate a failed computer.

Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.

1985-01-01

A component mode synthesis method for damped structures was developed and modal test methods were explored which could be employed to determine the relevant parameters required by the component mode synthesis method. Research was conducted on the following topics: (1) Development of a generalized time-domain component mode synthesis technique for damped systems; (2) Development of a frequency-domain component mode synthesis method for damped systems; and (3) Development of a system identification algorithm applicable to general damped systems. Abstracts are presented of the major publications which have been previously issued on these topics.

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.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

The techniques available for source identification are reviewed: remote sensing, injected tracers, and pollutants themselves as tracers. The use of the large number of trace elements in the ambient airborne particulate matter as a practical means of identifying sources is discussed. Trace constituents are determined by sensitive, inexpensive, nondestructive, multielement analytical methods such as instrumental neutron activation and charged particle X-ray fluorescence. The application to a large data set of pairwise correlation, the more advanced pattern recognition-cluster analysis approach with and without training sets, enrichment factors, and pollutant concentration rose displays for each element is described. It is shown that elemental constituents are related to specific source types: earth crustal, automotive, metallurgical, and more specific industries. A field-ready source identification system based on time and wind direction resolved sampling is described.

A Technique for Measuring Rotocraft Dynamic Stability in the 40 by 80 Foot Wind Tunnel

NASA Technical Reports Server (NTRS)

Gupta, N. K.; Bohn, J. G.

1977-01-01

An on-line technique is described for the measurement of tilt rotor aircraft dynamic stability in the Ames 40- by 80-Foot Wind Tunnel. The technique is based on advanced system identification methodology and uses the instrumental variables approach. It is particulary applicable to real time estimation problems with limited amounts of noise-contaminated data. Several simulations are used to evaluate the algorithm. Estimated natural frequencies and damping ratios are compared with simulation values. The algorithm is also applied to wind tunnel data in an off-line mode. The results are used to develop preliminary guidelines for effective use of the algorithm.

Simulation verification techniques study. Subsystem simulation validation techniques

NASA Technical Reports Server (NTRS)

Duncan, L. M.; Reddell, J. P.; Schoonmaker, P. B.

1974-01-01

Techniques for validation of software modules which simulate spacecraft onboard systems are discussed. An overview of the simulation software hierarchy for a shuttle mission simulator is provided. A set of guidelines for the identification of subsystem/module performance parameters and critical performance parameters are presented. Various sources of reference data to serve as standards of performance for simulation validation are identified. Environment, crew station, vehicle configuration, and vehicle dynamics simulation software are briefly discussed from the point of view of their interfaces with subsystem simulation modules. A detailed presentation of results in the area of vehicle subsystems simulation modules is included. A list of references, conclusions and recommendations are also given.

Method and apparatus for data decoding and processing

DOEpatents

Hunter, Timothy M.; Levy, Arthur J.

1992-01-01

A system and technique is disclosed for automatically controlling the decoding and digitizaiton of an analog tape. The system includes the use of a tape data format which includes a plurality of digital codes recorded on the analog tape in a predetermined proximity to a period of recorded analog data. The codes associated with each period of analog data include digital identification codes prior to the analog data, a start of data code coincident with the analog data recording, and an end of data code subsequent to the associated period of recorded analog data. The formatted tape is decoded in a processing and digitization system which includes an analog tape player coupled to a digitizer to transmit analog information from the recorded tape over at least one channel to the digitizer. At the same time, the tape player is coupled to a decoder and interface system which detects and decodes the digital codes on the tape corresponding to each period of recorded analog data and controls tape movement and digitizer initiation in response to preprogramed modes. A host computer is also coupled to the decoder and interface system and the digitizer and programmed to initiate specific modes of data decoding through the decoder and interface system including the automatic compilation and storage of digital identification information and digitized data for the period of recorded analog data corresponding to the digital identification data, compilation and storage of selected digitized data representing periods of recorded analog data, and compilation of digital identification information related to each of the periods of recorded analog data.

Fusion of imaging and nonimaging data for surveillance aircraft

NASA Astrophysics Data System (ADS)

Shahbazian, Elisa; Gagnon, Langis; Duquet, Jean Remi; Macieszczak, Maciej; Valin, Pierre

1997-06-01

This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight synthetic aperture radar (SSAR), a forward looking infra-red (FLIR) sensor and a link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (1) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (2) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (3) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as multi-sensor data fusion (MSDF), situation and threat assessment (STA) and resource management (RM).

Noninvasive forward-scattering system for rapid detection, characterization, and identification of Listeria colonies: image processing and data analysis

NASA Astrophysics Data System (ADS)

Rajwa, Bartek; Bayraktar, Bulent; Banada, Padmapriya P.; Huff, Karleigh; Bae, Euiwon; Hirleman, E. Daniel; Bhunia, Arun K.; Robinson, J. Paul

2006-10-01

Bacterial contamination by Listeria monocytogenes puts the public at risk and is also costly for the food-processing industry. Traditional methods for pathogen identification require complicated sample preparation for reliable results. Previously, we have reported development of a noninvasive optical forward-scattering system for rapid identification of Listeria colonies grown on solid surfaces. The presented system included application of computer-vision and patternrecognition techniques to classify scatter pattern formed by bacterial colonies irradiated with laser light. This report shows an extension of the proposed method. A new scatterometer equipped with a high-resolution CCD chip and application of two additional sets of image features for classification allow for higher accuracy and lower error rates. Features based on Zernike moments are supplemented by Tchebichef moments, and Haralick texture descriptors in the new version of the algorithm. Fisher's criterion has been used for feature selection to decrease the training time of machine learning systems. An algorithm based on support vector machines was used for classification of patterns. Low error rates determined by cross-validation, reproducibility of the measurements, and robustness of the system prove that the proposed technology can be implemented in automated devices for detection and classification of pathogenic bacteria.

High-Throughput Block Optical DNA Sequence Identification.

PubMed

Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

2018-01-01

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multimodal biometric digital watermarking on immigrant visas for homeland security

NASA Astrophysics Data System (ADS)

Sasi, Sreela; Tamhane, Kirti C.; Rajappa, Mahesh B.

2004-08-01

Passengers with immigrant Visa's are a major concern to the International Airports due to the various fraud operations identified. To curb tampering of genuine Visa, the Visa's should contain human identification information. Biometric characteristic is a common and reliable way to authenticate the identity of an individual [1]. A Multimodal Biometric Human Identification System (MBHIS) that integrates iris code, DNA fingerprint, and the passport number on the Visa photograph using digital watermarking scheme is presented. Digital Watermarking technique is well suited for any system requiring high security [2]. Ophthalmologists [3], [4], [5] suggested that iris scan is an accurate and nonintrusive optical fingerprint. DNA sequence can be used as a genetic barcode [6], [7]. While issuing Visa at the US consulates, the DNA sequence isolated from saliva, the iris code and passport number shall be digitally watermarked in the Visa photograph. This information is also recorded in the 'immigrant database'. A 'forward watermarking phase' combines a 2-D DWT transformed digital photograph with the personal identification information. A 'detection phase' extracts the watermarked information from this VISA photograph at the port of entry, from which iris code can be used for identification and DNA biometric for authentication, if an anomaly arises.

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.

Identification of an internal combustion engine model by nonlinear multi-input multi-output system identification. Ph.D. Thesis

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

Luh, G.C.

1994-01-01

This thesis presents the application of advanced modeling techniques to construct nonlinear forward and inverse models of internal combustion engines for the detection and isolation of incipient faults. The NARMAX (Nonlinear Auto-Regressive Moving Average modeling with eXogenous inputs) technique of system identification proposed by Leontaritis and Billings was used to derive the nonlinear model of a internal combustion engine, over operating conditions corresponding to the I/M240 cycle. The I/M240 cycle is a standard proposed by the United States Environmental Protection Agency to measure tailpipe emissions in inspection and maintenance programs and consists of a driving schedule developed for the purposemore » of testing compliance with federal vehicle emission standards for carbon monoxide, unburned hydrocarbons, and nitrogen oxides. The experimental work for model identification and validation was performed on a 3.0 liter V6 engine installed in an engine test cell at the Center for Automotive Research at The Ohio State University. In this thesis, different types of model structures were proposed to obtain multi-input multi-output (MIMO) nonlinear NARX models. A modification of the algorithm proposed by He and Asada was used to estimate the robust orders of the derived MIMO nonlinear models. A methodology for the analysis of inverse NARX model was developed. Two methods were proposed to derive the inverse NARX model: (1) inversion from the forward NARX model; and (2) direct identification of inverse model from the output-input data set. In this thesis, invertibility, minimum-phase characteristic of zero dynamics, and stability analysis of NARX forward model are also discussed. Stability in the sense of Lyapunov is also investigated to check the stability of the identified forward and inverse models. This application of inverse problem leads to the estimation of unknown inputs and to actuator fault diagnosis.« less

New capability for hazardous materials ID within sealed containers using a portable spatially offset Raman spectroscopy (SORS) device

NASA Astrophysics Data System (ADS)

Stokes, Robert J.; Bailey, Mike; Bonthron, Stuart; Stone, Thomas; Maskall, Guy; Presly, Oliver; Roy, Eric; Tombling, Craig; Loeffen, Paul W.

2016-10-01

Raman spectroscopy allows the acquisition of molecularly specific signatures of pure compounds and mixtures making it a popular method for material identification applications. In hazardous materials, security and counter terrorism applications, conventional handheld Raman systems are typically limited to operation by line-of-sight or through relatively transparent plastic bags / clear glass vials. If materials are concealed behind thicker, coloured or opaque barriers it can be necessary to open and take a sample. Spatially Offset Raman Spectroscopy (SORS)[1] is a novel variant of Raman spectroscopy whereby multiple measurements at differing positions are used to separate the spectrum arising from the sub layers of a sample from the spectrum at the surface. For the first time, a handheld system based on SORS has been developed and applied to hazardous materials identification. The system - "Resolve" - enables new capabilities in the rapid identification of materials concealed by a wide variety of non-metallic sealed containers such as; coloured and opaque plastics, paper, card, sacks, fabric and glass. The range of potential target materials includes toxic industrial chemicals, explosives, narcotics, chemical warfare agents and biological materials. Resolve has the potential to improve the safety, efficiency and critical decision making in incident management, search operations, policing and ports and border operations. The operator is able to obtain a positive identification of a potentially hazardous material without opening or disturbing the container - to gain access to take a sample - thus improving safety. The technique is fast and simple thus suit and breathing gear time is used more efficiently. SORS also allows Raman to be deployed at an earlier stage in an event before more intrusive techniques are used. Evidential information is preserved and the chain of custody protected. Examples of detection capability for a number of materials and barrier types are presented below.

Inverse analysis of aerodynamic loads from strain information using structural models and neural networks

NASA Astrophysics Data System (ADS)

Wada, Daichi; Sugimoto, Yohei

2017-04-01

Aerodynamic loads on aircraft wings are one of the key parameters to be monitored for reliable and effective aircraft operations and management. Flight data of the aerodynamic loads would be used onboard to control the aircraft and accumulated data would be used for the condition-based maintenance and the feedback for the fatigue and critical load modeling. The effective sensing techniques such as fiber optic distributed sensing have been developed and demonstrated promising capability of monitoring structural responses, i.e., strains on the surface of the aircraft wings. By using the developed techniques, load identification methods for structural health monitoring are expected to be established. The typical inverse analysis for load identification using strains calculates the loads in a discrete form of concentrated forces, however, the distributed form of the loads is essential for the accurate and reliable estimation of the critical stress at structural parts. In this study, we demonstrate an inverse analysis to identify the distributed loads from measured strain information. The introduced inverse analysis technique calculates aerodynamic loads not in a discrete but in a distributed manner based on a finite element model. In order to verify the technique through numerical simulations, we apply static aerodynamic loads on a flat panel model, and conduct the inverse identification of the load distributions. We take two approaches to build the inverse system between loads and strains. The first one uses structural models and the second one uses neural networks. We compare the performance of the two approaches, and discuss the effect of the amount of the strain sensing information.

Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis.

PubMed

Cohen, Mitchell J; Grossman, Adam D; Morabito, Diane; Knudson, M Margaret; Butte, Atul J; Manley, Geoffrey T

2010-01-01

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Characterization of Model-Based Reasoning Strategies for Use in IVHM Architectures

NASA Technical Reports Server (NTRS)

Poll, Scott; Iverson, David; Patterson-Hine, Ann

2003-01-01

Open architectures are gaining popularity for Integrated Vehicle Health Management (IVHM) applications due to the diversity of subsystem health monitoring strategies in use and the need to integrate a variety of techniques at the system health management level. The basic concept of an open architecture suggests that whatever monitoring or reasoning strategy a subsystem wishes to deploy, the system architecture will support the needs of that subsystem and will be capable of transmitting subsystem health status across subsystem boundaries and up to the system level for system-wide fault identification and diagnosis. There is a need to understand the capabilities of various reasoning engines and how they, coupled with intelligent monitoring techniques, can support fault detection and system level fault management. Researchers in IVHM at NASA Ames Research Center are supporting the development of an IVHM system for liquefying-fuel hybrid rockets. In the initial stage of this project, a few readily available reasoning engines were studied to assess candidate technologies for application in next generation launch systems. Three tools representing the spectrum of model-based reasoning approaches, from a quantitative simulation based approach to a graph-based fault propagation technique, were applied to model the behavior of the Hybrid Combustion Facility testbed at Ames. This paper summarizes the characterization of the modeling process for each of the techniques.

A new Information publishing system Based on Internet of things

NASA Astrophysics Data System (ADS)

Zhu, Li; Ma, Guoguang

2018-03-01

A new information publishing system based on Internet of things is proposed, which is composed of four level hierarchical structure, including the screen identification layer, the network transport layer, the service management layer and the publishing application layer. In the architecture, the screen identification layer has realized the internet of screens in which geographically dispersed independent screens are connected to the internet by the customized set-top boxes. The service management layer uses MQTT protocol to implement a lightweight broker-based publish/subscribe messaging mechanism in constrained environments such as internet of things to solve the bandwidth bottleneck. Meanwhile the cloud-based storage technique is used to storage and manage the promptly increasing multimedia publishing information. The paper has designed and realized a prototype SzIoScreen, and give some related test results.

Category identification of changed land-use polygons in an integrated image processing/geographic information system

NASA Technical Reports Server (NTRS)

Westmoreland, Sally; Stow, Douglas A.

1992-01-01

A framework is proposed for analyzing ancillary data and developing procedures for incorporating ancillary data to aid interactive identification of land-use categories in land-use updates. The procedures were developed for use within an integrated image processsing/geographic information systems (GIS) that permits simultaneous display of digital image data with the vector land-use data to be updated. With such systems and procedures, automated techniques are integrated with visual-based manual interpretation to exploit the capabilities of both. The procedural framework developed was applied as part of a case study to update a portion of the land-use layer in a regional scale GIS. About 75 percent of the area in the study site that experienced a change in land use was correctly labeled into 19 categories using the combination of automated and visual interpretation procedures developed in the study.

Analyses of amphibole asbestiform fibers in municipal water supplies

PubMed Central

Nicholson, William J.

1974-01-01

Details are given of the techniques used in the analysis of asbestiform fibers in the water systems of Duluth, Minnesota and other cities. Photographic electron diffraction and electron microprobe analyses indicated that the concentration of verified amphibole mineral fibers ranged from 20 × 106 to 75 × 106 fibers/l. Approximately 50–60% of the fibers were in the cummingtonite-grunerite series and 20% were in the actinolite-tremolite series. About 5% were chemically identical with amosite. A wide variety of analytical techniques must be employed for unique identification of the mineral species present in water systems. ImagesFIGURE 1.FIGURE 2.FIGURE 3.FIGURE 4.FIGURE 5.FIGURE 6. PMID:4470931

Applications of multiple-constraint matrix updates to the optimal control of large structures

NASA Technical Reports Server (NTRS)

Smith, S. W.; Walcott, B. L.

1992-01-01

Low-authority control or vibration suppression in large, flexible space structures can be formulated as a linear feedback control problem requiring computation of displacement and velocity feedback gain matrices. To ensure stability in the uncontrolled modes, these gain matrices must be symmetric and positive definite. In this paper, efficient computation of symmetric, positive-definite feedback gain matrices is accomplished through the use of multiple-constraint matrix update techniques originally developed for structural identification applications. Two systems were used to illustrate the application: a simple spring-mass system and a planar truss. From these demonstrations, use of this multiple-constraint technique is seen to provide a straightforward approach for computing the low-authority gains.

Bringing Bertillon Back: The Preservation and Research Application of Bertillon Materials in Museums, Archives, and Historical Societies

ERIC Educational Resources Information Center

Gridack, Paige

2009-01-01

Bertillon cards are underutilized resources, often regarded as the remnants of an antiquated nineteenth century police identification system. Through the application of computer search techniques, data manipulation, and outreach, not only can institutions provide their patrons access to this unique information, these collections can in turn help…

Bat wing biometrics: using collagen–elastin bundles in bat wings as a unique individual identifier

Treesearch

Sybill K. Amelon; Sarah E. Hooper; Kathryn M. Womack

2017-01-01

The ability to recognize individuals within an animal population is fundamental to conservation and management. Identification of individual bats has relied on artificial marking techniques that may negatively affect the survival and alter the behavior of individuals. Biometric systems use biological characteristics to identify individuals. The field of animal...

Driving profile modeling and recognition based on soft computing approach.

PubMed

Wahab, Abdul; Quek, Chai; Tan, Chin Keong; Takeda, Kazuya

2009-04-01

Advancements in biometrics-based authentication have led to its increasing prominence and are being incorporated into everyday tasks. Existing vehicle security systems rely only on alarms or smart card as forms of protection. A biometric driver recognition system utilizing driving behaviors is a highly novel and personalized approach and could be incorporated into existing vehicle security system to form a multimodal identification system and offer a greater degree of multilevel protection. In this paper, detailed studies have been conducted to model individual driving behavior in order to identify features that may be efficiently and effectively used to profile each driver. Feature extraction techniques based on Gaussian mixture models (GMMs) are proposed and implemented. Features extracted from the accelerator and brake pedal pressure were then used as inputs to a fuzzy neural network (FNN) system to ascertain the identity of the driver. Two fuzzy neural networks, namely, the evolving fuzzy neural network (EFuNN) and the adaptive network-based fuzzy inference system (ANFIS), are used to demonstrate the viability of the two proposed feature extraction techniques. The performances were compared against an artificial neural network (NN) implementation using the multilayer perceptron (MLP) network and a statistical method based on the GMM. Extensive testing was conducted and the results show great potential in the use of the FNN for real-time driver identification and verification. In addition, the profiling of driver behaviors has numerous other potential applications for use by law enforcement and companies dealing with buses and truck drivers.

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library.

PubMed

Lachaud, Laurence; Fernández-Arévalo, Anna; Normand, Anne-Cécile; Lami, Patrick; Nabet, Cécile; Donnadieu, Jean Luc; Piarroux, Martine; Djenad, Farid; Cassagne, Carole; Ravel, Christophe; Tebar, Silvia; Llovet, Teresa; Blanchet, Denis; Demar, Magalie; Harrat, Zoubir; Aoun, Karim; Bastien, Patrick; Muñoz, Carmen; Gállego, Montserrat; Piarroux, Renaud

2017-10-01

Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-based application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani , L. guyanensis , and L. braziliensis complexes was observed, as previously reported for other techniques. The tested application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers. Copyright © 2017 American Society for Microbiology.

INcreasing Security and Protection through Infrastructure REsilience: The INSPIRE Project

NASA Astrophysics Data System (ADS)

D'Antonio, Salvatore; Romano, Luigi; Khelil, Abdelmajid; Suri, Neeraj

The INSPIRE project aims at enhancing the European potential in the field of security by ensuring the protection of critical information infrastructures through (a) the identification of their vulnerabilities and (b) the development of innovative techniques for securing networked process control systems. To increase the resilience of such systems INSPIRE will develop traffic engineering algorithms, diagnostic processes and self-reconfigurable architectures along with recovery techniques. Hence, the core idea of the INSPIRE project is to protect critical information infrastructures by appropriately configuring, managing, and securing the communication network which interconnects the distributed control systems. A working prototype will be implemented as a final demonstrator of selected scenarios. Controls/Communication Experts will support project partners in the validation and demonstration activities. INSPIRE will also contribute to standardization process in order to foster multi-operator interoperability and coordinated strategies for securing lifeline systems.

Development and Optimization of a Fluorescent Differential Display PCR System for Analyzing the Stress Response in Lactobacillus sakei Strains

PubMed Central

Bonomo, Maria Grazia; Sico, Maria Anna; Grieco, Simona; Salzano, Giovanni

2009-01-01

Lactobacillus sakei is widely used as starter in the production process of Italian fermented sausages and its growth and survival are affected by various factors. We studied the differential expression of genome in response to different stresses by the fluorescent differential display (FDD) technique. This study resulted in the development and optimization of an innovative technique, with a high level of reproducibility and quality, which allows the identification of gene expression changes associated with different microbial behaviours under different growth conditions. PMID:22253979

Apollo experience report: Flight anomaly resolution

NASA Technical Reports Server (NTRS)

Lobb, J. D.

1975-01-01

The identification of flight anomalies, the determination of their causes, and the approaches taken for corrective action are described. Interrelationships of the broad range of disciplines involved with the complex systems and the team concept employed to ensure timely and accurate resolution of anomalies are discussed. The documentation techniques and the techniques for management of anomaly resolution are included. Examples of specific anomalies are presented in the original form of their progressive documentation. Flight anomaly resolution functioned as a part of the real-time mission support and postflight testing, and results were included in the postflight documentation.

A review of approaches to identifying patient phenotype cohorts using electronic health records

PubMed Central

Shivade, Chaitanya; Raghavan, Preethi; Fosler-Lussier, Eric; Embi, Peter J; Elhadad, Noemie; Johnson, Stephen B; Lai, Albert M

2014-01-01

Objective To summarize literature describing approaches aimed at automatically identifying patients with a common phenotype. Materials and methods We performed a review of studies describing systems or reporting techniques developed for identifying cohorts of patients with specific phenotypes. Every full text article published in (1) Journal of American Medical Informatics Association, (2) Journal of Biomedical Informatics, (3) Proceedings of the Annual American Medical Informatics Association Symposium, and (4) Proceedings of Clinical Research Informatics Conference within the past 3 years was assessed for inclusion in the review. Only articles using automated techniques were included. Results Ninety-seven articles met our inclusion criteria. Forty-six used natural language processing (NLP)-based techniques, 24 described rule-based systems, 41 used statistical analyses, data mining, or machine learning techniques, while 22 described hybrid systems. Nine articles described the architecture of large-scale systems developed for determining cohort eligibility of patients. Discussion We observe that there is a rise in the number of studies associated with cohort identification using electronic medical records. Statistical analyses or machine learning, followed by NLP techniques, are gaining popularity over the years in comparison with rule-based systems. Conclusions There are a variety of approaches for classifying patients into a particular phenotype. Different techniques and data sources are used, and good performance is reported on datasets at respective institutions. However, no system makes comprehensive use of electronic medical records addressing all of their known weaknesses. PMID:24201027

Cloud-based adaptive exon prediction for DNA analysis

PubMed Central

Putluri, Srinivasareddy; Fathima, Shaik Yasmeen

2018-01-01

Cloud computing offers significant research and economic benefits to healthcare organisations. Cloud services provide a safe place for storing and managing large amounts of such sensitive data. Under conventional flow of gene information, gene sequence laboratories send out raw and inferred information via Internet to several sequence libraries. DNA sequencing storage costs will be minimised by use of cloud service. In this study, the authors put forward a novel genomic informatics system using Amazon Cloud Services, where genomic sequence information is stored and accessed for processing. True identification of exon regions in a DNA sequence is a key task in bioinformatics, which helps in disease identification and design drugs. Three base periodicity property of exons forms the basis of all exon identification techniques. Adaptive signal processing techniques found to be promising in comparison with several other methods. Several adaptive exon predictors (AEPs) are developed using variable normalised least mean square and its maximum normalised variants to reduce computational complexity. Finally, performance evaluation of various AEPs is done based on measures such as sensitivity, specificity and precision using various standard genomic datasets taken from National Center for Biotechnology Information genomic sequence database. PMID:29515813

Damage detection and quantification in a structural model under seismic excitation using time-frequency analysis

NASA Astrophysics Data System (ADS)

Chan, Chun-Kai; Loh, Chin-Hsiung; Wu, Tzu-Hsiu

2015-04-01

In civil engineering, health monitoring and damage detection are typically carry out by using a large amount of sensors. Typically, most methods require global measurements to extract the properties of the structure. However, some sensors, like LVDT, cannot be used due to in situ limitation so that the global deformation remains unknown. An experiment is used to demonstrate the proposed algorithms: a one-story 2-bay reinforce concrete frame under weak and strong seismic excitation. In this paper signal processing techniques and nonlinear identification are used and applied to the response measurements of seismic response of reinforced concrete structures subject to different level of earthquake excitations. Both modal-based and signal-based system identification and feature extraction techniques are used to study the nonlinear inelastic response of RC frame using both input and output response data or output only measurement. From the signal-based damage identification method, which include the enhancement of time-frequency analysis of acceleration responses and the estimation of permanent deformation using directly from acceleration response data. Finally, local deformation measurement from dense optical tractor is also use to quantify the damage of the RC frame structure.

Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers

PubMed Central

Shattuck-Hufnagel, S.; Choi, J. Y.; Moro-Velázquez, L.; Gómez-García, J. A.

2017-01-01

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting. PMID:29240814

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

A comparison of machine learning techniques for detection of drug target articles.

PubMed

Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

2010-12-01

Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

High-accuracy user identification using EEG biometrics.

PubMed

Koike-Akino, Toshiaki; Mahajan, Ruhi; Marks, Tim K; Ye Wang; Watanabe, Shinji; Tuzel, Oncel; Orlik, Philip

2016-08-01

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.

Parameterized Linear Longitudinal Airship Model

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph

2010-01-01

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

Knowledge-based machine vision systems for space station automation

NASA Technical Reports Server (NTRS)

Ranganath, Heggere S.; Chipman, Laure J.

1989-01-01

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

High-Throughput Identification of Bacteria and Yeast by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry in Conventional Medical Microbiology Laboratories ▿

PubMed Central

van Veen, S. Q.; Claas, E. C. J.; Kuijper, Ed J.

2010-01-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is suitable for high-throughput and rapid diagnostics at low costs and can be considered an alternative for conventional biochemical and molecular identification systems in a conventional microbiological laboratory. First, we evaluated MALDI-TOF MS using 327 clinical isolates previously cultured from patient materials and identified by conventional techniques (Vitek-II, API, and biochemical tests). Discrepancies were analyzed by molecular analysis of the 16S genes. Of 327 isolates, 95.1% were identified correctly to genus level, and 85.6% were identified to species level by MALDI-TOF MS. Second, we performed a prospective validation study, including 980 clinical isolates of bacteria and yeasts. Overall performance of MALDI-TOF MS was significantly better than conventional biochemical systems for correct species identification (92.2% and 83.1%, respectively) and produced fewer incorrect genus identifications (0.1% and 1.6%, respectively). Correct species identification by MALDI-TOF MS was observed in 97.7% of Enterobacteriaceae, 92% of nonfermentative Gram-negative bacteria, 94.3% of staphylococci, 84.8% of streptococci, 84% of a miscellaneous group (mainly Haemophilus, Actinobacillus, Cardiobacterium, Eikenella, and Kingella [HACEK]), and 85.2% of yeasts. MALDI-TOF MS had significantly better performance than conventional methods for species identification of staphylococci and genus identification of bacteria belonging to HACEK group. Misidentifications by MALDI-TOF MS were clearly associated with an absence of sufficient spectra from suitable reference strains in the MALDI-TOF MS database. We conclude that MALDI-TOF MS can be implemented easily for routine identification of bacteria (except for pneumococci and viridans streptococci) and yeasts in a medical microbiological laboratory. PMID:20053859

High-throughput identification of bacteria and yeast by matrix-assisted laser desorption ionization-time of flight mass spectrometry in conventional medical microbiology laboratories.

PubMed

van Veen, S Q; Claas, E C J; Kuijper, Ed J

2010-03-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is suitable for high-throughput and rapid diagnostics at low costs and can be considered an alternative for conventional biochemical and molecular identification systems in a conventional microbiological laboratory. First, we evaluated MALDI-TOF MS using 327 clinical isolates previously cultured from patient materials and identified by conventional techniques (Vitek-II, API, and biochemical tests). Discrepancies were analyzed by molecular analysis of the 16S genes. Of 327 isolates, 95.1% were identified correctly to genus level, and 85.6% were identified to species level by MALDI-TOF MS. Second, we performed a prospective validation study, including 980 clinical isolates of bacteria and yeasts. Overall performance of MALDI-TOF MS was significantly better than conventional biochemical systems for correct species identification (92.2% and 83.1%, respectively) and produced fewer incorrect genus identifications (0.1% and 1.6%, respectively). Correct species identification by MALDI-TOF MS was observed in 97.7% of Enterobacteriaceae, 92% of nonfermentative Gram-negative bacteria, 94.3% of staphylococci, 84.8% of streptococci, 84% of a miscellaneous group (mainly Haemophilus, Actinobacillus, Cardiobacterium, Eikenella, and Kingella [HACEK]), and 85.2% of yeasts. MALDI-TOF MS had significantly better performance than conventional methods for species identification of staphylococci and genus identification of bacteria belonging to HACEK group. Misidentifications by MALDI-TOF MS were clearly associated with an absence of sufficient spectra from suitable reference strains in the MALDI-TOF MS database. We conclude that MALDI-TOF MS can be implemented easily for routine identification of bacteria (except for pneumococci and viridans streptococci) and yeasts in a medical microbiological laboratory.

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.

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

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. Parameter and state estimation

NASA Astrophysics Data System (ADS)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-09-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online parameter identification technique based on a weighted recursive least quadratic squares parameter estimator to determine the parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.

Estimating Ocean Currents from Automatic Identification System Based Ship Drift Measurements

NASA Astrophysics Data System (ADS)

Jakub, Thomas D.

Ship drift is a technique that has been used over the last century and a half to estimate ocean currents. Several of the shortcomings of the ship drift technique include obtaining the data from multiple ships, the time delay in getting those ship positions to a data center for processing and the limited resolution based on the amount of time between position measurements. These shortcomings can be overcome through the use of the Automatic Identification System (AIS). AIS enables more precise ocean current estimates, the option of finer resolution and more timely estimates. In this work, a demonstration of the use of AIS to compute ocean currents is performed. A corresponding error and sensitivity analysis is performed to help identify under which conditions errors will be smaller. A case study in San Francisco Bay with constant AIS message updates was compared against high frequency radar and demonstrated ocean current magnitude residuals of 19 cm/s for ship tracks in a high signal to noise environment. These ship tracks were only minutes long compared to the normally 12 to 24 hour ship tracks. The Gulf of Mexico case study demonstrated the ability to estimate ocean currents over longer baselines and identified the dependency of the estimates on the accuracy of time measurements. Ultimately, AIS measurements when combined with ship drift can provide another method of estimating ocean currents, particularly when other measurements techniques are not available.

Thermal Skin fabrication technology

NASA Technical Reports Server (NTRS)

Milam, T. B.

1972-01-01

Advanced fabrication techniques applicable to Thermal Skin structures were investigated, including: (1) chemical machining; (2) braze bonding; (3) diffusion bonding; and (4) electron beam welding. Materials investigated were nickel and nickel alloys. Sample Thermal Skin panels were manufactured using the advanced fabrication techniques studied and were structurally tested. Results of the program included: (1) development of improved chemical machining processes for nickel and several nickel alloys; (2) identification of design geometry limits; (3) identification of diffusion bonding requirements; (4) development of a unique diffusion bonding tool; (5) identification of electron beam welding limits; and (6) identification of structural properties of Thermal Skin material.

Evaluation of species-specific PCR, Bruker MS, VITEK MS and the VITEK 2 system for the identification of clinical Enterococcus isolates.

PubMed

Fang, H; Ohlsson, A-K; Ullberg, M; Ozenci, V

2012-11-01

The purpose of this investigation was to compare the performance of species-specific polymerase chain reaction (PCR), matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and phenotypic identification systems for the identification of Enterococcus species. A total of 132 clinical isolates were investigated by the following: (1) a multiplex real-time PCR assay targeting ddl Enterococcus faecium, ddl Enterococcus faecalis, vanC1 and vanC2/C3 genes, and a high-resolution melting (HRM) analysis of the groESL gene for the differentiation of Enterococcus casseliflavus and Enterococcus gallinarum; (2) Bruker MS; (3) VITEK MS; and (4) the VITEK 2 system. 16S rRNA gene sequencing was used as a reference method in the study. The 132 isolates were identified as 32 E. faecalis, 63 E. faecium, 16 E. casseliflavus and 21 E. gallinarum. The multiplex PCR, Bruker MS and VITEK MS were able to identify all the isolates correctly at the species level. The VITEK 2 system could identify 131/132 (99.2 %) and 121/132 (91.7 %) of the isolates at the genus and species levels, respectively. The HRM-groESL assay identified all (21/21) E. gallinarum isolates and 81.3 % (13/16) of the E. casseliflavus isolates. The PCR methods described in the present study are effective in identifying the enterococcal species. MALDI-TOF MS is a rapid, reliable and cost-effective identification technique for enterococci. The VITEK 2 system is less efficient at detecting non-faecalis and non-faecium Enterococcus species.

Identification of Aeromonas isolates by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.

PubMed

Lamy, Brigitte; Kodjo, Angeli; Laurent, Frédéric

2011-09-01

We evaluated the accuracy of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry for identifying aeromonads with an extraction procedure. Genus-level accuracy was 100%. Compared to rpoB gene sequencing, species-level accuracy was 90.6% (29/32) for type and reference strains and 91.4% for a collection of 139 clinical and environmental isolates, making this system one of the most accurate and rapid methods for phenotypic identification. The reliability of this technique was very promising, although some improvements in database composition, taxonomy, and discriminatory power are needed. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Three-dimensional gauge theories and gravitational instantons from string theory

NASA Astrophysics Data System (ADS)

Cherkis, Sergey Alexander

Various realizations of gauge theories in string theory allow an identification of their spaces of vacua with gravitational instantons. Also, they provide a correspondence of vacua of gauge theories with nonabelian monopole configurations and solutions of a system of integrable equations called Nahm equations. These identifications make it possible to apply powerful techniques of differential and algebraic geometry to solve the gauge theories in question. In other words, it becomes possible to find the exact metrics on their moduli spaces of vacua with all quantum corrections included. As another outcome we obtain for the first time the description of a series of all Dk-type gravitational instantons.

Road sign recognition using Viapix module and correlation

NASA Astrophysics Data System (ADS)

Ouerhani, Y.; Desthieux, M.; Alfalou, A.

2015-03-01

In this paper, we propose and validate a new system used to explore road assets. In this work we are interested on the vertical road signs. To do this, we are based on the combination of road signs detection, recognition and identification using data provides by sensors. The proposed approach consists on using panoramic views provided by the innovative device, VIAPIX®1, developed by our company ACTRIS2. We are based also on the optimized correlation technique for road signs recognition and identification on pictures. Obtained results shows the interest on using panoramic views compared to results obtained using images provided using only one camera.

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).

Oral mark in the application of an individual identification: From ashes to truth.

PubMed

Chugh, Anshul; Narwal, Anumeha

2017-01-01

Forensic odontology is the branch of dentistry which deals with the proper handling, examination, evaluation and presentation of dental findings in the interest of justice. After major disasters and perimortem assaults such as earthquakes, fires, severe head and neck trauma or gross decomposition, accurate and early identification of dead and injured becomes important. In the absence of other records in such cases, identification is based on restorations, missing teeth and prosthetic devices such as partial and complete removable/fixed prosthesis or implant retained devices. This brings out the major role of prosthodontics to investigate the identity of suspects in the criminal cases as well as the deceased human beings in traumatic injuries or in disasters. Denture identification systems are being used as means of postmortem identification of edentulous persons which has evolved from the inclusion of some form of printed label in a denture to more high-tech methods. The provision of implant retained complete lower denture, antemortem, and postmortem radiographs of edentulous persons and correlation of bite marks using special impression techniques provide another potential source of evidence for human identification. Hence, this literature review throws some light on the role played by prosthodontist in forensic odontology.

MALDI-TOF MS identification of anaerobic bacteria: assessment of pre-analytical variables and specimen preparation techniques.

PubMed

Hsu, Yen-Michael S; Burnham, Carey-Ann D

2014-06-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a tool for identifying clinically relevant anaerobes. We evaluated the analytical performance characteristics of the Bruker Microflex with Biotyper 3.0 software system for identification of anaerobes and examined the impact of direct formic acid (FA) treatment and other pre-analytical factors on MALDI-TOF MS performance. A collection of 101 anaerobic bacteria were evaluated, including Clostridium spp., Propionibacterium spp., Fusobacterium spp., Bacteroides spp., and other anaerobic bacterial of clinical relevance. The results of our study indicate that an on-target extraction with 100% FA improves the rate of accurate identification without introducing misidentification (P<0.05). In addition, we modify the reporting cutoffs for the Biotyper "score" yielding acceptable identification. We found that a score of ≥1.700 can maximize the rate of identification. Of interest, MALDI-TOF MS can correctly identify anaerobes grown in suboptimal conditions, such as on selective culture media and following oxygen exposure. In conclusion, we report on a number of simple and cost-effective pre- and post-analytical modifications could enhance MALDI-TOF MS identification for anaerobic bacteria. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of unique repeated patterns, location of mutation in DNA finger printing using artificial intelligence technique.

PubMed

Mukunthan, B; Nagaveni, N

2014-01-01

In genetic engineering, conventional techniques and algorithms employed by forensic scientists to assist in identification of individuals on the basis of their respective DNA profiles involves more complex computational steps and mathematical formulae, also the identification of location of mutation in a genomic sequence in laboratories is still an exigent task. This novel approach provides ability to solve the problems that do not have an algorithmic solution and the available solutions are also too complex to be found. The perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

Techniques for air pollution source identification are reviewed, and some results obtained with them are evaluated. Described techniques include remote sensing from satellites and aircraft, on-site monitoring, and the use of injected tracers and pollutants themselves as tracers. The use of a large number of trace elements in ambient airborne particulate matter as a practical means of identifying sources is discussed in detail. Sampling and analysis techniques are described, and it is shown that elemental constituents can be related to specific source types such as those found in the earth's crust and those associated with specific industries. Source identification sytems are noted which utilize charged particle X-ray fluorescence analysis of original field data.

Magnetic bead based immuno-detection of Listeria monocytogenes and Listeria ivanovii from infant formula and leafy green vegetables using the Bio-Plex suspension array system.

PubMed

Day, J B; Basavanna, U

2015-04-01

Listeriosis, a disease contracted via the consumption of foods contaminated with pathogenic Listeria species, can produce severe symptoms and high mortality in susceptible people and animals. The development of molecular methods and immuno-based techniques for detection of pathogenic Listeria in foods has been challenging due to the presence of assay inhibiting food components. In this study, we utilize a macrophage cell culture system for the isolation and enrichment of Listeria monocytogenes and Listeria ivanovii from infant formula and leafy green vegetables for subsequent identification using the Luminex xMAP technique. Macrophage monolayers were exposed to infant formula, lettuce and celery contaminated with L. monocytogenes or L. ivanovii. Magnetic microspheres conjugated to Listeria specific antibody were used to capture Listeria from infected macrophages and then analyzed using the Bio-Plex 200 analyzer. As few as 10 CFU/mL or g of L. monocytogenes was detected in all foods tested. The detection limit for L. ivanovii was 10 CFU/mL in infant formula and 100 CFU/g in leafy greens. Microsphere bound Listeria obtained from infected macrophage lysates could also be isolated on selective media for subsequent confirmatory identification. This method presumptively identifies L. monocytogenes and L. ivanovii from infant formula, lettuce and celery in less than 28 h with confirmatory identifications completed in less than 48 h. Published by Elsevier Ltd.

In vivo microcirculation imaging of the sub surface fingertip using correlation mapping optical coherence tomography (cmOCT)

NASA Astrophysics Data System (ADS)

Dsouza, Roshan I.; Zam, Azhar; Subhash, Hrebesh M.; Larin, Kirill V.; Leahy, Martin

2013-02-01

We describe a novel application of correlation mapping optical coherence tomography (cmOCT) for sub-surface fingerprint biometric identification. Fingerprint biometrics including automated fingerprint identification systems, are commonly used to recognise the fingerprint, since they constitute simple, effective and valuable physical evidence. Spoofing of biometric fingerprint devices can be easily done because of the limited information obtained from the surface topography. In order to overcome this limitation a potentially more secure source of information is required for biometric identification applications. In this study, we retrieve the microcirculation map of the subsurface fingertip by use of the cmOCT technique. To increase probing depth of the sub surface microcirculation, an optical clearing agent composed of 75% glycerol in aqueous solution was applied topically and kept in contact for 15 min. OCT intensity images were acquired from commercial research grade swept source OCT system (model OCT1300SS, Thorlabs Inc. USA). A 3D OCT scan of the fingertip was acquired over an area of 5x5 mm using 1024x1024 A-scans in approximately 70 s. The resulting volume was then processed using the cmOCT technique with a 7x7 kernel to provide a microcirculation map. We believe these results will demonstrate an enhanced security level over artificial fingertips. To the best of our knowledge, this is the first demonstration of imaging microcirculation map of the subsurface fingertip.

[Different wavelengths selection methods for identification of early blight on tomato leaves by using hyperspectral imaging technique].

PubMed

Cheng, Shu-Xi; Xie, Chuan-Qi; Wang, Qiao-Nan; He, Yong; Shao, Yong-Ni

2014-05-01

Identification of early blight on tomato leaves by using hyperspectral imaging technique based on different effective wavelengths selection methods (successive projections algorithm, SPA; x-loading weights, x-LW; gram-schmidt orthogonaliza-tion, GSO) was studied in the present paper. Hyperspectral images of seventy healthy and seventy infected tomato leaves were obtained by hyperspectral imaging system across the wavelength range of 380-1023 nm. Reflectance of all pixels in region of interest (ROI) was extracted by ENVI 4. 7 software. Least squares-support vector machine (LS-SVM) model was established based on the full spectral wavelengths. It obtained an excellent result with the highest identification accuracy (100%) in both calibration and prediction sets. Then, EW-LS-SVM and EW-LDA models were established based on the selected wavelengths suggested by SPA, x-LW and GSO, respectively. The results showed that all of the EW-LS-SVM and EW-LDA models performed well with the identification accuracy of 100% in EW-LS-SVM model and 100%, 100% and 97. 83% in EW-LDA model, respectively. Moreover, the number of input wavelengths of SPA-LS-SVM, x-LW-LS-SVM and GSO-LS-SVM models were four (492, 550, 633 and 680 nm), three (631, 719 and 747 nm) and two (533 and 657 nm), respectively. Fewer input variables were beneficial for the development of identification instrument. It demonstrated that it is feasible to identify early blight on tomato leaves by using hyperspectral imaging, and SPA, x-LW and GSO were effective wavelengths selection methods.

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.

HLRW management during MR reactor decommissioning in NRC 'Kurchatov Institute'

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

Chesnokov, Alexander; Ivanov, Oleg; Kolyadin, Vyacheslav

2013-07-01

A program of decommissioning of MR research reactor in the Kurchatov institute started in 2008. The decommissioning work presumed a preliminary stage, which included: removal of spent fuel from near reactor storage; removal of spent fuel assemble of metal liquid loop channel from a core; identification, sorting and disposal of radioactive objects from gateway of the reactor; identification, sorting and disposal of radioactive objects from cells of HLRW storage of the Kurchatov institute for radwaste creating form the decommissioning of MR. All these works were performed by a remote controlled means with use of a remote identification methods of highmore » radioactive objects. A distribution of activity along high radiated objects was measured by a collimated radiometer installed on the robot Brokk-90, a gamma image of the object was registered by gamma-visor. Spectrum of gamma radiation was measured by a gamma locator and semiconductor detector system. For identification of a presence of uranium isotopes in the HLRW a technique, based on the registration of characteristic radiation of U, was developed. For fragmentation of high radiated objects was used a cold cutting technique and dust suppression system was applied for reduction of volume activity of aerosols in air. The management of HLRW was performed by remote controlled robots Brokk-180 and Brokk-330. They executed sorting, cutting and parking of high radiated part of contaminated equipment. The use of these techniques allowed to reduce individual and collective doses of personal performed the decommissioning. The average individual dose of the personnel was 1,9 mSv/year in 2011, and the collective dose is estimated by 0,0605 man x Sv/year. Use of the remote control machines enables reducing the number of working personal (20 men) and doses. X-ray spectrometric methods enable determination of a presence of the U in high radiated objects and special cans and separation of them for further spent fuel inspection. The sorting of radwaste enabled shipping of the LLRW and ILRW to special repositories and keeping of the HLRW for decay in the Kurchatov institute repository. (authors)« less

Development of an Intelligent Videogrammetric Wind Tunnel Measurement System

NASA Technical Reports Server (NTRS)

Graves, Sharon S.; Burner, Alpheus W.

2004-01-01

A videogrammetric technique developed at NASA Langley Research Center has been used at five NASA facilities at the Langley and Ames Research Centers for deformation measurements on a number of sting mounted and semispan models. These include high-speed research and transport models tested over a wide range of aerodynamic conditions including subsonic, transonic, and supersonic regimes. The technique, based on digital photogrammetry, has been used to measure model attitude, deformation, and sting bending. In addition, the technique has been used to study model injection rate effects and to calibrate and validate methods for predicting static aeroelastic deformations of wind tunnel models. An effort is currently underway to develop an intelligent videogrammetric measurement system that will be both useful and usable in large production wind tunnels while providing accurate data in a robust and timely manner. Designed to encode a higher degree of knowledge through computer vision, the system features advanced pattern recognition techniques to improve automated location and identification of targets placed on the wind tunnel model to be used for aerodynamic measurements such as attitude and deformation. This paper will describe the development and strategy of the new intelligent system that was used in a recent test at a large transonic wind tunnel.

Evaluation of Raman spectroscopy for the trace analysis of biomolecules for Mars exobiology

NASA Astrophysics Data System (ADS)

Jehlicka, Jan; Edwards, Howell G. M.; Vitek, Petr; Culka, Adam

2010-05-01

Raman spectroscopy is an ideal technique for the identification of biomolecules and minerals for astrobiological applications. Raman spectroscopic instrumentation has been shown to be potentially valuable for the in-situ detection of spectral biomarkers originating from rock samples containing remnants of terrestrial endolithic colonisation. Within the future payloads designed by ESA and NASA for several missions focussing on life detection on Mars, Raman spectroscopy has been proposed as an important non-destructive analytical tool for the in-situ identification of organic compounds relevant to life detection on planetary and moon surfaces or near sub-surfaces. Portable Raman systems equipped with 785 nm lasers permit the detection of pure organic minerals, aminoacids, carboxylic acids, as well as NH-containing compounds outdoors at -20°C and at an altitude of 3300 m. A potential limitation for the use of Raman spectroscopic techniques is the detection of very low amounts of biomolecules in rock matrices. The detection of beta-carotene and aminoacids has been achieved in the field using a portable Raman system in admixture with crystalline powders of sulphates and halite. Relatively low detection limits less than 1 % for detecting beta-carotene, aminoacids using a portable Raman system were obtained analysing traces of these compounds in crystalline powders of sulphates and halite. Laboratory systems permit the detection of these biomolecules at even lower concentrations at sub-ppm level of the order of 0.1 to 1 mg kg-1. The comparative evaluation of laboratory versus field measurements permits the identification of critical issues for future field applications and directs attention to the improvements needed in the instrumentation . A comparison between systems using different laser excitation wavelengths shows excellent results for 785 nm laser excitation . The results of this study will inform the acquisition parameters necessary for the deployment of robotic miniaturised Raman spectrosocpic instrumentation intended for the detection of spectral signatures of extant or relict life on Mars.

[Contribution of Leishmania identification using polymerase chain reaction--restriction fragment length polymerase for epidemiological studies of cutaneous leishmaniasis in Tunisia].

PubMed

Bousslimi, N; Ben Abda, I; Ben Mously, R; Siala, E; Harrat, Z; Zallagua, N; Bouratbine, A; Aoun, K

2014-02-01

Three forms of cutaneous leishmaniasis (CL) are endemic in Tunisia. The identification of the causative species is useful to complete epidemiological data and to manage the cases. The aim of this study is to assess PCR-RFLP technique in the identification of Leishmania species responsible of CL in Tunisia and to compare the results of this technique to those of isoenzyme analysis. Sixty-one CL lesions were sampled. Dermal samples were tested by culture on NNN medium and analyzed by PCR-RFLP assay targeting the ITS1 region of ribosomal DNA. Species identification was performed by both iso-enzymatic typing for positive cultures and analysis of restriction profiles after enzymatic digestion by HaeIII of the obtained amplicons. Thirty-eight (62%) samples were positive by culture. The iso-enzymatic typing of 32 isolates identified 3 L. infantum, 23 L. major MON-25 and 6 L. tropica MON-8. Sixty samples were positive by PCR. The PCR-RFLP digestion profiles of the 56 PCR products identified 12 L. infantum, 38 L. major and 6 L. tropica. The results of both techniques were concordant in the 32 strains identified by both techniques. Species identification correlated with the geographical distribution of CL forms endemic in Tunisia. Results of PCR-RFLP revealed highly concordant with those of isoenzyme electrophoresis. Thanks to its simplicity, rapidity and ability to be performed directly on biological samples, this technique appears as an interesting alternative for the identification of Leishmania strains responsible of CL in Tunisia. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

A novel universal real-time PCR system using the attached universal duplex probes for quantitative analysis of nucleic acids.

PubMed

Yang, Litao; Liang, Wanqi; Jiang, Lingxi; Li, Wenquan; Cao, Wei; Wilson, Zoe A; Zhang, Dabing

2008-06-04

Real-time PCR techniques are being widely used for nucleic acids analysis, but one limitation of current frequently employed real-time PCR is the high cost of the labeled probe for each target molecule. We describe a real-time PCR technique employing attached universal duplex probes (AUDP), which has the advantage of generating fluorescence by probe hydrolysis and strand displacement over current real-time PCR methods. AUDP involves one set of universal duplex probes in which the 5' end of the fluorescent probe (FP) and a complementary quenching probe (QP) lie in close proximity so that fluorescence can be quenched. The PCR primer pair with attached universal template (UT) and the FP are identical to the UT sequence. We have shown that the AUDP technique can be used for detecting multiple target DNA sequences in both simplex and duplex real-time PCR assays for gene expression analysis, genotype identification, and genetically modified organism (GMO) quantification with comparable sensitivity, reproducibility, and repeatability with other real-time PCR methods. The results from GMO quantification, gene expression analysis, genotype identification, and GMO quantification using AUDP real-time PCR assays indicate that the AUDP real-time PCR technique has been successfully applied in nucleic acids analysis, and the developed AUDP real-time PCR technique will offer an alternative way for nucleic acid analysis with high efficiency, reliability, and flexibility at low cost.

Systemic Infection of an Immunocompromised Patient with Methylobacterium zatmanii

PubMed Central

Hornei, B.; Lüneberg, E.; Schmidt-Rotte, H.; Maaß, M.; Weber, K.; Heits, F.; Frosch, M.; Solbach, W.

1999-01-01

We describe the identification of Methylobacterium zatmanii as the causative agent of bacteremia and fever in an immunocompromised patient. The patient, a 60-year-old man, had a 5-month history of acute myeloid leukemia and had been on chemotherapy throughout this period. Seven days after the onset of neutropenia, the patient developed fever. The combination of ciprofloxacin, co-trimoxazole, imipenem, amikacin, and vancomycin led to a complete defervescence. On subculture from six positive blood cultures, the organism grew only on buffered charcoal yeast extract agar and not on standard agars. Identification by universal PCR and subsequent sequence analysis of the amplified 16S rRNA gene segment was achieved. This identification by molecular biology techniques was confirmed by conventional biochemical tests. To our knowledge, this is the first description of M. zatmanii isolated from patient material. PMID:9854105