A numerical scheme for the identification of hybrid systems describing the vibration of flexible beams with tip bodies

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1984-01-01

A cubic spline based Galerkin-like method is developed for the identification of a class of hybrid systems which describe the transverse vibration to flexible beams with attached tip bodies. The identification problem is formulated as a least squares fit to data subject to the system dynamics given by a coupled system of ordnary and partial differential equations recast as an abstract evolution equation (AEE) in an appropriate infinite dimensional Hilbert space. Projecting the AEE into spline-based subspaces leads naturally to a sequence of approximating finite dimensional identification problems. The solutions to these problems are shown to exist, are relatively easily computed, and are shown to, in some sense, converge to solutions to the original identification problem. Numerical results for a variety of examples are discussed.

Health monitoring system for transmission shafts based on adaptive parameter identification

NASA Astrophysics Data System (ADS)

Souflas, I.; Pezouvanis, A.; Ebrahimi, K. M.

2018-05-01

A health monitoring system for a transmission shaft is proposed. The solution is based on the real-time identification of the physical characteristics of the transmission shaft i.e. stiffness and damping coefficients, by using a physical oriented model and linear recursive identification. The efficacy of the suggested condition monitoring system is demonstrated on a prototype transient engine testing facility equipped with a transmission shaft capable of varying its physical properties. Simulation studies reveal that coupling shaft faults can be detected and isolated using the proposed condition monitoring system. Besides, the performance of various recursive identification algorithms is addressed. The results of this work recommend that the health status of engine dynamometer shafts can be monitored using a simple lumped-parameter shaft model and a linear recursive identification algorithm which makes the concept practically viable.

Comparison of System Identification Techniques for the Hydraulic Manipulator Test Bed (HMTB)

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1996-01-01

In this thesis linear, dynamic, multivariable state-space models for three joints of the ground-based Hydraulic Manipulator Test Bed (HMTB) are identified. HMTB, housed at the NASA Langley Research Center, is a ground-based version of the Dexterous Orbital Servicing System (DOSS), a representative space station manipulator. The dynamic models of the HMTB manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include sum of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement unit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.

A system identification technique based on the random decrement signatures. Part 1: Theory and simulation

NASA Technical Reports Server (NTRS)

Bedewi, Nabih E.; Yang, Jackson C. S.

1987-01-01

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The mathematics of the technique is presented in addition to the results of computer simulations conducted to demonstrate the prediction of the response of the system and the random forcing function initially introduced to excite the system.

Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network

NASA Astrophysics Data System (ADS)

Geng, Xiangyi; Lu, Shizeng; Jiang, Mingshun; Sui, Qingmei; Lv, Shanshan; Xiao, Hang; Jia, Yuxi; Jia, Lei

2018-06-01

A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

Research of mine water source identification based on LIF technology

NASA Astrophysics Data System (ADS)

Zhou, Mengran; Yan, Pengcheng

2016-09-01

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

Performance of an optical identification and interrogation system

NASA Astrophysics Data System (ADS)

Venugopalan, A.; Ghosh, A. K.; Verma, P.; Cheng, S.

2008-04-01

A free space optics based identification and interrogation system has been designed. The applications of the proposed system lie primarily in areas which require a secure means of mutual identification and information exchange between optical readers and tags. Conventional RFIDs raise issues regarding security threats, electromagnetic interference and health safety. The security of RF-ID chips is low due to the wide spatial spread of radio waves. Malicious nodes can read data being transmitted on the network, if they are in the receiving range. The proposed system provides an alternative which utilizes the narrow paraxial beams of lasers and an RSA-based authentication scheme. These provide enhanced security to communication between a tag and the base station or reader. The optical reader can also perform remote identification and the tag can be read from a far off distance, given line of sight. The free space optical identification and interrogation system can be used for inventory management, security systems at airports, port security, communication with high security systems, etc. to name a few. The proposed system was implemented with low-cost, off-the-shelf components and its performance in terms of throughput and bit error rate has been measured and analyzed. The range of operation with a bit-error-rate lower than 10-9 was measured to be about 4.5 m. The security of the system is based on the strengths of the RSA encryption scheme implemented using more than 1024 bits.

A system identification technique based on the random decrement signatures. Part 2: Experimental results

NASA Technical Reports Server (NTRS)

Bedewi, Nabih E.; Yang, Jackson C. S.

1987-01-01

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The results of an experiment conducted on an offshore platform scale model to verify the validity of the technique and to demonstrate its application in damage detection are presented.

A network identity authentication system based on Fingerprint identification technology

NASA Astrophysics Data System (ADS)

Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

2005-10-01

Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

Modelling and Closed-Loop System Identification of a Quadrotor-Based Aerial Manipulator

NASA Astrophysics Data System (ADS)

Dube, Chioniso; Pedro, Jimoh O.

2018-05-01

This paper presents the modelling and system identification of a quadrotor-based aerial manipulator. The aerial manipulator model is first derived analytically using the Newton-Euler formulation for the quadrotor and Recursive Newton-Euler formulation for the manipulator. The aerial manipulator is then simulated with the quadrotor under Proportional Derivative (PD) control, with the manipulator in motion. The simulation data is then used for system identification of the aerial manipulator. Auto Regressive with eXogenous inputs (ARX) models are obtained from the system identification for linear accelerations \\ddot{X} and \\ddot{Y} and yaw angular acceleration \\ddot{\\psi }. For linear acceleration \\ddot{Z}, and pitch and roll angular accelerations \\ddot{θ } and \\ddot{φ }, Auto Regressive Moving Average with eXogenous inputs (ARMAX) models are identified.

[Formula: see text]-regularized recursive total least squares based sparse system identification for the error-in-variables.

PubMed

Lim, Jun-Seok; Pang, Hee-Suk

2016-01-01

In this paper an [Formula: see text]-regularized recursive total least squares (RTLS) algorithm is considered for the sparse system identification. Although recursive least squares (RLS) has been successfully applied in sparse system identification, the estimation performance in RLS based algorithms becomes worse, when both input and output are contaminated by noise (the error-in-variables problem). We proposed an algorithm to handle the error-in-variables problem. The proposed [Formula: see text]-RTLS algorithm is an RLS like iteration using the [Formula: see text] regularization. The proposed algorithm not only gives excellent performance but also reduces the required complexity through the effective inversion matrix handling. Simulations demonstrate the superiority of the proposed [Formula: see text]-regularized RTLS for the sparse system identification setting.

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.

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.

Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.

DOT National Transportation Integrated Search

2012-12-01

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...

Personal identification by eyes.

PubMed

Marinović, Dunja; Njirić, Sanja; Coklo, Miran; Muzić, Vedrana

2011-09-01

Identification of persons through the eyes is in the field of biometrical science. Many security systems are based on biometric methods of personal identification, to determine whether a person is presenting itself truly. The human eye contains an extremely large number of individual characteristics that make it particularly suitable for the process of identifying a person. Today, the eye is considered to be one of the most reliable body parts for human identification. Systems using iris recognition are among the most secure biometric systems.

Crystal identification for a dual-layer-offset LYSO based PET system via Lu-176 background radiation and mean shift algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Ma, Tianyu; Xu, Tianpeng; Zeng, Ming; Gu, Yu; Dai, Tiantian; Liu, Yaqiang

2018-01-01

Modern positron emission tomography (PET) detectors are made from pixelated scintillation crystal arrays and readout by Anger logic. The interaction position of the gamma-ray should be assigned to a crystal using a crystal position map or look-up table. Crystal identification is a critical procedure for pixelated PET systems. In this paper, we propose a novel crystal identification method for a dual-layer-offset LYSO based animal PET system via Lu-176 background radiation and mean shift algorithm. Single photon event data of the Lu-176 background radiation are acquired in list-mode for 3 h to generate a single photon flood map (SPFM). Coincidence events are obtained from the same data using time information to generate a coincidence flood map (CFM). The CFM is used to identify the peaks of the inner layer using the mean shift algorithm. The response of the inner layer is deducted from the SPFM by subtracting CFM. Then, the peaks of the outer layer are also identified using the mean shift algorithm. The automatically identified peaks are manually inspected by a graphical user interface program. Finally, a crystal position map is generated using a distance criterion based on these peaks. The proposed method is verified on the animal PET system with 48 detector blocks on a laptop with an Intel i7-5500U processor. The total runtime for whole system peak identification is 67.9 s. Results show that the automatic crystal identification has 99.98% and 99.09% accuracy for the peaks of the inner and outer layers of the whole system respectively. In conclusion, the proposed method is suitable for the dual-layer-offset lutetium based PET system to perform crystal identification instead of external radiation sources.

DNA barcode-based molecular identification system for fish species.

PubMed

Kim, Sungmin; Eo, Hae-Seok; Koo, Hyeyoung; Choi, Jun-Kil; Kim, Won

2010-12-01

In this study, we applied DNA barcoding to identify species using short DNA sequence analysis. We examined the utility of DNA barcoding by identifying 53 Korean freshwater fish species, 233 other freshwater fish species, and 1339 saltwater fish species. We successfully developed a web-based molecular identification system for fish (MISF) using a profile hidden Markov model. MISF facilitates efficient and reliable species identification, overcoming the limitations of conventional taxonomic approaches. MISF is freely accessible at http://bioinfosys.snu.ac.kr:8080/MISF/misf.jsp .

A tool for developing an automatic insect identification system based on wing outlines

PubMed Central

Yang, He-Ping; Ma, Chun-Sen; Wen, Hui; Zhan, Qing-Bin; Wang, Xin-Li

2015-01-01

For some insect groups, wing outline is an important character for species identification. We have constructed a program as the integral part of an automated system to identify insects based on wing outlines (DAIIS). This program includes two main functions: (1) outline digitization and Elliptic Fourier transformation and (2) classifier model training by pattern recognition of support vector machines and model validation. To demonstrate the utility of this program, a sample of 120 owlflies (Neuroptera: Ascalaphidae) was split into training and validation sets. After training, the sample was sorted into seven species using this tool. In five repeated experiments, the mean accuracy for identification of each species ranged from 90% to 98%. The accuracy increased to 99% when the samples were first divided into two groups based on features of their compound eyes. DAIIS can therefore be a useful tool for developing a system of automated insect identification. PMID:26251292

Identification of Load Categories in Rotor System Based on Vibration Analysis

PubMed Central

Yang, Zhaojian

2017-01-01

Rotating machinery is often subjected to variable loads during operation. Thus, monitoring and identifying different load types is important. Here, five typical load types have been qualitatively studied for a rotor system. A novel load category identification method for rotor system based on vibration signals is proposed. This method is a combination of ensemble empirical mode decomposition (EEMD), energy feature extraction, and back propagation (BP) neural network. A dedicated load identification test bench for rotor system was developed. According to loads characteristics and test conditions, an experimental plan was formulated, and loading tests for five loads were conducted. Corresponding vibration signals of the rotor system were collected for each load condition via eddy current displacement sensor. Signals were reconstructed using EEMD, and then features were extracted followed by energy calculations. Finally, characteristics were input to the BP neural network, to identify different load types. Comparison and analysis of identifying data and test data revealed a general identification rate of 94.54%, achieving high identification accuracy and good robustness. This shows that the proposed method is feasible. Due to reliable and experimentally validated theoretical results, this method can be applied to load identification and fault diagnosis for rotor equipment used in engineering applications. PMID:28726754

Development of a real time magnetic island identification system for HL-2A tokamak.

PubMed

Chen, Chao; Sun, Shan; Ji, Xiaoquan; Yin, Zejie

2017-08-01

A novel real time magnetic island identification system for HL-2A is introduced. The identification method is based on the measurement of Mirnov probes and the equilibrium flux constructed by the equilibrium fit (EFIT) code. The system consists of an analog front board and a digital processing board connected by a shield cable. Four octal-channel analog-to-digital convertors are utilized for 100 KHz simultaneous sampling of all the probes, and the applications of PCI extensions for Instrumentation platform and reflective memory allow the system to receive EFIT results simultaneously. A high performance field programmable gate array (FPGA) is used to realize the real time identification algorithm. Based on the parallel and pipeline processing of the FPGA, the magnetic island structure can be identified with a cycle time of 3 ms during experiments.

Development of a real time magnetic island identification system for HL-2A tokamak

NASA Astrophysics Data System (ADS)

Chen, Chao; Sun, Shan; Ji, Xiaoquan; Yin, Zejie

2017-08-01

A novel real time magnetic island identification system for HL-2A is introduced. The identification method is based on the measurement of Mirnov probes and the equilibrium flux constructed by the equilibrium fit (EFIT) code. The system consists of an analog front board and a digital processing board connected by a shield cable. Four octal-channel analog-to-digital convertors are utilized for 100 KHz simultaneous sampling of all the probes, and the applications of PCI extensions for Instrumentation platform and reflective memory allow the system to receive EFIT results simultaneously. A high performance field programmable gate array (FPGA) is used to realize the real time identification algorithm. Based on the parallel and pipeline processing of the FPGA, the magnetic island structure can be identified with a cycle time of 3 ms during experiments.

General hybrid projective complete dislocated synchronization with non-derivative and derivative coupling based on parameter identification in several chaotic and hyperchaotic systems

NASA Astrophysics Data System (ADS)

Sun, Jun-Wei; Shen, Yi; Zhang, Guo-Dong; Wang, Yan-Feng; Cui, Guang-Zhao

2013-04-01

According to the Lyapunov stability theorem, a new general hybrid projective complete dislocated synchronization scheme with non-derivative and derivative coupling based on parameter identification is proposed under the framework of drive-response systems. Every state variable of the response system equals the summation of the hybrid drive systems in the previous hybrid synchronization. However, every state variable of the drive system equals the summation of the hybrid response systems while evolving with time in our method. Complete synchronization, hybrid dislocated synchronization, projective synchronization, non-derivative and derivative coupling, and parameter identification are included as its special item. The Lorenz chaotic system, Rössler chaotic system, memristor chaotic oscillator system, and hyperchaotic Lü system are discussed to show the effectiveness of the proposed methods.

Methods and application of system identification in shock and vibration.

NASA Technical Reports Server (NTRS)

Collins, J. D.; Young, J. P.; Kiefling, L.

1972-01-01

A logical picture is presented of current useful system identification techniques in the shock and vibration field. A technology tree diagram is developed for the purpose of organizing and categorizing the widely varying approaches according to the fundamental nature of each. Specific examples of accomplished activity for each identification category are noted and discussed. To provide greater insight into the most current trends in the system identification field, a somewhat detailed description is presented of the essential features of a recently developed technique that is based on making the maximum use of all statistically known information about a system.

Use of the MicroSeq 500 16S rRNA Gene-Based Sequencing for Identification of Bacterial Isolates That Commercial Automated Systems Failed To Identify Correctly

PubMed Central

Fontana, Carla; Favaro, Marco; Pelliccioni, Marco; Pistoia, Enrico Salvatore; Favalli, Cartesio

2005-01-01

Reliable automated identification and susceptibility testing of clinically relevant bacteria is an essential routine for microbiology laboratories, thus improving patient care. Examples of automated identification systems include the Phoenix (Becton Dickinson) and the VITEK 2 (bioMérieux). However, more and more frequently, microbiologists must isolate “difficult” strains that automated systems often fail to identify. An alternative approach could be the genetic identification of isolates; this is based on 16S rRNA gene sequencing and analysis. The aim of the present study was to evaluate the possible use of MicroSeq 500 (Applera) for sequencing the 16S rRNA gene to identify isolates whose identification is unobtainable by conventional systems. We analyzed 83 “difficult” clinical isolates: 25 gram-positive and 58 gram-negative strains that were contemporaneously identified by both systems—VITEK 2 and Phoenix—while genetic identification was performed by using the MicroSeq 500 system. The results showed that phenotypic identifications by VITEK 2 and Phoenix were remarkably similar: 74% for gram-negative strains (43 of 58) and 80% for gram-positive strains were concordant by both systems and also concordant with genetic characterization. The exceptions were the 15 gram-negative and 9 gram-positive isolates whose phenotypic identifications were contrasting or inconclusive. For these, the use of MicroSeq 500 was fundamental to achieving species identification. In clinical microbiology the use of MicroSeq 500, particularly for strains with ambiguous biochemical profiles (including slow-growing strains), identifies strains more easily than do conventional systems. Moreover, MicroSeq 500 is easy to use and cost-effective, making it applicable also in the clinical laboratory. PMID:15695654

Tip-tilt disturbance model identification based on non-linear least squares fitting for Linear Quadratic Gaussian control

NASA Astrophysics Data System (ADS)

Yang, Kangjian; Yang, Ping; Wang, Shuai; Dong, Lizhi; Xu, Bing

2018-05-01

We propose a method to identify tip-tilt disturbance model for Linear Quadratic Gaussian control. This identification method based on Levenberg-Marquardt method conducts with a little prior information and no auxiliary system and it is convenient to identify the tip-tilt disturbance model on-line for real-time control. This identification method makes it easy that Linear Quadratic Gaussian control runs efficiently in different adaptive optics systems for vibration mitigation. The validity of the Linear Quadratic Gaussian control associated with this tip-tilt disturbance model identification method is verified by experimental data, which is conducted in replay mode by simulation.

Stochastic system identification in structural dynamics

USGS Publications Warehouse

Safak, Erdal

1988-01-01

Recently, new identification methods have been developed by using the concept of optimal-recursive filtering and stochastic approximation. These methods, known as stochastic identification, are based on the statistical properties of the signal and noise, and do not require the assumptions of current methods. The criterion for stochastic system identification is that the difference between the recorded output and the output from the identified system (i.e., the residual of the identification) should be equal to white noise. In this paper, first a brief review of the theory is given. Then, an application of the method is presented by using ambient vibration data from a nine-story building.

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Approach to the problem of the parameters optimization of the shooting system

NASA Astrophysics Data System (ADS)

Demidova, L. A.; Sablina, V. A.; Sokolova, Y. S.

2018-02-01

The problem of the objects identification on the base of their hyperspectral features has been considered. It is offered to use the SVM classifiers’ ensembles, adapted to specifics of the problem of the objects identification on the base of their hyperspectral features. The results of the objects identification on the base of their hyperspectral features with using of the SVM classifiers have been presented.

Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

NASA Astrophysics Data System (ADS)

Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

2018-03-01

Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

Reduction in specimen labeling errors after implementation of a positive patient identification system in phlebotomy.

PubMed

Morrison, Aileen P; Tanasijevic, Milenko J; Goonan, Ellen M; Lobo, Margaret M; Bates, Michael M; Lipsitz, Stuart R; Bates, David W; Melanson, Stacy E F

2010-06-01

Ensuring accurate patient identification is central to preventing medical errors, but it can be challenging. We implemented a bar code-based positive patient identification system for use in inpatient phlebotomy. A before-after design was used to evaluate the impact of the identification system on the frequency of mislabeled and unlabeled samples reported in our laboratory. Labeling errors fell from 5.45 in 10,000 before implementation to 3.2 in 10,000 afterward (P = .0013). An estimated 108 mislabeling events were prevented by the identification system in 1 year. Furthermore, a workflow step requiring manual preprinting of labels, which was accompanied by potential labeling errors in about one quarter of blood "draws," was removed as a result of the new system. After implementation, a higher percentage of patients reported having their wristband checked before phlebotomy. Bar code technology significantly reduced the rate of specimen identification errors.

Advantage of MALDI-TOF-MS over biochemical-based phenotyping for microbial identification illustrated on industrial applications.

PubMed

Urwyler, S K; Glaubitz, J

2016-02-01

Fast microbial identification is becoming increasingly necessary in industry to improve microbial control and reduce biocide consumption. We compared the performances of two systems based on MALDI-TOF MS (VITEK MS and BIOTYPER) and two based on biochemical testing (BIOLOG, VITEK 2 Compact) with genetic methods for the identification of environmental bacteria. At genus level both MALDI-TOF MS-based systems showed the lowest number of false (4%) and approx. 60% correct identifications. In contrast, the biochemical-based systems assigned 25% of the genera incorrectly. The differences were even more apparent at the species level. The BIOTYPER was most conservative, where assigning a species led to the lowest percentage of species identifications (54%) but also to the least wrong assignments (4%). The other three systems showed higher levels of false assignments: 8·7, 40 and 46% respectively. The genus identification performance on four industrial products of the BIOTYPER could be increased up to 94·3% (average 88% of 167 isolates) by evolving the database in a product specific manner. Comparison of the bacterial population in the example of paints, and raw materials used therein, at different production steps demonstrated unequivocally that the contamination of the final paint product originated not from the main raw material. MALDI-TOF-MS has revolutionized speed and precision of microbial identification for clinical isolates outperforming conventional methods. In contrast, few performance studies have been published so far focusing on suitability for particularly industrial applications, geomicrobiology and environmental analytics. This study evaluates the performance of this proteomic phenotyping on such industrial isolates in comparison with biochemical-based phenotyping and genotyping. Further the study exemplifies the power of MALDI-TOF-MS to trace cost-efficiently the dominating cultivable bacterial species throughout an industrial paint production process. Vital information can be retrieved to identify the most crucial contaminating source for the final product. © 2015 The Authors published by John Wiley & Sons Ltd on behalf of Society for Applied Microbiology.

Performance enhancement for audio-visual speaker identification using dynamic facial muscle model.

PubMed

Asadpour, Vahid; Towhidkhah, Farzad; Homayounpour, Mohammad Mehdi

2006-10-01

Science of human identification using physiological characteristics or biometry has been of great concern in security systems. However, robust multimodal identification systems based on audio-visual information has not been thoroughly investigated yet. Therefore, the aim of this work to propose a model-based feature extraction method which employs physiological characteristics of facial muscles producing lip movements. This approach adopts the intrinsic properties of muscles such as viscosity, elasticity, and mass which are extracted from the dynamic lip model. These parameters are exclusively dependent on the neuro-muscular properties of speaker; consequently, imitation of valid speakers could be reduced to a large extent. These parameters are applied to a hidden Markov model (HMM) audio-visual identification system. In this work, a combination of audio and video features has been employed by adopting a multistream pseudo-synchronized HMM training method. Noise robust audio features such as Mel-frequency cepstral coefficients (MFCC), spectral subtraction (SS), and relative spectra perceptual linear prediction (J-RASTA-PLP) have been used to evaluate the performance of the multimodal system once efficient audio feature extraction methods have been utilized. The superior performance of the proposed system is demonstrated on a large multispeaker database of continuously spoken digits, along with a sentence that is phonetically rich. To evaluate the robustness of algorithms, some experiments were performed on genetically identical twins. Furthermore, changes in speaker voice were simulated with drug inhalation tests. In 3 dB signal to noise ratio (SNR), the dynamic muscle model improved the identification rate of the audio-visual system from 91 to 98%. Results on identical twins revealed that there was an apparent improvement on the performance for the dynamic muscle model-based system, in which the identification rate of the audio-visual system was enhanced from 87 to 96%.

The power grid AGC frequency bias coefficient online identification method based on wide area information

NASA Astrophysics Data System (ADS)

Wang, Zian; Li, Shiguang; Yu, Ting

2015-12-01

This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) 2001-2004

EPA Science Inventory

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identific...

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital.

PubMed

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung; Lee, Jae Ho

2013-06-01

The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly.

Research of Uncertainty Reasoning in Pineapple Disease Identification System

NASA Astrophysics Data System (ADS)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

A MEMS-based, wireless, biometric-like security system

NASA Astrophysics Data System (ADS)

Cross, Joshua D.; Schneiter, John L.; Leiby, Grant A.; McCarter, Steven; Smith, Jeremiah; Budka, Thomas P.

2010-04-01

We present a system for secure identification applications that is based upon biometric-like MEMS chips. The MEMS chips have unique frequency signatures resulting from fabrication process variations. The MEMS chips possess something analogous to a "voiceprint". The chips are vacuum encapsulated, rugged, and suitable for low-cost, highvolume mass production. Furthermore, the fabrication process is fully integrated with standard CMOS fabrication methods. One is able to operate the MEMS-based identification system similarly to a conventional RFID system: the reader (essentially a custom network analyzer) detects the power reflected across a frequency spectrum from a MEMS chip in its vicinity. We demonstrate prototype "tags" - MEMS chips placed on a credit card-like substrate - to show how the system could be used in standard identification or authentication applications. We have integrated power scavenging to provide DC bias for the MEMS chips through the use of a 915 MHz source in the reader and a RF-DC conversion circuit on the tag. The system enables a high level of protection against typical RFID hacking attacks. There is no need for signal encryption, so back-end infrastructure is minimal. We believe this system would make a viable low-cost, high-security system for a variety of identification and authentication applications.

FBI fingerprint identification automation study: AIDS 3 evaluation report. Volume 9: Functional requirements

NASA Technical Reports Server (NTRS)

1980-01-01

The current system and subsystem used by the Identification Division are described. System constraints that dictate the system environment are discussed and boundaries within which solutions must be found are described. The functional requirements were related to the performance requirements. These performance requirements were then related to their applicable subsystems. The flow of data, documents, or other pieces of information from one subsystem to another or from the external world into the identification system is described. Requirements and design standards for a computer based system are presented.

Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

A bimodal biometric identification system

NASA Astrophysics Data System (ADS)

Laghari, Mohammad S.; Khuwaja, Gulzar A.

2013-03-01

Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.

Rule Based Expert System for Monitoring Real Time Drug Supply in Hospital Using Radio Frequency Identification Technology

NASA Astrophysics Data System (ADS)

Driandanu, Galih; Surarso, Bayu; Suryono

2018-02-01

A radio frequency identification (RFID) has obtained increasing attention with the emergence of various applications. This study aims to examine the implementation of rule based expert system supported by RFID technology into a monitoring information system of drug supply in a hospital. This research facilitates in monitoring the real time drug supply by using data sample from the hospital pharmacy. This system able to identify and count the number of drug and provide warning and report in real time. the conclusion is the rule based expert system and RFID technology can facilitate the performance in monitoring the drug supply quickly and precisely.

Software For Fault-Tree Diagnosis Of A System

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

76 FR 59660 - Proposed Information Collection; Comment Request; Permitting, Vessel Identification, and Vessel...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-27

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration Proposed Information Collection; Comment Request; Permitting, Vessel Identification, and Vessel Monitoring System Requirements for... satellite- based vessel monitoring system (VMS). This collection of information is needed for permit...

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

A Heterogeneous Wireless Identification Network for the Localization of Animals Based on Stochastic Movements

PubMed Central

Gutiérrez, Álvaro; González, Carlos; Jiménez-Leube, Javier; Zazo, Santiago; Dopico, Nelson; Raos, Ivana

2009-01-01

The improvement in the transmission range in wireless applications without the use of batteries remains a significant challenge in identification applications. In this paper, we describe a heterogeneous wireless identification network mostly powered by kinetic energy, which allows the localization of animals in open environments. The system relies on radio communications and a global positioning system. It is made up of primary and secondary nodes. Secondary nodes are kinetic-powered and take advantage of animal movements to activate the node and transmit a specific identifier, reducing the number of batteries of the system. Primary nodes are battery-powered and gather secondary-node transmitted information to provide it, along with position and time data, to a final base station in charge of the animal monitoring. The system allows tracking based on contextual information obtained from statistical data. PMID:22412344

Optimal sensor placement for time-domain identification using a wavelet-based genetic algorithm

NASA Astrophysics Data System (ADS)

Mahdavi, Seyed Hossein; Razak, Hashim Abdul

2016-06-01

This paper presents a wavelet-based genetic algorithm strategy for optimal sensor placement (OSP) effective for time-domain structural identification. Initially, the GA-based fitness evaluation is significantly improved by using adaptive wavelet functions. Later, a multi-species decimal GA coding system is modified to be suitable for an efficient search around the local optima. In this regard, a local operation of mutation is introduced in addition with regeneration and reintroduction operators. It is concluded that different characteristics of applied force influence the features of structural responses, and therefore the accuracy of time-domain structural identification is directly affected. Thus, the reliable OSP strategy prior to the time-domain identification will be achieved by those methods dealing with minimizing the distance of simulated responses for the entire system and condensed system considering the force effects. The numerical and experimental verification on the effectiveness of the proposed strategy demonstrates the considerably high computational performance of the proposed OSP strategy, in terms of computational cost and the accuracy of identification. It is deduced that the robustness of the proposed OSP algorithm lies in the precise and fast fitness evaluation at larger sampling rates which result in the optimum evaluation of the GA-based exploration and exploitation phases towards the global optimum solution.

Identification and molecular epidemiology of dermatophyte isolates by repetitive-sequence-PCR-based DNA fingerprinting using the DiversiLab system in Turkey.

PubMed

Koc, A Nedret; Atalay, Mustafa A; Inci, Melek; Sariguzel, Fatma M; Sav, Hafize

2017-05-01

Dermatophyte species, isolation and identification in clinical samples are still difficult and take a long time. The identification and molecular epidemiology of dermatophytes commonly isolated in a clinical laboratory in Turkey by repetitive sequence-based PCR (rep-PCR) were assessed by comparing the results with those of reference identification. A total of 44 dermatophytes isolated from various clinical specimens of 20 patients with superficial mycoses in Kayseri and 24 patients in Hatay were studied. The identification of dermatophyte isolates was based on the reference identification and rep-PCR using the DiversiLab System (BioMerieux). The genotyping of dermatophyte isolates from different patients was determined by rep-PCR. In the identification of dermatophyte isolates, agreement between rep-PCR and conventional methods was 87.8 % ( 36 of 41). The dermatophyte strains belonged to four clones (A -D) which were determined by the use of rep-PCR. The dermatophyte strains in Clone B, D showed identical patterns with respect to the region. In conclusion, rep-PCR appears to be useful for evaluation of the identification and clonal relationships between Trichophyton rubrum species complex and Trichophyton mentagrophytes species complex isolates. The similarity and diversity of these isolates may be assessed according to different regions by rep-PCR. © 2017 Blackwell Verlag GmbH.

[Application of the computer-based respiratory sound analysis system based on Mel-frequency cepstral coefficient and dynamic time warping in healthy children].

PubMed

Yan, W Y; Li, L; Yang, Y G; Lin, X L; Wu, J Z

2016-08-01

We designed a computer-based respiratory sound analysis system to identify pediatric normal lung sound. To verify the validity of the computer-based respiratory sound analysis system. First we downloaded the standard lung sounds from the network database (website: http: //www.easyauscultation.com/lung-sounds-reference-guide) and recorded 3 samples of abnormal loud sound (rhonchi, wheeze and crackles) from three patients of The Department of Pediatrics, the First Affiliated Hospital of Xiamen University. We regarded such lung sounds as"reference lung sounds". The"test lung sounds"were recorded from 29 children form Kindergarten of Xiamen University. we recorded lung sound by portable electronic stethoscope and valid lung sounds were selected by manual identification. We introduced Mel-frequency cepstral coefficient (MFCC) to extract lung sound features and dynamic time warping (DTW) for signal classification. We had 39 standard lung sounds, recorded 58 test lung sounds. This computer-based respiratory sound analysis system was carried out in 58 lung sound recognition, correct identification of 52 times, error identification 6 times. Accuracy was 89.7%. Based on MFCC and DTW, our computer-based respiratory sound analysis system can effectively identify healthy lung sounds of children (accuracy can reach 89.7%), fully embodies the reliability of the lung sounds analysis system.

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.

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital

PubMed Central

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung

2013-01-01

Objectives The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. Methods We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. Results The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. Conclusions We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly. PMID:23882415

Algorithm for personal identification in distance learning system based on registration of keyboard rhythm

NASA Astrophysics Data System (ADS)

Nikitin, P. V.; Savinov, A. N.; Bazhenov, R. I.; Sivandaev, S. V.

2018-05-01

The article describes the method of identifying a person in distance learning systems based on a keyboard rhythm. An algorithm for the organization of access control is proposed, which implements authentication, identification and verification of a person using the keyboard rhythm. Authentication methods based on biometric personal parameters, including those based on the keyboard rhythm, due to the inexistence of biometric characteristics without a particular person, are able to provide an advanced accuracy and inability to refuse authorship and convenience for operators of automated systems, in comparison with other methods of conformity checking. Methods of permanent hidden keyboard monitoring allow detecting the substitution of a student and blocking the key system.

Performance metrics for the evaluation of hyperspectral chemical identification systems

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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.

An online ID identification system for liquefied-gas cylinder plant

NASA Astrophysics Data System (ADS)

He, Jin; Ding, Zhenwen; Han, Lei; Zhang, Hao

2017-11-01

An automatic ID identification system for gas cylinders' online production was developed based on the production conditions and requirements of the Technical Committee for Standardization of Gas Cylinders. A cylinder ID image acquisition system was designed to improve the image contrast of ID regions on gas cylinders against the background. Then the ID digits region was located by the CNN template matching algorithm. Following that, an adaptive threshold method based on the analysis of local average grey value and standard deviation was proposed to overcome defects of non-uniform background in the segmentation results. To improve the single digit identification accuracy, two BP neural networks were trained respectively for the identification of all digits and the easily confusable digits. If the single digit was classified as one of confusable digits by the former BP neural network, it was further tested by the later one, and the later result was taken as the final identification result of this single digit. At last, the majority voting was adopted to decide the final identification result for the 6-digit cylinder ID. The developed system was installed on a production line of a liquefied-petroleum-gas cylinder plant and worked in parallel with the existing weighing step on the line. Through the field test, the correct identification rate for single ID digit was 94.73%, and none of the tested 2000 cylinder ID was misclassified through the majority voting.

Incomplete data based parameter identification of nonlinear and time-variant oscillators with fractional derivative elements

NASA Astrophysics Data System (ADS)

Kougioumtzoglou, Ioannis A.; dos Santos, Ketson R. M.; Comerford, Liam

2017-09-01

Various system identification techniques exist in the literature that can handle non-stationary measured time-histories, or cases of incomplete data, or address systems following a fractional calculus modeling. However, there are not many (if any) techniques that can address all three aforementioned challenges simultaneously in a consistent manner. In this paper, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear and time-variant oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear sub-systems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sensing theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. Several linear and nonlinear time-variant systems with fractional derivative elements are used as numerical examples to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.

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.

CASTE (Course Assembly System and Tutorial Environment) and CVI: (Combat Vehicle Identification) A First Application of an Intelligent Tutorial System to Combat Vehicle Identification.

DTIC Science & Technology

1984-09-01

based training systems and hence to realize an embedded trainer that is both intelligent and effective . The o(Continued) DO,; FOAM AM 71 1ឹ...Performance Effectiveness and Simulation Approved for public releate; dlitribution unlimited iii &a3laAfc*ia £&&etaL* ■’—’,£-«.■£./■.,’-f...oriented approaches to computer-based training systems and hence realise an embedded trainer that is both intelli- gent and effective . To this end

Decision support environment for medical product safety surveillance.

PubMed

Botsis, Taxiarchis; Jankosky, Christopher; Arya, Deepa; Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Wang, Wei; Zhang, Guangfan; Forshee, Richard; Goud, Ravi; Menschik, David; Walderhaug, Mark; Woo, Emily Jane; Scott, John

2016-12-01

We have developed a Decision Support Environment (DSE) for medical experts at the US Food and Drug Administration (FDA). The DSE contains two integrated systems: The Event-based Text-mining of Health Electronic Records (ETHER) and the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA). These systems assist medical experts in reviewing reports submitted to the Vaccine Adverse Event Reporting System (VAERS) and the FDA Adverse Event Reporting System (FAERS). In this manuscript, we describe the DSE architecture and key functionalities, and examine its potential contributions to the signal management process by focusing on four use cases: the identification of missing cases from a case series, the identification of duplicate case reports, retrieving cases for a case series analysis, and community detection for signal identification and characterization. Published by Elsevier Inc.

Recent Applications of the Volterra Theory to Aeroelastic Phenomena

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Note: Model-based identification method of a cable-driven wearable device for arm rehabilitation

NASA Astrophysics Data System (ADS)

Cui, Xiang; Chen, Weihai; Zhang, Jianbin; Wang, Jianhua

2015-09-01

Cable-driven exoskeletons have used active cables to actuate the system and are worn on subjects to provide motion assistance. However, this kind of wearable devices usually contains uncertain kinematic parameters. In this paper, a model-based identification method has been proposed for a cable-driven arm exoskeleton to estimate its uncertainties. The identification method is based on the linearized error model derived from the kinematics of the exoskeleton. Experiment has been conducted to demonstrate the feasibility of the proposed model-based method in practical application.

Automatic identification of alpine mass movements based on seismic and infrasound signals

NASA Astrophysics Data System (ADS)

Schimmel, Andreas; Hübl, Johannes

2017-04-01

The automatic detection and identification of alpine mass movements like debris flows, debris floods or landslides gets increasing importance for mitigation measures in the densely populated and intensively used alpine regions. Since this mass movement processes emits characteristically seismic and acoustic waves in the low frequency range this events can be detected and identified based on this signals. So already several approaches for detection and warning systems based on seismic or infrasound signals has been developed. But a combination of both methods, which can increase detection probability and reduce false alarms is currently used very rarely and can serve as a promising method for developing an automatic detection and identification system. So this work presents an approach for a detection and identification system based on a combination of seismic and infrasound sensors, which can detect sediment related mass movements from a remote location unaffected by the process. The system is based on one infrasound sensor and one geophone which are placed co-located and a microcontroller where a specially designed detection algorithm is executed which can detect mass movements in real time directly at the sensor site. Further this work tries to get out more information from the seismic and infrasound spectrum produced by different sediment related mass movements to identify the process type and estimate the magnitude of the event. The system is currently installed and tested on five test sites in Austria, two in Italy and one in Switzerland as well as one in Germany. This high number of test sites is used to get a large database of very different events which will be the basis for a new identification method for alpine mass movements. These tests shows promising results and so this system provides an easy to install and inexpensive approach for a detection and warning system.

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

System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator

DTIC Science & Technology

2006-08-01

commanded torque to move away from these singularity points. The introduction of this error may not degrade the performance for large slew angle ...trajectory has been generated and quaternion feedback control has been implemented for reference trajectory tracking. The testbed was reasonably well...System Identification and Automatic Mass Balancing of Ground-Based Three-Axis Spacecraft Simulator Jae-Jun Kim∗ and Brij N. Agrawal † Department of

Application of higher order SVD to vibration-based system identification and damage detection

NASA Astrophysics Data System (ADS)

Chao, Shu-Hsien; Loh, Chin-Hsiung; Weng, Jian-Huang

2012-04-01

Singular value decomposition (SVD) is a powerful linear algebra tool. It is widely used in many different signal processing methods, such principal component analysis (PCA), singular spectrum analysis (SSA), frequency domain decomposition (FDD), subspace identification and stochastic subspace identification method ( SI and SSI ). In each case, the data is arranged appropriately in matrix form and SVD is used to extract the feature of the data set. In this study three different algorithms on signal processing and system identification are proposed: SSA, SSI-COV and SSI-DATA. Based on the extracted subspace and null-space from SVD of data matrix, damage detection algorithms can be developed. The proposed algorithm is used to process the shaking table test data of the 6-story steel frame. Features contained in the vibration data are extracted by the proposed method. Damage detection can then be investigated from the test data of the frame structure through subspace-based and nullspace-based damage indices.

Load power device, system and method of load control and management employing load identification

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

Yang, Yi; Luebke, Charles John; Schoepf, Thomas J.

A load power device includes a power input, at least one power output for at least one load, a plurality of sensors structured to sense voltage and current at the at least one power output, and a processor. The processor provides: (a) load identification based upon the sensed voltage and current, and (b) load control and management based upon the load identification.

Two models for identification and predicting behaviour of an induction motor system

NASA Astrophysics Data System (ADS)

Kuo, Chien-Hsun

2018-01-01

System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.

A review of automatic patient identification options for public health care centers with restricted budgets.

PubMed

García-Betances, Rebeca I; Huerta, Mónica K

2012-01-01

A comparative review is presented of available technologies suitable for automatic reading of patient identification bracelet tags. Existing technologies' backgrounds, characteristics, advantages and disadvantages, are described in relation to their possible use by public health care centers with budgetary limitations. A comparative assessment is presented of suitable automatic identification systems based on graphic codes, both one- (1D) and two-dimensional (2D), printed on labels, as well as those based on radio frequency identification (RFID) tags. The analysis looks at the tradeoffs of these technologies to provide guidance to hospital administrator looking to deploy patient identification technology. The results suggest that affordable automatic patient identification systems can be easily and inexpensively implemented using 2D code printed on low cost bracelet labels, which can then be read and automatically decoded by ordinary mobile smart phones. Because of mobile smart phones' present versatility and ubiquity, the implantation and operation of 2D code, and especially Quick Response® (QR) Code, technology emerges as a very attractive alternative to automate the patients' identification processes in low-budget situations.

A Review of Automatic Patient Identification Options for Public Health Care Centers with Restricted Budgets

PubMed Central

García-Betances, Rebeca I.; Huerta, Mónica K.

2012-01-01

A comparative review is presented of available technologies suitable for automatic reading of patient identification bracelet tags. Existing technologies’ backgrounds, characteristics, advantages and disadvantages, are described in relation to their possible use by public health care centers with budgetary limitations. A comparative assessment is presented of suitable automatic identification systems based on graphic codes, both one- (1D) and two-dimensional (2D), printed on labels, as well as those based on radio frequency identification (RFID) tags. The analysis looks at the tradeoffs of these technologies to provide guidance to hospital administrator looking to deploy patient identification technology. The results suggest that affordable automatic patient identification systems can be easily and inexpensively implemented using 2D code printed on low cost bracelet labels, which can then be read and automatically decoded by ordinary mobile smart phones. Because of mobile smart phones’ present versatility and ubiquity, the implantation and operation of 2D code, and especially Quick Response® (QR) Code, technology emerges as a very attractive alternative to automate the patients’ identification processes in low-budget situations. PMID:23569629

System identification using Nuclear Norm & Tabu Search optimization

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

Biometric identification based on feature fusion with PCA and SVM

NASA Astrophysics Data System (ADS)

Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

2018-04-01

Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.

A miniaturised semiautomated system for the identification of Yersinia species within the genus Yersinia.

PubMed

Neubauer, H; Molitor, M; Rahalison, L; Aleksic, S; Backes, H; Chanteau, S; Meyer, H

2000-01-01

Commercially available identification systems based on biochemical reactions of bacteria are not suited for typing the species of the genus Yersinia (Y.) or the biovars (BV) of the species Y. enterocolitica. This failure is caused by the limited number of biochemical reactions applied, resulting in the absence of important discriminatory key reactions. The MICRONAUT identification system (Merlin, Bornheim-Hersel) makes use of dried substrates/enzymes reactions in the wells of a 96-well microtitration plate, reading of the results by a scanner device and typing of the isolate by the calculation of probabilities according to a data base. For this study a special identification panel was designed on which 38 substrates and enzyme reactions were configurated including 20 reactions for the identification of the species of the genus and the Y. enterocolitica biovars. The database was calculated using the results obtained from a total of 250 Yersinia strains of the eleven species of the genus. Reevaluation of the results of these strains revealed an overall sensitivity of 98%, as only four strains were not identified satisfactorily. Considering also questionable results the sensitivity was still 85%. The system was also used to identify Y. pestis isolates, but in this case reading was done visually. The printouts usually cite species designation, identification quality and probabilities. The sealing of the plates in an aluminium bag guarantees long life and long lasting quality. However, an evaluation of the system with a considerable number of strains has to be done in a next step. The 'Yersinia identification set' can replace time-consuming tube testing in the future and is a big step forward towards a sensitive identification of Yersinia isolates in the routine laboratory.

COMPARISON BETWEEN AUTOMATED SYSTEM AND PCR-BASED METHOD FOR IDENTIFICATION AND ANTIMICROBIAL SUSCEPTIBILITY PROFILE OF CLINICAL Enterococcus spp

PubMed Central

Furlaneto-Maia, Luciana; Rocha, Kátia Real; Siqueira, Vera Lúcia Dias; Furlaneto, Márcia Cristina

2014-01-01

Enterococci are increasingly responsible for nosocomial infections worldwide. This study was undertaken to compare the identification and susceptibility profile using an automated MicrosScan system, PCR-based assay and disk diffusion assay of Enterococcus spp. We evaluated 30 clinical isolates of Enterococcus spp. Isolates were identified by MicrosScan system and PCR-based assay. The detection of antibiotic resistance genes (vancomycin, gentamicin, tetracycline and erythromycin) was also determined by PCR. Antimicrobial susceptibilities to vancomycin (30 µg), gentamicin (120 µg), tetracycline (30 µg) and erythromycin (15 µg) were tested by the automated system and disk diffusion method, and were interpreted according to the criteria recommended in CLSI guidelines. Concerning Enterococcus identification the general agreement between data obtained by the PCR method and by the automatic system was 90.0% (27/30). For all isolates of E. faecium and E. faecalis we observed 100% agreement. Resistance frequencies were higher in E. faecium than E. faecalis. The resistance rates obtained were higher for erythromycin (86.7%), vancomycin (80.0%), tetracycline (43.35) and gentamicin (33.3%). The correlation between disk diffusion and automation revealed an agreement for the majority of the antibiotics with category agreement rates of > 80%. The PCR-based assay, the van(A) gene was detected in 100% of vancomycin resistant enterococci. This assay is simple to conduct and reliable in the identification of clinically relevant enterococci. The data obtained reinforced the need for an improvement of the automated system to identify some enterococci. PMID:24626409

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

PubMed

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

2010-04-01

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

Tracking by Identification Using Computer Vision and Radio

PubMed Central

Mandeljc, Rok; Kovačič, Stanislav; Kristan, Matej; Perš, Janez

2013-01-01

We present a novel system for detection, localization and tracking of multiple people, which fuses a multi-view computer vision approach with a radio-based localization system. The proposed fusion combines the best of both worlds, excellent computer-vision-based localization, and strong identity information provided by the radio system, and is therefore able to perform tracking by identification, which makes it impervious to propagated identity switches. We present comprehensive methodology for evaluation of systems that perform person localization in world coordinate system and use it to evaluate the proposed system as well as its components. Experimental results on a challenging indoor dataset, which involves multiple people walking around a realistically cluttered room, confirm that proposed fusion of both systems significantly outperforms its individual components. Compared to the radio-based system, it achieves better localization results, while at the same time it successfully prevents propagation of identity switches that occur in pure computer-vision-based tracking. PMID:23262485

Determination of new retention indices for quick identification of essential oils compounds.

PubMed

Hérent, Marie-France; De Bie, Véronique; Tilquin, Bernard

2007-02-19

The classical methods of chromatographic identification of compounds were based on calculation of retention indices by using different stationary phases. The aim of the work was to differentiate essential oils extracted from different plant species by identification of some of their major compounds. The method of identification was based on the calculation of new retention indices of essential oils compounds fractionated on a polar chromatographic column with temperature programming system. Similar chromatograms have been obtained on the same column for one plant family with two different temperature gradients allowing the rapid identification of essential oils of different species, sub-species or chemotypes of Citrus, Mentha and Thymus.

ECG Identification System Using Neural Network with Global and Local Features

ERIC Educational Resources Information Center

Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

2016-01-01

This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

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.

A network identity authentication protocol of bank account system based on fingerprint identification and mixed encryption

NASA Astrophysics Data System (ADS)

Zhu, Lijuan; Liu, Jingao

2013-07-01

This paper describes a network identity authentication protocol of bank account system based on fingerprint identification and mixed encryption. This protocol can provide every bank user a safe and effective way to manage his own bank account, and also can effectively prevent the hacker attacks and bank clerk crime, so that it is absolute to guarantee the legitimate rights and interests of bank users.

Failure detection and identification for a reconfigurable flight control system

NASA Technical Reports Server (NTRS)

Dallery, Francois

1987-01-01

Failure detection and identification logic for a fault-tolerant longitudinal control system were investigated. Aircraft dynamics were based upon the cruise condition for a hypothetical transonic business jet transport configuration. The fault-tolerant control system consists of conventional control and estimation plus a new outer loop containing failure detection, identification, and reconfiguration (FDIR) logic. It is assumed that the additional logic has access to all measurements, as well as to the outputs of the control and estimation logic. The pilot may also command the FDIR logic to perform special tests.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

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.

Hierarchical minutiae matching for fingerprint and palmprint identification.

PubMed

Chen, Fanglin; Huang, Xiaolin; Zhou, Jie

2013-12-01

Fingerprints and palmprints are the most common authentic biometrics for personal identification, especially for forensic security. Previous research have been proposed to speed up the searching process in fingerprint and palmprint identification systems, such as those based on classification or indexing, in which the deterioration of identification accuracy is hard to avert. In this paper, a novel hierarchical minutiae matching algorithm for fingerprint and palmprint identification systems is proposed. This method decomposes the matching step into several stages and rejects many false fingerprints or palmprints on different stages, thus it can save much time while preserving a high identification rate. Experimental results show that the proposed algorithm can save almost 50% searching time compared with traditional methods and illustrate its effectiveness.

An Intelligent Tutoring System for Antibody Identification

PubMed Central

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

1990-01-01

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

Evaluation of the RapID-ANA system for identification of anaerobic bacteria of veterinary origin.

PubMed

Adney, W S; Jones, R L

1985-12-01

This study evaluated the ability of the RapID-ANA system (Innovative Diagnostic Systems, Inc., Atlanta, Ga.) to accurately identify a spectrum of freshly isolated veterinary anaerobes. A total of 183 isolates were tested and included 7 Actinomyces spp., 53 Bacteroides spp., 32 Clostridium spp., 2 Eubacterium spp., 65 Fusobacterium spp., 1 Peptococcus spp., 22 Peptostreptococcus spp., and 1 Propionibacterium spp. All isolates were initially identified by conventional biochemical testing and gas-liquid chromatography of short-chain fatty acid metabolites. Additional tests were performed as required by the RapID-ANA system. Of these isolates, 81.4% were correctly identified to the genus level, including 59.6% to the species level, 14.2% were incorrectly identified at the genus level, and 4.4% were not identified. Initially, 20.2% of the strains were not identified because the microcodes were not in the code book. The majority of the incorrect identifications were caused by the misidentification of Fusobacterium spp. as Bacteroides spp. Errors also occurred when veterinary anaerobes not included in the data base were assigned an identification from the existing data base. The RapID-ANA system appears to be a promising new method for rapid identification of veterinary anaerobes; however, further evaluation with an extended data base is needed before the system can accurately identify all clinically significant anaerobes.

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.

Identification of open quantum systems from observable time traces

DOE PAGES

Zhang, Jun; Sarovar, Mohan

2015-05-27

Estimating the parameters that dictate the dynamics of a quantum system is an important task for quantum information processing and quantum metrology, as well as fundamental physics. In our paper we develop a method for parameter estimation for Markovian open quantum systems using a temporal record of measurements on the system. Furthermore, the method is based on system realization theory and is a generalization of our previous work on identification of Hamiltonian parameters.

Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

NASA Astrophysics Data System (ADS)

Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

2018-01-01

Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

Comparison of traditional gas chromatography (GC), headspace GC, and the microbial identification library GC system for the identification of Clostridium difficile.

PubMed Central

Cundy, K V; Willard, K E; Valeri, L J; Shanholtzer, C J; Singh, J; Peterson, L R

1991-01-01

Three gas chromatography (GC) methods were compared for the identification of 52 clinical Clostridium difficile isolates, as well as 17 non-C. difficile Clostridium isolates. Headspace GC and Microbial Identification System (MIS) GC, an automated system which utilizes a software library developed at the Virginia Polytechnic Institute to identify organisms based on the fatty acids extracted from the bacterial cell wall, were compared against the reference method of traditional GC. Headspace GC and MIS were of approximately equivalent accuracy in identifying the 52 C. difficile isolates (52 of 52 versus 51 of 52, respectively). However, 7 of 52 organisms required repeated sample preparation before an identification was achieved by the MIS method. Both systems effectively differentiated C. difficile from non-C. difficile clostridia, although the MIS method correctly identified only 9 of 17. We conclude that the headspace GC system is an accurate method of C. difficile identification, which requires only one-fifth of the sample preparation time of MIS GC and one-half of the sample preparation time of traditional GC. PMID:2007632

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.

Effects-Based Operations: Useful or Useless

DTIC Science & Technology

2010-05-03

the effects -based approach largely irrelevant. 30 The idea of Consequence Identification, however, is not to identify all outcomes , but rather to... effects -based thinking could provide operational planners and commanders with a valuable consequence identification tool. It further argues that System...to achieve specific effects that contribute directly to desired military and political outcomes .” 14 Air Force Brig Gen David Deptula further writes

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

MAC, A System for Automatically IPR Identification, Collection and Distribution

NASA Astrophysics Data System (ADS)

Serrão, Carlos

Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

On using the Hilbert transform for blind identification of complex modes: A practical approach

NASA Astrophysics Data System (ADS)

Antunes, Jose; Debut, Vincent; Piteau, Pilippe; Delaune, Xavier; Borsoi, Laurent

2018-01-01

The modal identification of dynamical systems under operational conditions, when subjected to wide-band unmeasured excitations, is today a viable alternative to more traditional modal identification approaches based on processing sets of measured FRFs or impulse responses. Among current techniques for performing operational modal identification, the so-called blind identification methods are the subject of considerable investigation. In particular, the SOBI (Second-Order Blind Identification) method was found to be quite efficient. SOBI was originally developed for systems with normal modes. To address systems with complex modes, various extension approaches have been proposed, in particular: (a) Using a first-order state-space formulation for the system dynamics; (b) Building complex analytic signals from the measured responses using the Hilbert transform. In this paper we further explore the latter option, which is conceptually interesting while preserving the model order and size. Focus is on applicability of the SOBI technique for extracting the modal responses from analytic signals built from a set of vibratory responses. The novelty of this work is to propose a straightforward computational procedure for obtaining the complex cross-correlation response matrix to be used for the modal identification procedure. After clarifying subtle aspects of the general theoretical framework, we demonstrate that the correlation matrix of the analytic responses can be computed through a Hilbert transform of the real correlation matrix, so that the actual time-domain responses are no longer required for modal identification purposes. The numerical validation of the proposed technique is presented based on time-domain simulations of a conceptual physical multi-modal system, designed to display modes ranging from normal to highly complex, while keeping modal damping low and nearly independent of the modal complexity, and which can prove very interesting in test bench applications. Numerical results for complex modal identifications are presented, and the quality of the identified modal matrix and modal responses, extracted using the complex SOBI technique and implementing the proposed formulation, is assessed.

Numerical studies of identification in nonlinear distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Lo, C. K.; Reich, Simeon; Rosen, I. G.

1989-01-01

An abstract approximation framework and convergence theory for the identification of first and second order nonlinear distributed parameter systems developed previously by the authors and reported on in detail elsewhere are summarized and discussed. The theory is based upon results for systems whose dynamics can be described by monotone operators in Hilbert space and an abstract approximation theorem for the resulting nonlinear evolution system. The application of the theory together with numerical evidence demonstrating the feasibility of the general approach are discussed in the context of the identification of a first order quasi-linear parabolic model for one dimensional heat conduction/mass transport and the identification of a nonlinear dissipation mechanism (i.e., damping) in a second order one dimensional wave equation. Computational and implementational considerations, in particular, with regard to supercomputing, are addressed.

Blind identification of the number of sub-carriers for orthogonal frequency division multiplexing-based elastic optical networking

NASA Astrophysics Data System (ADS)

Zhao, Lei; Xu, Hengying; Bai, Chenglin

2018-03-01

In orthogonal frequency division multiplexing (OFDM)-based elastic optical networking (EON), it is imperative to identify unknown parameters of OFDM-based EON signals quickly, intelligently and robustly. Because the number of sub-carriers determines the size of the sub-carriers spacing and then affects the symbol period of the OFDM and the anti-dispersion capability of the system, the identification of the number of sub-carriers has a profound effect on the identification of other key parameters of the system. In this paper, we proposed a method of number identification for sub-carriers of OFDM-based EON signals with help of high-order cyclic cumulant. The specific fourth-order cyclic cumulant exists only at the location of its sub-carriers frequencies. So the identification of the number of sub-carriers can be implemented by detecting the cyclic-frequencies. The proposed scheme in our study can be divided into three sub-stages, i.e. estimating the spectral range, calculating the high-order cyclic cumulant and identifying the number of sub-carriers. When the optical signal-to-noise ratios (OSNR) varied from 16dB to 22dB, the number of sub-carriers (64-512) was successfully identified in the experiment, and from the statistical point of view, the average identification absolute accuracy (IAAs) exceeded 94%.

The clinical information system GastroBase: integration of image processing and laboratory communication.

PubMed

Kocna, P

1995-01-01

GastroBase, a clinical information system, incorporates patient identification, medical records, images, laboratory data, patient history, physical examination, and other patient-related information. Program modules are written in C; all data is processed using Novell-Btrieve data manager. Patient identification database represents the main core of this information systems. A graphic library developed in the past year and graphic modules with a special video-card enables the storing, archiving, and linking of different images to the electronic patient-medical-record. GastroBase has been running for more than four years in daily routine and the database contains more than 25,000 medical records and 1,500 images. This new version of GastroBase is now incorporated into the clinical information system of University Clinic in Prague.

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

PubMed

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

2013-01-01

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

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 %.

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.

Rapid identification of Yersinia pestis and Brucella melitensis by chip-based continuous flow PCR

NASA Astrophysics Data System (ADS)

Dietzsch, Michael; Hlawatsch, Nadine; Melzer, Falk; Tomaso, Herbert; Gärtner, Claudia; Neubauer, Heinrich

2012-06-01

To combat the threat of biological agents like Yersinia pestis and Brucella melitensis in bioterroristic scenarios requires fast, easy-to-use and safe identification systems. In this study we describe a system for rapid amplification of specific genetic markers for the identification of Yersinia pestis and Brucella melitensis. Using chip based PCR and continuous flow technology we were able to amplify the targets simultaneously with a 2-step reaction profile within 20 minutes. The subsequent analysis of amplified fragments by standard gel electrophoresis requires another 45 minutes. We were able to detect both pathogens within 75 minutes being much faster than most other nucleic acid amplification technologies.

Design and implementation of an identification system in construction site safety for proactive accident prevention.

PubMed

Yang, Huanjia; Chew, David A S; Wu, Weiwei; Zhou, Zhipeng; Li, Qiming

2012-09-01

Identifying accident precursors using real-time identity information has great potential to improve safety performance in construction industry, which is still suffering from day to day records of accident fatality and injury. Based on the requirements analysis for identifying precursor and the discussion of enabling technology solutions for acquiring and sharing real-time automatic identification information on construction site, this paper proposes an identification system design for proactive accident prevention to improve construction site safety. Firstly, a case study is conducted to analyze the automatic identification requirements for identifying accident precursors in construction site. Results show that it mainly consists of three aspects, namely access control, training and inspection information and operation authority. The system is then designed to fulfill these requirements based on ZigBee enabled wireless sensor network (WSN), radio frequency identification (RFID) technology and an integrated ZigBee RFID sensor network structure. At the same time, an information database is also designed and implemented, which includes 15 tables, 54 queries and several reports and forms. In the end, a demonstration system based on the proposed system design is developed as a proof of concept prototype. The contributions of this study include the requirement analysis and technical design of a real-time identity information tracking solution for proactive accident prevention on construction sites. The technical solution proposed in this paper has a significant importance in improving safety performance on construction sites. Moreover, this study can serve as a reference design for future system integrations where more functions, such as environment monitoring and location tracking, can be added. Copyright © 2011 Elsevier Ltd. All rights reserved.

Classification of Suncus murinus species complex (Soricidae: Crocidurinae) in Peninsular Malaysia using image analysis and machine learning approaches.

PubMed

Abu, Arpah; Leow, Lee Kien; Ramli, Rosli; Omar, Hasmahzaiti

2016-12-22

Taxonomists frequently identify specimen from various populations based on the morphological characteristics and molecular data. This study looks into another invasive process in identification of house shrew (Suncus murinus) using image analysis and machine learning approaches. Thus, an automated identification system is developed to assist and simplify this task. In this study, seven descriptors namely area, convex area, major axis length, minor axis length, perimeter, equivalent diameter and extent which are based on the shape are used as features to represent digital image of skull that consists of dorsal, lateral and jaw views for each specimen. An Artificial Neural Network (ANN) is used as classifier to classify the skulls of S. murinus based on region (northern and southern populations of Peninsular Malaysia) and sex (adult male and female). Thus, specimen classification using Training data set and identification using Testing data set were performed through two stages of ANNs. At present, the classifier used has achieved an accuracy of 100% based on skulls' views. Classification and identification to regions and sexes have also attained 72.5%, 87.5% and 80.0% of accuracy for dorsal, lateral, and jaw views, respectively. This results show that the shape characteristic features used are substantial because they can differentiate the specimens based on regions and sexes up to the accuracy of 80% and above. Finally, an application was developed and can be used for the scientific community. This automated system demonstrates the practicability of using computer-assisted systems in providing interesting alternative approach for quick and easy identification of unknown species.

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.

Evaluating current automatic de-identification methods with Veteran's health administration clinical documents.

PubMed

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

2012-07-27

The increased use and adoption of Electronic Health Records (EHR) causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI), which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act "Safe Harbor" method.This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA) clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. We installed and evaluated five text de-identification systems "out-of-the-box" using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique 'PHI' category. Performance of the systems was assessed using recall (equivalent to sensitivity) and precision (equivalent to positive predictive value) metrics, as well as the F(2)-measure. Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest "out-of-the-box" F(2)-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F(2)-measure to 79% with partial matches. The "out-of-the-box" evaluation of text de-identification systems provided us with compelling insight about the best methods for de-identification of VHA clinical documents. The errors analysis demonstrated an important need for customization to PHI formats specific to VHA documents. This study informed the planning and development of a "best-of-breed" automatic de-identification application for VHA clinical text.

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

PubMed

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

2013-07-18

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

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

PubMed Central

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

2013-01-01

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

The confidence-accuracy relationship in eyewitness identification: effects of lineup instructions, foil similarity, and target-absent base rates.

PubMed

Brewer, Neil; Wells, Gary L

2006-03-01

Discriminating accurate from mistaken eyewitness identifications is a major issue facing criminal justice systems. This study examined whether eyewitness confidence assists such decisions under a variety of conditions using a confidence-accuracy (CA) calibration approach. Participants (N = 1,200) viewed a simulated crime and attempted 2 separate identifications from 8-person target-present or target-absent lineups. Confidence and accuracy were calibrated for choosers (but not nonchoosers) for both targets under all conditions. Lower overconfidence was associated with higher diagnosticity, lower target-absent base rates, and shorter identification latencies. Although researchers agree that courtroom expressions of confidence are uninformative, our findings indicate that confidence assessments obtained immediately after a positive identification can provide a useful guide for investigators about the likely accuracy of an identification.

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

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

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

Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies.

PubMed

Kushida, Clete A; Nichols, Deborah A; Jadrnicek, Rik; Miller, Ric; Walsh, James K; Griffin, Kara

2012-07-01

De-identification and anonymization are strategies that are used to remove patient identifiers in electronic health record data. The use of these strategies in multicenter research studies is paramount in importance, given the need to share electronic health record data across multiple environments and institutions while safeguarding patient privacy. Systematic literature search using keywords of de-identify, deidentify, de-identification, deidentification, anonymize, anonymization, data scrubbing, and text scrubbing. Search was conducted up to June 30, 2011 and involved 6 different common literature databases. A total of 1798 prospective citations were identified, and 94 full-text articles met the criteria for review and the corresponding articles were obtained. Search results were supplemented by review of 26 additional full-text articles; a total of 120 full-text articles were reviewed. A final sample of 45 articles met inclusion criteria for review and discussion. Articles were grouped into text, images, and biological sample categories. For text-based strategies, the approaches were segregated into heuristic, lexical, and pattern-based systems versus statistical learning-based systems. For images, approaches that de-identified photographic facial images and magnetic resonance image data were described. For biological samples, approaches that managed the identifiers linked with these samples were discussed, particularly with respect to meeting the anonymization requirements needed for Institutional Review Board exemption under the Common Rule. Current de-identification strategies have their limitations, and statistical learning-based systems have distinct advantages over other approaches for the de-identification of free text. True anonymization is challenging, and further work is needed in the areas of de-identification of datasets and protection of genetic information.

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.

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.

Improving substructure identification accuracy of shear structures using virtual control system

NASA Astrophysics Data System (ADS)

Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

2018-02-01

Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

Hypermedia in the Plant Sciences: The Weed Key and Identification System/Videodisc.

ERIC Educational Resources Information Center

Ragan, Lawrence C.

1991-01-01

In cooperation with a university educational technology unit, an agronomy professor used hypercard and videodisk technology to develop a computer program for identification of 181 weed species based on user-selected characteristics. This solution was found during a search for a way to organize course content in a concise, manageable system. (MSE)

Identification of mathematical model of human breathing in system “Artificial lungs – self-contained breathing apparatus”

NASA Astrophysics Data System (ADS)

Onevsky, P. M.; Onevsky, M. P.; Pogonin, V. A.

2018-03-01

The structure and mathematical models of the main subsystems of the control system of the “Artificial Lungs” are presented. This structure implements the process of imitation of human external respiration in the system “Artificial lungs - self-contained breathing apparatus”. A presented algorithm for parametric identification of the model is based on spectral operators, which allows using it in real time.

A new analytical platform based on field-flow fractionation and olfactory sensor to improve the detection of viable and non-viable bacteria in food.

PubMed

Roda, Barbara; Mirasoli, Mara; Zattoni, Andrea; Casale, Monica; Oliveri, Paolo; Bigi, Alessandro; Reschiglian, Pierluigi; Simoni, Patrizia; Roda, Aldo

2016-10-01

An integrated sensing system is presented for the first time, where a metal oxide semiconductor sensor-based electronic olfactory system (MOS array), employed for pathogen bacteria identification based on their volatile organic compound (VOC) characterisation, is assisted by a preliminary separative technique based on gravitational field-flow fractionation (GrFFF). In the integrated system, a preliminary step using GrFFF fractionation of a complex sample provided bacteria-enriched fractions readily available for subsequent MOS array analysis. The MOS array signals were then analysed employing a chemometric approach using principal components analysis (PCA) for a first-data exploration, followed by linear discriminant analysis (LDA) as a classification tool, using the PCA scores as input variables. The ability of the GrFFF-MOS system to distinguish between viable and non-viable cells of the same strain was demonstrated for the first time, yielding 100 % ability of correct prediction. The integrated system was also applied as a proof of concept for multianalyte purposes, for the detection of two bacterial strains (Escherichia coli O157:H7 and Yersinia enterocolitica) simultaneously present in artificially contaminated milk samples, obtaining a 100 % ability of correct prediction. Acquired results show that GrFFF band slicing before MOS array analysis can significantly increase reliability and reproducibility of pathogen bacteria identification based on their VOC production, simplifying the analytical procedure and largely eliminating sample matrix effects. The developed GrFFF-MOS integrated system can be considered a simple straightforward approach for pathogen bacteria identification directly from their food matrix. Graphical abstract An integrated sensing system is presented for pathogen bacteria identification in food, in which field-flow fractionation is exploited to prepare enriched cell fractions prior to their analysis by electronic olfactory system analysis.

Dynamic model of production enterprises based on accounting registers and its identification

NASA Astrophysics Data System (ADS)

Sirazetdinov, R. T.; Samodurov, A. V.; Yenikeev, I. A.; Markov, D. S.

2016-06-01

The report focuses on the mathematical modeling of economic entities based on accounting registers. Developed the dynamic model of financial and economic activity of the enterprise as a system of differential equations. Created algorithms for identification of parameters of the dynamic model. Constructed and identified the model of Russian machine-building enterprises.

Tier identification (TID) for tiered memory characteristics

DOEpatents

Chang, Jichuan; Lim, Kevin T; Ranganathan, Parthasarathy

2014-03-25

A tier identification (TID) is to indicate a characteristic of a memory region associated with a virtual address in a tiered memory system. A thread may be serviced according to a first path based on the TID indicating a first characteristic. The thread may be serviced according to a second path based on the TID indicating a second characteristic.

Process identification of the SCR system of coal-fired power plant for de-NOx based on historical operation data.

PubMed

Li, Jian; Shi, Raoqiao; Xu, Chuanlong; Wang, Shimin

2018-05-08

The selective catalytic reduction (SCR) system, as one principal flue gas treatment method employed for the NO x emission control of the coal-fired power plant, is nonlinear and time-varying with great inertia and large time delay. It is difficult for the present SCR control system to achieve satisfactory performance with the traditional feedback and feedforward control strategies. Although some improved control strategies, such as the Smith predictor control and the model predictive control, have been proposed for this issue, a well-matched identification model is essentially required to realize a superior control of the SCR system. Industrial field experiment is an alternative way to identify the SCR system model in the coal-fired power plant. But it undesirably disturbs the operation system and is costly in time and manpower. In this paper, a process identification model of the SCR system is proposed and developed by applying the asymptotic method to the sufficiently excited data, selected from the original historical operation database of a 350 MW coal-fired power plant according to the condition number of the Fisher information matrix. Numerical simulations are carried out based on the practical historical operation data to evaluate the performance of the proposed model. Results show that the proposed model can efficiently achieve the process identification of the SCR system.

Frequency response function-based explicit framework for dynamic identification in human-structure systems

NASA Astrophysics Data System (ADS)

Wei, Xiaojun; Živanović, Stana

2018-05-01

The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

PubMed

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

HAZARDOUS WASTE IDENTIFICATION

EPA Science Inventory

This research is in direct support of the regulatory reform efforts under the Hazarous Waste Identification (HWIR) and is related to the development of national "exit levels" based on sound scientific data and models. Research focuses on developing a systems approach to modelin...

Ontology-based specification, identification and analysis of perioperative risks.

PubMed

Uciteli, Alexandr; Neumann, Juliane; Tahar, Kais; Saleh, Kutaiba; Stucke, Stephan; Faulbrück-Röhr, Sebastian; Kaeding, André; Specht, Martin; Schmidt, Tobias; Neumuth, Thomas; Besting, Andreas; Stegemann, Dominik; Portheine, Frank; Herre, Heinrich

2017-09-06

Medical personnel in hospitals often works under great physical and mental strain. In medical decision-making, errors can never be completely ruled out. Several studies have shown that between 50 and 60% of adverse events could have been avoided through better organization, more attention or more effective security procedures. Critical situations especially arise during interdisciplinary collaboration and the use of complex medical technology, for example during surgical interventions and in perioperative settings (the period of time before, during and after surgical intervention). In this paper, we present an ontology and an ontology-based software system, which can identify risks across medical processes and supports the avoidance of errors in particular in the perioperative setting. We developed a practicable definition of the risk notion, which is easily understandable by the medical staff and is usable for the software tools. Based on this definition, we developed a Risk Identification Ontology (RIO) and used it for the specification and the identification of perioperative risks. An agent system was developed, which gathers risk-relevant data during the whole perioperative treatment process from various sources and provides it for risk identification and analysis in a centralized fashion. The results of such an analysis are provided to the medical personnel in form of context-sensitive hints and alerts. For the identification of the ontologically specified risks, we developed an ontology-based software module, called Ontology-based Risk Detector (OntoRiDe). About 20 risks relating to cochlear implantation (CI) have already been implemented. Comprehensive testing has indicated the correctness of the data acquisition, risk identification and analysis components, as well as the web-based visualization of results.

Identification procedure for epistemic uncertainties using inverse fuzzy arithmetic

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

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.

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

PubMed

Zeng, Q; Cimino, J J

2001-04-01

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

Advances in Raman spectroscopy for explosive identification in aviation security

NASA Astrophysics Data System (ADS)

Santillán, Javier D.; Brown, Christopher D.; Jalenak, Wayne

2007-04-01

In the operational airport environment, the rapid identification of potentially hazardous materials such as improvised explosive devices, chemical warfare agents and flammable and explosive liquids is increasingly critical. Peroxide-based explosives pose a particularly insidious threat because they can be made from commonly available and relatively innocuous household chemicals, such as bleach and hydrogen peroxide. Raman spectroscopy has been validated as a valuable tool for rapid identification of chemicals, explosives, and narcotics and their precursors while allowing "line-of-sight" interrogation through bottles or other translucent containers. This enables safe identification of both precursor substances, such as acetone, and end-products, such as TATP, without direct sampling, contamination and exposure by security personnel. To date, Raman systems have been laboratory-based, requiring careful operation and maintenance by technology experts. The capital and ongoing expenses of these systems is also significant. Recent advances in Raman component technologies have dramatically reduced the footprint and cost, while improving the reliability and ease of use of Raman spectroscopy systems. Such technologies are not only bringing the lab to the field, but are also protecting civilians and security personnel in the process.

Implanting inequality: empirical evidence of social and ethical risks of implantable radio-frequency identification (RFID) devices.

PubMed

Monahan, Torin; Fisher, Jill A

2010-10-01

The aim of this study was to assess empirically the social and ethical risks associated with implantable radio-frequency identification (RFID) devices. Qualitative research included observational studies in twenty-three U.S. hospitals that have implemented new patient identification systems and eighty semi-structured interviews about the social and ethical implications of new patient identification systems, including RFID implants. The study identified three primary social and ethical risks associated with RFID implants: (i) unfair prioritization of patients based on their participation in the system, (ii) diminished trust of patients by care providers, and (iii) endangerment of patients who misunderstand the capabilities of the systems. RFID implants may aggravate inequalities in access to care without any clear health benefits. This research underscores the importance of critically evaluating new healthcare technologies from the perspective of both normative ethics and empirical ethics.

JellyWeb: an interactive information system on Scyphozoa, Cubozoa and Staurozoa

PubMed Central

Martellos, Stefano; Ukosich, Luca; Avian, Massimo

2016-01-01

Abstract Identification of organisms is traditionally based on the use of “classic” identification keys, normally printed on paper. These keys have several drawbacks: they are mainly based on the systematics, requiring identification of orders, families and genera at first; they are written by experts for other experts, in a specific scientific jargon; they have a “frozen” structure (sequence of theses/antitheses); once published, they cannot be changed or updated without printing a new edition. Due to the use of computers, it is now possible to build new digital identification tools, which: 1) can be produced automatically, if the characters are stored in a database; 2) can be freed from the traditional systematics, giving priority to easy-to-observe characters, incl. those usually uncommon to the classical keys, such as ecology and distribution; 3) can be updated in real time once published on-line; 4) can be available on different media, and on mobile devices. An important feature of these new digital tools is their “collaborative” nature. They can be enriched by the contribution of several researchers, which can cooperate while maintaining rights and property of the resources and data they contribute to the system. JellyWeb, the information system on Scyphozoa, Cubozoa and Staurozoa has been developed in Trieste since 2010. The system was created with the aim of – potentially – becoming a starting point for a wide collaborative effort in developing a user-friendly worldwide digital identification system for jellyfishes. PMID:26877677

Segmentation of financial seals and its implementation on a DSP-based system

NASA Astrophysics Data System (ADS)

He, Jin; Liu, Tiegen; Guo, Jingjing; Zhang, Hao

2009-11-01

Automatic seal imprint identification is an important part of modern financial security. Accurate segmentation is the basis of correct identification. In this paper, a DSP (digital signal processor) based identification system was designed, and an adaptive algorithm was proposed to extract binary seal images from financial instruments. As the kernel of the identification system, a DSP chip of TMS320DM642 was used to implement image processing, controlling and coordinating works of each system module. The proposed algorithm consisted of three stages, including extraction of grayscale seal image, denoising and binarization. A grayscale seal image was extracted by color transform from a financial instrument image. Adaptive morphological operations were used to highlight details of the extracted grayscale seal image and smooth the background. After median filter for noise elimination, the filtered seal image was binarized by Otsu's method. The algorithm was developed based on the DSP development environment CCS and real-time operation system DSP/BIOS. To simplify the implementation of the proposed algorithm, the calibration of white balance and the coarse positioning of the seal imprint were implemented by TMS320DM642 controlling image acquisition. IMGLIB of TMS320DM642 was used for the efficiency improvement. The experiment result showed that financial seal imprints, even with intricate and dense strokes can be correctly segmented by the proposed algorithm. Adhesion and incompleteness distortions in the segmentation results were reduced, even when the original seal imprint had a poor quality.

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.

Characterization of palmprints by wavelet signatures via directional context modeling.

PubMed

Zhang, Lei; Zhang, David

2004-06-01

The palmprint is one of the most reliable physiological characteristics that can be used to distinguish between individuals. Current palmprint-based systems are more user friendly, more cost effective, and require fewer data signatures than traditional fingerprint-based identification systems. The principal lines and wrinkles captured in a low-resolution palmprint image provide more than enough information to uniquely identify an individual. This paper presents a palmprint identification scheme that characterizes a palmprint using a set of statistical signatures. The palmprint is first transformed into the wavelet domain, and the directional context of each wavelet subband is defined and computed in order to collect the predominant coefficients of its principal lines and wrinkles. A set of statistical signatures, which includes gravity center, density, spatial dispersivity and energy, is then defined to characterize the palmprint with the selected directional context values. A classification and identification scheme based on these signatures is subsequently developed. This scheme exploits the features of principal lines and prominent wrinkles sufficiently and achieves satisfactory results. Compared with the line-segments-matching or interesting-points-matching based palmprint verification schemes, the proposed scheme uses a much smaller amount of data signatures. It also provides a convenient classification strategy and more accurate identification.

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

NASA Astrophysics Data System (ADS)

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

1996-03-01

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

Music Identification System Using MPEG-7 Audio Signature Descriptors

PubMed Central

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

2013-01-01

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

Model reference adaptive control (MRAC)-based parameter identification applied to surface-mounted permanent magnet synchronous motor

NASA Astrophysics Data System (ADS)

Zhong, Chongquan; Lin, Yaoyao

2017-11-01

In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the reference model and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.

Data Driven Model Development for the Supersonic Semispan Transport (S(sup 4)T)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2011-01-01

We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models and a data-driven system identification procedure. It is shown via analysis of experimental Super- Sonic SemiSpan Transport (S4T) wind-tunnel data using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

A high-speed BCI based on code modulation VEP

NASA Astrophysics Data System (ADS)

Bin, Guangyu; Gao, Xiaorong; Wang, Yijun; Li, Yun; Hong, Bo; Gao, Shangkai

2011-04-01

Recently, electroencephalogram-based brain-computer interfaces (BCIs) have attracted much attention in the fields of neural engineering and rehabilitation due to their noninvasiveness. However, the low communication speed of current BCI systems greatly limits their practical application. In this paper, we present a high-speed BCI based on code modulation of visual evoked potentials (c-VEP). Thirty-two target stimuli were modulated by a time-shifted binary pseudorandom sequence. A multichannel identification method based on canonical correlation analysis (CCA) was used for target identification. The online system achieved an average information transfer rate (ITR) of 108 ± 12 bits min-1 on five subjects with a maximum ITR of 123 bits min-1 for a single subject.

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.

Bar code-based pre-transfusion check in pre-operative autologous blood donation.

PubMed

Ohsaka, Akimichi; Furuta, Yoshiaki; Ohsawa, Toshiya; Kobayashi, Mitsue; Abe, Katsumi; Inada, Eiichi

2010-10-01

The objective of this study was to demonstrate the feasibility of a bar code-based identification system for the pre-transfusion check at the bedside in the setting of pre-operative autologous blood donation (PABD). Between July 2003 and December 2008 we determined the compliance rate and causes of failure of electronic bedside checking for PABD transfusion. A total of 5627 (9% of all transfusions) PABD units were administered without a single mistransfusion. The overall rate of compliance with electronic checking was 99%. The bar code-based identification system was applicable to the pre-transfusion check for PABD transfusion. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-07-01

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

Software Risk Identification for Interplanetary Probes

NASA Technical Reports Server (NTRS)

Dougherty, Robert J.; Papadopoulos, Periklis E.

2005-01-01

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

Federal Logistics Information System. FLIS Procedures Manual Publications. Volume 15.

DTIC Science & Technology

1995-01-01

which provides for the processing of adjustments/revisions to established item identifications and characteristics in the FLIS Data Base. Item Logistics...A function in FLIS which provides for the processing of adjustments/revisions to established item identifications and characteristics in the FLIS...the materiel management functions for assigned items. Mechanization of Warehousing and Shipment Processing (MOWASP). A uniform data 6 system designed

Flight test planning and parameter extraction for rotorcraft system identification

NASA Technical Reports Server (NTRS)

Wang, J. C.; Demiroz, M. Y.; Talbot, P. D.

1986-01-01

The present study is concerned with the mathematical modelling of aircraft dynamics on the basis of an investigation conducted with the aid of the Rotor System Research Aircraft (RSRA). The particular characteristics of RSRA make it possible to investigate aircraft properties which cannot be readily studied elsewhere, for example in the wind tunnel. The considered experiment had mainly the objective to develop an improved understanding of the physics of rotor flapping dynamics and rotor loads in maneuvers. The employed approach is based on a utilization of parameter identification methodology (PID) with application to helicopters. A better understanding of the contribution of the main rotor to the overall aircraft forces and moments is also to be obtained. Attention is given to the mathematical model of a rotorcraft system, an integrated identification method, flight data processing, and the identification of RSRA mathematical models.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

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.

Optimisation of fluorescence guidance during robot-assisted laparoscopic sentinel node biopsy for prostate cancer.

PubMed

KleinJan, Gijs H; van den Berg, Nynke S; Brouwer, Oscar R; de Jong, Jeroen; Acar, Cenk; Wit, Esther M; Vegt, Erik; van der Noort, Vincent; Valdés Olmos, Renato A; van Leeuwen, Fijs W B; van der Poel, Henk G

2014-12-01

The hybrid tracer was introduced to complement intraoperative radiotracing towards the sentinel nodes (SNs) with fluorescence guidance. Improve in vivo fluorescence-based SN identification for prostate cancer by optimising hybrid tracer preparation, injection technique, and fluorescence imaging hardware. Forty patients with a Briganti nomogram-based risk >10% of lymph node (LN) metastases were included. After intraprostatic tracer injection, SN mapping was performed (lymphoscintigraphy and single-photon emission computed tomography with computed tomography (SPECT-CT)). In groups 1 and 2, SNs were pursued intraoperatively using a laparoscopic gamma probe followed by fluorescence imaging (FI). In group 3, SNs were initially located via FI. Compared with group 1, in groups 2 and 3, a new tracer formulation was introduced that had a reduced total injected volume (2.0 ml vs. 3.2 ml) but increased particle concentration. For groups 1 and 2, the Tricam SLII with D-Light C laparoscopic FI (LFI) system was used. In group 3, the LFI system was upgraded to an Image 1 HUB HD with D-Light P system. Hybrid tracer-based SN biopsy, extended pelvic lymph node dissection, and robot-assisted radical prostatectomy. Number and location of the preoperatively identified SNs, in vivo fluorescence-based SN identification rate, tumour status of SNs and LNs, postoperative complications, and biochemical recurrence (BCR). Mean fluorescence-based SN identification improved from 63.7% (group 1) to 85.2% and 93.5% for groups 2 and 3, respectively (p=0.012). No differences in postoperative complications were found. BCR occurred in three pN0 patients. Stepwise optimisation of the hybrid tracer formulation and the LFI system led to a significant improvement in fluorescence-assisted SN identification. Preoperative SPECT-CT remained essential for guiding intraoperative SN localisation. Intraoperative fluorescence-based SN visualisation can be improved by enhancing the hybrid tracer formulation and laparoscopic fluorescence imaging system. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Inertial parameter identification using contact force information for an unknown object captured by a space manipulator

NASA Astrophysics Data System (ADS)

Chu, Zhongyi; Ma, Ye; Hou, Yueyang; Wang, Fengwen

2017-02-01

This paper presents a novel identification method for the intact inertial parameters of an unknown object in space captured by a manipulator in a space robotic system. With strong dynamic and kinematic coupling existing in the robotic system, the inertial parameter identification of the unknown object is essential for the ideal control strategy based on changes in the attitude and trajectory of the space robot via capturing operations. Conventional studies merely refer to the principle and theory of identification, and an error analysis process of identification is deficient for a practical scenario. To solve this issue, an analysis of the effect of errors on identification is illustrated first, and the accumulation of measurement or estimation errors causing poor identification precision is demonstrated. Meanwhile, a modified identification equation incorporating the contact force, as well as the force/torque of the end-effector, is proposed to weaken the accumulation of errors and improve the identification accuracy. Furthermore, considering a severe disturbance condition caused by various measured noises, the hybrid immune algorithm, Recursive Least Squares and Affine Projection Sign Algorithm (RLS-APSA), is employed to decode the modified identification equation to ensure a stable identification property. Finally, to verify the validity of the proposed identification method, the co-simulation of ADAMS-MATLAB is implemented by multi-degree of freedom models of a space robotic system, and the numerical results show a precise and stable identification performance, which is able to guarantee the execution of aerospace operations and prevent failed control strategies.

De-identification of clinical notes via recurrent neural network and conditional random field.

PubMed

Liu, Zengjian; Tang, Buzhou; Wang, Xiaolong; Chen, Qingcai

2017-11-01

De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-scale and RDOC Individualized Domains (N-GRID) clinical natural language processing (NLP) challenge contains a de-identification track in de-identifying electronic medical records (EMRs) (i.e., track 1). The challenge organizers provide 1000 annotated mental health records for this track, 600 out of which are used as a training set and 400 as a test set. We develop a hybrid system for the de-identification task on the training set. Firstly, four individual subsystems, that is, a subsystem based on bidirectional LSTM (long-short term memory, a variant of recurrent neural network), a subsystem-based on bidirectional LSTM with features, a subsystem based on conditional random field (CRF) and a rule-based subsystem, are used to identify PHI instances. Then, an ensemble learning-based classifiers is deployed to combine all PHI instances predicted by above three machine learning-based subsystems. Finally, the results of the ensemble learning-based classifier and the rule-based subsystem are merged together. Experiments conducted on the official test set show that our system achieves the highest micro F1-scores of 93.07%, 91.43% and 95.23% under the "token", "strict" and "binary token" criteria respectively, ranking first in the 2016 CEGS N-GRID NLP challenge. In addition, on the dataset of 2014 i2b2 NLP challenge, our system achieves the highest micro F1-scores of 96.98%, 95.11% and 98.28% under the "token", "strict" and "binary token" criteria respectively, outperforming other state-of-the-art systems. All these experiments prove the effectiveness of our proposed method. Copyright © 2017. Published by Elsevier Inc.

Modelling of Biometric Identification System with Given Parameters Using Colored Petri Nets

NASA Astrophysics Data System (ADS)

Petrosyan, G.; Ter-Vardanyan, L.; Gaboutchian, A.

2017-05-01

Biometric identification systems use given parameters and function on the basis of Colored Petri Nets as a modelling language developed for systems in which communication, synchronization and distributed resources play an important role. Colored Petri Nets combine the strengths of Classical Petri Nets with the power of a high-level programming language. Coloured Petri Nets have both, formal intuitive and graphical presentations. Graphical CPN model consists of a set of interacting modules which include a network of places, transitions and arcs. Mathematical representation has a well-defined syntax and semantics, as well as defines system behavioural properties. One of the best known features used in biometric is the human finger print pattern. During the last decade other human features have become of interest, such as iris-based or face recognition. The objective of this paper is to introduce the fundamental concepts of Petri Nets in relation to tooth shape analysis. Biometric identification systems functioning has two phases: data enrollment phase and identification phase. During the data enrollment phase images of teeth are added to database. This record contains enrollment data as a noisy version of the biometrical data corresponding to the individual. During the identification phase an unknown individual is observed again and is compared to the enrollment data in the database and then system estimates the individual. The purpose of modeling biometric identification system by means of Petri Nets is to reveal the following aspects of the functioning model: the efficiency of the model, behavior of the model, mistakes and accidents in the model, feasibility of the model simplification or substitution of its separate components for more effective components without interfering system functioning. The results of biometric identification system modeling and evaluating are presented and discussed.

Identification of gram-negative bacilli using the Autobac IDX.

PubMed

Burdash, N M; Welborn, A L; Teti, G; Bannister, E R; Manos, J P

1985-01-01

The Autobac IDX is a new system for the rapid identification of clinically significant members of the Enterobacteriaceae and Aeromonas, Acinetobacter, Alcaligenes, Flavobacterium, Moraxella, and Pseudomonas species. The use of 18 differentially inhibitory compounds such as dyes and antibiotics along with a computerized algorithm based on a multivariate analysis provides the basis for the identification of 30 different groups of gram-negative bacilli. Required preliminary tests include observations on the presence or absence of swarming on a sheep blood agar plate and noting the following: growth, lactose fermentation, and bile precipitation from a MacConkey plate. Spot indole and spot oxidase tests must be performed as well. Identification by the Autobac IDX System takes 3-6 hr after completion of the preliminary tests. From a total of 403 isolates tested, the Autobac system agreed with the MicroID AND N/F systems on 382 identifications (94.8%). Four isolates, two Acinetobacter anitratus, one Serratia marcescens and one Moraxella osloensis could not be identified by IDX. Additional testing was required on 35 (8.7%) of the isolates.

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.

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.

Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots

NASA Astrophysics Data System (ADS)

Chellal, R.; Cuvillon, L.; Laroche, E.

2017-04-01

This paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.

Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Tang, Chenghao

2017-12-01

High sensitivity of a distributed optical-fiber vibration sensing (DOVS) system based on the phase-sensitivity optical time domain reflectometry (Φ-OTDR) technology also brings in high nuisance alarm rates (NARs) in real applications. In this paper, feature extraction methods of wavelet decomposition (WD) and wavelet packet decomposition (WPD) are comparatively studied for three typical field testing signals, and an artificial neural network (ANN) is built for the event identification. The comparison results prove that the WPD performs a little better than the WD for the DOVS signal analysis and identification in oil pipeline safety monitoring. The identification rate can be improved up to 94.4%, and the nuisance alarm rate can be effectively controlled as low as 5.6% for the identification network with the wavelet packet energy distribution features.

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.

Usage of the Upgraded Vassilissa Separator for Synthesis of Super-Heavy Elements

NASA Astrophysics Data System (ADS)

Yeremin, A. V.; Malyshev, O. N.; Popeko, A. G.; Sagaidak, R. N.; Chepigin, V. I.; Kabachenko, A. P.; Belozerov, A. V.; Chelnokov, M. L.; Gorshkov, V. A.; Svirikhin, A. I.; Korotkov, S. P.; Rohach, J.; Brida, I.; Berek, G.

2002-12-01

Electrostatic separator VASSILISSA is used for exploring complete fussion nuclear reactions. The magnetic analyzer, based on D37 dipole magnet, was installed after the second triplet of quadrupole lenses of the separator for the mass identification of evaporation residues. Mass identification is an powerful tool for identification of recoil atoms of super-heavy elements. The new detection system consisting of the time-of-fiight system and 32-strips position-sensitive detector array was installed in the focal plane of the separator. The mass resolution of the separator after upgrade was found to be about 2.5 %.

Fault Identification Based on Nlpca in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhang, Yagang; Wang, Zengping; Zhang, Jinfang

2012-07-01

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

A Novel Fiber Optic Based Surveillance System for Prevention of Pipeline Integrity Threats.

PubMed

Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F; Piote, Daniel; Pastor-Graells, Juan; Martin-Lopez, Sonia; Corredera, Pedro; Gonzalez-Herraez, Miguel

2017-02-12

This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

Automatic Publication of a MIS Product to GeoNetwork: Case of the AIS Indexer

DTIC Science & Technology

2012-11-01

installation and configuration The following instructions are for installing and configuring the software packages Java 1.6 and MySQL 5.5 which are...An Automatic Identification System (AIS) reception indexer Java application was developed in the summer of 2011, based on the work of Lapinski and...release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT An Automatic Identification System (AIS) reception indexer Java application was

Acquisition Management for Systems-of-Systems: Analysis of Alternatives via Computational Exploratory Model

DTIC Science & Technology

2012-02-03

node to the analysis of eigenmodes (connected trees /networks) of disruption sequences. The identification of disruption eigenmodes is particularly...investment portfolio approach enables the identification of optimal SoS network topologies and provides a tool for acquisition professionals to...a program based on its ability to provide a new capability for a given cost, and not on its ability to meet specific performance requirements ( Spacy

Synthesizing spatiotemporally sparse smartphone sensor data for bridge modal identification

NASA Astrophysics Data System (ADS)

Ozer, Ekin; Feng, Maria Q.

2016-08-01

Smartphones as vibration measurement instruments form a large-scale, citizen-induced, and mobile wireless sensor network (WSN) for system identification and structural health monitoring (SHM) applications. Crowdsourcing-based SHM is possible with a decentralized system granting citizens with operational responsibility and control. Yet, citizen initiatives introduce device mobility, drastically changing SHM results due to uncertainties in the time and the space domains. This paper proposes a modal identification strategy that fuses spatiotemporally sparse SHM data collected by smartphone-based WSNs. Multichannel data sampled with the time and the space independence is used to compose the modal identification parameters such as frequencies and mode shapes. Structural response time history can be gathered by smartphone accelerometers and converted into Fourier spectra by the processor units. Timestamp, data length, energy to power conversion address temporal variation, whereas spatial uncertainties are reduced by geolocation services or determining node identity via QR code labels. Then, parameters collected from each distributed network component can be extended to global behavior to deduce modal parameters without the need of a centralized and synchronous data acquisition system. The proposed method is tested on a pedestrian bridge and compared with a conventional reference monitoring system. The results show that the spatiotemporally sparse mobile WSN data can be used to infer modal parameters despite non-overlapping sensor operation schedule.

De-identification of patient notes with recurrent neural networks.

PubMed

Dernoncourt, Franck; Lee, Ji Young; Uzuner, Ozlem; Szolovits, Peter

2017-05-01

Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can only access de-identified notes, in order to protect the confidentiality of patients. In the United States, the Health Insurance Portability and Accountability Act (HIPAA) defines 18 types of protected health information that needs to be removed to de-identify patient notes. Manual de-identification is impractical given the size of electronic health record databases, the limited number of researchers with access to non-de-identified notes, and the frequent mistakes of human annotators. A reliable automated de-identification system would consequently be of high value. We introduce the first de-identification system based on artificial neural networks (ANNs), which requires no handcrafted features or rules, unlike existing systems. We compare the performance of the system with state-of-the-art systems on two datasets: the i2b2 2014 de-identification challenge dataset, which is the largest publicly available de-identification dataset, and the MIMIC de-identification dataset, which we assembled and is twice as large as the i2b2 2014 dataset. Our ANN model outperforms the state-of-the-art systems. It yields an F1-score of 97.85 on the i2b2 2014 dataset, with a recall of 97.38 and a precision of 98.32, and an F1-score of 99.23 on the MIMIC de-identification dataset, with a recall of 99.25 and a precision of 99.21. Our findings support the use of ANNs for de-identification of patient notes, as they show better performance than previously published systems while requiring no manual feature engineering. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Detection of small surface vessels in near, medium, and far infrared spectral bands

NASA Astrophysics Data System (ADS)

Dulski, R.; Milewski, S.; Kastek, M.; Trzaskawka, P.; Szustakowski, M.; Ciurapinski, W.; Zyczkowski, M.

2011-11-01

Protection of naval bases and harbors requires close co-operation between security and access control systems covering land areas and those monitoring sea approach routes. The typical location of naval bases and harbors - usually next to a large city - makes it difficult to detect and identify a threat in the dense regular traffic of various sea vessels (i.e. merchant ships, fishing boats, tourist ships). Due to the properties of vessel control systems, such as AIS (Automatic Identification System), and the effectiveness of radar and optoelectronic systems against different targets it seems that fast motor boats called RIB (Rigid Inflatable Boat) could be the most serious threat to ships and harbor infrastructure. In the paper the process and conditions for the detection and identification of high-speed boats in the areas of ports and naval bases in the near, medium and far infrared is presented. Based on the results of measurements and recorded thermal images the actual temperature contrast delta T (RIB / sea) will be determined, which will further allow to specify the theoretical ranges of detection and identification of the RIB-type targets for an operating security system. The data will also help to determine the possible advantages of image fusion where the component images are taken in different spectral ranges. This will increase the probability of identifying the object by the multi-sensor security system equipped additionally with the appropriate algorithms for detecting, tracking and performing the fusion of images from the visible and infrared cameras.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Sensor network based vehicle classification and license plate identification system

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

Frigo, Janette Rose; Brennan, Sean M; Rosten, Edward J

Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform.more » Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.« less

Acute asthma severity identification of expert system flow in emergency department

NASA Astrophysics Data System (ADS)

Sharif, Nurul Atikah Mohd; Ahmad, Norazura; Ahmad, Nazihah; Desa, Wan Laailatul Hanim Mat

2017-11-01

Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

Continuous-Flow Detector for Rapid Pathogen Identification

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

Barrett, Louise M.; Skulan, Andrew J.; Singh, Anup K.

2006-09-01

This report describes the continued development of a low-power, portable detector for the rapid identification of pathogens such as B. anthracis and smallpox. Based on our successful demonstration of the continuous filter/concentrator inlet, we believe strongly that the inlet section will enable differentiation between viable and non-viable populations, between types of cells, and between pathogens and background contamination. Selective, continuous focusing of particles in a microstream enables highly selective and sensitive identification using fluorescently labeled antibodies and other receptors such as peptides, aptamers, or small ligands to minimize false positives. Processes such as mixing and lysing will also benefit frommore » the highly localized particle streams. The concentrator is based on faceted prisms to contract microfluidic flows while maintaining uniform flowfields. The resulting interfaces, capable of high throughput, serve as high-, low-, and band-pass filters to direct selected bioparticles to a rapid, affinity-based detection system. The proposed device is superior to existing array-based detectors as antibody-pathogen binding can be accomplished in seconds rather than tens of minutes or even hours. The system is being designed to interface with aerosol collectors under development by the National Laboratories or commercial systems. The focused stream is designed to be interrogated using diode lasers to differentiate pathogens by light scattering. Identification of particles is done using fluorescently labeled antibodies to tag the particles, followed by multiplexed laser-induced fluorescence (LIF) detection (achieved by labeling each antibody with a different dye).« less

A study of parameter identification

NASA Technical Reports Server (NTRS)

Herget, C. J.; Patterson, R. E., III

1978-01-01

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Data Driven Model Development for the SuperSonic SemiSpan Transport (S(sup 4)T)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2011-01-01

In this report, we will investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models, and a data-driven system identification procedure. It is shown via analysis of experimental SuperSonic SemiSpan Transport (S4T) wind-tunnel data that by using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Implementing a Multi-Tiered System of Support (MTSS): Collaboration between School Psychologists and Administrators to Promote Systems-Level Change

ERIC Educational Resources Information Center

Eagle, John W.; Dowd-Eagle, Shannon E.; Snyder, Andrew; Holtzman, Elizabeth Gibbons

2015-01-01

Current educational reform mandates the implementation of school-based models for early identification and intervention, progress monitoring, and data-based assessment of student progress. This article provides an overview of interdisciplinary collaboration for systems-level consultation within a Multi-Tiered System of Support (MTSS) framework.…

Evaluation of the Accelerate Pheno System for Fast Identification and Antimicrobial Susceptibility Testing from Positive Blood Cultures in Bloodstream Infections Caused by Gram-Negative Pathogens.

PubMed

Marschal, Matthias; Bachmaier, Johanna; Autenrieth, Ingo; Oberhettinger, Philipp; Willmann, Matthias; Peter, Silke

2017-07-01

Bloodstream infections (BSI) are an important cause of morbidity and mortality. Increasing rates of antimicrobial-resistant pathogens limit treatment options, prompting an empirical use of broad-range antibiotics. Fast and reliable diagnostic tools are needed to provide adequate therapy in a timely manner and to enable a de-escalation of treatment. The Accelerate Pheno system (Accelerate Diagnostics, USA) is a fully automated test system that performs both identification and antimicrobial susceptibility testing (AST) directly from positive blood cultures within approximately 7 h. In total, 115 episodes of BSI with Gram-negative bacteria were included in our study and compared to conventional culture-based methods. The Accelerate Pheno system correctly identified 88.7% (102 of 115) of all BSI episodes and 97.1% (102 of 105) of isolates that are covered by the system's identification panel. The Accelerate Pheno system generated an AST result for 91.3% (95 of 104) samples in which the Accelerate Pheno system identified a Gram-negative pathogen. The overall category agreement between the Accelerate Pheno system and culture-based AST was 96.4%, the rates for minor discrepancies 1.4%, major discrepancies 2.3%, and very major discrepancies 1.0%. Of note, ceftriaxone, piperacillin-tazobactam, and carbapenem resistance was correctly detected in blood culture specimens with extended-spectrum beta-lactamase-producing Escherichia coli ( n = 7) and multidrug-resistant Pseudomonas aeruginosa ( n = 3) strains. The utilization of the Accelerate Pheno system reduced the time to result for identification by 27.49 h ( P < 0.0001) and for AST by 40.39 h ( P < 0.0001) compared to culture-based methods in our laboratory setting. In conclusion, the Accelerate Pheno system provided fast, reliable results while significantly improving turnaround time in blood culture diagnostics of Gram-negative BSI. Copyright © 2017 American Society for Microbiology.

Automatic identification of the reference system based on the fourth ventricular landmarks in T1-weighted MR images.

PubMed

Fu, Yili; Gao, Wenpeng; Chen, Xiaoguang; Zhu, Minwei; Shen, Weigao; Wang, Shuguo

2010-01-01

The reference system based on the fourth ventricular landmarks (including the fastigial point and ventricular floor plane) is used in medical image analysis of the brain stem. The objective of this study was to develop a rapid, robust, and accurate method for the automatic identification of this reference system on T1-weighted magnetic resonance images. The fully automated method developed in this study consisted of four stages: preprocessing of the data set, expectation-maximization algorithm-based extraction of the fourth ventricle in the region of interest, a coarse-to-fine strategy for identifying the fastigial point, and localization of the base point. The method was evaluated on 27 Brain Web data sets qualitatively and 18 Internet Brain Segmentation Repository data sets and 30 clinical scans quantitatively. The results of qualitative evaluation indicated that the method was robust to rotation, landmark variation, noise, and inhomogeneity. The results of quantitative evaluation indicated that the method was able to identify the reference system with an accuracy of 0.7 +/- 0.2 mm for the fastigial point and 1.1 +/- 0.3 mm for the base point. It took <6 seconds for the method to identify the related landmarks on a personal computer with an Intel Core 2 6300 processor and 2 GB of random-access memory. The proposed method for the automatic identification of the reference system based on the fourth ventricular landmarks was shown to be rapid, robust, and accurate. The method has potentially utility in image registration and computer-aided surgery.

A Combined sEMG and Accelerometer System for Monitoring Functional Activity in Stroke.

PubMed

Roy, S; Cheng, M; Chang, S; Moore, J; De Luca, G; Nawab, S; De Luca, C

2014-04-23

Remote monitoring of physical activity using bodyworn sensors provides an alternative to assessment of functional independence by subjective, paper-based questionnaires. This study investigated the classification accuracy of a combined surface electromyographic (sEMG) and accelerometer (ACC) sensor system for monitoring activities of daily living in patients with stroke. sEMG and ACC data were recorded from 10 hemi paretic patients while they carried out a sequence of 11 activities of daily living (Identification tasks), and 10 activities used to evaluate misclassification errors (non-Identification tasks). The sEMG and ACC sensor data were analyzed using a multilayered neural network and an adaptive neuro-fuzzy inference system to identify the minimal sensor configuration needed to accurately classify the identification tasks, with a minimal number of misclassifications from the non-Identification tasks. The results demonstrated that the highest sensitivity and specificity for the identification tasks was achieved using a subset of 4 ACC sensors and adjacent sEMG sensors located on both upper arms, one forearm, and one thigh, respectively. This configuration resulted in a mean sensitivity of 95.0 %, and a mean specificity of 99.7 % for the identification tasks, and a mean misclassification error of < 10% for the non-Identification tasks. The findings support the feasibility of a hybrid sEMG and ACC wearable sensor system for automatic recognition of motor tasks used to assess functional independence in patients with stroke.

Design and Implementation of Mobile Learning System for Soldiers’ Vocational Skill Identification Based on Android

NASA Astrophysics Data System (ADS)

Ma, Jinqiang

2017-09-01

To carry out the identification of the professional skills of the soldiers is to further promote the regularization of the needs of the fire brigade, in accordance with the “public security active forces soldiers professional skills identification implementation approach” to meet the needs of candidates for mobile learning to solve the paper learning materials bring a lot of inconvenience; This article uses the Android technology to develop a set of soldiers professional skills Identification Theory learning app, the learning software based on mobile learning, learning function is perfect, you can learn to practice, to achieve the goal of learning at any time, to enhance the soldier's post ability has a good practical value.

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.

Radar signal categorization using a neural network

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Evaluation of the Vitek MS Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry System for Identification of Clinically Relevant Filamentous Fungi.

PubMed

McMullen, Allison R; Wallace, Meghan A; Pincus, David H; Wilkey, Kathy; Burnham, C A

2016-08-01

Invasive fungal infections have a high rate of morbidity and mortality, and accurate identification is necessary to guide appropriate antifungal therapy. With the increasing incidence of invasive disease attributed to filamentous fungi, rapid and accurate species-level identification of these pathogens is necessary. Traditional methods for identification of filamentous fungi can be slow and may lack resolution. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a rapid and accurate method for identification of bacteria and yeasts, but a paucity of data exists on the performance characteristics of this method for identification of filamentous fungi. The objective of our study was to evaluate the accuracy of the Vitek MS for mold identification. A total of 319 mold isolates representing 43 genera recovered from clinical specimens were evaluated. Of these isolates, 213 (66.8%) were correctly identified using the Vitek MS Knowledge Base, version 3.0 database. When a modified SARAMIS (Spectral Archive and Microbial Identification System) database was used to augment the version 3.0 Knowledge Base, 245 (76.8%) isolates were correctly identified. Unidentified isolates were subcultured for repeat testing; 71/319 (22.3%) remained unidentified. Of the unidentified isolates, 69 were not in the database. Only 3 (0.9%) isolates were misidentified by MALDI-TOF MS (including Aspergillus amoenus [n = 2] and Aspergillus calidoustus [n = 1]) although 10 (3.1%) of the original phenotypic identifications were not correct. In addition, this methodology was able to accurately identify 133/144 (93.6%) Aspergillus sp. isolates to the species level. MALDI-TOF MS has the potential to expedite mold identification, and misidentifications are rare. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Completing fishing monitoring with spaceborne Vessel Detection System (VDS) and Automatic Identification System (AIS) to assess illegal fishing in Indonesia.

PubMed

Longépé, Nicolas; Hajduch, Guillaume; Ardianto, Romy; Joux, Romain de; Nhunfat, Béatrice; Marzuki, Marza I; Fablet, Ronan; Hermawan, Indra; Germain, Olivier; Subki, Berny A; Farhan, Riza; Muttaqin, Ahmad Deni; Gaspar, Philippe

2017-10-26

The Indonesian fisheries management system is now equipped with the state-of-the-art technologies to deter and combat Illegal, Unreported and Unregulated (IUU) fishing. Since October 2014, non-cooperative fishing vessels can be detected from spaceborne Vessel Detection System (VDS) based on high resolution radar imagery, which directly benefits to coordinated patrol vessels in operation context. This study attempts to monitor the amount of illegal fishing in the Arafura Sea based on this new source of information. It is analyzed together with Vessel Monitoring System (VMS) and satellite-based Automatic Identification System (Sat-AIS) data, taking into account their own particularities. From October 2014 to March 2015, i.e. just after the establishment of a new moratorium by the Indonesian authorities, the estimated share of fishing vessels not carrying VMS, thus being illegal, ranges from 42 to 47%. One year later in January 2016, this proportion decreases and ranges from 32 to 42%. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance evaluation of wavelet-based face verification on a PDA recorded database

NASA Astrophysics Data System (ADS)

Sellahewa, Harin; Jassim, Sabah A.

2006-05-01

The rise of international terrorism and the rapid increase in fraud and identity theft has added urgency to the task of developing biometric-based person identification as a reliable alternative to conventional authentication methods. Human Identification based on face images is a tough challenge in comparison to identification based on fingerprints or Iris recognition. Yet, due to its unobtrusive nature, face recognition is the preferred method of identification for security related applications. The success of such systems will depend on the support of massive infrastructures. Current mobile communication devices (3G smart phones) and PDA's are equipped with a camera which can capture both still and streaming video clips and a touch sensitive display panel. Beside convenience, such devices provide an adequate secure infrastructure for sensitive & financial transactions, by protecting against fraud and repudiation while ensuring accountability. Biometric authentication systems for mobile devices would have obvious advantages in conflict scenarios when communication from beyond enemy lines is essential to save soldier and civilian life. In areas of conflict or disaster the luxury of fixed infrastructure is not available or destroyed. In this paper, we present a wavelet-based face verification scheme that have been specifically designed and implemented on a currently available PDA. We shall report on its performance on the benchmark audio-visual BANCA database and on a newly developed PDA recorded audio-visual database that take include indoor and outdoor recordings.

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.

Automatic de-identification of textual documents in the electronic health record: a review of recent research

PubMed Central

2010-01-01

Background In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. Methods This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. Results The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries. Conclusions In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication. PMID:20678228

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

PubMed

Meystre, Stephane M; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2010-08-02

In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries. In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication.

Model of Emotional Expressions in Movements

ERIC Educational Resources Information Center

Rozaliev, Vladimir L.; Orlova, Yulia A.

2013-01-01

This paper presents a new approach to automated identification of human emotions based on analysis of body movements, a recognition of gestures and poses. Methodology, models and automated system for emotion identification are considered. To characterize the person emotions in the model, body movements are described with linguistic variables and a…

Competitive code-based fast palmprint identification using a set of cover trees

NASA Astrophysics Data System (ADS)

Yue, Feng; Zuo, Wangmeng; Zhang, David; Wang, Kuanquan

2009-06-01

A palmprint identification system recognizes a query palmprint image by searching for its nearest neighbor from among all the templates in a database. When applied on a large-scale identification system, it is often necessary to speed up the nearest-neighbor searching process. We use competitive code, which has very fast feature extraction and matching speed, for palmprint identification. To speed up the identification process, we extend the cover tree method and propose to use a set of cover trees to facilitate the fast and accurate nearest-neighbor searching. We can use the cover tree method because, as we show, the angular distance used in competitive code can be decomposed into a set of metrics. Using the Hong Kong PolyU palmprint database (version 2) and a large-scale palmprint database, our experimental results show that the proposed method searches for nearest neighbors faster than brute force searching.

Early Engagement of Safety and Mission Assurance Expertise Using Systems Engineering Tools: A Risk-Based Approach to Early Identification of Safety and Assurance Requirements

NASA Technical Reports Server (NTRS)

Darpel, Scott; Beckman, Sean

2016-01-01

Decades of systems engineering practice have demonstrated that the earlier the identification of requirements occurs, the lower the chance that costly redesigns will needed later in the project life cycle. A better understanding of all requirements can also improve the likelihood of a design's success. Significant effort has been put into developing tools and practices that facilitate requirements determination, including those that are part of the model-based systems engineering (MBSE) paradigm. These efforts have yielded improvements in requirements definition, but have thus far focused on a design's performance needs. The identification of safety & mission assurance (S&MA) related requirements, in comparison, can occur after preliminary designs are already established, yielding forced redesigns. Engaging S&MA expertise at an earlier stage, facilitated by the use of MBSE tools, and focused on actual project risk, can yield the same type of design life cycle improvements that have been realized in technical and performance requirements.

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

Network-Based Approaches in Drug Discovery and Early Development

PubMed Central

Harrold, JM; Ramanathan, M; Mager, DE

2015-01-01

Identification of novel targets is a critical first step in the drug discovery and development process. Most diseases such as cancer, metabolic disorders, and neurological disorders are complex, and their pathogenesis involves multiple genetic and environmental factors. Finding a viable drug target–drug combination with high potential for yielding clinical success within the efficacy–toxicity spectrum is extremely challenging. Many examples are now available in which network-based approaches show potential for the identification of novel targets and for the repositioning of established targets. The objective of this article is to highlight network approaches for identifying novel targets with greater chances of gaining approved drugs with maximal efficacy and minimal side effects. Further enhancement of these approaches may emerge from effectively integrating computational systems biology with pharmacodynamic systems analysis. Coupling genomics, proteomics, and metabolomics databases with systems pharmacology modeling may aid in the development of disease-specific networks that can be further used to build confidence in target identification. PMID:24025802

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.

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.

Agile SE Enablers and Quantification Project: Identification, Characterization, and Evaluation Criteria for Systems Engineering Agile Enablers

DTIC Science & Technology

2015-01-16

Enablers Draft Technical Report SERC -2015-049-1 January 16, 2015 Principal Investigator: Dr. Richard Turner, Stevens Institute of...Hudson, Hoboken, NJ 07030 1 Copyright © 2015 Stevens Institute of Technology The Systems Engineering Research Center ( SERC ) is a federally...inappropriate enablers are not pursued. The identification criteria developed for RT-124 are based on earlier SERC work. [4, 5, 6]: 1 Operated by DAU

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.

Person identification by using 3D palmprint data

NASA Astrophysics Data System (ADS)

Bai, Xuefei; Huang, Shujun; Gao, Nan; Zhang, Zonghua

2016-11-01

Person identification based on biometrics is drawing more and more attentions in identity and information safety. This paper presents a biometric system to identify person using 3D palmprint data, including a non-contact system capturing 3D palmprint quickly and a method identifying 3D palmprint fast. In order to reduce the effect of slight shaking of palm on the data accuracy, a DLP (Digital Light Processing) projector is utilized to trigger a CCD camera based on structured-light and triangulation measurement and 3D palmprint data could be gathered within 1 second. Using the obtained database and the PolyU 3D palmprint database, feature extraction and matching method is presented based on MCI (Mean Curvature Image), Gabor filter and binary code list. Experimental results show that the proposed method can identify a person within 240 ms in the case of 4000 samples. Compared with the traditional 3D palmprint recognition methods, the proposed method has high accuracy, low EER (Equal Error Rate), small storage space, and fast identification speed.

Multilingual Data Selection for Low Resource Speech Recognition

DTIC Science & Technology

2016-09-12

Figure 1: Identification of language clusters using scores from an LID system training languages used in the Base and OP1 evaluation periods of the Babel...the posterior scores over frames. For a set of languages that are used to train the lan- guage identification (LID) network, pairs of languages that...which are combined during test time to produce 10 dimensional language 3854 Figure 3: Identification of language clusters using scores from individually

Automatic Identification of Subtechniques in Skating-Style Roller Skiing Using Inertial Sensors

PubMed Central

Sakurai, Yoshihisa; Fujita, Zenya; Ishige, Yusuke

2016-01-01

This study aims to develop and validate an automated system for identifying skating-style cross-country subtechniques using inertial sensors. In the first experiment, the performance of a male cross-country skier was used to develop an automated identification system. In the second, eight male and seven female college cross-country skiers participated to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, and a small video camera on a backpack. All subjects skied through a 3450 m roller ski course using a skating style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, as well as by visual observations from a video recording of the same ski run. The system correctly identified 6418 subtechniques from a total of 6768 cycles, which indicates an accuracy of 94.8%. The precisions of the automatic system for identifying the V1R, V1L, V2R, V2L, V2AR, and V2AL subtechniques were 87.6%, 87.0%, 97.5%, 97.8%, 92.1%, and 92.0%, respectively. Most incorrect identification cases occurred during a subtechnique identification that included a transition and turn event. Identification accuracy can be improved by separately identifying transition and turn events. This system could be used to evaluate each skier’s subtechniques in course conditions. PMID:27049388

Computerized bar code-based blood identification systems and near-miss transfusion episodes and transfusion errors.

PubMed

Nuttall, Gregory A; Abenstein, John P; Stubbs, James R; Santrach, Paula; Ereth, Mark H; Johnson, Pamela M; Douglas, Emily; Oliver, William C

2013-04-01

To determine whether the use of a computerized bar code-based blood identification system resulted in a reduction in transfusion errors or near-miss transfusion episodes. Our institution instituted a computerized bar code-based blood identification system in October 2006. After institutional review board approval, we performed a retrospective study of transfusion errors from January 1, 2002, through December 31, 2005, and from January 1, 2007, through December 31, 2010. A total of 388,837 U were transfused during the 2002-2005 period. There were 6 misidentification episodes of a blood product being transfused to the wrong patient during that period (incidence of 1 in 64,806 U or 1.5 per 100,000 transfusions; 95% CI, 0.6-3.3 per 100,000 transfusions). There was 1 reported near-miss transfusion episode (incidence of 0.3 per 100,000 transfusions; 95% CI, <0.1-1.4 per 100,000 transfusions). A total of 304,136 U were transfused during the 2007-2010 period. There was 1 misidentification episode of a blood product transfused to the wrong patient during that period when the blood bag and patient's armband were scanned after starting to transfuse the unit (incidence of 1 in 304,136 U or 0.3 per 100,000 transfusions; 95% CI, <0.1-1.8 per 100,000 transfusions; P=.14). There were 34 reported near-miss transfusion errors (incidence of 11.2 per 100,000 transfusions; 95% CI, 7.7-15.6 per 100,000 transfusions; P<.001). Institution of a computerized bar code-based blood identification system was associated with a large increase in discovered near-miss events. Copyright © 2013 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Robust uncertainty evaluation for system identification on distributed wireless platforms

NASA Astrophysics Data System (ADS)

Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

2016-04-01

Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on data from a progressive damage action on a prestressed concrete bridge. References [1] E. Carden and P. Fanning. Vibration based condition monitoring: a review. Structural Health Monitoring, 3(4):355-377, 2004. [2] M. Döhler and L. Mevel. Efficient multi-order uncertainty computation for stochastic subspace identification. Mechanical Systems and Signal Processing, 38(2):346-366, 2013. [3] M.Döhler, L. Mevel. Modular subspace-based system identification from multi-setup measurements. IEEE Transactions on Automatic Control, 57(11):2951-2956, 2012. [4] M. Döhler, X.-B. Lam, and L. Mevel. Uncertainty quantification for modal parameters from stochastic subspace identification on multi-setup measurements. MechanicalSystems and Signal Processing, 36(2):562-581, 2013. [5] A Crinière, J Dumoulin, L Mevel, G Andrade-Barosso, M Simonin. The Cloud2SM Project.European Geosciences Union General Assembly (EGU2015), Apr 2015, Vienne, Austria. 2015.

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.

Development of a New Marker System for Identification of Spirodela polyrhiza and Landoltia punctata

PubMed Central

Feng, Bo; Fang, Yang; Xu, Zhibin; Xiang, Chao; Zhou, Chunhong; Jiang, Fei; Wang, Tao

2017-01-01

Lemnaceae (commonly called duckweed) is an aquatic plant ideal for quantitative analysis in plant sciences. Several species of this family represent the smallest and fastest growing flowering plants. Different ecotypes of the same species vary in their biochemical and physiological properties. Thus, selecting of desirable ecotypes of a species is very important. Here, we developed a simple and rapid molecular identification system for Spirodela polyrhiza and Landoltia punctata based on the sequence polymorphism. First, several pairs of primers were designed and three markers were selected as good for identification. After PCR amplification, DNA fragments (the combination of three PCR products) in different duckweeds were detected using capillary electrophoresis. The high-resolution capillary electrophoresis displayed high identity to the sequencing results. The combination of the PCR products containing several DNA fragments highly improved the identification frequency. These results indicate that this method is not only good for interspecies identification but also ideal for intraspecies distinguishing. Meanwhile, 11 haplotypes were found in both the S. polyrhiza and L. punctata ecotypes. The results suggest that this marker system is useful for large-scale identification of duckweed and for the screening of desirable ecotypes to improve the diverse usage in duckweed utilization. PMID:28168191

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

DOE PAGES

Liu, Hesen; Zhu, Lin; Pan, Zhuohong; ...

2015-09-14

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-outputmore » (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.« less

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.

Quantum Hamiltonian identification from measurement time traces.

PubMed

Zhang, Jun; Sarovar, Mohan

2014-08-22

Precise identification of parameters governing quantum processes is a critical task for quantum information and communication technologies. In this Letter, we consider a setting where system evolution is determined by a parametrized Hamiltonian, and the task is to estimate these parameters from temporal records of a restricted set of system observables (time traces). Based on the notion of system realization from linear systems theory, we develop a constructive algorithm that provides estimates of the unknown parameters directly from these time traces. We illustrate the algorithm and its robustness to measurement noise by applying it to a one-dimensional spin chain model with variable couplings.

Electronic labelling in recycling of manufactured articles.

PubMed

Olejnik, Lech; Krammer, Alfred

2002-12-01

The concept of a recycling system aiming at the recovery of resources from manufactured articles is proposed. The system integrates electronic labels for product identification and internet for global data exchange. A prototype for the recycling of electric motors has been developed, which implements a condition-based recycling decision system to automatically select the environmentally and economically appropriate recycling strategy, thereby opening a potential market for second-hand motors and creating a profitable recycling process itself. The project has been designed to evaluate the feasibility of electronic identification applied on a large number of motors and to validate the system in real field conditions.

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.

Identification of Putative Cardiovascular System Developmental Toxicants using a Classification Model based on Signaling Pathway-Adverse Outcome Pathways

EPA Science Inventory

An important challenge for an integrative approach to developmental systems toxicology is associating putative molecular initiating events (MIEs), cell signaling pathways, cell function and modeled fetal exposure kinetics. We have developed a chemical classification model based o...

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.

Multicenter Evaluation of the Vitek MS Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry System for Identification of Gram-Positive Aerobic Bacteria

PubMed Central

Burnham, Carey-Ann D.; Bythrow, Maureen; Garner, Omai B.; Ginocchio, Christine C.; Jennemann, Rebecca; Lewinski, Michael A.; Manji, Ryhana; Mochon, A. Brian; Procop, Gary W.; Richter, Sandra S.; Sercia, Linda; Westblade, Lars F.; Ferraro, Mary Jane; Branda, John A.

2013-01-01

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF) is gaining momentum as a tool for bacterial identification in the clinical microbiology laboratory. Compared with conventional methods, this technology can more readily and conveniently identify a wide range of organisms. Here, we report the findings from a multicenter study to evaluate the Vitek MS v2.0 system (bioMérieux, Inc.) for the identification of aerobic Gram-positive bacteria. A total of 1,146 unique isolates, representing 13 genera and 42 species, were analyzed, and results were compared to those obtained by nucleic acid sequence-based identification as the reference method. For 1,063 of 1,146 isolates (92.8%), the Vitek MS provided a single identification that was accurate to the species level. For an additional 31 isolates (2.7%), multiple possible identifications were provided, all correct at the genus level. Mixed-genus or single-choice incorrect identifications were provided for 18 isolates (1.6%). Although no identification was obtained for 33 isolates (2.9%), there was no specific bacterial species for which the Vitek MS consistently failed to provide identification. In a subset of 463 isolates representing commonly encountered important pathogens, 95% were accurately identified to the species level and there were no misidentifications. Also, in all but one instance, the Vitek MS correctly differentiated Streptococcus pneumoniae from other viridans group streptococci. The findings demonstrate that the Vitek MS system is highly accurate for the identification of Gram-positive aerobic bacteria in the clinical laboratory setting. PMID:23658261

Multicenter evaluation of the Vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Gram-positive aerobic bacteria.

PubMed

Rychert, Jenna; Burnham, Carey-Ann D; Bythrow, Maureen; Garner, Omai B; Ginocchio, Christine C; Jennemann, Rebecca; Lewinski, Michael A; Manji, Ryhana; Mochon, A Brian; Procop, Gary W; Richter, Sandra S; Sercia, Linda; Westblade, Lars F; Ferraro, Mary Jane; Branda, John A

2013-07-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF) is gaining momentum as a tool for bacterial identification in the clinical microbiology laboratory. Compared with conventional methods, this technology can more readily and conveniently identify a wide range of organisms. Here, we report the findings from a multicenter study to evaluate the Vitek MS v2.0 system (bioMérieux, Inc.) for the identification of aerobic Gram-positive bacteria. A total of 1,146 unique isolates, representing 13 genera and 42 species, were analyzed, and results were compared to those obtained by nucleic acid sequence-based identification as the reference method. For 1,063 of 1,146 isolates (92.8%), the Vitek MS provided a single identification that was accurate to the species level. For an additional 31 isolates (2.7%), multiple possible identifications were provided, all correct at the genus level. Mixed-genus or single-choice incorrect identifications were provided for 18 isolates (1.6%). Although no identification was obtained for 33 isolates (2.9%), there was no specific bacterial species for which the Vitek MS consistently failed to provide identification. In a subset of 463 isolates representing commonly encountered important pathogens, 95% were accurately identified to the species level and there were no misidentifications. Also, in all but one instance, the Vitek MS correctly differentiated Streptococcus pneumoniae from other viridans group streptococci. The findings demonstrate that the Vitek MS system is highly accurate for the identification of Gram-positive aerobic bacteria in the clinical laboratory setting.

An approximation theory for the identification of linear thermoelastic systems

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

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

Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized inmore » the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.« less

Nonlinear dynamic macromodeling techniques for audio systems

NASA Astrophysics Data System (ADS)

Ogrodzki, Jan; Bieńkowski, Piotr

2015-09-01

This paper develops a modelling method and a models identification technique for the nonlinear dynamic audio systems. Identification is performed by means of a behavioral approach based on a polynomial approximation. This approach makes use of Discrete Fourier Transform and Harmonic Balance Method. A model of an audio system is first created and identified and then it is simulated in real time using an algorithm of low computational complexity. The algorithm consists in real time emulation of the system response rather than in simulation of the system itself. The proposed software is written in Python language using object oriented programming techniques. The code is optimized for a multithreads environment.

ArcAtlas in the Classroom: Pattern Identification, Description, and Explanation

ERIC Educational Resources Information Center

DeMers, Michael N.; Vincent, Jeffrey S.

2007-01-01

The use of geographic information systems (GIS) in the classroom provides a robust and effective method of teaching the primary spatial skills of identification, description, and explanation of spatial pattern. A major handicap for the development of GIS-based learning experiences, especially for non-GIS specialist educators, is the availability…

Technology-Enhanced Formative Assessment of Plant Identification

ERIC Educational Resources Information Center

Conejo, Ricardo; Garcia-Viñas, Juan Ignacio; Gastón, Aitor; Barros, Beatriz

2016-01-01

Developing plant identification skills is an important part of the curriculum of any botany course in higher education. Frequent practice with dried and fresh plants is necessary to recognize the diversity of forms, states, and details that a species can present. We have developed a web-based assessment system for mobile devices that is able to…

Automatic Molar Extraction from Dental Panoramic Radiographs for Forensic Personal Identification

NASA Astrophysics Data System (ADS)

Samopa, Febriliyan; Asano, Akira; Taguchi, Akira

Measurement of an individual molar provides rich information for forensic personal identification. We propose a computer-based system for extracting an individual molar from dental panoramic radiographs. A molar is obtained by extracting the region-of-interest, separating the maxilla and mandible, and extracting the boundaries between teeth. The proposed system is almost fully automatic; all that the user has to do is clicking three points on the boundary between the maxilla and the mandible.

High frequency modal identification on noisy high-speed camera data

NASA Astrophysics Data System (ADS)

Javh, Jaka; Slavič, Janko; Boltežar, Miha

2018-01-01

Vibration measurements using optical full-field systems based on high-speed footage are typically heavily burdened by noise, as the displacement amplitudes of the vibrating structures are often very small (in the range of micrometers, depending on the structure). The modal information is troublesome to measure as the structure's response is close to, or below, the noise level of the camera-based measurement system. This paper demonstrates modal parameter identification for such noisy measurements. It is shown that by using the Least-Squares Complex-Frequency method combined with the Least-Squares Frequency-Domain method, identification at high-frequencies is still possible. By additionally incorporating a more precise sensor to identify the eigenvalues, a hybrid accelerometer/high-speed camera mode shape identification is possible even below the noise floor. An accelerometer measurement is used to identify the eigenvalues, while the camera measurement is used to produce the full-field mode shapes close to 10 kHz. The identified modal parameters improve the quality of the measured modal data and serve as a reduced model of the structure's dynamics.

Computer-assisted bar-coding system significantly reduces clinical laboratory specimen identification errors in a pediatric oncology hospital.

PubMed

Hayden, Randall T; Patterson, Donna J; Jay, Dennis W; Cross, Carl; Dotson, Pamela; Possel, Robert E; Srivastava, Deo Kumar; Mirro, Joseph; Shenep, Jerry L

2008-02-01

To assess the ability of a bar code-based electronic positive patient and specimen identification (EPPID) system to reduce identification errors in a pediatric hospital's clinical laboratory. An EPPID system was implemented at a pediatric oncology hospital to reduce errors in patient and laboratory specimen identification. The EPPID system included bar-code identifiers and handheld personal digital assistants supporting real-time order verification. System efficacy was measured in 3 consecutive 12-month time frames, corresponding to periods before, during, and immediately after full EPPID implementation. A significant reduction in the median percentage of mislabeled specimens was observed in the 3-year study period. A decline from 0.03% to 0.005% (P < .001) was observed in the 12 months after full system implementation. On the basis of the pre-intervention detected error rate, it was estimated that EPPID prevented at least 62 mislabeling events during its first year of operation. EPPID decreased the rate of misidentification of clinical laboratory samples. The diminution of errors observed in this study provides support for the development of national guidelines for the use of bar coding for laboratory specimens, paralleling recent recommendations for medication administration.

Chip-based droplet sorting

DOEpatents

Beer, Neil Reginald; Lee, Abraham; Hatch, Andrew

2014-07-01

A non-contact system for sorting monodisperse water-in-oil emulsion droplets in a microfluidic device based on the droplet's contents and their interaction with an applied electromagnetic field or by identification and sorting.

An Oracle-based co-training framework for writer identification in offline handwriting

NASA Astrophysics Data System (ADS)

Porwal, Utkarsh; Rajan, Sreeranga; Govindaraju, Venu

2012-01-01

State-of-the-art techniques for writer identification have been centered primarily on enhancing the performance of the system for writer identification. Machine learning algorithms have been used extensively to improve the accuracy of such system assuming sufficient amount of data is available for training. Little attention has been paid to the prospect of harnessing the information tapped in a large amount of un-annotated data. This paper focuses on co-training based framework that can be used for iterative labeling of the unlabeled data set exploiting the independence between the multiple views (features) of the data. This paradigm relaxes the assumption of sufficiency of the data available and tries to generate labeled data from unlabeled data set along with improving the accuracy of the system. However, performance of co-training based framework is dependent on the effectiveness of the algorithm used for the selection of data points to be added in the labeled set. We propose an Oracle based approach for data selection that learns the patterns in the score distribution of classes for labeled data points and then predicts the labels (writers) of the unlabeled data point. This method for selection statistically learns the class distribution and predicts the most probable class unlike traditional selection algorithms which were based on heuristic approaches. We conducted experiments on publicly available IAM dataset and illustrate the efficacy of the proposed approach.

Biometric identification based on novel frequency domain facial asymmetry measures

NASA Astrophysics Data System (ADS)

Mitra, Sinjini; Savvides, Marios; Vijaya Kumar, B. V. K.

2005-03-01

In the modern world, the ever-growing need to ensure a system's security has spurred the growth of the newly emerging technology of biometric identification. The present paper introduces a novel set of facial biometrics based on quantified facial asymmetry measures in the frequency domain. In particular, we show that these biometrics work well for face images showing expression variations and have the potential to do so in presence of illumination variations as well. A comparison of the recognition rates with those obtained from spatial domain asymmetry measures based on raw intensity values suggests that the frequency domain representation is more robust to intra-personal distortions and is a novel approach for performing biometric identification. In addition, some feature analysis based on statistical methods comparing the asymmetry measures across different individuals and across different expressions is presented.

Physician staffed helicopter emergency medical service case identification - a before and after study in children.

PubMed

Garner, Alan A; Lee, Anna; Weatherall, Andrew; Langcake, Mary; Balogh, Zsolt J

2016-07-12

Severely injured children may have better outcomes when transported directly to a Paediatric Trauma Centre (PTC). A case identification system using the crew of a physician staffed helicopter emergency medical service (P-HEMS) that identified severely injured children for P-HEMS dispatch was previously associated with high rates of direct transfer. It was theorised that discontinuation of this system may have resulted in deterioration of system performance. Severe paediatric trauma cases were identified from a state based trauma registry over two time periods. In Period A the P-HEMS case identification system operated in parallel with a paramedic dispatcher (Rapid Launch Trauma Co-ordinator-RLTC) operating from a central control room (n = 71). In Period B the paramedic dispatcher operated in isolation (n = 126). Case identification and direct transfer rates were compared as was time to arrival at the PTC. After cessation of the P-HEMS system the rate of case identification fell from 62 to 31 % (P < 0.001), identification of fatal cases fell from 100 to 47 % (P < 0.001), the rate of direct transfer to a PTC fell from 66 to 53 % (P = 0.076) and the time to arrival in a PTC increased from a median 69 (interquartile range 52 - 104) mins to 97 (interquartile range 56 - 305) mins (P = 0.003). When analysing the rate of direct transfer to a PTC as a function of team composition, after adjusting for age and injury severity scores, there was no change in the rate between the physician and paramedic groups across the two time periods (relative risk 0.92, 95 % CI: 0.44 to 1.41). The parallel identification system improves case identification rates and decreases time to arrival at the PTC, whilst requiring RLTC authorisation preserves the safety and efficiency benefits of centralised dispatch. The model could be extended to adult patients with similar benefits. A case identification system relying solely on RLTC paramedics resulted in a significantly lower case identification rate and increased prehospital time with a non-significant fall in direct transfer rate to the PTC. The elimination of the P-HEMS input from the tasking system resulted in worse performance indicators and has the potential for poorer outcomes.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

The development of small-scale mechanization means positioning algorithm using radio frequency identification technology in industrial plants

NASA Astrophysics Data System (ADS)

Astafiev, A.; Orlov, A.; Privezencev, D.

2018-01-01

The article is devoted to the development of technology and software for the construction of positioning and control systems for small mechanization in industrial plants based on radio frequency identification methods, which will be the basis for creating highly efficient intelligent systems for controlling the product movement in industrial enterprises. The main standards that are applied in the field of product movement control automation and radio frequency identification are considered. The article reviews modern publications and automation systems for the control of product movement developed by domestic and foreign manufacturers. It describes the developed algorithm for positioning of small-scale mechanization means in an industrial enterprise. Experimental studies in laboratory and production conditions have been conducted and described in the article.

Development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification

NASA Astrophysics Data System (ADS)

Astafiev, A.; Orlov, A.; Privezencev, D.

2018-01-01

The article is devoted to the development of technology and software for the construction of positioning and control systems in industrial plants based on aggregation to determine the current storage area using computer vision and radiofrequency identification. It describes the developed of the project of hardware for industrial products positioning system in the territory of a plant on the basis of radio-frequency grid. It describes the development of the project of hardware for industrial products positioning system in the plant on the basis of computer vision methods. It describes the development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification. Experimental studies in laboratory and production conditions have been conducted and described in the article.

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.

Development of an adaptive failure detection and identification system for detecting aircraft control element failures

NASA Technical Reports Server (NTRS)

Bundick, W. Thomas

1990-01-01

A methodology for designing a failure detection and identification (FDI) system to detect and isolate control element failures in aircraft control systems is reviewed. An FDI system design for a modified B-737 aircraft resulting from this methodology is also reviewed, and the results of evaluating this system via simulation are presented. The FDI system performed well in a no-turbulence environment, but it experienced an unacceptable number of false alarms in atmospheric turbulence. An adaptive FDI system, which adjusts thresholds and other system parameters based on the estimated turbulence level, was developed and evaluated. The adaptive system performed well over all turbulence levels simulated, reliably detecting all but the smallest magnitude partially-missing-surface failures.

Direct maldi-tof mass spectrometry assay of blood culture broths for rapid identification of Candida species causing bloodstream infections: an observational study in two large microbiology laboratories.

PubMed

Spanu, Teresa; Posteraro, Brunella; Fiori, Barbara; D'Inzeo, Tiziana; Campoli, Serena; Ruggeri, Alberto; Tumbarello, Mario; Canu, Giulia; Trecarichi, Enrico Maria; Parisi, Gabriella; Tronci, Mirella; Sanguinetti, Maurizio; Fadda, Giovanni

2012-01-01

We evaluated the reliability of the Bruker Daltonik's MALDI Biotyper system in species-level identification of yeasts directly from blood culture bottles. Identification results were concordant with those of the conventional culture-based method for 95.9% of Candida albicans (187/195) and 86.5% of non-albicans Candida species (128/148). Results were available in 30 min (median), suggesting that this approach is a reliable, time-saving tool for routine identification of Candida species causing bloodstream infection.

Text block identification in restoration process of Javanese script damage

NASA Astrophysics Data System (ADS)

Himamunanto, A. R.; Setyowati, E.

2018-05-01

Generally, in a sheet of documents there are two objects of information, namely text and image. A text block area in the sheet of manuscript is a vital object because the restoration process would be done only in this object. Text block or text area identification becomes an important step before. This paper describes the steps leading to the restoration of Java script destruction. The process stages are: pre-processing, identification of text block, segmentation, damage identification, restoration. The test result based on the input manuscript “Hamong Tani” show that the system works with a success rate of 82.07%

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS ...

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identification Guidance provides a rigorous and scientifically defensible method for determining the causes of biological impairments of aquatic ecosystems. It is being used by states as part of the TMDL process and is being applied to other impaired ecosystems such as Superfund sites. However, because of the complexity of causal relationships in ecosystems, and because the guidance includes a strength-of-evidence analysis which uses multiple causal considerations, the process is complex and information intensive. CADDIS helps users deal with that inherent complexity. Increasingly, the regulatory, remedial, and restoration actions taken to manage impaired environments are based on measurement and analysis of the biotic community. When an aquatic assemblage has been identified as impaired, an accurate and defensible assessment of the cause can help ensure that appropriate actions are taken. The U.S. EPA's Stressor Identification Guidance describes a methodology for identifying the most likely causes of observed impairments in aquatic systems. Stressor identification requires extensive knowledge of the mechanisms, symptoms, and stressor-response relationships for various specific stressors as well as the ability to use that knowledge in a

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.

Lower Mississippi River Ports and Waterways Safety System (PAWSS) RF coverage test results

DOT National Transportation Integrated Search

1999-11-01

The Coast Guard plans to operate an Automatic Identification System (AID) Digital Selective Calling (DSC) based transponder system as part of the Ports and Waterways Safety System (PAWSS) in the lower Mississippi River. the AIS uses two duplex channe...

Human Activity Recognition in AAL Environments Using Random Projections.

PubMed

Damaševičius, Robertas; Vasiljevas, Mindaugas; Šalkevičius, Justas; Woźniak, Marcin

2016-01-01

Automatic human activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors attached to the subject's body and permit continuous monitoring of numerous physiological signals reflecting the state of human actions. Successful identification of human activities can be immensely useful in healthcare applications for Ambient Assisted Living (AAL), for automatic and intelligent activity monitoring systems developed for elderly and disabled people. In this paper, we propose the method for activity recognition and subject identification based on random projections from high-dimensional feature space to low-dimensional projection space, where the classes are separated using the Jaccard distance between probability density functions of projected data. Two HAR domain tasks are considered: activity identification and subject identification. The experimental results using the proposed method with Human Activity Dataset (HAD) data are presented.

Human Activity Recognition in AAL Environments Using Random Projections

PubMed Central

Damaševičius, Robertas; Vasiljevas, Mindaugas; Šalkevičius, Justas; Woźniak, Marcin

2016-01-01

Automatic human activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors attached to the subject's body and permit continuous monitoring of numerous physiological signals reflecting the state of human actions. Successful identification of human activities can be immensely useful in healthcare applications for Ambient Assisted Living (AAL), for automatic and intelligent activity monitoring systems developed for elderly and disabled people. In this paper, we propose the method for activity recognition and subject identification based on random projections from high-dimensional feature space to low-dimensional projection space, where the classes are separated using the Jaccard distance between probability density functions of projected data. Two HAR domain tasks are considered: activity identification and subject identification. The experimental results using the proposed method with Human Activity Dataset (HAD) data are presented. PMID:27413392

Identification Approach to Alleviate Effects of Unmeasured Heat Gains for MIMO Building Thermal Systems

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

Cai, Jie; Kim, Donghun; Braun, James E.

It is important to have practical methods for constructing a good mathematical model for a building's thermal system for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. Identification approaches based on semi-physical model structures are popular in building science for those purposes. However conventional gray box identification approaches applied to thermal networks would fail when significant unmeasured heat gains present in estimation data. Although this situation is very common and practical, there has been little research to tackle this issue in building science. This paper presents an overall identification approach to alleviate influences of unmeasured disturbances,more » and hence to obtain improved gray-box building models. The approach was applied to an existing open space building and the performance is demonstrated.« less

Seed storage proteins as a system for teaching protein identification by mass spectrometry in biochemistry laboratory.

PubMed

Wilson, Karl A; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed, requiring more time and expertise than instructors of large laboratory classes can devote. We have developed an experimental module for our Biochemistry Laboratory course that engages students in MS-based protein identification following protein separation by one-dimensional SDS-PAGE, a technique that is usually taught in this type of course. The module is based on soybean seed storage proteins, a relatively simple mixture of proteins present in high levels in the seed, allowing the identification of the main protein bands by MS/MS and in some cases, even by peptide mass fingerprinting. Students can identify their protein bands using software available on the Internet, and are challenged to deduce post-translational modifications that have occurred upon germination. A collection of mass spectral data and tutorials that can be used as a stand-alone computer-based laboratory module were also assembled. Copyright © 2013 International Union of Biochemistry and Molecular Biology, Inc.

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes

PubMed Central

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-yung

2016-01-01

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency. PMID:27792156

Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID)

NASA Astrophysics Data System (ADS)

Nugraha, Joanna Ardhyanti Mita; Suryono; Suseno, dan Jatmiko Endro

2018-02-01

Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID) as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP). This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

PubMed

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-Yung

2016-10-25

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

Systems and methods for remote long standoff biometric identification using microwave cardiac signals

NASA Technical Reports Server (NTRS)

McGrath, William R. (Inventor); Talukder, Ashit (Inventor)

2012-01-01

Systems and methods for remote, long standoff biometric identification using microwave cardiac signals are provided. In one embodiment, the invention relates to a method for remote biometric identification using microwave cardiac signals, the method including generating and directing first microwave energy in a direction of a person, receiving microwave energy reflected from the person, the reflected microwave energy indicative of cardiac characteristics of the person, segmenting a signal indicative of the reflected microwave energy into a waveform including a plurality of heart beats, identifying patterns in the microwave heart beats waveform, and identifying the person based on the identified patterns and a stored microwave heart beats waveform.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1990-01-01

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

Asymptotic inference in system identification for the atom maser.

PubMed

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

2012-11-28

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

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.

PINS Testing and Modification for Explosive Identification

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

E.H. Seabury; A.J. Caffrey

2011-09-01

The INL's Portable Isotopic Neutron Spectroscopy System (PINS)1 non-intrusively identifies the chemical fill of munitions and sealed containers. PINS is used routinely by the U.S. Army, the Defense Threat Reduction Agency, and foreign military units to determine the contents of munitions and other containers suspected to contain explosives, smoke-generating chemicals, and chemical warfare agents such as mustard and nerve gas. The objects assayed with PINS range from softball-sized M139 chemical bomblets to 200 gallon DOT 500X ton containers. INL had previously examined2 the feasibility of using a similar system for the identification of explosives, and based on this proof-of-principle test,more » the development of a dedicated system for the identification of explosives in an improvised nuclear device appears entirely feasible. INL has been tasked by NNSA NA-42 Render Safe Research and Development with the development of such a system.« less

R&D on a Detector for Very High Momentum Charged Hadron Identification in ALICE

NASA Astrophysics Data System (ADS)

Gallas, A.

2006-04-01

The latest theoretical and experimental results from experiments at RHIC suggest investigating a physics domain in heavy ion collisions for pt higher than the one planned to be covered at present by the Particle Identification (PID) system of the ALICE experiment. We present here a possible upgrade of the High Momentum Particle Identification Detector (HMPID) based on the idea of the Threshold Imaging Cherenkov (TIC) detector operated for the first time by the NA44 experiment.

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.

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.

The Confidence-Accuracy Relationship in Eyewitness Identification: Effects of Lineup Instructions, Foil Similarity, and Target-Absent Base Rates

ERIC Educational Resources Information Center

Brewer, Neil; Wells, Gary L.

2006-01-01

Discriminating accurate from mistaken eyewitness identifications is a major issue facing criminal justice systems. This study examined whether eyewitness confidence assists such decisions under a variety of conditions using a confidence-accuracy (CA) calibration approach. Participants (N = 1,200) viewed a simulated crime and attempted 2 separate…

Automatically identifying health outcome information in MEDLINE records.

PubMed

Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George

2006-01-01

Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.

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.

Study on Intelligent Multi-concentrates Feeding System for Dairy Cow

NASA Astrophysics Data System (ADS)

Yan, Yinfa; Wang, Ranran; Song, Zhanhua; Yan, Shitao; Li, Fa-De

To implement precision feeding for dairy cow, an intelligent multi-concentrates feeding system was developed. The system consists of two parts, one is precision ingredients control subsystem, the other is multi-concentrates discharge subsystem. The former controls the latter with 4 stepper motors. The precision ingredients control subsystem was designed based on Samsung S3C2440 ARM9 microprocessor and WinCE5.0 embedded operating system. The feeding system identifies the dairy cow with passive transponder using RFID (Radio frequency identification) reader. According to the differences of based diet intake and individual dairy cow milk yield, the system can automatically and quantificationally discharge 4 kinds of different concentrates on the basis of the cow identification ID. The intelligent multi-concentrates feeding system for dairy cow has been designed and implemented. According to the experiment results, the concentrate feeding error is less than 5%, the cow inditification delay time is less than 0.5s and the cow inditification error rate is less than 0.01%.

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

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

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

Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement

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

Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.

2011-09-23

In this paper, a method to classify and identify power system events based on the characteristic ellipsoid of phasor measurement is presented. The decision tree technique is used to perform the event classification and identification. Event types, event locations and clearance times are identified by decision trees based on the indices of the characteristic ellipsoid. A sufficiently large number of transient events were simulated on the New England 10-machine 39-bus system based on different system configurations. Transient simulations taking into account different event types, clearance times and various locations are conducted to simulate phasor measurement. Bus voltage magnitudes and recordedmore » reactive and active power flows are used to build the characteristic ellipsoid. The volume, eccentricity, center and projection of the longest axis in the parameter space coordinates of the characteristic ellipsoids are used to classify and identify events. Results demonstrate that the characteristic ellipsoid and the decision tree are capable to detect the event type, location, and clearance time with very high accuracy.« less

Fuzzy variable impedance control based on stiffness identification for human-robot cooperation

NASA Astrophysics Data System (ADS)

Mao, Dachao; Yang, Wenlong; Du, Zhijiang

2017-06-01

This paper presents a dynamic fuzzy variable impedance control algorithm for human-robot cooperation. In order to estimate the intention of human for co-manipulation, a fuzzy inference system is set up to adjust the impedance parameter. Aiming at regulating the output fuzzy universe based on the human arm’s stiffness, an online stiffness identification method is developed. A drag interaction task is conducted on a 5-DOF robot with variable impedance control. Experimental results demonstrate that the proposed algorithm is superior.

In-Flight Pitot-Static Calibration

NASA Technical Reports Server (NTRS)

Foster, John V. (Inventor); Cunningham, Kevin (Inventor)

2016-01-01

A GPS-based pitot-static calibration system uses global output-error optimization. High data rate measurements of static and total pressure, ambient air conditions, and GPS-based ground speed measurements are used to compute pitot-static pressure errors over a range of airspeed. System identification methods rapidly compute optimal pressure error models with defined confidence intervals.

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

PubMed Central

Efremov, Ljupcho; Leoncini, Emanuele; Amore, Rosarita; Posteraro, Patrizia; Ricciardi, Walter

2015-01-01

Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 isolates), and Vitek 2 (2,853 isolates) systems. The random-effects pooled identification ratios at the species level were 0.89 (95% confidence interval [CI], 0.80 to 0.95) for the API ID32C system, 0.89 (95% CI, 0.83 to 0.93) for the AuxaColor system, and 0.93 (95% CI, 0.89 to 0.96) for the Vitek 2 system (P for heterogeneity, 0.255). Overall, the accuracy of studies using phenotypic analysis-based comparison methods was comparable to that of studies using molecular analysis-based comparison methods. Subanalysis of studies conducted on Candida yeasts showed that the Vitek 2 system was significantly more accurate (pooled ratio, 0.94 [95% CI, 0.85 to 0.99]) than the API ID32C system (pooled ratio, 0.84 [95% CI, 0.61 to 0.99]) and the AuxaColor system (pooled ratio, 0.76 [95% CI, 0.67 to 0.84]) with respect to uncommon species (P for heterogeneity, <0.05). Subanalysis of studies conducted on non-Candida yeasts (i.e., Cryptococcus, Rhodotorula, Saccharomyces, and Trichosporon) revealed pooled identification accuracies of ≥98% for the Vitek 2, API ID32C (excluding Cryptococcus), and AuxaColor (only Rhodotorula) systems, with significant low or null levels of heterogeneity (P > 0.05). Nonetheless, clinical microbiologists should reconsider the usefulness of these systems, particularly in light of new diagnostic tools such as matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry, which allow for considerably shortened turnaround times and/or avoid the requirement for additional tests for species identity confirmation. PMID:25994160

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy.

PubMed

Posteraro, Brunella; Efremov, Ljupcho; Leoncini, Emanuele; Amore, Rosarita; Posteraro, Patrizia; Ricciardi, Walter; Sanguinetti, Maurizio

2015-08-01

Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 isolates), and Vitek 2 (2,853 isolates) systems. The random-effects pooled identification ratios at the species level were 0.89 (95% confidence interval [CI], 0.80 to 0.95) for the API ID32C system, 0.89 (95% CI, 0.83 to 0.93) for the AuxaColor system, and 0.93 (95% CI, 0.89 to 0.96) for the Vitek 2 system (P for heterogeneity, 0.255). Overall, the accuracy of studies using phenotypic analysis-based comparison methods was comparable to that of studies using molecular analysis-based comparison methods. Subanalysis of studies conducted on Candida yeasts showed that the Vitek 2 system was significantly more accurate (pooled ratio, 0.94 [95% CI, 0.85 to 0.99]) than the API ID32C system (pooled ratio, 0.84 [95% CI, 0.61 to 0.99]) and the AuxaColor system (pooled ratio, 0.76 [95% CI, 0.67 to 0.84]) with respect to uncommon species (P for heterogeneity, <0.05). Subanalysis of studies conducted on non-Candida yeasts (i.e., Cryptococcus, Rhodotorula, Saccharomyces, and Trichosporon) revealed pooled identification accuracies of ≥98% for the Vitek 2, API ID32C (excluding Cryptococcus), and AuxaColor (only Rhodotorula) systems, with significant low or null levels of heterogeneity (P > 0.05). Nonetheless, clinical microbiologists should reconsider the usefulness of these systems, particularly in light of new diagnostic tools such as matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry, which allow for considerably shortened turnaround times and/or avoid the requirement for additional tests for species identity confirmation. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Model-Based Diagnostics for Propellant Loading Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Foygel, Michael; Smelyanskiy, Vadim N.

2011-01-01

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Online fingerprint verification.

PubMed

Upendra, K; Singh, S; Kumar, V; Verma, H K

2007-01-01

As organizations search for more secure authentication methods for user access, e-commerce, and other security applications, biometrics is gaining increasing attention. With an increasing emphasis on the emerging automatic personal identification applications, fingerprint based identification is becoming more popular. The most widely used fingerprint representation is the minutiae based representation. The main drawback with this representation is that it does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Also, it is difficult quickly to match two fingerprint images containing different number of unregistered minutiae points. In this study filter bank based representation, which eliminates these weakness, is implemented and the overall performance of the developed system is tested. The results have shown that this system can be used effectively for secure online verification applications.

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.

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.

Intelligent dental identification system (IDIS) in forensic medicine.

PubMed

Chomdej, T; Pankaow, W; Choychumroon, S

2006-04-20

This study reports the design and development of the intelligent dental identification system (IDIS), including its efficiency and reliability. Five hundred patients were randomly selected from the Dental Department at Police General Hospital in Thailand to create a population of 3000 known subjects. From the original 500 patients, 100 were randomly selected to create a sample of 1000 unidentifiable subjects (400 subjects with completeness and possible alterations of dental information corresponding to natural occurrences and general dental treatments after the last clinical examination, such as missing teeth, dental caries, dental restorations, and dental prosthetics, 100 subjects with completeness and no alteration of dental information, 500 subjects with incompleteness and no alteration of dental information). Attempts were made to identify the unknown subjects utilizing IDIS. The use of IDIS advanced method resulted in consistent outstanding identification in the range of 82.61-100% with minimal error 0-1.19%. The results of this study indicate that IDIS can be used to support dental identification. It supports not only all types of dentitions: primary, mixed, and permanent but also for incomplete and altered dental information. IDIS is particularly useful in providing the huge quantity and redundancy of related documentation associated with forensic odontology. As a computerized system, IDIS can reduce the time required for identification and store dental digital images with many processing features. Furthermore, IDIS establishes enhancements of documental dental record with odontogram and identification codes, electrical dental record with dental database system, and identification methods and algorithms. IDIS was conceptualized based on the guidelines and standards of the American Board of Forensic Odontology (ABFO) and International Criminal Police Organization (INTERPOL).

Personal identification based on prescription eyewear.

PubMed

Berg, Gregory E; Collins, Randall S

2007-03-01

This study presents a web-based tool that can be used to assist in identification of unknown individuals using spectacle prescriptions. Currently, when lens prescriptions are used in forensic identifications, investigators are constrained to a simple "match" or "no-match" judgment with an antemortem prescription. It is not possible to evaluate the strength of the conclusion, or rather, the potential or real error rates associated with the conclusion. Three databases totaling over 385,000 individual prescriptions are utilized in this study to allow forensic analysts to easily determine the strength of individuation of a spectacle match to antemortem records by calculating the frequency at which the observed prescription occurs in various U.S. populations. Optical refractive errors are explained, potential states and combinations of refractive errors are described, measuring lens corrections is discussed, and a detailed description of the databases is presented. The practical application of this system is demonstrated using two recent forensic identifications. This research provides a valuable personal identification tool that can be used in cases where eyeglass portions are recovered in forensic contexts.

Resting State EEG-based biometrics for individual identification using convolutional neural networks.

PubMed

Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

2015-08-01

Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

Development of a PCR-based assay for rapid and reliable identification of pathogenic Fusaria.

PubMed

Mishra, Prashant K; Fox, Roland T V; Culham, Alastair

2003-01-28

Identification of Fusarium species has always been difficult due to confusing phenotypic classification systems. We have developed a fluorescent-based polymerase chain reaction assay that allows for rapid and reliable identification of five toxigenic and pathogenic Fusarium species. The species includes Fusarium avenaceum, F. culmorum, F. equiseti, F. oxysporum and F. sambucinum. The method is based on the PCR amplification of species-specific DNA fragments using fluorescent oligonucleotide primers, which were designed based on sequence divergence within the internal transcribed spacer region of nuclear ribosomal DNA. Besides providing an accurate, reliable, and quick diagnosis of these Fusaria, another advantage with this method is that it reduces the potential for exposure to carcinogenic chemicals as it substitutes the use of fluorescent dyes in place of ethidium bromide. Apart from its multidisciplinary importance and usefulness, it also obviates the need for gel electrophoresis.

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

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.

Application of dynamic recurrent neural networks in nonlinear system identification

NASA Astrophysics Data System (ADS)

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

2006-11-01

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

Nonlinear system identification technique validation

NASA Astrophysics Data System (ADS)

Rudko, M.; Bussgang, J. J.

1982-01-01

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

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

Davida, G.I.; Frankel, Y.; Matt, B.J.

In developing secure applications and systems, the designers often must incorporate secure user identification in the design specification. In this paper, the authors study secure off line authenticated user identification schemes based on a biometric system that can measure a user`s biometric accurately (up to some Hamming distance). The schemes presented here enhance identification and authorization in secure applications by binding a biometric template with authorization information on a token such as a magnetic strip. Also developed here are schemes specifically designed to minimize the compromise of a user`s private biometrics data, encapsulated in the authorization information, without requiring securemore » hardware tokens. In this paper the authors furthermore study the feasibility of biometrics performing as an enabling technology for secure system and application design. The authors investigate a new technology which allows a user`s biometrics to facilitate cryptographic mechanisms.« less

Potential for DNA-based identification of Great Lakes fauna: match and mismatch between taxa inventories and DNA barcode libraries.

PubMed

Trebitz, Anett S; Hoffman, Joel C; Grant, George W; Billehus, Tyler M; Pilgrim, Erik M

2015-07-22

DNA-based identification of mixed-organism samples offers the potential to greatly reduce the need for resource-intensive morphological identification, which would be of value both to bioassessment and non-native species monitoring. The ability to assign species identities to DNA sequences found depends on the availability of comprehensive DNA reference libraries. Here, we compile inventories for aquatic metazoans extant in or threatening to invade the Laurentian Great Lakes and examine the availability of reference mitochondrial COI DNA sequences (barcodes) in the Barcode of Life Data System for them. We found barcode libraries largely complete for extant and threatening-to-invade vertebrates (100% of reptile, 99% of fish, and 92% of amphibian species had barcodes). In contrast, barcode libraries remain poorly developed for precisely those organisms where morphological identification is most challenging; 46% of extant invertebrates lacked reference barcodes with rates especially high among rotifers, oligochaetes, and mites. Lack of species-level identification for many aquatic invertebrates also is a barrier to matching DNA sequences with physical specimens. Attaining the potential for DNA-based identification of mixed-organism samples covering the breadth of aquatic fauna requires a concerted effort to build supporting barcode libraries and voucher collections.

Potential for DNA-based identification of Great Lakes fauna: match and mismatch between taxa inventories and DNA barcode libraries

NASA Astrophysics Data System (ADS)

Trebitz, Anett S.; Hoffman, Joel C.; Grant, George W.; Billehus, Tyler M.; Pilgrim, Erik M.

2015-07-01

DNA-based identification of mixed-organism samples offers the potential to greatly reduce the need for resource-intensive morphological identification, which would be of value both to bioassessment and non-native species monitoring. The ability to assign species identities to DNA sequences found depends on the availability of comprehensive DNA reference libraries. Here, we compile inventories for aquatic metazoans extant in or threatening to invade the Laurentian Great Lakes and examine the availability of reference mitochondrial COI DNA sequences (barcodes) in the Barcode of Life Data System for them. We found barcode libraries largely complete for extant and threatening-to-invade vertebrates (100% of reptile, 99% of fish, and 92% of amphibian species had barcodes). In contrast, barcode libraries remain poorly developed for precisely those organisms where morphological identification is most challenging; 46% of extant invertebrates lacked reference barcodes with rates especially high among rotifers, oligochaetes, and mites. Lack of species-level identification for many aquatic invertebrates also is a barrier to matching DNA sequences with physical specimens. Attaining the potential for DNA-based identification of mixed-organism samples covering the breadth of aquatic fauna requires a concerted effort to build supporting barcode libraries and voucher collections.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

First experiences in the implementation of biometric technology to link data from Health and Demographic Surveillance Systems with health facility data.

PubMed

Serwaa-Bonsu, Adwoa; Herbst, Abraham J; Reniers, Georges; Ijaa, Wilfred; Clark, Benjamin; Kabudula, Chodziwadziwa; Sankoh, Osman

2010-02-24

In developing countries, Health and Demographic Surveillance Systems (HDSSs) provide a framework for tracking demographic and health dynamics over time in a defined geographical area. Many HDSSs co-exist with facility-based data sources in the form of Health Management Information Systems (HMIS). Integrating both data sources through reliable record linkage could provide both numerator and denominator populations to estimate disease prevalence and incidence rates in the population and enable determination of accurate health service coverage. To measure the acceptability and performance of fingerprint biometrics to identify individuals in demographic surveillance populations and those attending health care facilities serving the surveillance populations. Two HDSS sites used fingerprint biometrics for patient and/or surveillance population participant identification. The proportion of individuals for whom a fingerprint could be successfully enrolled were characterised in terms of age and sex. Adult (18-65 years) fingerprint enrolment rates varied between 94.1% (95% CI 93.6-94.5) for facility-based fingerprint data collection at the Africa Centre site to 96.7% (95% CI 95.9-97.6) for population-based fingerprint data collection at the Agincourt site. Fingerprint enrolment rates in children under 1 year old (Africa Centre site) were only 55.1% (95% CI 52.7-57.4). By age 5, child fingerprint enrolment rates were comparable to those of adults. This work demonstrates the feasibility of fingerprint-based individual identification for population-based research in developing countries. Record linkage between demographic surveillance population databases and health care facility data based on biometric identification systems would allow for a more comprehensive evaluation of population health, including the ability to study health service utilisation from a population perspective, rather than the more restrictive health service perspective.

Parametric system identification of resonant micro/nanosystems operating in a nonlinear response regime

NASA Astrophysics Data System (ADS)

Sabater, A. B.; Rhoads, J. F.

2017-02-01

The parametric system identification of macroscale resonators operating in a nonlinear response regime can be a challenging research problem, but at the micro- and nanoscales, experimental constraints add additional complexities. For example, due to the small and noisy signals micro/nanoresonators produce, a lock-in amplifier is commonly used to characterize the amplitude and phase responses of the systems. While the lock-in enables detection, it also prohibits the use of established time-domain, multi-harmonic, and frequency-domain methods, which rely upon time-domain measurements. As such, the only methods that can be used for parametric system identification are those based on fitting experimental data to an approximate solution, typically derived via perturbation methods and/or Galerkin methods, of a reduced-order model. Thus, one could view the parametric system identification of micro/nanosystems operating in a nonlinear response regime as the amalgamation of four coupled sub-problems: nonparametric system identification, or proper experimental design and data acquisition; the generation of physically consistent reduced-order models; the calculation of accurate approximate responses; and the application of nonlinear least-squares parameter estimation. This work is focused on the theoretical foundations that underpin each of these sub-problems, as the methods used to address one sub-problem can strongly influence the results of another. To provide context, an electromagnetically transduced microresonator is used as an example. This example provides a concrete reference for the presented findings and conclusions.

Jan Evangelista Purkynje (1787-1869): first to describe fingerprints.

PubMed

Grzybowski, Andrzej; Pietrzak, Krzysztof

2015-01-01

Fingerprints have been used for years as the accepted tool in criminology and for identification. The first system of classification of fingerprints was introduced by Jan Evangelista Purkynje (1787-1869), a Czech physiologist, in 1823. He divided the papillary lines into nine types, based on their geometric arrangement. This work, however, was not recognized internationally for many years. In 1858, Sir William Herschel (1833-1917) registered fingerprints for those signing documents at the Indian magistrate's office in Jungipoor. Henry Faulds (1843-1930) in 1880 proposed using ink for fingerprint determination and people identification, and Francis Galton (1822-1911) collected 8000 fingerprints and developed their classification based on the spirals, loops, and arches. In 1892, Juan Vucetich (1858-1925) created his own fingerprint identification system and proved that a woman was responsible for killing two of her sons. In 1896, a London police officer Edward Henry (1850-1931) expanded on earlier systems of classification and used papillary lines to identify criminals; it was his system that was adopted by the forensic world. The work of Jan Evangelista Purkynje (1787-1869) (Figure 1), who in 1823 was the first to describe in detail fingerprints, is almost forgotten. He also established their classification. The year 2013 marked the 190th anniversary of the publication of his work on this topic. Our contribution is an attempt to introduce the reader to this scientist and his discoveries in the field of fingerprint identification. Copyright © 2015.

Development of statistical models to forecast crossing times of commercial vehicles.

DOT National Transportation Integrated Search

2011-07-01

Border crossing time measurement systems for commercial vehicles are being implemented throughout : the U.S.-Mexico border. These systems are based on radio frequency identification (RFID) technology. : With funding from the Federal Highway Administr...

Air Force Technical Objective Document FY 87

DTIC Science & Technology

1985-12-01

Air Force Systems Command Edwards Air Force Base. Cal ifornia 93523-5000 NOTICES THIS DOCUMENT IS FOR INFORMATION AND GUIDANCE ONL Y This...acquisition of Air Foree weapon systems . Each Air Foree laboratory annually formulates Q Research and Technology (R& T) Pion in response to available...guidance based on USAF requirements, the identification of scientific and technological opportunities, and the needs of present and projected systems

DTREEv2, a computer-based support system for the risk assessment of genetically modified plants.

PubMed

Pertry, Ine; Nothegger, Clemens; Sweet, Jeremy; Kuiper, Harry; Davies, Howard; Iserentant, Dirk; Hull, Roger; Mezzetti, Bruno; Messens, Kathy; De Loose, Marc; de Oliveira, Dulce; Burssens, Sylvia; Gheysen, Godelieve; Tzotzos, George

2014-03-25

Risk assessment of genetically modified organisms (GMOs) remains a contentious area and a major factor influencing the adoption of agricultural biotech. Methodologically, in many countries, risk assessment is conducted by expert committees with little or no recourse to databases and expert systems that can facilitate the risk assessment process. In this paper we describe DTREEv2, a computer-based decision support system for the identification of hazards related to the introduction of GM-crops into the environment. DTREEv2 structures hazard identification and evaluation by means of an Event-Tree type of analysis. The system produces an output flagging identified hazards and potential risks. It is intended to be used for the preparation and evaluation of biosafety dossiers and, as such, its usefulness extends to researchers, risk assessors and regulators in government and industry. Copyright © 2013 Elsevier B.V. All rights reserved.

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

The aviation safety reporting system

NASA Technical Reports Server (NTRS)

Reynard, W. D.

1984-01-01

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

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

NASA Astrophysics Data System (ADS)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

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.

[Principles for molecular identification of traditional Chinese materia medica using DNA barcoding].

PubMed

Chen, Shi-Lin; Yao, Hui; Han, Jian-Ping; Xin, Tian-Yi; Pang, Xiao-Hui; Shi, Lin-Chun; Luo, Kun; Song, Jing-Yuan; Hou, Dian-Yun; Shi, Shang-Mei; Qian, Zhong-Zhi

2013-01-01

Since the research of molecular identification of Chinese Materia Medica (CMM) using DNA barcode is rapidly developing and popularizing, the principle of this method is approved to be listed in the Supplement of the Pharmacopoeia of the People's Republic of China. Based on the study on comprehensive samples, the DNA barcoding systems have been established to identify CMM, i.e. ITS2 as a core barcode and psbA-trnH as a complementary locus for identification of planta medica, and COI as a core barcode and ITS2 as a complementary locus for identification of animal medica. This article introduced the principle of molecular identification of CMM using DNA barcoding and its drafting instructions. Furthermore, its application perspective was discussed.

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.

Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

PubMed Central

Hübl, Johannes; McArdell, Brian W.; Walter, Fabian

2018-01-01

The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. PMID:29789449

A web-based institutional DICOM distribution system with the integration of the Clinical Trial Processor (CTP).

PubMed

Aryanto, K Y E; Broekema, A; Langenhuysen, R G A; Oudkerk, M; van Ooijen, P M A

2015-05-01

To develop and test a fast and easy rule-based web-environment with optional de-identification of imaging data to facilitate data distribution within a hospital environment. A web interface was built using Hypertext Preprocessor (PHP), an open source scripting language for web development, and Java with SQL Server to handle the database. The system allows for the selection of patient data and for de-identifying these when necessary. Using the services provided by the RSNA Clinical Trial Processor (CTP), the selected images were pushed to the appropriate services using a protocol based on the module created for the associated task. Five pipelines, each performing a different task, were set up in the server. In a 75 month period, more than 2,000,000 images are transferred and de-identified in a proper manner while 20,000,000 images are moved from one node to another without de-identification. While maintaining a high level of security and stability, the proposed system is easy to setup, it integrate well with our clinical and research practice and it provides a fast and accurate vendor-neutral process of transferring, de-identifying, and storing DICOM images. Its ability to run different de-identification processes in parallel pipelines is a major advantage in both clinical and research setting.

NLP-based Identification of Pneumonia Cases from Free-Text Radiological Reports

PubMed Central

Elkin, Peter L.; Froehling, David; Wahner-Roedler, Dietlind; Trusko, Brett; Welsh, Gail; Ma, Haobo; Asatryan, Armen X.; Tokars, Jerome I.; Rosenbloom, S. Trent; Brown, Steven H.

2008-01-01

Radiological reports are a rich source of clinical data which can be mined to assist with biosurveillance of emerging infectious diseases. In addition to biosurveillance, radiological reports are an important source of clinical data for health service research. Pneumonias and other radiological findings on chest xray or chest computed tomography (CT) are one type of relevant finding to both biosurveillance and health services research. In this study we examined the ability of a Natural Language Processing system to accurately identify pneumonias and other lesions from within free-text radiological reports. The system encoded the reports in the SNOMED CT Ontology and then a set of SNOMED CT based rules were created in our Health Archetype Language aimed at the identification of these radiological findings and diagnoses. The encoded rule was executed against the SNOMED CT encodings of the radiological reports. The accuracy of the reports was compared with a Clinician review of the Radiological Reports. The accuracy of the system in the identification of pneumonias was high with a Sensitivity (recall) of 100%, a specificity of 98%, and a positive predictive value (precision) of 97%. We conclude that SNOMED CT based computable rules are accurate enough for the automated biosurveillance of pneumonias from radiological reports. PMID:18998791

Single cell adhesion force measurement for cell viability identification using an AFM cantilever-based micro putter

NASA Astrophysics Data System (ADS)

Shen, Yajing; Nakajima, Masahiro; Kojima, Seiji; Homma, Michio; Kojima, Masaru; Fukuda, Toshio

2011-11-01

Fast and sensitive cell viability identification is a key point for single cell analysis. To address this issue, this paper reports a novel single cell viability identification method based on the measurement of single cell shear adhesion force using an atomic force microscopy (AFM) cantilever-based micro putter. Viable and nonviable yeast cells are prepared and put onto three kinds of substrate surfaces, i.e. tungsten probe, gold and ITO substrate surfaces. A micro putter is fabricated from the AFM cantilever by focused ion beam etching technique. The spring constant of the micro putter is calibrated using the nanomanipulation approach. The shear adhesion force between the single viable or nonviable cell and each substrate is measured using the micro putter based on the nanorobotic manipulation system inside an environmental scanning electron microscope. The adhesion force is calculated based on the deflection of the micro putter beam. The results show that the adhesion force of the viable cell to the substrate is much larger than that of the nonviable cell. This identification method is label free, fast, sensitive and can give quantitative results at the single cell level.

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.

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

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

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

1989-01-01

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

Fast and automatic thermographic material identification for the recycling process

NASA Astrophysics Data System (ADS)

Haferkamp, Heinz; Burmester, Ingo

1998-03-01

Within the framework of the future closed loop recycling process the automatic and economical sorting of plastics is a decisive element. The at the present time available identification and sorting systems are not yet suitable for the sorting of technical plastics since essential demands, as the realization of high recognition reliability and identification rates considering the variety of technical plastics, can not be guaranteed. Therefore the Laser Zentrum Hannover e.V. in cooperation with the Hoerotron GmbH and the Preussag Noell GmbH has carried out investigations on a rapid thermographic and laser-supported material- identification-system for automatic material-sorting- systems. The automatic identification of different engineering plastics coming from electronic or automotive waste is possible. Identification rates up to 10 parts per second are allowed by the effort from fast IR line scanners. The procedure is based on the following principle: within a few milliseconds a spot on the relevant sample is heated by a CO2 laser. The samples different and specific chemical and physical material properties cause different temperature distributions on their surfaces that are measured by a fast IR-linescan system. This 'thermal impulse response' has to be analyzed by means of a computer system. Investigations have shown that it is possible to analyze more than 18 different sorts of plastics at a frequency of 10 Hz. Crucial for the development of such a system is the rapid processing of imaging data, the minimization of interferences caused by oscillating samples geometries, and a wide range of possible additives in plastics in question. One possible application area is sorting of plastics coming from car- and electronic waste recycling.

A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products*

PubMed Central

auf dem Keller, Ulrich; Prudova, Anna; Gioia, Magda; Butler, Georgina S.; Overall, Christopher M.

2010-01-01

Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed. PMID:20305283

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.

Adaptive modeling, identification, and control of dynamic structural systems. I. Theory

USGS Publications Warehouse

Safak, Erdal

1989-01-01

A concise review of the theory of adaptive modeling, identification, and control of dynamic structural systems based on discrete-time recordings is presented. Adaptive methods have four major advantages over the classical methods: (1) Removal of the noise from the signal is done over the whole frequency band; (2) time-varying characteristics of systems can be tracked; (3) systems with unknown characteristics can be controlled; and (4) a small segment of the data is needed during the computations. Included in the paper are the discrete-time representation of single-input single-output (SISO) systems, models for SISO systems with noise, the concept of stochastic approximation, recursive prediction error method (RPEM) for system identification, and the adaptive control. Guidelines for model selection and model validation and the computational aspects of the method are also discussed in the paper. The present paper is the first of two companion papers. The theory given in the paper is limited to that which is necessary to follow the examples for applications in structural dynamics presented in the second paper.

Evaluation and implementation of QR Code Identity Tag system for Healthcare in Turkey.

PubMed

Uzun, Vassilya; Bilgin, Sami

2016-01-01

For this study, we designed a QR Code Identity Tag system to integrate into the Turkish healthcare system. This system provides QR code-based medical identification alerts and an in-hospital patient identification system. Every member of the medical system is assigned a unique QR Code Tag; to facilitate medical identification alerts, the QR Code Identity Tag can be worn as a bracelet or necklace or carried as an ID card. Patients must always possess the QR Code Identity bracelets within hospital grounds. These QR code bracelets link to the QR Code Identity website, where detailed information is stored; a smartphone or standalone QR code scanner can be used to scan the code. The design of this system allows authorized personnel (e.g., paramedics, firefighters, or police) to access more detailed patient information than the average smartphone user: emergency service professionals are authorized to access patient medical histories to improve the accuracy of medical treatment. In Istanbul, we tested the self-designed system with 174 participants. To analyze the QR Code Identity Tag system's usability, the participants completed the System Usability Scale questionnaire after using the system.

In-flight detection and identification and accommodation of aircraft icing

NASA Astrophysics Data System (ADS)

Caliskan, Fikret; Hajiyev, Chingiz

2012-11-01

The recent improvements and research on aviation have focused on the subject of aircraft safe flight even in the severe weather conditions. As one type of such weather conditions, aircraft icing considerably has negative effects on the aircraft flight performance. The risks of the iced aerodynamic surfaces of the flying aircraft have been known since the beginning of the first flights. Until recent years, as a solution for this event, the icing conditions ahead flight route are estimated from radars or other environmental sensors, hence flight paths are changed, or, if it exists, anti-icing/de-icing systems are used. This work aims at the detection and identification of airframe icing based on statistical properties of aircraft dynamics and reconfigurable control protecting aircraft from hazardous icing conditions. In this paper, aircraft icing identification based on neural networks is investigated. Following icing identification, reconfigurable control is applied for protecting the aircraft from hazardous icing conditions.

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.

NCTR using a polarization-agile coherent radar system

NASA Astrophysics Data System (ADS)

Walton, E. K.; Moffatt, D. L.; Garber, F. D.; Kamis, A.; Lai, C. Y.

1986-01-01

This report describes the results of the first year of a research project performed by the Ohio State University ElectroScience Laboratory (OSU/ESL) for the Naval Weapons Center (NWC). The goal of this project is to explore the use of the polarization properties of the signal scattered from a radar target for the purpose of radar target identification. Various radar target identification algorithms were applied to the case of a full polarization coherent radar system, and were tested using a specific data base and noise model. The data base used to test the performance of the radar target identification algorithms developed here is a unique set of measurements made on scale models of aircraft. Measurements were made using the OSU/ESL Compact Radar Measurement Range. The range was operated in a broad-band (1-12 GHZ) mode and the full polarization matrix was measured. Calibrated values (amplitude and phase) of the RCS for the three polarization states were thus available. The polarization states are listed below.

Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory.

PubMed

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

2015-11-13

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system.

IDENTIFICATION OF ACTIVE BACTERIAL COMMUNITIES IN A MODEL DRINKING WATER BIOFILM SYSTEM USING 16S RRNA-BASED CLONE LIBRARIES

EPA Science Inventory

Recent phylogenetic studies have used DNA as the target molecule for the development of environmental 16S rDNA clone libraries. As DNA may persist in the environment, DNA-based libraries cannot be used to identify metabolically active bacteria in water systems. In this study, a...

Registering Names and Addresses for Information Technology.

ERIC Educational Resources Information Center

Knapp, Arthur A.

The identification of administrative authorities and the development of associated procedures for registering and accessing names and addresses of communications data systems are considered in this paper. It is noted that, for data communications systems using standards based on the Open Systems Interconnection (OSI) Reference Model specified by…

Developing an electronic system to manage and track emergency medications.

PubMed

Hamm, Mark W; Calabrese, Samuel V; Knoer, Scott J; Duty, Ashley M

2018-03-01

The development of a Web-based program to track and manage emergency medications with radio frequency identification (RFID) is described. At the Cleveland Clinic, medication kit restocking records and dispense locations were historically documented using a paper record-keeping system. The Cleveland Clinic investigated options to replace the paper-based tracking logs with a Web-based program that could track the real-time location and inventory of emergency medication kits. Vendor collaboration with a board of pharmacy (BOP) compliance inspector and pharmacy personnel resulted in the creation of a dual barcoding system using medication and pocket labels. The Web-based program was integrated with a Cleveland Clinic-developed asset tracking system using active RFID tags to give the real-time location of the medication kit. The Web-based program and the asset tracking system allowed identification of kits nearing expiration or containing recalled medications. Conversion from a paper-based system to a Web-based program began in October 2013. After 119 days, data were evaluated to assess the success of the conversion. Pharmacists spent an average of 27 minutes per day approving medication kits during the postimplementation period versus 102 minutes daily using the paper-based system, representing a 74% decrease in pharmacist time spent on this task. Prospective reports are generated monthly to allow the manager to assess the expected workload and adjust staffing for the next month. Implementation of a BOP-approved Web-based system for managing and tracking emergency medications with RFID integration decreased pharmacist review time, minimized compliance risk, and increased access to real-time data. Copyright © 2018 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry.

PubMed

Akimoto, Nayumi; Ara, Takeshi; Nakajima, Daisuke; Suda, Kunihiro; Ikeda, Chiaki; Takahashi, Shingo; Muneto, Reiko; Yamada, Manabu; Suzuki, Hideyuki; Shibata, Daisuke; Sakurai, Nozomu

2017-04-28

Currently, in mass spectrometry-based metabolomics, limited reference mass spectra are available for flavonoid identification. In the present study, a database of probable mass fragments for 6,867 known flavonoids (FsDatabase) was manually constructed based on new structure- and fragmentation-related rules using new heuristics to overcome flavonoid complexity. We developed the FlavonoidSearch system for flavonoid annotation, which consists of the FsDatabase and a computational tool (FsTool) to automatically search the FsDatabase using the mass spectra of metabolite peaks as queries. This system showed the highest identification accuracy for the flavonoid aglycone when compared to existing tools and revealed accurate discrimination between the flavonoid aglycone and other compounds. Sixteen new flavonoids were found from parsley, and the diversity of the flavonoid aglycone among different fruits and vegetables was investigated.

Intelligent Engine Systems Work Element 1.3: Sub System Health Management

NASA Technical Reports Server (NTRS)

Ashby, Malcolm; Simpson, Jeffrey; Singh, Anant; Ferguson, Emily; Frontera, mark

2005-01-01

The objectives of this program were to develop health monitoring systems and physics-based fault detection models for engine sub-systems including the start, lubrication, and fuel. These models will ultimately be used to provide more effective sub-system fault identification and isolation to reduce engine maintenance costs and engine down-time. Additionally, the bearing sub-system health is addressed in this program through identification of sensing requirements, a review of available technologies and a demonstration of a demonstration of a conceptual monitoring system for a differential roller bearing. This report is divided into four sections; one for each of the subtasks. The start system subtask is documented in section 2.0, the oil system is covered in section 3.0, bearing in section 4.0, and the fuel system is presented in section 5.0.

Developing Human-Machine Interfaces to Support Appropriate Trust and Reliance on Automated Combat Identification Systems (Developpement d’Interfaces Homme-Machine Pour Appuyer la Confiance dans les Systemes Automatises d’Identification au Combat)

DTIC Science & Technology

2008-03-31

on automation; the ‘response bias’ approach. This new approach is based on Signal Detection Theory (SDT) (Macmillan & Creelman , 1991; Wickens...SDT), response bias will vary with the expectation of the target probability, whereas their sensitivity will stay constant (Macmillan & Creelman ...measures, C has the simplest statistical properties (Macmillan & Creelman , 1991, p273), and it was also the measure used in Dzindolet et al.’s study

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

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1984-01-01

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

A plasmid-based reporter system for live cell imaging of dengue virus infected cells.

PubMed

Medin, Carey L; Valois, Sierra; Patkar, Chinmay G; Rothman, Alan L

2015-01-01

Cell culture models are used widely to study the effects of dengue virus (DENV) on host cell function. Current methods of identification of cells infected with an unmodified DENV requires fixation and permeablization of cells to allow DENV-specific antibody staining. This method does not permit imaging of viable cells over time. In this report, a plasmid-based reporter was developed to allow non-destructive identification of DENV-infected cells. The plasmid-based reporter was demonstrated to be broadly applicable to the four DENV serotypes, including low-passaged strains, and was specifically cleaved by the viral protease with minimal interference on viral production. This study reveals the potential for this novel reporter system to advance the studies of virus-host interactions during DENV infection. Copyright © 2014 Elsevier B.V. All rights reserved.

Cavity parameters identification for TESLA control system development

NASA Astrophysics Data System (ADS)

Czarski, Tomasz; Pozniak, Krysztof T.; Romaniuk, Ryszard S.; Simrock, Stefan

2005-08-01

Aim of the control system development for TESLA cavity is a more efficient stabilization of the pulsed, accelerating EM field inside resonator. Cavity parameters identification is an essential task for the comprehensive control algorithm. TESLA cavity simulator has been successfully implemented using high-speed FPGA technology. Electromechanical model of the cavity resonator includes Lorentz force detuning and beam loading. The parameters identification is based on the electrical model of the cavity. The model is represented by state space equation for envelope of the cavity voltage driven by current generator and beam loading. For a given model structure, the over-determined matrix equation is created covering long enough measurement range with the solution according to the least-squares method. A low-degree polynomial approximation is applied to estimate the time-varying cavity detuning during the pulse. The measurement channel distortion is considered, leading to the external cavity model seen by the controller. The comprehensive algorithm of the cavity parameters identification was implemented in the Matlab system with different modes of operation. Some experimental results were presented for different cavity operational conditions. The following considerations have lead to the synthesis of the efficient algorithm for the cavity control system predicted for the potential FPGA technology implementation.

Radio System for Locating Emergency Workers

NASA Technical Reports Server (NTRS)

Larson, William; Medelius, Pedro; Starr, Stan; Bedette, Guy; Taylor, John; Moerk, Steve

2003-01-01

A system based on low-power radio transponders and associated analog and digital electronic circuitry has been developed for locating firefighters and other emergency workers deployed in a building or other structure. The system has obvious potential for saving lives and reducing the risk of injuries. The system includes (1) a central station equipped with a computer and a transceiver; (2) active radio-frequency (RF) identification tags, each placed in a different room or region of the structure; and (3) transponder units worn by the emergency workers. The RF identification tags can be installed in a new building as built-in components of standard fire-detection devices or ground-fault electrical outlets or can be attached to such devices in a previously constructed building, without need for rewiring the building. Each RF identification tag contains information that uniquely identifies it. When each tag is installed, information on its location and identity are reported to, and stored at, the central station. In an emergency, if a building has not been prewired with RF identification tags, leading emergency workers could drop sequentially numbered portable tags in the rooms of the building, reporting the tag numbers and locations by radio to the central station as they proceed.

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.

21 CFR 864.9900 - Cord blood processing system and storage container.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Cord blood processing system and storage container... Manufacture Human Cells, Tissues, and Cellular and Tissue-Based Products (HCT/Ps) § 864.9900 Cord blood processing system and storage container. (a) Identification. A cord blood processing system and storage...

21 CFR 864.9900 - Cord blood processing system and storage container.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Cord blood processing system and storage container... Manufacture Human Cells, Tissues, and Cellular and Tissue-Based Products (HCT/Ps) § 864.9900 Cord blood processing system and storage container. (a) Identification. A cord blood processing system and storage...

21 CFR 864.9900 - Cord blood processing system and storage container.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Cord blood processing system and storage container... Manufacture Human Cells, Tissues, and Cellular and Tissue-Based Products (HCT/Ps) § 864.9900 Cord blood processing system and storage container. (a) Identification. A cord blood processing system and storage...

21 CFR 864.9900 - Cord blood processing system and storage container.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cord blood processing system and storage container... Manufacture Human Cells, Tissues, and Cellular and Tissue-Based Products (HCT/Ps) § 864.9900 Cord blood processing system and storage container. (a) Identification. A cord blood processing system and storage...

21 CFR 864.9900 - Cord blood processing system and storage container.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Cord blood processing system and storage container... Manufacture Human Cells, Tissues, and Cellular and Tissue-Based Products (HCT/Ps) § 864.9900 Cord blood processing system and storage container. (a) Identification. A cord blood processing system and storage...

21 CFR 862.1450 - Lactic acid test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Lactic acid test system. 862.1450 Section 862.1450....1450 Lactic acid test system. (a) Identification. A lactic acid test system is a device intended to measure lactic acid in whole blood and plasma. Lactic acid measurements that evaluate the acid-base status...

21 CFR 862.1450 - Lactic acid test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Lactic acid test system. 862.1450 Section 862.1450....1450 Lactic acid test system. (a) Identification. A lactic acid test system is a device intended to measure lactic acid in whole blood and plasma. Lactic acid measurements that evaluate the acid-base status...

21 CFR 862.1450 - Lactic acid test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Lactic acid test system. 862.1450 Section 862.1450....1450 Lactic acid test system. (a) Identification. A lactic acid test system is a device intended to measure lactic acid in whole blood and plasma. Lactic acid measurements that evaluate the acid-base status...

21 CFR 862.1450 - Lactic acid test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Lactic acid test system. 862.1450 Section 862.1450....1450 Lactic acid test system. (a) Identification. A lactic acid test system is a device intended to measure lactic acid in whole blood and plasma. Lactic acid measurements that evaluate the acid-base status...

21 CFR 862.1655 - Pyruvic acid test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... treatment of acid-base and electrolyte disturbances or anoxia (the reduction of oxygen in body tissues). (b... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Pyruvic acid test system. 862.1655 Section 862....1655 Pyruvic acid test system. (a) Identification. A pyruvic acid test system is a device intended to...

21 CFR 862.1655 - Pyruvic acid test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... treatment of acid-base and electrolyte disturbances or anoxia (the reduction of oxygen in body tissues). (b... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Pyruvic acid test system. 862.1655 Section 862....1655 Pyruvic acid test system. (a) Identification. A pyruvic acid test system is a device intended to...

21 CFR 862.1655 - Pyruvic acid test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... treatment of acid-base and electrolyte disturbances or anoxia (the reduction of oxygen in body tissues). (b... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Pyruvic acid test system. 862.1655 Section 862....1655 Pyruvic acid test system. (a) Identification. A pyruvic acid test system is a device intended to...

21 CFR 862.1655 - Pyruvic acid test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... treatment of acid-base and electrolyte disturbances or anoxia (the reduction of oxygen in body tissues). (b... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Pyruvic acid test system. 862.1655 Section 862....1655 Pyruvic acid test system. (a) Identification. A pyruvic acid test system is a device intended to...

21 CFR 862.1655 - Pyruvic acid test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... treatment of acid-base and electrolyte disturbances or anoxia (the reduction of oxygen in body tissues). (b... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Pyruvic acid test system. 862.1655 Section 862....1655 Pyruvic acid test system. (a) Identification. A pyruvic acid test system is a device intended to...

System parameter identification from projection of inverse analysis

NASA Astrophysics Data System (ADS)

Liu, K.; Law, S. S.; Zhu, X. Q.

2017-05-01

The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.

Waterway Performance Monitoring via Automatic Identification System (AIS) Data

DTIC Science & Technology

2013-08-01

Transceivers onboard the vessels broadcast the 4 AIS signal containing position, heading, speed, and other identifying information to shore- based 5 towers...Great Lakes system based 31 on the voyage histories reconstructed with the Destination field from the AIS static reports. In 32 spite of the much... Information Systems for Estimating Coastal Maritime Risk. 38 Transportation Research Record: Journal of the Transportation Research Board, No. 2222, 39 TRB

Secure ADS-B authentication system and method

NASA Technical Reports Server (NTRS)

Viggiano, Marc J (Inventor); Valovage, Edward M (Inventor); Samuelson, Kenneth B (Inventor); Hall, Dana L (Inventor)

2010-01-01

A secure system for authenticating the identity of ADS-B systems, including: an authenticator, including a unique id generator and a transmitter transmitting the unique id to one or more ADS-B transmitters; one or more ADS-B transmitters, including a receiver receiving the unique id, one or more secure processing stages merging the unique id with the ADS-B transmitter's identification, data and secret key and generating a secure code identification and a transmitter transmitting a response containing the secure code and ADSB transmitter's data to the authenticator; the authenticator including means for independently determining each ADS-B transmitter's secret key, a receiver receiving each ADS-B transmitter's response, one or more secure processing stages merging the unique id, ADS-B transmitter's identification and data and generating a secure code, and comparison processing comparing the authenticator-generated secure code and the ADS-B transmitter-generated secure code and providing an authentication signal based on the comparison result.

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.

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.

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.

Acquisition of a Scanning Laser Vibrometer System for Experimental Studies on Nonparametric Nonlinear System Identification and Aeroelastic Instability Suppression

DTIC Science & Technology

2011-03-06

based LCO suppression system housed in a winglet , specifically designed for the GTW. Upon completion of rehabilitation and modifications to the wing to...accommodate the winglet /NES, the full system will be ready for additional testing in the TDT. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF...University, will result in the design of an NES-based LCO suppression system housed in a winglet , specifically designed for the GTW. Upon completion of

Immunity-based detection, identification, and evaluation of aircraft sub-system failures

NASA Astrophysics Data System (ADS)

Moncayo, Hever Y.

This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also analyzed in this thesis. They showed to have an important effect on detection performance and are a critical aspect when designing the configuration of the AIS. The results presented in this thesis show that the AIS paradigm addresses directly the complexity and multi-dimensionality associated with a damaged aircraft dynamic response and provides the tools necessary for a comprehensive/integrated solution to the FDIE problem. Excellent detection, identification, and evaluation performance has been recorded for all types of failures considered. The implementation of the proposed AIS-based scheme can potentially have a significant impact on the safety of aircraft operation. The output information obtained from the scheme will be useful to increase pilot situational awareness and determine automated compensation.

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.

Orientation-modulated attention effect on visual evoked potential: Application for PIN system using brain-computer interface.

PubMed

Wilaiprasitporn, Theerawit; Yagi, Tohru

2015-01-01

This research demonstrates the orientation-modulated attention effect on visual evoked potential. We combined this finding with our previous findings about the motion-modulated attention effect and used the result to develop novel visual stimuli for a personal identification number (PIN) application based on a brain-computer interface (BCI) framework. An electroencephalography amplifier with a single electrode channel was sufficient for our application. A computationally inexpensive algorithm and small datasets were used in processing. Seven healthy volunteers participated in experiments to measure offline performance. Mean accuracy was 83.3% at 13.9 bits/min. Encouraged by these results, we plan to continue developing the BCI-based personal identification application toward real-time systems.

[Measures to prevent patient identification errors in blood collection/physiological function testing utilizing a laboratory information system].

PubMed

Shimazu, Chisato; Hoshino, Satoshi; Furukawa, Taiji

2013-08-01

We constructed an integrated personal identification workflow chart using both bar code reading and an all in-one laboratory information system. The information system not only handles test data but also the information needed for patient guidance in the laboratory department. The reception terminals at the entrance, displays for patient guidance and patient identification tools at blood-sampling booths are all controlled by the information system. The number of patient identification errors was greatly reduced by the system. However, identification errors have not been abolished in the ultrasound department. After re-evaluation of the patient identification process in this department, we recognized that the major reason for the errors came from excessive identification workflow. Ordinarily, an ultrasound test requires patient identification 3 times, because 3 different systems are required during the entire test process, i.e. ultrasound modality system, laboratory information system and a system for producing reports. We are trying to connect the 3 different systems to develop a one-time identification workflow, but it is not a simple task and has not been completed yet. Utilization of the laboratory information system is effective, but is not yet perfect for patient identification. The most fundamental procedure for patient identification is to ask a person's name even today. Everyday checks in the ordinary workflow and everyone's participation in safety-management activity are important for the prevention of patient identification errors.

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

DOT National Transportation Integrated Search

1999-06-01

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

Luminescent Method for Porcelain Identification

NASA Astrophysics Data System (ADS)

Platova, R. A.; Rassulov, V. A.; Platov, Yu. T.

2018-05-01

Porcelain identification according to the material type (hard, soft, and bone) was reduced to a system of classification functions that were constructed based on interrelationships of luminescence band intensities of optically active impurity centers (Fe3+ and Mn2+), a molecular center ({UO}_2^{2+}) , and intrinsic defects (O*, oxygen center). Porcelains with different compositions and calcination conditions had different combinations and intensity ratios of bands of optically active centers.

Nonlinear damage identification of breathing cracks in Truss system

NASA Astrophysics Data System (ADS)

Zhao, Jie; DeSmidt, Hans

2014-03-01

The breathing cracks in truss system are detected by Frequency Response Function (FRF) based damage identification method. This method utilizes damage-induced changes of frequency response functions to estimate the severity and location of structural damage. This approach enables the possibility of arbitrary interrogation frequency and multiple inputs/outputs which greatly enrich the dataset for damage identification. The dynamical model of truss system is built using the finite element method and the crack model is based on fracture mechanics. Since the crack is driven by tensional and compressive forces of truss member, only one damage parameter is needed to represent the stiffness reduction of each truss member. Assuming that the crack constantly breathes with the exciting frequency, the linear damage detection algorithm is developed in frequency/time domain using Least Square and Newton Raphson methods. Then, the dynamic response of the truss system with breathing cracks is simulated in the time domain and meanwhile the crack breathing status for each member is determined by the feedback from real-time displacements of member's nodes. Harmonic Fourier Coefficients (HFCs) of dynamical response are computed by processing the data through convolution and moving average filters. Finally, the results show the effectiveness of linear damage detection algorithm in identifying the nonlinear breathing cracks using different combinations of HFCs and sensors.

Portable Brain-Computer Interface for the Intensive Care Unit Patient Communication Using Subject-Dependent SSVEP Identification.

PubMed

Dehzangi, Omid; Farooq, Muhamed

2018-01-01

A major predicament for Intensive Care Unit (ICU) patients is inconsistent and ineffective communication means. Patients rated most communication sessions as difficult and unsuccessful. This, in turn, can cause distress, unrecognized pain, anxiety, and fear. As such, we designed a portable BCI system for ICU communications (BCI4ICU) optimized to operate effectively in an ICU environment. The system utilizes a wearable EEG cap coupled with an Android app designed on a mobile device that serves as visual stimuli and data processing module. Furthermore, to overcome the challenges that BCI systems face today in real-world scenarios, we propose a novel subject-specific Gaussian Mixture Model- (GMM-) based training and adaptation algorithm. First, we incorporate subject-specific information in the training phase of the SSVEP identification model using GMM-based training and adaptation. We evaluate subject-specific models against other subjects. Subsequently, from the GMM discriminative scores, we generate the transformed vectors, which are passed to our predictive model. Finally, the adapted mixture mean scores of the subject-specific GMMs are utilized to generate the high-dimensional supervectors. Our experimental results demonstrate that the proposed system achieved 98.7% average identification accuracy, which is promising in order to provide effective and consistent communication for patients in the intensive care.

Crack identification for rigid pavements using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bahaddin Ersoz, Ahmet; Pekcan, Onur; Teke, Turker

2017-09-01

Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation of existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based pavement monitoring systems have been in-use in assessing the remaining life of in-service pavements. Although such systems produce accurate results, their use can be expensive and data processing can be time consuming, which make them infeasible considering the demand for quick pavement evaluation. To overcome such problems, Unmanned Aerial Vehicles (UAVs) can be used as an alternative as they are relatively cheaper and easier-to-use. In this study, we propose a UAV based pavement crack identification system for monitoring rigid pavements’ existing conditions. The system consists of recently introduced image processing algorithms used together with conventional machine learning techniques, both of which are used to perform detection of cracks on rigid pavements’ surface and their classification. Through image processing, the distinct features of labelled crack bodies are first obtained from the UAV based images and then used for training of a Support Vector Machine (SVM) model. The performance of the developed SVM model was assessed with a field study performed along a rigid pavement exposed to low traffic and serious temperature changes. Available cracks were classified using the UAV based system and obtained results indicate it ensures a good alternative solution for pavement monitoring applications.

Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)

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

Tuffner, Francis; Marinovici, PNNL Laurentiu; Hauer, PNNL John

2014-02-21

The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to helpmore » guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.« less

A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems.

PubMed

Kazemi, Mahdi; Arefi, Mohammad Mehdi

2017-03-01

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

Identification of propulsion systems

NASA Technical Reports Server (NTRS)

Merrill, Walter; Guo, Ten-Huei; Duyar, Ahmet

1991-01-01

This paper presents a tutorial on the use of model identification techniques for the identification of propulsion system models. These models are important for control design, simulation, parameter estimation, and fault detection. Propulsion system identification is defined in the context of the classical description of identification as a four step process that is unique because of special considerations of data and error sources. Propulsion system models are described along with the dependence of system operation on the environment. Propulsion system simulation approaches are discussed as well as approaches to propulsion system identification with examples for both air breathing and rocket systems.

Research on the transfer learning of the vehicle logo recognition

NASA Astrophysics Data System (ADS)

Zhao, Wei

2017-08-01

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

Identification of blood culture isolates directly from positive blood cultures by use of matrix-assisted laser desorption ionization-time of flight mass spectrometry and a commercial extraction system: analysis of performance, cost, and turnaround time.

PubMed

Lagacé-Wiens, Philippe R S; Adam, Heather J; Karlowsky, James A; Nichol, Kimberly A; Pang, Paulette F; Guenther, Jodi; Webb, Amanda A; Miller, Crystal; Alfa, Michelle J

2012-10-01

Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry represents a revolution in the rapid identification of bacterial and fungal pathogens in the clinical microbiology laboratory. Recently, MALDI-TOF has been applied directly to positive blood culture bottles for the rapid identification of pathogens, leading to reductions in turnaround time and potentially beneficial patient impacts. The development of a commercially available extraction kit (Bruker Sepsityper) for use with the Bruker MALDI BioTyper has facilitated the processing required for identification of pathogens directly from positive from blood cultures. We report the results of an evaluation of the accuracy, cost, and turnaround time of this method for 61 positive monomicrobial and 2 polymicrobial cultures representing 26 species. The Bruker MALDI BioTyper with the Sepsityper gave a valid (score, >1.7) identification for 85.2% of positive blood cultures with no misidentifications. The mean reduction in turnaround time to identification was 34.3 h (P < 0.0001) in the ideal situation where MALDI-TOF was used for all blood cultures and 26.5 h in a more practical setting where conventional identification or identification from subcultures was required for isolates that could not be directly identified by MALDI-TOF. Implementation of a MALDI-TOF-based identification system for direct identification of pathogens from blood cultures is expected to be associated with a marginal increase in operating costs for most laboratories. However, the use of MALDI-TOF for direct identification is accurate and should result in reduced turnaround time to identification.

49 CFR 1544.231 - Airport-approved and exclusive area personnel identification systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... carry out a personnel identification system for identification media that are airport-approved, or identification media that are issued for use in an exclusive area. The system must include the following: (1) Personnel identification media that— (i) Convey a full face image, full name, employer, and identification...

Device-Free Passive Identity Identification via WiFi Signals.

PubMed

Lv, Jiguang; Yang, Wu; Man, Dapeng

2017-11-02

Device-free passive identity identification attracts much attention in recent years, and it is a representative application in sensorless sensing. It can be used in many applications such as intrusion detection and smart building. Previous studies show the sensing potential of WiFi signals in a device-free passive manner. It is confirmed that human's gait is unique from each other similar to fingerprint and iris. However, the identification accuracy of existing approaches is not satisfactory in practice. In this paper, we present Wii, a device-free WiFi-based Identity Identification approach utilizing human's gait based on Channel State Information (CSI) of WiFi signals. Principle Component Analysis (PCA) and low pass filter are applied to remove the noises in the signals. We then extract several entities' gait features from both time and frequency domain, and select the most effective features according to information gain. Based on these features, Wii realizes stranger recognition through Gaussian Mixture Model (GMM) and identity identification through a Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. It is implemented using commercial WiFi devices and evaluated on a dataset with more than 1500 gait instances collected from eight subjects walking in a room. The results indicate that Wii can effectively recognize strangers and can achieves high identification accuracy with low computational cost. As a result, Wii has the potential to work in typical home security systems.

Device-Free Passive Identity Identification via WiFi Signals

PubMed Central

Yang, Wu; Man, Dapeng

2017-01-01

Device-free passive identity identification attracts much attention in recent years, and it is a representative application in sensorless sensing. It can be used in many applications such as intrusion detection and smart building. Previous studies show the sensing potential of WiFi signals in a device-free passive manner. It is confirmed that human’s gait is unique from each other similar to fingerprint and iris. However, the identification accuracy of existing approaches is not satisfactory in practice. In this paper, we present Wii, a device-free WiFi-based Identity Identification approach utilizing human’s gait based on Channel State Information (CSI) of WiFi signals. Principle Component Analysis (PCA) and low pass filter are applied to remove the noises in the signals. We then extract several entities’ gait features from both time and frequency domain, and select the most effective features according to information gain. Based on these features, Wii realizes stranger recognition through Gaussian Mixture Model (GMM) and identity identification through a Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. It is implemented using commercial WiFi devices and evaluated on a dataset with more than 1500 gait instances collected from eight subjects walking in a room. The results indicate that Wii can effectively recognize strangers and can achieves high identification accuracy with low computational cost. As a result, Wii has the potential to work in typical home security systems. PMID:29099091

A reliable DNA barcode reference library for the identification of the North European shelf fish fauna.

PubMed

Knebelsberger, Thomas; Landi, Monica; Neumann, Hermann; Kloppmann, Matthias; Sell, Anne F; Campbell, Patrick D; Laakmann, Silke; Raupach, Michael J; Carvalho, Gary R; Costa, Filipe O

2014-09-01

Valid fish species identification is an essential step both for fundamental science and fisheries management. The traditional identification is mainly based on external morphological diagnostic characters, leading to inconsistent results in many cases. Here, we provide a sequence reference library based on mitochondrial cytochrome c oxidase subunit I (COI) for a valid identification of 93 North Atlantic fish species originating from the North Sea and adjacent waters, including many commercially exploited species. Neighbour-joining analysis based on K2P genetic distances formed nonoverlapping clusters for all species with a ≥99% bootstrap support each. Identification was successful for 100% of the species as the minimum genetic distance to the nearest neighbour always exceeded the maximum intraspecific distance. A barcoding gap was apparent for the whole data set. Within-species distances ranged from 0 to 2.35%, while interspecific distances varied between 3.15 and 28.09%. Distances between congeners were on average 51-fold higher than those within species. The validation of the sequence library by applying BOLDs barcode index number (BIN) analysis tool and a ranking system demonstrated high taxonomic reliability of the DNA barcodes for 85% of the investigated fish species. Thus, the sequence library presented here can be confidently used as a benchmark for identification of at least two-thirds of the typical fish species recorded for the North Sea. © 2014 John Wiley & Sons Ltd.

New pattern recognition system in the e-nose for Chinese spirit identification

NASA Astrophysics Data System (ADS)

Hui, Zeng; Qiang, Li; Yu, Gu

2016-02-01

This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

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.

Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2016-02-03

A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.

PubMed

Vilar, Santiago; Hripcsak, George

2016-01-01

Drug-target identification is crucial to discover novel applications for existing drugs and provide more insights about mechanisms of biological actions, such as adverse drug effects (ADEs). Computational methods along with the integration of current big data sources provide a useful framework for drug-target and drug-adverse effect discovery. In this article, we propose a method based on the integration of 3D chemical similarity, target and adverse effect data to generate a drug-target-adverse effect predictor along with a simple leveraging system to improve identification of drug-targets and drug-adverse effects. In the first step, we generated a system for multiple drug-target identification based on the application of 3D drug similarity into a large target dataset extracted from the ChEMBL. Next, we developed a target-adverse effect predictor combining targets from ChEMBL with phenotypic information provided by SIDER data source. Both modules were linked to generate a final predictor that establishes hypothesis about new drug-target-adverse effect candidates. Additionally, we showed that leveraging drug-target candidates with phenotypic data is very useful to improve the identification of drug-targets. The integration of phenotypic data into drug-target candidates yielded up to twofold precision improvement. In the opposite direction, leveraging drug-phenotype candidates with target data also yielded a significant enhancement in the performance. The modeling described in the current study is simple and efficient and has applications at large scale in drug repurposing and drug safety through the identification of mechanism of action of biological effects.

Time frequency analysis for automated sleep stage identification in fullterm and preterm neonates.

PubMed

Fraiwan, Luay; Lweesy, Khaldon; Khasawneh, Natheer; Fraiwan, Mohammad; Wenz, Heinrich; Dickhaus, Hartmut

2011-08-01

This work presents a new methodology for automated sleep stage identification in neonates based on the time frequency distribution of single electroencephalogram (EEG) recording and artificial neural networks (ANN). Wigner-Ville distribution (WVD), Hilbert-Hough spectrum (HHS) and continuous wavelet transform (CWT) time frequency distributions were used to represent the EEG signal from which features were extracted using time frequency entropy. The classification of features was done using feed forward back-propagation ANN. The system was trained and tested using data taken from neonates of post-conceptual age of 40 weeks for both preterm (14 recordings) and fullterm (15 recordings). The identification of sleep stages was successfully implemented and the classification based on the WVD outperformed the approaches based on CWT and HHS. The accuracy and kappa coefficient were found to be 0.84 and 0.65 respectively for the fullterm neonates' recordings and 0.74 and 0.50 respectively for preterm neonates' recordings.

Unsupervised real-time speaker identification for daily movies

NASA Astrophysics Data System (ADS)

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

2002-07-01

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

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.

Rapid Identification of Mycobacterial Whole Cells in Solid and Liquid Culture Media by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry ▿

PubMed Central

Lotz, Aurélie; Ferroni, Agnès; Beretti, Jean-Luc; Dauphin, Brunhilde; Carbonnelle, Etienne; Guet-Revillet, Hélène; Veziris, Nicolas; Heym, Béate; Jarlier, Vincent; Gaillard, Jean-Louis; Pierre-Audigier, Catherine; Frapy, Eric; Berche, Patrick; Nassif, Xavier; Bille, Emmanuelle

2010-01-01

Mycobacterial identification is based on several methods: conventional biochemical tests that require several weeks for accurate identification, and molecular tools that are now routinely used. However, these techniques are expensive and time-consuming. In this study, an alternative method was developed using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). This approach allows a characteristic mass spectral fingerprint to be obtained from whole inactivated mycobacterial cells. We engineered a strategy based on specific profiles in order to identify the most clinically relevant species of mycobacteria. To validate the mycobacterial database, a total of 311 strains belonging to 31 distinct species and 4 species complexes grown in Löwenstein-Jensen (LJ) and liquid (mycobacterium growth indicator tube [MGIT]) media were analyzed. No extraction step was required. Correct identifications were obtained for 97% of strains from LJ and 77% from MGIT media. No misidentification was noted. Our results, based on a very simple protocol, suggest that this system may represent a serious alternative for clinical laboratories to identify mycobacterial species. PMID:20943874

Automated pancreatic cyst screening using natural language processing: a new tool in the early detection of pancreatic cancer

PubMed Central

Roch, Alexandra M; Mehrabi, Saeed; Krishnan, Anand; Schmidt, Heidi E; Kesterson, Joseph; Beesley, Chris; Dexter, Paul R; Palakal, Mathew; Schmidt, C Max

2015-01-01

Introduction As many as 3% of computed tomography (CT) scans detect pancreatic cysts. Because pancreatic cysts are incidental, ubiquitous and poorly understood, follow-up is often not performed. Pancreatic cysts may have a significant malignant potential and their identification represents a ‘window of opportunity’ for the early detection of pancreatic cancer. The purpose of this study was to implement an automated Natural Language Processing (NLP)-based pancreatic cyst identification system. Method A multidisciplinary team was assembled. NLP-based identification algorithms were developed based on key words commonly used by physicians to describe pancreatic cysts and programmed for automated search of electronic medical records. A pilot study was conducted prospectively in a single institution. Results From March to September 2013, 566 233 reports belonging to 50 669 patients were analysed. The mean number of patients reported with a pancreatic cyst was 88/month (range 78–98). The mean sensitivity and specificity were 99.9% and 98.8%, respectively. Conclusion NLP is an effective tool to automatically identify patients with pancreatic cysts based on electronic medical records (EMR). This highly accurate system can help capture patients ‘at-risk’ of pancreatic cancer in a registry. PMID:25537257

Identification of Active Bacterial Communities in Drinking Water Using 16S rRNA-Based Sequence Analyses

EPA Science Inventory

DNA-based methods have considerably increased our understanding of the bacterial diversity of water distribution systems (WDS). However, as DNA may persist after cell death, the use of DNA-based methods cannot be used to describe metabolically-active microbes. In contrast, intra...

Auto identification technology and its impact on patient safety in the Operating Room of the Future.

PubMed

Egan, Marie T; Sandberg, Warren S

2007-03-01

Automatic identification technologies, such as bar coding and radio frequency identification, are ubiquitous in everyday life but virtually nonexistent in the operating room. User expectations, based on everyday experience with automatic identification technologies, have generated much anticipation that these systems will improve readiness, workflow, and safety in the operating room, with minimal training requirements. We report, in narrative form, a multi-year experience with various automatic identification technologies in the Operating Room of the Future Project at Massachusetts General Hospital. In each case, the additional human labor required to make these ;labor-saving' technologies function in the medical environment has proved to be their undoing. We conclude that while automatic identification technologies show promise, significant barriers to realizing their potential still exist. Nevertheless, overcoming these obstacles is necessary if the vision of an operating room of the future in which all processes are monitored, controlled, and optimized is to be achieved.

Flexible polyurethane foam modelling and identification of viscoelastic parameters for automotive seating applications

NASA Astrophysics Data System (ADS)

Deng, R.; Davies, P.; Bajaj, A. K.

2003-05-01

A hereditary model and a fractional derivative model for the dynamic properties of flexible polyurethane foams used in automotive seat cushions are presented. Non-linear elastic and linear viscoelastic properties are incorporated into these two models. A polynomial function of compression is used to represent the non-linear elastic behavior. The viscoelastic property is modelled by a hereditary integral with a relaxation kernel consisting of two exponential terms in the hereditary model and by a fractional derivative term in the fractional derivative model. The foam is used as the only viscoelastic component in a foam-mass system undergoing uniaxial compression. One-term harmonic balance solutions are developed to approximate the steady state response of the foam-mass system to the harmonic base excitation. System identification procedures based on the direct non-linear optimization and a sub-optimal method are formulated to estimate the material parameters. The effects of the choice of the cost function, frequency resolution of data and imperfections in experiments are discussed. The system identification procedures are also applied to experimental data from a foam-mass system. The performances of the two models for data at different compression and input excitation levels are compared, and modifications to the structure of the fractional derivative model are briefly explored. The role of the viscous damping term in both types of model is discussed.

Identification des parametres du moteur de l'avion Cessna Citation X pour la phase de croisiere a partir des tests en vol et a base des reseaux de neurones =

NASA Astrophysics Data System (ADS)

Zaag, Mahdi

La disponibilite des modeles precis des avions est parmi les elements cles permettant d'assurer leurs ameliorations. Ces modeles servent a ameliorer les commandes de vol et de concevoir de nouveaux systemes aerodynamiques pour la conception des ailes deformables des avions. Ce projet consiste a concevoir un systeme d'identification de certains parametres du modele du moteur de l'avion d'affaires americain Cessna Citation X pour la phase de croisiere a partir des essais en vol. Ces essais ont ete effectues sur le simulateur de vol concu et fabrique par CAE Inc. qui possede le niveau D de la dynamique de vol. En effet, le niveau D est le plus haut niveau de precision donne par l'autorite federale de reglementation FAA de l'aviation civile aux Etats-Unis. Une methodologie basee sur les reseaux de neurones optimises a l'aide d'un algorithme intitule le "grand deluge etendu" est utilisee dans la conception de ce systeme d'identification. Plusieurs tests de vol pour differentes altitudes et differents nombres de Mach ont ete realises afin de s'en servir comme bases de donnees pour l'apprentissage des reseaux de neurones. La validation de ce modele a ete realisee a l'aide des donnees du simulateur. Malgre la nonlinearite et la complexite du systeme, les parametres du moteur ont ete tres bien predits pour une enveloppe de vol determinee. Ce modele estime pourrait etre utilise pour des analyses de fonctionnement du moteur et pourrait assurer le controle de l'avion pendant cette phase de croisiere. L'identification des parametres du moteur pourrait etre realisee aussi pour les autres phases de montee et de descente afin d'obtenir son modele complet pour toute l'enveloppe du vol de l'avion Cessna Citation X (montee, croisiere, descente). Cette methode employee dans ce travail pourrait aussi etre efficace pour realiser un modele pour l'identification des coefficients aerodynamiques du meme avion a partir toujours des essais en vol. None None None

An efficient identification approach for stable and unstable nonlinear systems using Colliding Bodies Optimization algorithm.

PubMed

Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P

2015-11-01

This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting nurses' acceptance of radiofrequency identification technology.

PubMed

Norten, Adam

2012-10-01

The technology of radiofrequency identification allows for the scanning of radiofrequency identification-tagged objects and individuals without line-of-sight requirements. Healthcare organizations use radiofrequency identification to ensure the health and safety of patients and medical personnel and to uncover inefficiencies. Although the successful implementation of a system incorporating radiofrequency identification technologies requires acceptance and use of the technology, some nurses using radiofrequency identification in hospitals feel like "Big Brother" is watching them. This predictive study used a theoretical model assessing the effect of five independent variables: privacy concerns, attitudes, subjective norms, controllability, and self-efficacy, on a dependent variable, nurses' behavioral intention to use radiofrequency identification. A Web-based questionnaire containing previously validated questions was answered by 106 US RNs. Multiple linear regression showed that all constructs together accounted for 60% of the variance in nurses' intention to use radiofrequency identification. Of the predictors in the model, attitudes provided the largest unique contribution when the other predictors in the model were held constant; subjective norms also provided a unique contribution. Privacy concerns, controllability, and self-efficacy did not provide a significant contribution to nurses' behavioral intention to use radiofrequency identification.

An accurate sleep stages classification system using a new class of optimally time-frequency localized three-band wavelet filter bank.

PubMed

Sharma, Manish; Goyal, Deepanshu; Achuth, P V; Acharya, U Rajendra

2018-07-01

Sleep related disorder causes diminished quality of lives in human beings. Sleep scoring or sleep staging is the process of classifying various sleep stages which helps to detect the quality of sleep. The identification of sleep-stages using electroencephalogram (EEG) signals is an arduous task. Just by looking at an EEG signal, one cannot determine the sleep stages precisely. Sleep specialists may make errors in identifying sleep stages by visual inspection. To mitigate the erroneous identification and to reduce the burden on doctors, a computer-aided EEG based system can be deployed in the hospitals, which can help identify the sleep stages, correctly. Several automated systems based on the analysis of polysomnographic (PSG) signals have been proposed. A few sleep stage scoring systems using EEG signals have also been proposed. But, still there is a need for a robust and accurate portable system developed using huge dataset. In this study, we have developed a new single-channel EEG based sleep-stages identification system using a novel set of wavelet-based features extracted from a large EEG dataset. We employed a novel three-band time-frequency localized (TBTFL) wavelet filter bank (FB). The EEG signals are decomposed using three-level wavelet decomposition, yielding seven sub-bands (SBs). This is followed by the computation of discriminating features namely, log-energy (LE), signal-fractal-dimensions (SFD), and signal-sample-entropy (SSE) from all seven SBs. The extracted features are ranked and fed to the support vector machine (SVM) and other supervised learning classifiers. In this study, we have considered five different classification problems (CPs), (two-class (CP-1), three-class (CP-2), four-class (CP-3), five-class (CP-4) and six-class (CP-5)). The proposed system yielded accuracies of 98.3%, 93.9%, 92.1%, 91.7%, and 91.5% for CP-1 to CP-5, respectively, using 10-fold cross validation (CV) technique. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Beer, Neil Reginald; Lee, Abraham; Hatch, Andrew

A non-contact system for sorting monodisperse water-in-oil emulsion droplets in a microfluidic device based on the droplet's contents and their interaction with an applied electromagnetic field or by identification and sorting.

3D topography measurements on correlation cells—a new approach to forensic ballistics identifications

NASA Astrophysics Data System (ADS)

Song, John; Chu, Wei; Tong, Mingsi; Soons, Johannes

2014-06-01

Based on three-dimensional (3D) topography measurements on correlation cells, the National Institute of Standards and Technology (NIST) has developed the ‘NIST Ballistics Identification System (NBIS)’ aimed at accurate ballistics identifications and fast ballistics evidence searches. The 3D topographies are divided into arrays of correlation cells to identify ‘valid correlation areas’ and eliminate ‘invalid correlation areas’ from the matching and identification procedure. A ‘congruent matching cells’ (CMC)’ method using three types of identification parameters of the paired correlation cells (cross correlation function maximum CCFmax, spatial registration position in x-y and registration angle θ) is used for high accuracy ballistics identifications. ‘Synchronous processing’ is proposed for correlating multiple cell pairs at the same time to increase the correlation speed. The proposed NBIS can be used for correlations of both geometrical topographies and optical intensity images. All the correlation parameters and algorithms are in the public domain and subject to open tests. An error rate reporting procedure has been developed that can greatly add to the scientific support for the firearm and toolmark identification specialty, and give confidence to the trier of fact in court proceedings. The NBIS is engineered to employ transparent identification parameters and criteria, statistical models and correlation algorithms. In this way, interoperability between different ballistics identification systems can be more easily achieved. This interoperability will make the NBIS suitable for ballistics identifications and evidence searches with large national databases, such as the National Integrated Ballistic Information Network in the United States.

Broad spectrum microarray for fingerprint-based bacterial species identification

PubMed Central

2010-01-01

Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups. PMID:20163710

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

Not Available

This manual is a guide to use the file protection mechanisms available on the Martin Marietta Energy Systems, Inc. Scientific and Technical Computing (STC) System VAXes. User identification codes (UICs) and general identifiers are discussed as a basis for understanding UIC-based and access control list (ACL) protection. 5 figs.

Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology

PubMed Central

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests’ pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture. PMID:22736996

Feasibility study on a portable field pest classification system design based on DSP and 3G wireless communication technology.

PubMed

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests' pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture.

Adaptive identifier for uncertain complex nonlinear systems based on continuous neural networks.

PubMed

Alfaro-Ponce, Mariel; Cruz, Amadeo Argüelles; Chairez, Isaac

2014-03-01

This paper presents the design of a complex-valued differential neural network identifier for uncertain nonlinear systems defined in the complex domain. This design includes the construction of an adaptive algorithm to adjust the parameters included in the identifier. The algorithm is obtained based on a special class of controlled Lyapunov functions. The quality of the identification process is characterized using the practical stability framework. Indeed, the region where the identification error converges is derived by the same Lyapunov method. This zone is defined by the power of uncertainties and perturbations affecting the complex-valued uncertain dynamics. Moreover, this convergence zone is reduced to its lowest possible value using ideas related to the so-called ellipsoid methodology. Two simple but informative numerical examples are developed to show how the identifier proposed in this paper can be used to approximate uncertain nonlinear systems valued in the complex domain.

Identification of Patients with Family History of Pancreatic Cancer--Investigation of an NLP System Portability.

PubMed

Mehrabi, Saeed; Krishnan, Anand; Roch, Alexandra M; Schmidt, Heidi; Li, DingCheng; Kesterson, Joe; Beesley, Chris; Dexter, Paul; Schmidt, Max; Palakal, Mathew; Liu, Hongfang

2015-01-01

In this study we have developed a rule-based natural language processing (NLP) system to identify patients with family history of pancreatic cancer. The algorithm was developed in a Unstructured Information Management Architecture (UIMA) framework and consisted of section segmentation, relation discovery, and negation detection. The system was evaluated on data from two institutions. The family history identification precision was consistent across the institutions shifting from 88.9% on Indiana University (IU) dataset to 87.8% on Mayo Clinic dataset. Customizing the algorithm on the the Mayo Clinic data, increased its precision to 88.1%. The family member relation discovery achieved precision, recall, and F-measure of 75.3%, 91.6% and 82.6% respectively. Negation detection resulted in precision of 99.1%. The results show that rule-based NLP approaches for specific information extraction tasks are portable across institutions; however customization of the algorithm on the new dataset improves its performance.

Appearance-based multimodal human tracking and identification for healthcare in the digital home.

PubMed

Yang, Mau-Tsuen; Huang, Shen-Yen

2014-08-05

There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare.

Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home

PubMed Central

Yang, Mau-Tsuen; Huang, Shen-Yen

2014-01-01

There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare. PMID:25098207

33 CFR 401.20 - Automatic Identification System.

Code of Federal Regulations, 2010 CFR

2010-07-01

...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... Identification System. (a) Each of the following vessels must use an Automatic Identification System (AIS... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Automatic Identification System...

Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing

PubMed Central

Wang, Xuefeng

2017-01-01

This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees. PMID:28749977

Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing.

PubMed

Wu, Chunyan; Wang, Xuefeng

2017-01-01

This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees.

Interactive Cohort Identification of Sleep Disorder Patients Using Natural Language Processing and i2b2.

PubMed

Chen, W; Kowatch, R; Lin, S; Splaingard, M; Huang, Y

2015-01-01

Nationwide Children's Hospital established an i2b2 (Informatics for Integrating Biology & the Bedside) application for sleep disorder cohort identification. Discrete data were gleaned from semistructured sleep study reports. The system showed to work more efficiently than the traditional manual chart review method, and it also enabled searching capabilities that were previously not possible. We report on the development and implementation of the sleep disorder i2b2 cohort identification system using natural language processing of semi-structured documents. We developed a natural language processing approach to automatically parse concepts and their values from semi-structured sleep study documents. Two parsers were developed: a regular expression parser for extracting numeric concepts and a NLP based tree parser for extracting textual concepts. Concepts were further organized into i2b2 ontologies based on document structures and in-domain knowledge. 26,550 concepts were extracted with 99% being textual concepts. 1.01 million facts were extracted from sleep study documents such as demographic information, sleep study lab results, medications, procedures, diagnoses, among others. The average accuracy of terminology parsing was over 83% when comparing against those by experts. The system is capable of capturing both standard and non-standard terminologies. The time for cohort identification has been reduced significantly from a few weeks to a few seconds. Natural language processing was shown to be powerful for quickly converting large amount of semi-structured or unstructured clinical data into discrete concepts, which in combination of intuitive domain specific ontologies, allows fast and effective interactive cohort identification through the i2b2 platform for research and clinical use.

Interactive Cohort Identification of Sleep Disorder Patients Using Natural Language Processing and i2b2

PubMed Central

Chen, W.; Kowatch, R.; Lin, S.; Splaingard, M.

2015-01-01

Summary Nationwide Children’s Hospital established an i2b2 (Informatics for Integrating Biology & the Bedside) application for sleep disorder cohort identification. Discrete data were gleaned from semistructured sleep study reports. The system showed to work more efficiently than the traditional manual chart review method, and it also enabled searching capabilities that were previously not possible. Objective We report on the development and implementation of the sleep disorder i2b2 cohort identification system using natural language processing of semi-structured documents. Methods We developed a natural language processing approach to automatically parse concepts and their values from semi-structured sleep study documents. Two parsers were developed: a regular expression parser for extracting numeric concepts and a NLP based tree parser for extracting textual concepts. Concepts were further organized into i2b2 ontologies based on document structures and in-domain knowledge. Results 26,550 concepts were extracted with 99% being textual concepts. 1.01 million facts were extracted from sleep study documents such as demographic information, sleep study lab results, medications, procedures, diagnoses, among others. The average accuracy of terminology parsing was over 83% when comparing against those by experts. The system is capable of capturing both standard and non-standard terminologies. The time for cohort identification has been reduced significantly from a few weeks to a few seconds. Conclusion Natural language processing was shown to be powerful for quickly converting large amount of semi-structured or unstructured clinical data into discrete concepts, which in combination of intuitive domain specific ontologies, allows fast and effective interactive cohort identification through the i2b2 platform for research and clinical use. PMID:26171080

Blind identification of the Millikan Library from earthquake data considering soil–structure interaction

USGS Publications Warehouse

Ghahari, S. F.; Abazarsa, F.; Avci, O.; Çelebi, Mehmet; Taciroglu, E.

2016-01-01

The Robert A. Millikan Library is a reinforced concrete building with a basement level and nine stories above the ground. Located on the campus of California Institute of Technology (Caltech) in Pasadena California, it is among the most densely instrumented buildings in the U.S. From the early dates of its construction, it has been the subject of many investigations, especially regarding soil–structure interaction effects. It is well accepted that the structure is significantly interacting with the surrounding soil, which implies that the true foundation input motions cannot be directly recorded during earthquakes because of inertial effects. Based on this limitation, input–output modal identification methods are not applicable to this soil–structure system. On the other hand, conventional output-only methods are typically based on the unknown input signals to be stationary whitenoise, which is not the case for earthquake excitations. Through the use of recently developed blind identification (i.e. output-only) methods, it has become possible to extract such information from only the response signals because of earthquake excitations. In the present study, we employ such a blind identification method to extract the modal properties of the Millikan Library. We present some modes that have not been identified from force vibration tests in several studies to date. Then, to quantify the contribution of soil–structure interaction effects, we first create a detailed Finite Element (FE) model using available information about the superstructure; and subsequently update the soil–foundation system's dynamic stiffnesses at each mode such that the modal properties of the entire soil–structure system agree well with those obtained via output-only modal identification.

Four year-olds use norm-based coding for face identity.

PubMed

Jeffery, Linda; Read, Ainsley; Rhodes, Gillian

2013-05-01

Norm-based coding, in which faces are coded as deviations from an average face, is an efficient way of coding visual patterns that share a common structure and must be distinguished by subtle variations that define individuals. Adults and school-aged children use norm-based coding for face identity but it is not yet known if pre-school aged children also use norm-based coding. We reasoned that the transition to school could be critical in developing a norm-based system because school places new demands on children's face identification skills and substantially increases experience with faces. Consistent with this view, face identification performance improves steeply between ages 4 and 7. We used face identity aftereffects to test whether norm-based coding emerges between these ages. We found that 4 year-old children, like adults, showed larger face identity aftereffects for adaptors far from the average than for adaptors closer to the average, consistent with use of norm-based coding. We conclude that experience prior to age 4 is sufficient to develop a norm-based face-space and that failure to use norm-based coding cannot explain 4 year-old children's poor face identification skills. Copyright © 2013 Elsevier B.V. All rights reserved.

Reliability and validity of DS-ADHD: A decision support system on attention deficit hyperactivity disorders.

PubMed

Chu, Kuo-Chung; Huang, Yu-Shu; Tseng, Chien-Fu; Huang, Hsin-Jou; Wang, Chih-Huan; Tai, Hsin-Yi

2017-03-01

The purpose of this study is to examine the reliability of the clinical use of the self-built decision support system, diagnosis-supported attention deficit hyperactivity disorder (DS-ADHD), in an effort to develop the DS-ADHD system, by probing into the development of indicating patterns of past screening support systems for ADHD. The study collected data based on 107 subjects, who were divided into two groups, non-ADHD and ADHD, based on the doctor's determination, using the DSM-IV diagnostic standards. The two groups then underwent Test of Variables of Attention (TOVA) and DS-ADHD testing. The survey and testing results underwent one-way ANOVA and split-half method statistical analysis, in order to further understand whether there were any differences between the DS-ADHD and the identification tools used in today's clinical trials. The results of the study are as follows: 1) The ROC area between the TOVA and the clinical identification rate is 0.787 (95% confidence interval: 0.701-0.872); 2) The ROC area between the DS-ADHD and the clinical identification rate is 0.867 (95% confidence interval: 0.801-0.933). The study results show that DS-ADHD has the characteristics of screening for ADHD, based on its reliability and validity. It does not display any statistical differences when compared with TOVA systems that are currently on the market. However, the system is more effective and the accuracy rate is better than TOVA. It is a good tool to screen ADHD not only in Chinese children, but also in western country. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Structural and practical identifiability analysis of S-system.

PubMed

Zhan, Choujun; Li, Benjamin Yee Shing; Yeung, Lam Fat

2015-12-01

In the field of systems biology, biological reaction networks are usually modelled by ordinary differential equations. A sub-class, the S-systems representation, is a widely used form of modelling. Existing S-systems identification techniques assume that the system itself is always structurally identifiable. However, due to practical limitations, biological reaction networks are often only partially measured. In addition, the captured data only covers a limited trajectory, therefore data can only be considered as a local snapshot of the system responses with respect to the complete set of state trajectories over the entire state space. Hence the estimated model can only reflect partial system dynamics and may not be unique. To improve the identification quality, the structural and practical identifiablility of S-system are studied. The S-system is shown to be identifiable under a set of assumptions. Then, an application on yeast fermentation pathway was conducted. Two case studies were chosen; where the first case is based on a larger state trajectories and the second case is based on a smaller one. By expanding the dataset which span a relatively larger state space, the uncertainty of the estimated system can be reduced. The results indicated that initial concentration is related to the practical identifiablity.

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network

PubMed Central

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-01-01

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO2, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO2 and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO2; smoke and temperature; smoke, CO2 and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%–92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition. PMID:27527175

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

PubMed

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-08-04

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

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

Molecular-Based Identification and Detection of Salmonella in Food Production Systems: Current Perspectives.

PubMed

Ricke, Steven C; Kim, Sun Ae; Shi, Zhaohao; Park, Si Hong

2018-04-19

Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies has greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Technical note: Efficient online source identification algorithm for integration within a contamination event management system

NASA Astrophysics Data System (ADS)

Deuerlein, Jochen; Meyer-Harries, Lea; Guth, Nicolai

2017-07-01

Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

Damage identification of a TLP floating wind turbine by meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Ettefagh, M. M.

2015-12-01

Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring (SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP (Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms (GA), Artificial Immune System (AIS), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine (TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.

Blind system identification of two-thermocouple sensor based on cross-relation method.

PubMed

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

Blind system identification of two-thermocouple sensor based on cross-relation method

NASA Astrophysics Data System (ADS)

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

Intelligent person identification system using stereo camera-based height and stride estimation

NASA Astrophysics Data System (ADS)

Ko, Jung-Hwan; Jang, Jae-Hun; Kim, Eun-Soo

2005-05-01

In this paper, a stereo camera-based intelligent person identification system is suggested. In the proposed method, face area of the moving target person is extracted from the left image of the input steros image pair by using a threshold value of YCbCr color model and by carrying out correlation between the face area segmented from this threshold value of YCbCr color model and the right input image, the location coordinates of the target face can be acquired, and then these values are used to control the pan/tilt system through the modified PID-based recursive controller. Also, by using the geometric parameters between the target face and the stereo camera system, the vertical distance between the target and stereo camera system can be calculated through a triangulation method. Using this calculated vertical distance and the angles of the pan and tilt, the target's real position data in the world space can be acquired and from them its height and stride values can be finally extracted. Some experiments with video images for 16 moving persons show that a person could be identified with these extracted height and stride parameters.

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.

[Evaluation of common commercial systems for the identification of yeast isolates in microbiology laboratories: a multicenter study].

PubMed

Karabıçak, Nilgün; Uludağ Altun, Hatice; Karatuna, Onur; Hazırolan, Gülşen; Aksu, Neriman; Adiloğlu, Ali; Akyar, Işın

2015-04-01

Accurate and rapid identification of yeast isolates have become important in recent years for not only antifungal susceptibility testing due to the species-specific clinical resistance breakpoints but also early initiation of appropriate antifungal therapy. In clinical microbiology laboratories species identification of yeasts is often performed with several commercial systems based on biochemical properties and rarely according to the physiological and morphological characteristics. The aim of this study was to compare the two common commercial systems, VITEK 2 YST ID Card (Vitek; bioMérieux, France) and API 20C AUX (API; bioMérieux, France) with conventional mycological methods. A total of 473 clinical yeast strains isolated from clinical specimens in different university and training/research hospitals and identified by Vitek system were included in the study. The isolates were re-identified with API and conventional methods including morphological identification in the Mycology Reference Laboratory of the Public Health Institute of Turkey. Candida dubliniensis MYA 583, Candida krusei ATCC 6258, Candida parapsilosis ATCC 22019, Candida albicans ATCC 10231 and Cryptococcus neoformans ATCC 32268 were used as quality control strains and those standard strains were studied consecutively 10 days with both of the methods. The results of identification by Vitek and API were compared with the results of conventional methods for those 473 yeast isolates [6 genus (Candida, Cryptococcus, Blastoshizomyces, Rhodotorula, Saccharomyces, Trichosporon), 17 species (5 common and 12 rarely isolated)]. The performances of the systems were better (Vitek: 95%; API: 96%) for the commonly detected species (C.albicans, C.parapsilosis, C.glabrata, C.tropicalis and C.krusei) than those for rarely detected species (Vitek: 78.4%; API: 71.6%) (p= 0.155). Misidentification or unidentification were mostly detected for C.parapsilosis (Vitek: 6/87; API: 7/87) and C.glabrata (Vitek: 9/104; API: 3/104) by both of the systems. For rarely detected yeast isolates, misidentification or unidentification were most frequently observed in species of C.pelliculosa (Vitek: 3/11; API: 6/11) and C.dubliniensis (API and Vitek: 2/5) isolates. Candida guilliermondii (API: 2/5) isolates had lower rate of identification with API compared to other species. Blastoschizomyces capitatus and Saccharomyces cerevisiae isolates could not be identified by both of the systems. As a result, the accurate diagnosis of Vitek and API systems were similar in terms of consistency (86.3%). Two systems performed well in correct identification of common clinical yeast species (at least 95%), while the identification of rare species was more challenging indicating that they require further morphological and physiological testing. The addition of morphological identification to commercial systems will be useful for accurate diagnosis and treatment of mixed infections.

Discrimination of Scedosporium prolificans against Pseudallescheria boydii and Scedosporium apiospermum by semiautomated repetitive sequence-based PCR.

PubMed

Steinmann, J; Schmidt, D; Buer, J; Rath, P-M

2011-07-01

The laboratory identification of Pseudallescheria and Scedosporium isolates at the species level is important for clinical and epidemiological purposes. This study used semiautomated repetitive sequence-based polymerase chain reaction (rep-PCR) to identify Pseudallescheria/Scedosporium. Reference strains of Pseudallescheria boydii (n = 12), Scedosporium prolificans (n = 8), Scedosporium apiospermum (n = 9), and clinical/environmental isolates (P. boydii, 7; S. prolificans, 7; S. apiospermum, 7) were analyzed by rep-PCR. All clinical isolates were identified by morphological and phenotypic characteristics and by sequence analysis. Species identification of reference strains was based on the results of available databases. Rep-PCR studies were also conducted with various molds to differentiate Pseudallescheria/Scedosporium spp. from other commonly encountered filamentous fungi. All tested Pseudallescheria/Scedosporium isolates were distinguishable from the other filamentous fungi. All Scedosporium prolificans strains clustered within the cutoff of 85%, and species identification by rep-PCR showed an agreement of 100% with sequence analysis. However, several isolates of P. boydii and S. apiospermum did not cluster within the 85% cutoff with the same species by rep-PCR. Although the identification of P. boydii and S. apiospermum was not correct, the semiautomated rep-PCR system is a promising tool for the identification of S. prolificans isolates.

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.

Two New Real-Time PCR-based Surveillance Systems for “Candidatus Liberibacter” Species Detection

USDA-ARS?s Scientific Manuscript database

We developed two novel surveillance systems for “Candidatus Liberibacter” (CL) species detection and identification. The first system is called “single tube dual primer Taq-Man PCR” (STDP). The procedure involves two sequential rounds of PCR using the CL asiaticus species-specific outer and inner pr...

Proposal for a National Serials Data System.

ERIC Educational Resources Information Center

Adams, Scott

A hypothetical model is given for a National Serials Data System based on the best educated guesses of what the system should do and how, therefore, it should function. The model focuses attention on the ultimate goal rather than on the decision-making processes relating to choice of data elements, unique identification codes, etc. This conceptual…

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

PubMed Central

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

2015-01-01

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

Data-driven mono-component feature identification via modified nonlocal means and MEWT for mechanical drivetrain fault diagnosis

NASA Astrophysics Data System (ADS)

Pan, Jun; Chen, Jinglong; Zi, Yanyang; Yuan, Jing; Chen, Binqiang; He, Zhengjia

2016-12-01

It is significant to perform condition monitoring and fault diagnosis on rolling mills in steel-making plant to ensure economic benefit. However, timely fault identification of key parts in a complicated industrial system under operating condition is still a challenging task since acquired condition signals are usually multi-modulated and inevitably mixed with strong noise. Therefore, a new data-driven mono-component identification method is proposed in this paper for diagnostic purpose. First, the modified nonlocal means algorithm (NLmeans) is proposed to reduce noise in vibration signals without destroying its original Fourier spectrum structure. During the modified NLmeans, two modifications are investigated and performed to improve denoising effect. Then, the modified empirical wavelet transform (MEWT) is applied on the de-noised signal to adaptively extract empirical mono-component modes. Finally, the modes are analyzed for mechanical fault identification based on Hilbert transform. The results show that the proposed data-driven method owns superior performance during system operation compared with the MEWT method.

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

PubMed

Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

2017-07-01

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

[QR-Code based patient tracking: a cost-effective option to improve patient safety].

PubMed

Fischer, M; Rybitskiy, D; Strauß, G; Dietz, A; Dressler, C R

2013-03-01

Hospitals are implementing a risk management system to avoid patient or surgery mix-ups. The trend is to use preoperative checklists. This work deals specifically with a type of patient identification, which is realized by storing patient data on a patient-fixed medium. In 127 ENT surgeries data relevant for patient identification were encrypted in a 2D-QR-Code. The code, as a separate document coming with the patient chart or as a patient wristband, has been decrypted in the OR and the patient data were presented visible for all persons. The decoding time, the compliance of the patient data, as well as the duration of the patient identification was compared with the traditional patient identification by inspection of the patient chart. A total of 125 QR codes were read. The time for the decrypting of QR-Code was 5.6 s, the time for the screen view for patient identification was 7.9 s, and for a comparison group of 75 operations traditional patient identification was 27.3 s. Overall, there were 6 relevant information errors in the two parts of the experiment. This represents a ratio of 0.6% for 8 relevant classes per each encrypted QR code. This work allows a cost effective way to technically support patient identification based on electronic patient data. It was shown that the use in the clinical routine is possible. The disadvantage is a potential misinformation from incorrect or missing information in the HIS, or due to changes of the data after the code was created. The QR-code-based patient tracking is seen as a useful complement to the already widely used identification wristband. © Georg Thieme Verlag KG Stuttgart · New York.

Artificial Olfactory System for Trace Identification of Explosive Vapors Realized by Optoelectronic Schottky Sensing.

PubMed

Guo, Linjuan; Yang, Zheng; Dou, Xincun

2017-02-01

A rapid, ultrasensitive artificial olfactory system based on an individual optoelectronic Schottky junction is demonstrated for the discriminative detection of explosive vapors, including military explosives and improvised explosives. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Multi-Agent Diagnosis and Control of an Air Revitalization System for Life Support in Space

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Kowing, Jeffrey; Nieten, Joseph; Graham, Jeffrey s.; Schreckenghost, Debra; Bonasso, Pete; Fleming, Land D.; MacMahon, Matt; Thronesbery, Carroll

2000-01-01

An architecture of interoperating agents has been developed to provide control and fault management for advanced life support systems in space. In this adjustable autonomy architecture, software agents coordinate with human agents and provide support in novel fault management situations. This architecture combines the Livingstone model-based mode identification and reconfiguration (MIR) system with the 3T architecture for autonomous flexible command and control. The MIR software agent performs model-based state identification and diagnosis. MIR identifies novel recovery configurations and the set of commands required for the recovery. The AZT procedural executive and the human operator use the diagnoses and recovery recommendations, and provide command sequencing. User interface extensions have been developed to support human monitoring of both AZT and MIR data and activities. This architecture has been demonstrated performing control and fault management for an oxygen production system for air revitalization in space. The software operates in a dynamic simulation testbed.

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

NASA Astrophysics Data System (ADS)

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

2011-07-01

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

The 2002 NASA Faculty Fellowship Program Research Reports

NASA Technical Reports Server (NTRS)

Bland, J. (Compiler)

2003-01-01

Contents include the following: System Identification of X-33. Neural Network Advanced Ceramic Technology for Space Applications at NASA MSFC. Developing a MATLAB-Based Tool for Visualization and Transformation. Subsurface Stress Fields in Single Crystal (Anisotropic). Contacts Our Space Future: A Challenge to the Conceptual Artist Concept Art for Presentation and Education. Identification and Characterization of Extremophile Microorganisms. Significant to Astrobiology. Mathematical Investigation of Gamma Ray and Neutron. Absorption Grid Patterns for Homeland Defense-Related Fourier Imaging Systems. The Potential of Microwave Radiation for Processing Martian Soil. Fuzzy Logic Trajectory Design and Guidance for Terminal Area.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

An iterated cubature unscented Kalman filter for large-DoF systems identification with noisy data

NASA Astrophysics Data System (ADS)

Ghorbani, Esmaeil; Cha, Young-Jin

2018-04-01

Structural and mechanical system identification under dynamic loading has been an important research topic over the last three or four decades. Many Kalman-filtering-based approaches have been developed for linear and nonlinear systems. For example, to predict nonlinear systems, an unscented Kalman filter was applied. However, from extensive literature reviews, the unscented Kalman filter still showed weak performance on systems with large degrees of freedom. In this research, a modified unscented Kalman filter is proposed by integration of a cubature Kalman filter to improve the system identification performance of systems with large degrees of freedom. The novelty of this work lies on conjugating the unscented transform with the cubature integration concept to find a more accurate output from the transformation of the state vector and its related covariance matrix. To evaluate the proposed method, three different numerical models (i.e., the single degree-of-freedom Bouc-Wen model, the linear 3-degrees-of-freedom system, and the 10-degrees-of-freedom system) are investigated. To evaluate the robustness of the proposed method, high levels of noise in the measured response data are considered. The results show that the proposed method is significantly superior to the traditional UKF for noisy measured data in systems with large degrees of freedom.

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.

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.

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

PubMed

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

2016-07-13

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

A neural network-based approach to noise identification of interferometric GW antennas: the case of the 40 m Caltech laser interferometer

NASA Astrophysics Data System (ADS)

Acernese, F.; Barone, F.; de Rosa, M.; De Rosa, R.; Eleuteri, A.; Milano, L.; Tagliaferri, R.

2002-06-01

In this paper, a neural network-based approach is presented for the real time noise identification of a GW laser interferometric antenna. The 40 m Caltech laser interferometer output data provide a realistic test bed for noise identification algorithms because of the presence of many relevant effects: violin resonances in the suspensions, main power harmonics, ring-down noise from servo control systems, electronic noises, glitches and so on. These effects can be assumed to be present in all the first interferometric long baseline GW antennas such as VIRGO, LIGO, GEO and TAMA. For noise identification, we used the Caltech-40 m laser interferometer data. The results we obtained are pretty good notwithstanding the high initial computational cost. The algorithm we propose is general and robust, taking into account that it does not require a priori information on the data, nor a precise model, and it constitutes a powerful tool for time series data analysis.

PINS Spectrum Identification Guide

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

A.J. Caffrey

2012-03-01

The Portable Isotopic Neutron Spectroscopy—PINS, for short—system identifies the chemicals inside munitions and containers without opening them, a decided safety advantage if the fill chemical is a hazardous substance like a chemical warfare agent or an explosive. The PINS Spectrum Identification Guide is intended as a reference for technical professionals responsible for the interpretation of PINS gamma-ray spectra. The guide is divided into two parts. The three chapters that constitute Part I cover the science and technology of PINS. Neutron activation analysis is the focus of Chapter 1. Chapter 2 explores PINS hardware, software, and related operational issues. Gamma-ray spectralmore » analysis basics are introduced in Chapter 3. The six chapters of Part II cover the identification of PINS spectra in detail. Like the PINS decision tree logic, these chapters are organized by chemical element: phosphorus-based chemicals, chlorine-based chemicals, etc. These descriptions of hazardous, toxic, and/or explosive chemicals conclude with a chapter on the identification of the inert chemicals, e.g. sand, used to fill practice munitions.« less

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.

Studies in knowledge-based diagnosis of failures in robotic assembly

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

StakeMeter: value-based stakeholder identification and quantification framework for value-based software systems.

PubMed

Babar, Muhammad Imran; Ghazali, Masitah; Jawawi, Dayang N A; Bin Zaheer, Kashif

2015-01-01

Value-based requirements engineering plays a vital role in the development of value-based software (VBS). Stakeholders are the key players in the requirements engineering process, and the selection of critical stakeholders for the VBS systems is highly desirable. Based on the stakeholder requirements, the innovative or value-based idea is realized. The quality of the VBS system is associated with the concrete set of valuable requirements, and the valuable requirements can only be obtained if all the relevant valuable stakeholders participate in the requirements elicitation phase. The existing value-based approaches focus on the design of the VBS systems. However, the focus on the valuable stakeholders and requirements is inadequate. The current stakeholder identification and quantification (SIQ) approaches are neither state-of-the-art nor systematic for the VBS systems. The existing approaches are time-consuming, complex and inconsistent which makes the initiation process difficult. Moreover, the main motivation of this research is that the existing SIQ approaches do not provide the low level implementation details for SIQ initiation and stakeholder metrics for quantification. Hence, keeping in view the existing SIQ problems, this research contributes in the form of a new SIQ framework called 'StakeMeter'. The StakeMeter framework is verified and validated through case studies. The proposed framework provides low-level implementation guidelines, attributes, metrics, quantification criteria and application procedure as compared to the other methods. The proposed framework solves the issues of stakeholder quantification or prioritization, higher time consumption, complexity, and process initiation. The framework helps in the selection of highly critical stakeholders for the VBS systems with less judgmental error.

41 CFR 101-42.202 - Identification of hazardous materials.

Code of Federal Regulations, 2011 CFR

2011-07-01

...'s Federal Supply Service (4FQ) maintains an automated data base, accessible via modem and computer... on the terminal screen, the system allows for the addition of the MSDS to the user's local data base... personnel who handle, store, ship, use or dispose of hazardous materials. Each record in the data base is...

41 CFR 101-42.202 - Identification of hazardous materials.

Code of Federal Regulations, 2010 CFR

2010-07-01

...'s Federal Supply Service (4FQ) maintains an automated data base, accessible via modem and computer... on the terminal screen, the system allows for the addition of the MSDS to the user's local data base... personnel who handle, store, ship, use or dispose of hazardous materials. Each record in the data base is...

41 CFR 101-42.202 - Identification of hazardous materials.

Code of Federal Regulations, 2013 CFR

2013-07-01

...'s Federal Supply Service (4FQ) maintains an automated data base, accessible via modem and computer... on the terminal screen, the system allows for the addition of the MSDS to the user's local data base... personnel who handle, store, ship, use or dispose of hazardous materials. Each record in the data base is...

41 CFR 101-42.202 - Identification of hazardous materials.

Code of Federal Regulations, 2014 CFR

2014-07-01

...'s Federal Supply Service (4FQ) maintains an automated data base, accessible via modem and computer... on the terminal screen, the system allows for the addition of the MSDS to the user's local data base... personnel who handle, store, ship, use or dispose of hazardous materials. Each record in the data base is...

41 CFR 101-42.202 - Identification of hazardous materials.

Code of Federal Regulations, 2012 CFR

2012-07-01

...'s Federal Supply Service (4FQ) maintains an automated data base, accessible via modem and computer... on the terminal screen, the system allows for the addition of the MSDS to the user's local data base... personnel who handle, store, ship, use or dispose of hazardous materials. Each record in the data base is...

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.

On the optimal identification of tag sets in time-constrained RFID configurations.

PubMed

Vales-Alonso, Javier; Bueno-Delgado, María Victoria; Egea-López, Esteban; Alcaraz, Juan José; Pérez-Mañogil, Juan Manuel

2011-01-01

In Radio Frequency Identification facilities the identification delay of a set of tags is mainly caused by the random access nature of the reading protocol, yielding a random identification time of the set of tags. In this paper, the cumulative distribution function of the identification time is evaluated using a discrete time Markov chain for single-set time-constrained passive RFID systems, namely those ones where a single group of tags is assumed to be in the reading area and only for a bounded time (sojourn time) before leaving. In these scenarios some tags in a set may leave the reader coverage area unidentified. The probability of this event is obtained from the cumulative distribution function of the identification time as a function of the sojourn time. This result provides a suitable criterion to minimize the probability of losing tags. Besides, an identification strategy based on splitting the set of tags in smaller subsets is also considered. Results demonstrate that there are optimal splitting configurations that reduce the overall identification time while keeping the same probability of losing tags.

Advancements in robust algorithm formulation for speaker identification of whispered speech

NASA Astrophysics Data System (ADS)

Fan, Xing

Whispered speech is an alternative speech production mode from neutral speech, which is used by talkers intentionally in natural conversational scenarios to protect privacy and to avoid certain content from being overheard/made public. Due to the profound differences between whispered and neutral speech in production mechanism and the absence of whispered adaptation data, the performance of speaker identification systems trained with neutral speech degrades significantly. This dissertation therefore focuses on developing a robust closed-set speaker recognition system for whispered speech by using no or limited whispered adaptation data from non-target speakers. This dissertation proposes the concept of "High''/"Low'' performance whispered data for the purpose of speaker identification. A variety of acoustic properties are identified that contribute to the quality of whispered data. An acoustic analysis is also conducted to compare the phoneme/speaker dependency of the differences between whispered and neutral data in the feature domain. The observations from those acoustic analysis are new in this area and also serve as a guidance for developing robust speaker identification systems for whispered speech. This dissertation further proposes two systems for speaker identification of whispered speech. One system focuses on front-end processing. A two-dimensional feature space is proposed to search for "Low''-quality performance based whispered utterances and separate feature mapping functions are applied to vowels and consonants respectively in order to retain the speaker's information shared between whispered and neutral speech. The other system focuses on speech-mode-independent model training. The proposed method generates pseudo whispered features from neutral features by using the statistical information contained in a whispered Universal Background model (UBM) trained from extra collected whispered data from non-target speakers. Four modeling methods are proposed for the transformation estimation in order to generate the pseudo whispered features. Both of the above two systems demonstrate a significant improvement over the baseline system on the evaluation data. This dissertation has therefore contributed to providing a scientific understanding of the differences between whispered and neutral speech as well as improved front-end processing and modeling method for speaker identification of whispered speech. Such advancements will ultimately contribute to improve the robustness of speech processing systems.

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

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.

Utility of 16S rDNA Sequencing for Identification of Rare Pathogenic Bacteria.

PubMed

Loong, Shih Keng; Khor, Chee Sieng; Jafar, Faizatul Lela; AbuBakar, Sazaly

2016-11-01

Phenotypic identification systems are established methods for laboratory identification of bacteria causing human infections. Here, the utility of phenotypic identification systems was compared against 16S rDNA identification method on clinical isolates obtained during a 5-year study period, with special emphasis on isolates that gave unsatisfactory identification. One hundred and eighty-seven clinical bacteria isolates were tested with commercial phenotypic identification systems and 16S rDNA sequencing. Isolate identities determined using phenotypic identification systems and 16S rDNA sequencing were compared for similarity at genus and species level, with 16S rDNA sequencing as the reference method. Phenotypic identification systems identified ~46% (86/187) of the isolates with identity similar to that identified using 16S rDNA sequencing. Approximately 39% (73/187) and ~15% (28/187) of the isolates showed different genus identity and could not be identified using the phenotypic identification systems, respectively. Both methods succeeded in determining the species identities of 55 isolates; however, only ~69% (38/55) of the isolates matched at species level. 16S rDNA sequencing could not determine the species of ~20% (37/187) of the isolates. The 16S rDNA sequencing is a useful method over the phenotypic identification systems for the identification of rare and difficult to identify bacteria species. The 16S rDNA sequencing method, however, does have limitation for species-level identification of some bacteria highlighting the need for better bacterial pathogen identification tools. © 2016 Wiley Periodicals, Inc.

Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory

PubMed Central

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

2015-01-01

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system. PMID:26580620

COI barcode based species-specific primers for identification of five species of stored-product pests from genus Cryptolestes (Coleoptera: Laemophloeidae).

PubMed

Varadínová, Z; Wang, Y J; Kučerová, Z; Stejskal, V; Opit, G; Cao, Y; Li, F J; Li, Z H

2015-04-01

Flat grain beetles of the genus Cryptolestes (Coleoptera: Laemophloeidae) are one of the economically most important stored-product pests which feed on many kinds of agricultural products, especially grains. Nine of more than 40 described Cryptolestes species are recognized as stored-product pests and two of the pest species have a cosmopolitan distribution. Given the rapid growth in global trade of food products, ecological barriers to the spread of pests are easily overcome. Therefore, development of reliable systems for routine quarantine inspection and early infestation detection is vital. In the present study, we established a new rapid and accurate cytochrome c oxidase subunit I-based system for molecular identification of five common stored-product Cryptolestes species, namely, Cryptolestes capensis, Cryptolestes ferrugineus, Cryptolestes pusilloides, Cryptolestes pusillus and Cryptolestes turcicus. Five species-specific primer pairs for traditional uniplex polymerase chain reaction assay are described and their specificity and sensitivity for the identification process is evaluated using larval samples of 12 different populations from three continents (Asia, Europe and North America).

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.

First experiences in the implementation of biometric technology to link data from Health and Demographic Surveillance Systems with health facility data

PubMed Central

Serwaa-Bonsu, Adwoa; Herbst, Abraham J.; Reniers, Georges; Ijaa, Wilfred; Clark, Benjamin; Kabudula, Chodziwadziwa; Sankoh, Osman

2010-01-01

Background In developing countries, Health and Demographic Surveillance Systems (HDSSs) provide a framework for tracking demographic and health dynamics over time in a defined geographical area. Many HDSSs co-exist with facility-based data sources in the form of Health Management Information Systems (HMIS). Integrating both data sources through reliable record linkage could provide both numerator and denominator populations to estimate disease prevalence and incidence rates in the population and enable determination of accurate health service coverage. Objective To measure the acceptability and performance of fingerprint biometrics to identify individuals in demographic surveillance populations and those attending health care facilities serving the surveillance populations. Methodology Two HDSS sites used fingerprint biometrics for patient and/or surveillance population participant identification. The proportion of individuals for whom a fingerprint could be successfully enrolled were characterised in terms of age and sex. Results Adult (18–65 years) fingerprint enrolment rates varied between 94.1% (95% CI 93.6–94.5) for facility-based fingerprint data collection at the Africa Centre site to 96.7% (95% CI 95.9–97.6) for population-based fingerprint data collection at the Agincourt site. Fingerprint enrolment rates in children under 1 year old (Africa Centre site) were only 55.1% (95% CI 52.7–57.4). By age 5, child fingerprint enrolment rates were comparable to those of adults. Conclusion This work demonstrates the feasibility of fingerprint-based individual identification for population-based research in developing countries. Record linkage between demographic surveillance population databases and health care facility data based on biometric identification systems would allow for a more comprehensive evaluation of population health, including the ability to study health service utilisation from a population perspective, rather than the more restrictive health service perspective. PMID:20200659

Recursive inversion of externally defined linear systems

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Candidate Causes. Sediments. In: Causal Analysis, Diagnosis Decision Information System, USEPA Website

EPA Science Inventory

CADDIS is an online application that helps scientists and engineers in the Regions, States, and Tribes find, access, organize, use, and share information to conduct causal evaluations in aquatic systems. It is based on the USEPA stressor identification process, a formal method fo...

Identification of FOPDT and SOPDT process dynamics using closed loop test.

PubMed

Bajarangbali, Raghunath; Majhi, Somanath; Pandey, Saurabh

2014-07-01

In this paper, identification of stable and unstable first order, second order overdamped and underdamped process dynamics with time delay is presented. Relay with hysteresis is used to induce a limit cycle output and using this information, unknown process model parameters are estimated. State space based generalized analytical expressions are derived to achieve accurate results. To show the performance of the proposed method expressions are also derived for systems with a zero. In real time systems, measurement noise is an important issue during identification of process dynamics. A relay with hysteresis reduces the effect of measurement noise, in addition a new multiloop control strategy is proposed to recover the original limit cycle. Simulation results are included to validate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

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.

[Typing of skin staphylococci using the commercial identification system Staphy-Test].

PubMed

Pospísil, L; Pospísilova, A; Kocur, M

1989-01-01

The authors examined 150 strains of S. aureus and 180 strains of S. epidermidis isolated from different dermatoses. The determination of S. aureus and S. epidermidis was based on common routine tests as plasmacoagulase, production of hemolysin, acid production from mannitol and production of pigment. This determination was verified with the aid of a new identification system STAPHYtest. The STAPHYtest confirmed the previous diagnosis of S. aureus in 60.66% and that of S. epidermidis in 31.66% of strains only. The remaining strains were identified by means of STAPHYtest as S. simulans, S. xylosus, S. hominis, S. haemolyticus, S. warneri, S. auricularis, S. sciuri and Micrococcus sp. The authors discuss the importance of an curate identification of skin staphylococci by means of STAPHYtest for taxonomic purposes and for classification of staphylococci influence on different dermatoses.

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.

Prospective Evaluation of a Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry System in a Hospital Clinical Microbiology Laboratory for Identification of Bacteria and Yeasts: a Bench-by-Bench Study for Assessing the Impact on Time to Identification and Cost-Effectiveness

PubMed Central

Tan, K. E.; Ellis, B. C.; Lee, R.; Stamper, P. D.; Zhang, S. X.

2012-01-01

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has been found to be an accurate, rapid, and inexpensive method for the identification of bacteria and yeasts. Previous evaluations have compared the accuracy, time to identification, and costs of the MALDI-TOF MS method against standard identification systems or commercial panels. In this prospective study, we compared a protocol incorporating MALDI-TOF MS (MALDI protocol) with the current standard identification protocols (standard protocol) to determine the performance in actual practice using a specimen-based, bench-by-bench approach. The potential impact on time to identification (TTI) and costs had MALDI-TOF MS been the first-line identification method was quantitated. The MALDI protocol includes supplementary tests, notably for Streptococcus pneumoniae and Shigella, and indications for repeat MALDI-TOF MS attempts, often not measured in previous studies. A total of 952 isolates (824 bacterial isolates and 128 yeast isolates) recovered from 2,214 specimens were assessed using the MALDI protocol. Compared with standard protocols, the MALDI protocol provided identifications 1.45 days earlier on average (P < 0.001). In our laboratory, we anticipate that the incorporation of the MALDI protocol can reduce reagent and labor costs of identification by $102,424 or 56.9% within 12 months. The model included the fixed annual costs of the MALDI-TOF MS, such as the cost of protein standards and instrument maintenance, and the annual prevalence of organisms encountered in our laboratory. This comprehensive cost analysis model can be generalized to other moderate- to high-volume laboratories. PMID:22855510

Prospective evaluation of a matrix-assisted laser desorption ionization-time of flight mass spectrometry system in a hospital clinical microbiology laboratory for identification of bacteria and yeasts: a bench-by-bench study for assessing the impact on time to identification and cost-effectiveness.

PubMed

Tan, K E; Ellis, B C; Lee, R; Stamper, P D; Zhang, S X; Carroll, K C

2012-10-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been found to be an accurate, rapid, and inexpensive method for the identification of bacteria and yeasts. Previous evaluations have compared the accuracy, time to identification, and costs of the MALDI-TOF MS method against standard identification systems or commercial panels. In this prospective study, we compared a protocol incorporating MALDI-TOF MS (MALDI protocol) with the current standard identification protocols (standard protocol) to determine the performance in actual practice using a specimen-based, bench-by-bench approach. The potential impact on time to identification (TTI) and costs had MALDI-TOF MS been the first-line identification method was quantitated. The MALDI protocol includes supplementary tests, notably for Streptococcus pneumoniae and Shigella, and indications for repeat MALDI-TOF MS attempts, often not measured in previous studies. A total of 952 isolates (824 bacterial isolates and 128 yeast isolates) recovered from 2,214 specimens were assessed using the MALDI protocol. Compared with standard protocols, the MALDI protocol provided identifications 1.45 days earlier on average (P < 0.001). In our laboratory, we anticipate that the incorporation of the MALDI protocol can reduce reagent and labor costs of identification by $102,424 or 56.9% within 12 months. The model included the fixed annual costs of the MALDI-TOF MS, such as the cost of protein standards and instrument maintenance, and the annual prevalence of organisms encountered in our laboratory. This comprehensive cost analysis model can be generalized to other moderate- to high-volume laboratories.

Identification and Analysis of National Airspace System Resource Constraints

NASA Technical Reports Server (NTRS)

Smith, Jeremy C.; Marien, Ty V.; Viken, Jeffery K.; Neitzke, Kurt W.; Kwa, Tech-Seng; Dollyhigh, Samuel M.; Fenbert, James W.; Hinze, Nicolas K.

2015-01-01

This analysis is the deliverable for the Airspace Systems Program, Systems Analysis Integration and Evaluation Project Milestone for the Systems and Portfolio Analysis (SPA) focus area SPA.4.06 Identification and Analysis of National Airspace System (NAS) Resource Constraints and Mitigation Strategies. "Identify choke points in the current and future NAS. Choke points refer to any areas in the en route, terminal, oceanic, airport, and surface operations that constrain actual demand in current and projected future operations. Use the Common Scenarios based on Transportation Systems Analysis Model (TSAM) projections of future demand developed under SPA.4.04 Tools, Methods and Scenarios Development. Analyze causes, including operational and physical constraints." The NASA analysis is complementary to a NASA Research Announcement (NRA) "Development of Tools and Analysis to Evaluate Choke Points in the National Airspace System" Contract # NNA3AB95C awarded to Logistics Management Institute, Sept 2013.

47 CFR 80.231 - Technical Requirements for Class B Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Identification System (AIS) equipment. 80.231 Section 80.231 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... § 80.231 Technical Requirements for Class B Automatic Identification System (AIS) equipment. (a) Class B Automatic Identification System (AIS) equipment must meet the technical requirements of IEC 62287...

47 CFR 80.231 - Technical Requirements for Class B Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Identification System (AIS) equipment. 80.231 Section 80.231 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... § 80.231 Technical Requirements for Class B Automatic Identification System (AIS) equipment. (a) Class B Automatic Identification System (AIS) equipment must meet the technical requirements of IEC 62287...

47 CFR 80.231 - Technical Requirements for Class B Automatic Identification System (AIS) equipment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Identification System (AIS) equipment. 80.231 Section 80.231 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... § 80.231 Technical Requirements for Class B Automatic Identification System (AIS) equipment. (a) Class B Automatic Identification System (AIS) equipment must meet the technical requirements of IEC 62287...

Planning for Competency-Based Teacher Education at the State Level.

ERIC Educational Resources Information Center

Roth, Robert A.

There are eight areas which require attention in planning for state implementation of performance-based teacher education (PBTE): (a) initiation action, (b) goal statement formulation, (c) state role identification, (d) certification pattern design, (e) delivery system structure, (f) support mechanism organization, (g) regulation changes…

Genie Inference Engine Rule Writer’s Guide.

DTIC Science & Technology

1987-08-01

33 APPENDIX D. Animal Bootstrap File.............................................................. 39...APPENDIX E. Sample Run of Animal Identification Expert System.......................... 43 APPENDIX F. Numeric Test Knowledge Base...and other data s.tructures stored in the knowledge base (KB), queries the user for input, and draws conclusions. Genie (GENeric Inference Engine) is

Phytophthora-ID.org: A sequence-based Phytophthora identification tool

Treesearch

N.J. Grünwald; F.N. Martin; M.M. Larsen; C.M. Sullivan; C.M. Press; M.D. Coffey; E.M. Hansen; J.L. Parke

2010-01-01

Contemporary species identification relies strongly on sequence-based identification, yet resources for identification of many fungal and oomycete pathogens are rare. We developed two web-based, searchable databases for rapid identification of Phytophthora spp. based on sequencing of the internal transcribed spacer (ITS) or the cytochrome oxidase...

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

Not Available

Standardization of grant and contract awardee names has been an area of concern since the development of the Department`s Procurement and Assistance Data System (PADS). A joint effort was begun in 1983 by the Office of Scientific and Technical Information (OSTI) and the Office of Procurement and Assistance Management/Information Systems and Analysis Division to develop a means for providing uniformity of awardee names. As a result of this effort, a method of assigning vendor identification codes to each unique awardee name, division, city, and state combination was developed and is maintained by OSTI. Changes to vendor identification codes or awardeemore » names contained in PADS can be made only by OSTI. Awardee names in the Directory indicate that the awardee has had a prime contract (excluding purchase orders of $10,000 or less) with, or a financial assistance award from, the Department. Award status--active, inactive, or retired--is not shown. The Directory is in alphabetic sequence based on awardee name and reflects the OSTI-assigned vendor identification code to the right of the name. A vendor identification code is assigned to each unique awardee name, division, city, and state (for place of performance). The same vendor identification code is used for awards throughout the Department.« less

Neural network modeling of nonlinear systems based on Volterra series extension of a linear model

NASA Technical Reports Server (NTRS)

Soloway, Donald I.; Bialasiewicz, Jan T.

1992-01-01

A Volterra series approach was applied to the identification of nonlinear systems which are described by a neural network model. A procedure is outlined by which a mathematical model can be developed from experimental data obtained from the network structure. Applications of the results to the control of robotic systems are discussed.

Polluter identification with spaceborne radar imagery, AIS and forward drift modeling.

PubMed

Longépé, N; Mouche, A A; Goacolou, M; Granier, N; Carrere, L; Lebras, J Y; Lozach, P; Besnard, S

2015-12-30

This study defines and assesses a new operational concept to identify the origin of pollution at sea, based on Synthetic Aperture Radar, Automatic Identification System, and a forward drift model. As opposed to traditional methodologies where the SAR detected pollution is backtracked in the past, our approach assumes that all the vessels pollute all along their way. Based on all the AIS data flows, the forward-tracked simulated pollutions are then compared to the detected pollution, and the potential polluter can be finally identified. Case studies are presented to showcase its usefulness in a variety of maritime situations with a focus on orphan pollutions in a dense traffic area. Out of the identification of the suspected polluters, the age and eventually the type of the pollution can be retrieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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

Identifying Executable Plans

NASA Technical Reports Server (NTRS)

Bedrax-Weiss, Tania; Jonsson, Ari K.; Frank, Jeremy D.; McGann, Conor

2003-01-01

Generating plans for execution imposes a different set of requirements on the planning process than those imposed by planning alone. In highly unpredictable execution environments, a fully-grounded plan may become inconsistent frequently when the world fails to behave as expected. Intelligent execution permits making decisions when the most up-to-date information is available, ensuring fewer failures. Planning should acknowledge the capabilities of the execution system, both to ensure robust execution in the face of uncertainty, which also relieves the planner of the burden of making premature commitments. We present Plan Identification Functions (PIFs), which formalize what it means for a plan to be executable, md are used in conjunction with a complete model of system behavior to halt the planning process when an executable plan is found. We describe the implementation of plan identification functions for a temporal, constraint-based planner. This particular implementation allows the description of many different plan identification functions. characteristics crf the xectieonfvii rnm-enft,h e best plan to hand to the execution system will contain more or less commitment and information.

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

Automated extraction of family history information from clinical notes.

PubMed

Bill, Robert; Pakhomov, Serguei; Chen, Elizabeth S; Winden, Tamara J; Carter, Elizabeth W; Melton, Genevieve B

2014-01-01

Despite increased functionality for obtaining family history in a structured format within electronic health record systems, clinical notes often still contain this information. We developed and evaluated an Unstructured Information Management Application (UIMA)-based natural language processing (NLP) module for automated extraction of family history information with functionality for identifying statements, observations (e.g., disease or procedure), relative or side of family with attributes (i.e., vital status, age of diagnosis, certainty, and negation), and predication ("indicator phrases"), the latter of which was used to establish relationships between observations and family member. The family history NLP system demonstrated F-scores of 66.9, 92.4, 82.9, 57.3, 97.7, and 61.9 for detection of family history statements, family member identification, observation identification, negation identification, vital status, and overall extraction of the predications between family members and observations, respectively. While the system performed well for detection of family history statements and predication constituents, further work is needed to improve extraction of certainty and temporal modifications.

Automated Extraction of Family History Information from Clinical Notes

PubMed Central

Bill, Robert; Pakhomov, Serguei; Chen, Elizabeth S.; Winden, Tamara J.; Carter, Elizabeth W.; Melton, Genevieve B.

2014-01-01

Despite increased functionality for obtaining family history in a structured format within electronic health record systems, clinical notes often still contain this information. We developed and evaluated an Unstructured Information Management Application (UIMA)-based natural language processing (NLP) module for automated extraction of family history information with functionality for identifying statements, observations (e.g., disease or procedure), relative or side of family with attributes (i.e., vital status, age of diagnosis, certainty, and negation), and predication (“indicator phrases”), the latter of which was used to establish relationships between observations and family member. The family history NLP system demonstrated F-scores of 66.9, 92.4, 82.9, 57.3, 97.7, and 61.9 for detection of family history statements, family member identification, observation identification, negation identification, vital status, and overall extraction of the predications between family members and observations, respectively. While the system performed well for detection of family history statements and predication constituents, further work is needed to improve extraction of certainty and temporal modifications. PMID:25954443

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.

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.

UAV-borne X-band radar for MAV collision avoidance

NASA Astrophysics Data System (ADS)

Moses, Allistair A.; Rutherford, Matthew J.; Kontitsis, Michail; Valavanis, Kimon P.

2011-05-01

Increased use of Miniature (Unmanned) Aerial Vehicles (MAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further increases in levels of autonomy and consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for MAV integration are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other MAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, performance of visual-range optical sensor systems can suffer greatly when operating in the conditions that are typically encountered during search and rescue, surveillance, combat, and most common MAV applications. However, the addition of a miniature radar system can, in consort with other sensors, provide comprehensive target detection and identification capabilities for MAVs. This trend is observed in manned aviation where radar systems are the primary detection and identification sensor system. Within this document a miniature, lightweight X-Band radar system for use on a miniature (710mm rotor diameter) rotorcraft is described. We present analyses of the performance of the system in a realistic scenario with two MAVs. Additionally, an analysis of MAV navigation and collision avoidance behaviors is performed to determine the effect of integrating radar systems into MAV-class vehicles.

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.

Enhanced terahertz imaging system performance analysis and design tool for concealed weapon identification

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Franck, Charmaine C.; Espinola, Richard L.; Petkie, Douglas T.; De Lucia, Frank C.; Jacobs, Eddie L.

2011-11-01

The U.S. Army Research Laboratory (ARL) and the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) have developed a terahertz-band imaging system performance model/tool for detection and identification of concealed weaponry. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security & Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). This paper will provide a comprehensive review of an enhanced, user-friendly, Windows-executable, terahertz-band imaging system performance analysis and design tool that now includes additional features such as a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures. This newly enhanced THz imaging system design tool is an extension of the advanced THz imaging system performance model that was developed under the Defense Advanced Research Project Agency's (DARPA) Terahertz Imaging Focal-Plane Technology (TIFT) program. This paper will also provide example system component (active-illumination source and detector) trade-study analyses using the new features of this user-friendly THz imaging system performance analysis and design tool.

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.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

NASA Technical Reports Server (NTRS)

Zeyada, Y.; Hess, R. A.

1999-01-01

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations i The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzyinference identification can be used to reflect changes in simulator fidelity for the task examined.

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

NASA Technical Reports Server (NTRS)

Zeyada, Y.; Hess, R. A.

1999-01-01

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations. The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy-inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzy-inference identification can be used to reflect changes in simulator fidelity for the task examined.

An Analysis of Serial Number Tracking Automatic Identification Technology as Used in Naval Aviation Programs

NASA Astrophysics Data System (ADS)

Csorba, Robert

2002-09-01

The Government Accounting Office found that the Navy, between 1996 and 1998, lost 3 billion in materiel in-transit. This thesis explores the benefits and cost of automatic identification and serial number tracking technologies under consideration by the Naval Supply Systems Command and the Naval Air Systems Command. Detailed cost-savings estimates are made for each aircraft type in the Navy inventory. Project and item managers of repairable components using Serial Number Tracking were surveyed as to the value of this system. It concludes that two thirds of the in-transit losses can be avoided with implementation of effective information technology-based logistics and maintenance tracking systems. Recommendations are made for specific steps and components of such an implementation. Suggestions are made for further research.

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.

Design and Validation of a Radio-Frequency Identification-Based Device for Routinely Assessing Gait Speed in a Geriatrics Clinic.

PubMed

Barry, Lisa C; Hatchman, Laura; Fan, Zhaoyan; Guralnik, Jack M; Gao, Robert X; Kuchel, George A

2018-05-01

To evaluate the feasibility, acceptability, and validity of a radio-frequency identification (RFID)-based system to measure gait speed in a clinical setting as a first step to using unobtrusive gait speed assessment in routine clinical care. Feasibility study comparing gait speed assessed using an RFID-based system with gait speed assessed using handheld stopwatch, the criterion standard. Outpatient geriatrics clinic at a Connecticut-based academic medical center. Clinic attendees who could walk independently with or without an assistive device (N=50) and healthcare providers (N=9). Gait speed was measured in twice using 2 methods each time before participants entered an examination room. Participants walked at their usual pace while gait speed was recorded simultaneously using the RFID-based system and a handheld stopwatch operated by a trained study investigator. After 2 trials, participants completed a brief survey regarding their experience. At the end of the study period, clinic healthcare providers completed a separate survey. Test-retest reliability of the RFID-based system was high (intraclass correlation coefficient = 0.953). The mean difference ± standard deviation in gait speed between the RFID-based system and the stopwatch was -0.003±0.035 m/s (p=.53) and did not differ significantly according to age, sex, or use of an assistive walking aid. Acceptability of the device was high, and 8 of 9 providers indicated that measuring gait speed using the RFID-based system should be a part of routine clinical care. RFID technology may offer a practical means of overcoming barriers to routine measurement of gait speed in real-world outpatient clinical settings. © 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

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.

Laser system for identification, tracking, and control of flying insects

USDA-ARS?s Scientific Manuscript database

Flying insects are common vectors for transmission of pathogens and inflict significant harm on humans in large parts of the developing world. Besides the direct impact to humans, these pathogens also cause harm to crops and result in agricultural losses. Here, we present a laser-based system that c...

Risk-Based Neuro-Grid Architecture for Multimodal Biometrics

NASA Astrophysics Data System (ADS)

Venkataraman, Sitalakshmi; Kulkarni, Siddhivinayak

Recent research indicates that multimodal biometrics is the way forward for a highly reliable adoption of biometric identification systems in various applications, such as banks, businesses, government and even home environments. However, such systems would require large distributed datasets with multiple computational realms spanning organisational boundaries and individual privacies.