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

PubMed Central

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

1994-01-01

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

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.

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.

The specific diagnosis of gastrointestinal nematode infections in livestock: larval culture technique, its limitations and alternative DNA-based approaches.

PubMed

Roeber, Florian; Kahn, Lewis

2014-10-15

The specific diagnosis of gastrointestinal nematode infections in ruminants is routinely based on larval culture technique and on the morphological identification of developed third-stage larvae. However, research on the ecology and developmental requirements of different species suggests that environmental conditions (e.g., temperature and humidity) for optimal development to occur vary between the different species. Thus, employing a common culture protocol for all species will favour the development of certain species over others and can cause a biased result in particular when species proportions in a mixed infection are to be determined. Furthermore, the morphological identification of L3 larvae is complicated by a lack of distinctive, obvious features that would allow the identification of all key species. In the present paper we review in detail the potential limitations of larval culture technique and morphological identification and provide account to some modern molecular alternatives to the specific diagnosis of gastrointestinal nematode infection in ruminants. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

Identification of Terrestrial Reflectance From Remote Sensing

NASA Technical Reports Server (NTRS)

Alter-Gartenberg, Rachel; Nolf, Scott R.; Stacy, Kathryn (Technical Monitor)

2000-01-01

Correcting for atmospheric effects is an essential part of surface-reflectance recovery from radiance measurements. Model-based atmospheric correction techniques enable an accurate identification and classification of terrestrial reflectances from multi-spectral imagery. Successful and efficient removal of atmospheric effects from remote-sensing data is a key factor in the success of Earth observation missions. This report assesses the performance, robustness and sensitivity of two atmospheric-correction and reflectance-recovery techniques as part of an end-to-end simulation of hyper-spectral acquisition, identification and classification.

Techniques for characterization and eradication of potato cyst nematode: a review.

PubMed

Bairwa, Aarti; Venkatasalam, E P; Sudha, R; Umamaheswari, R; Singh, B P

2017-09-01

Correct identification of species and pathotypes is must for eradication of potato cyst nematodes (PCN). The identification of PCN species after completing the life cycle is very difficult because it is based on morphological and morphometrical characteristics. Genetically different populations of PCN are morphologically same and differentiated based on the host differential study. Later on these traditional techniques have been replaced by biochemical techniques viz, one and two dimensional gel electrophoresis, capillary gel electrophoresis, isozymes, dot blot hybridization and isoelectric focusing etc. to distinguish both the species. One and two dimensional gel electrophoresis has used to examine inter- and intra-specific differences in proteins of Globodera rostochiensis and G. pallida . Now application of PCR and DNA based characterization techniques like RAPD, AFLP and RFLP are the important tools for differentiating inter- and intra specific variation in PCN and has given opportunities to accurate identification of PCN. For managing the PCN, till now we are following integrated pest management (IPM) strategies, however these strategies are not effective to eradicate the PCN. Therefore to eradicate the PCN we need noval management practices like RNAi (RNA interference) or Gene silencing.

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.

Aircraft flight flutter testing at the NASA Ames-Dryden Flight Research Facility

NASA Technical Reports Server (NTRS)

Kehoe, Michael W.

1988-01-01

Many parameter identification techniques have been used at the NASA Ames Research Center, Dryden Research Facility at Edwards Air Force Base to determine the aeroelastic stability of new and modified research vehicles in flight. This paper presents a summary of each technique used with emphasis on fast Fourier transform methods. Experiences gained from application of these techniques to various flight test programs are discussed. Also presented are data-smoothing techniques used for test data distorted by noise. Data are presented for various aircraft to demonstrate the accuracy of each parameter identification technique discussed.

A robust star identification algorithm with star shortlisting

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Identification of Organic Colorants in Art Objects by Solution Spectrophotometry: Pigments.

ERIC Educational Resources Information Center

Billmeyer, Fred W., Jr.; And Others

1981-01-01

Describes solution spectrophotometry as a simple, rapid identification technique for organic paint pigments. Reports research which includes analytical schemes for the extraction and separation of organic pigments based on their solubilities, and the preparation of an extensive reference collection of spectral curves allowing their identification.…

Fractional System Identification: An Approach Using Continuous Order-Distributions

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

1999-01-01

This paper discusses the identification of fractional- and integer-order systems using the concept of continuous order-distribution. Based on the ability to define systems using continuous order-distributions, it is shown that frequency domain system identification can be performed using least squares techniques after discretizing the order-distribution.

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.

Analysis and Identification of Acid-Base Indicator Dyes by Thin-Layer Chromatography

ERIC Educational Resources Information Center

Clark, Daniel D.

2007-01-01

Thin-layer chromatography (TLC) is a very simple and effective technique that is used by chemists by different purposes, including the monitoring of the progress of a reaction. TLC can also be easily used for the analysis and identification of various acid-base indicator dyes.

[Research on airborne hyperspectral identification of red tide organism dominant species based on SVM].

PubMed

Ma, Yi; Zhang, Jie; Cui, Ting-wei

2006-12-01

Airborne hyperspectral identification of red tide organism dominant species can provide technique for distinguishing red tide and its toxin, and provide support for scaling the disaster. Based on support vector machine(SVM), the present paper provides an identification model of red tide dominant species. Utilizing this model, the authors accomplished three identification experiments with the hyperspectral data obtained on 16th July, and 19th and 25th August, 2001. It is shown from the identification results that the model has a high precision and is not restricted by high dimension of the hyperspectral data.

Mapping sites of aspirin-induced acetylations in live cells by quantitative acid-cleavable activity-based protein profiling (QA-ABPP)

PubMed Central

Wang, Jigang; Zhang, Chong-Jing; Zhang, Jianbin; He, Yingke; Lee, Yew Mun; Chen, Songbi; Lim, Teck Kwang; Ng, Shukie; Shen, Han-Ming; Lin, Qingsong

2015-01-01

Target-identification and understanding of mechanism-of-action (MOA) are challenging for development of small-molecule probes and their application in biology and drug discovery. For example, although aspirin has been widely used for more than 100 years, its molecular targets have not been fully characterized. To cope with this challenge, we developed a novel technique called quantitative acid-cleavable activity-based protein profiling (QA-ABPP) with combination of the following two parts: (i) activity-based protein profiling (ABPP) and iTRAQ™ quantitative proteomics for identification of target proteins and (ii) acid-cleavable linker-based ABPP for identification of peptides with specific binding sites. It is known that reaction of aspirin with its target proteins leads to acetylation. We thus applied the above technique using aspirin-based probes in human cancer HCT116 cells. We identified 1110 target proteins and 2775 peptides with exact acetylation sites. By correlating these two sets of data, 523 proteins were identified as targets of aspirin. We used various biological assays to validate the effects of aspirin on inhibition of protein synthesis and induction of autophagy which were elicited from the pathway analysis of Aspirin target profile. This technique is widely applicable for target identification in the field of drug discovery and biology, especially for the covalent drugs. PMID:25600173

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.

[Applications of three-dimensional fluorescence spectrum of dissolved organic matter to identification of red tide algae].

PubMed

Lü, Gui-Cai; Zhao, Wei-Hong; Wang, Jiang-Tao

2011-01-01

The identification techniques for 10 species of red tide algae often found in the coastal areas of China were developed by combining the three-dimensional fluorescence spectra of fluorescence dissolved organic matter (FDOM) from the cultured red tide algae with principal component analysis. Based on the results of principal component analysis, the first principal component loading spectrum of three-dimensional fluorescence spectrum was chosen as the identification characteristic spectrum for red tide algae, and the phytoplankton fluorescence characteristic spectrum band was established. Then the 10 algae species were tested using Bayesian discriminant analysis with a correct identification rate of more than 92% for Pyrrophyta on the level of species, and that of more than 75% for Bacillariophyta on the level of genus in which the correct identification rates were more than 90% for the phaeodactylum and chaetoceros. The results showed that the identification techniques for 10 species of red tide algae based on the three-dimensional fluorescence spectra of FDOM from the cultured red tide algae and principal component analysis could work well.

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.

Standoff laser-based spectroscopy for explosives detection

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2007-10-01

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

Measurement of gamma' precipitates in a nickel-based superalloy using energy-filtered transmission electron microscopy coupled with automated segmenting techniques.

PubMed

Tiley, J S; Viswanathan, G B; Shiveley, A; Tschopp, M; Srinivasan, R; Banerjee, R; Fraser, H L

2010-08-01

Precipitates of the ordered L1(2) gamma' phase (dispersed in the face-centered cubic or FCC gamma matrix) were imaged in Rene 88 DT, a commercial multicomponent Ni-based superalloy, using energy-filtered transmission electron microscopy (EFTEM). Imaging was performed using the Cr, Co, Ni, Ti and Al elemental L-absorption edges in the energy loss spectrum. Manual and automated segmentation procedures were utilized for identification of precipitate boundaries and measurement of precipitate sizes. The automated region growing technique for precipitate identification in images was determined to measure accurately precipitate diameters. In addition, the region growing technique provided a repeatable method for optimizing segmentation techniques for varying EFTEM conditions. (c) 2010 Elsevier Ltd. All rights reserved.

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Molecular Identification of Ectomycorrhizal Mycelium in Soil Horizons

PubMed Central

Landeweert, Renske; Leeflang, Paula; Kuyper, Thom W.; Hoffland, Ellis; Rosling, Anna; Wernars, Karel; Smit, Eric

2003-01-01

Molecular identification techniques based on total DNA extraction provide a unique tool for identification of mycelium in soil. Using molecular identification techniques, the ectomycorrhizal (EM) fungal community under coniferous vegetation was analyzed. Soil samples were taken at different depths from four horizons of a podzol profile. A basidiomycete-specific primer pair (ITS1F-ITS4B) was used to amplify fungal internal transcribed spacer (ITS) sequences from total DNA extracts of the soil horizons. Amplified basidiomycete DNA was cloned and sequenced, and a selection of the obtained clones was analyzed phylogenetically. Based on sequence similarity, the fungal clone sequences were sorted into 25 different fungal groups, or operational taxonomic units (OTUs). Out of 25 basidiomycete OTUs, 7 OTUs showed high nucleotide homology (≥99%) with known EM fungal sequences and 16 were found exclusively in the mineral soil. The taxonomic positions of six OTUs remained unclear. OTU sequences were compared to sequences from morphotyped EM root tips collected from the same sites. Of the 25 OTUs, 10 OTUs had ≥98% sequence similarity with these EM root tip sequences. The present study demonstrates the use of molecular techniques to identify EM hyphae in various soil types. This approach differs from the conventional method of EM root tip identification and provides a novel approach to examine EM fungal communities in soil. PMID:12514012

A novel analytical technique suitable for the identification of plastics.

PubMed

Nečemer, Marijan; Kump, Peter; Sket, Primož; Plavec, Janez; Grdadolnik, Jože; Zvanut, Maja

2013-01-01

The enormous development and production of plastic materials in the last century resulted in increasing numbers of such kinds of objects. Development of a simple and fast technique to classify different types of plastics could be used in many activities dealing with plastic materials such as packaging of food, sorting of used plastic materials, and also, if technique would be non-destructive, for conservation of plastic artifacts in museum collections, a relatively new field of interest since 1990. In our previous paper we introduced a non-destructive technique for fast identification of unknown plastics based on EDXRF spectrometry,1 using as a case study some plastic artifacts archived in the Museum in order to show the advantages of the nondestructive identification of plastic material. In order to validate our technique it was necessary to apply for this purpose the comparison of analyses with some of the analytical techniques, which are more suitable and so far rather widely applied in identifying some most common sorts of plastic materials.

Performance of optimized McRAPD in identification of 9 yeast species frequently isolated from patient samples: potential for automation.

PubMed

Trtkova, Jitka; Pavlicek, Petr; Ruskova, Lenka; Hamal, Petr; Koukalova, Dagmar; Raclavsky, Vladislav

2009-11-10

Rapid, easy, economical and accurate species identification of yeasts isolated from clinical samples remains an important challenge for routine microbiological laboratories, because susceptibility to antifungal agents, probability to develop resistance and ability to cause disease vary in different species. To overcome the drawbacks of the currently available techniques we have recently proposed an innovative approach to yeast species identification based on RAPD genotyping and termed McRAPD (Melting curve of RAPD). Here we have evaluated its performance on a broader spectrum of clinically relevant yeast species and also examined the potential of automated and semi-automated interpretation of McRAPD data for yeast species identification. A simple fully automated algorithm based on normalized melting data identified 80% of the isolates correctly. When this algorithm was supplemented by semi-automated matching of decisive peaks in first derivative plots, 87% of the isolates were identified correctly. However, a computer-aided visual matching of derivative plots showed the best performance with average 98.3% of the accurately identified isolates, almost matching the 99.4% performance of traditional RAPD fingerprinting. Since McRAPD technique omits gel electrophoresis and can be performed in a rapid, economical and convenient way, we believe that it can find its place in routine identification of medically important yeasts in advanced diagnostic laboratories that are able to adopt this technique. It can also serve as a broad-range high-throughput technique for epidemiological surveillance.

Identification and assessment of hazardous compounds in drinking water.

PubMed

Fawell, J K; Fielding, M

1985-12-01

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

Identification of hallucinogenic fungi from the genera Psilocybe and Panaeolus by amplified fragment length polymorphism.

PubMed

Lee, J C; Cole, M; Linacre, A

2000-05-01

Unambiguous identification of the hallucinogenic fungi of the genera Psilocybe and Panaeolus is required by national and international drug control legislation. We report on a DNA-based test using the technique of amplified fragment length polymorphism (AFLP). AFLP can differentiate species of the two genera Psilocybe and Panaeolus by using different primer sets. The identification of hallucinogenic fungi using a DNA-based test, which can be used in conjunction with morphological features, will assist in forensic investigations.

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.

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass-Spectrometry (MALDI-TOF MS) Based Microbial Identifications: Challenges and Scopes for Microbial Ecologists

PubMed Central

Rahi, Praveen; Prakash, Om; Shouche, Yogesh S.

2016-01-01

Matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) based biotyping is an emerging technique for high-throughput and rapid microbial identification. Due to its relatively higher accuracy, comprehensive database of clinically important microorganisms and low-cost compared to other microbial identification methods, MALDI-TOF MS has started replacing existing practices prevalent in clinical diagnosis. However, applicability of MALDI-TOF MS in the area of microbial ecology research is still limited mainly due to the lack of data on non-clinical microorganisms. Intense research activities on cultivation of microbial diversity by conventional as well as by innovative and high-throughput methods has substantially increased the number of microbial species known today. This important area of research is in urgent need of rapid and reliable method(s) for characterization and de-replication of microorganisms from various ecosystems. MALDI-TOF MS based characterization, in our opinion, appears to be the most suitable technique for such studies. Reliability of MALDI-TOF MS based identification method depends mainly on accuracy and width of reference databases, which need continuous expansion and improvement. In this review, we propose a common strategy to generate MALDI-TOF MS spectral database and advocated its sharing, and also discuss the role of MALDI-TOF MS based high-throughput microbial identification in microbial ecology studies. PMID:27625644

Raman sorting and identification of single living micro-organisms with optical tweezers

NASA Astrophysics Data System (ADS)

Xie, Changan; Chen, De; Li, Yong-Qing

2005-07-01

We report on a novel technique for sorting and identification of single biological cells and food-borne bacteria based on laser tweezers and Raman spectroscopy (LTRS). With this technique, biological cells of different physiological states in a sample chamber were identified by their Raman spectral signatures and then they were selectively manipulated into a clean collection chamber with optical tweezers through a microchannel. As an example, we sorted the live and dead yeast cells into the collection chamber and validated this with a standard staining technique. We also demonstrated that bacteria existing in spoiled foods could be discriminated from a variety of food particles based on their characteristic Raman spectra and then isolated with laser manipulation. This label-free LTRS sorting technique may find broad applications in microbiology and rapid examination of food-borne diseases.

Provably secure identity-based identification and signature schemes from code assumptions

PubMed Central

Zhao, Yiming

2017-01-01

Code-based cryptography is one of few alternatives supposed to be secure in a post-quantum world. Meanwhile, identity-based identification and signature (IBI/IBS) schemes are two of the most fundamental cryptographic primitives, so several code-based IBI/IBS schemes have been proposed. However, with increasingly profound researches on coding theory, the security reduction and efficiency of such schemes have been invalidated and challenged. In this paper, we construct provably secure IBI/IBS schemes from code assumptions against impersonation under active and concurrent attacks through a provably secure code-based signature technique proposed by Preetha, Vasant and Rangan (PVR signature), and a security enhancement Or-proof technique. We also present the parallel-PVR technique to decrease parameter values while maintaining the standard security level. Compared to other code-based IBI/IBS schemes, our schemes achieve not only preferable public parameter size, private key size, communication cost and signature length due to better parameter choices, but also provably secure. PMID:28809940

Provably secure identity-based identification and signature schemes from code assumptions.

PubMed

Song, Bo; Zhao, Yiming

2017-01-01

Code-based cryptography is one of few alternatives supposed to be secure in a post-quantum world. Meanwhile, identity-based identification and signature (IBI/IBS) schemes are two of the most fundamental cryptographic primitives, so several code-based IBI/IBS schemes have been proposed. However, with increasingly profound researches on coding theory, the security reduction and efficiency of such schemes have been invalidated and challenged. In this paper, we construct provably secure IBI/IBS schemes from code assumptions against impersonation under active and concurrent attacks through a provably secure code-based signature technique proposed by Preetha, Vasant and Rangan (PVR signature), and a security enhancement Or-proof technique. We also present the parallel-PVR technique to decrease parameter values while maintaining the standard security level. Compared to other code-based IBI/IBS schemes, our schemes achieve not only preferable public parameter size, private key size, communication cost and signature length due to better parameter choices, but also provably secure.

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

NASA Technical Reports Server (NTRS)

Greenwood, Eric, II; Schmitz, Fredric H.

2010-01-01

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Automatic topic identification of health-related messages in online health community using text classification.

PubMed

Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

Identification of species origin of meat and meat products on the DNA basis: a review.

PubMed

Kumar, Arun; Kumar, Rajiv Ranjan; Sharma, Brahm Deo; Gokulakrishnan, Palanisamy; Mendiratta, Sanjod Kumar; Sharma, Deepak

2015-01-01

The adulteration/substitution of meat has always been a concern for various reasons such as public health, religious factors, wholesomeness, and unhealthy competition in meat market. Consumer should be protected from these malicious practices of meat adulterations by quick, precise, and specific identification of meat animal species. Several analytical methodologies have been employed for meat speciation based on anatomical, histological, microscopic, organoleptic, chemical, electrophoretic, chromatographic, or immunological principles. However, by virtue of their inherent limitations, most of these techniques have been replaced by the recent DNA-based molecular techniques. In the last decades, several methods based on polymerase chain reaction have been proposed as useful means for identifying the species origin in meat and meat products, due to their high specificity and sensitivity, as well as rapid processing time and low cost. This review intends to provide an updated and extensive overview on the DNA-based methods for species identification in meat and meat products.

Heart Sound Biometric System Based on Marginal Spectrum Analysis

PubMed Central

Zhao, Zhidong; Shen, Qinqin; Ren, Fangqin

2013-01-01

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

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

NASA Technical Reports Server (NTRS)

Molusis, J. A.

1982-01-01

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

NASA Astrophysics Data System (ADS)

Akashi-Ronquest, M.; Amaudruz, P.-A.; Batygov, M.; Beltran, B.; Bodmer, M.; Boulay, M. G.; Broerman, B.; Buck, B.; Butcher, A.; Cai, B.; Caldwell, T.; Chen, M.; Chen, Y.; Cleveland, B.; Coakley, K.; Dering, K.; Duncan, F. A.; Formaggio, J. A.; Gagnon, R.; Gastler, D.; Giuliani, F.; Gold, M.; Golovko, V. V.; Gorel, P.; Graham, K.; Grace, E.; Guerrero, N.; Guiseppe, V.; Hallin, A. L.; Harvey, P.; Hearns, C.; Henning, R.; Hime, A.; Hofgartner, J.; Jaditz, S.; Jillings, C. J.; Kachulis, C.; Kearns, E.; Kelsey, J.; Klein, J. R.; Kuźniak, M.; LaTorre, A.; Lawson, I.; Li, O.; Lidgard, J. J.; Liimatainen, P.; Linden, S.; McFarlane, K.; McKinsey, D. N.; MacMullin, S.; Mastbaum, A.; Mathew, R.; McDonald, A. B.; Mei, D.-M.; Monroe, J.; Muir, A.; Nantais, C.; Nicolics, K.; Nikkel, J. A.; Noble, T.; O'Dwyer, E.; Olsen, K.; Orebi Gann, G. D.; Ouellet, C.; Palladino, K.; Pasuthip, P.; Perumpilly, G.; Pollmann, T.; Rau, P.; Retière, F.; Rielage, K.; Schnee, R.; Seibert, S.; Skensved, P.; Sonley, T.; Vázquez-Jáuregui, E.; Veloce, L.; Walding, J.; Wang, B.; Wang, J.; Ward, M.; Zhang, C.

2015-05-01

Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector.

The significance of gtf genes in caries expression: a rapid identification of Streptococcus mutans from dental plaque of child patients.

PubMed

Mishra, Apurva; Pandey, Ramesh K; Manickam, Natesan

2015-01-01

Rapid phylogenetic and functional gene (gtfB) identification of S. mutans from the dental plaque derived from children. Dental plaque collected from fifteen patients of age group 7-12 underwent centrifugation followed by genomic DNA extraction for S. mutans. Genomic DNA was processed with S. mutans specific primers in suitable PCR condtions for phylogenetic and functional gene (gtfB) identification. The yield and results were confirmed by agarose gel electrophoresis. 1% agarose gel electrophoresis depicts the positive PCR amplification at 1,485 bp when compared with standard 1 kbp indicating the presence of S. mutans in the test sample. Another PCR reaction was set using gtfB primers specific for S. mutans for functional gene identification. 1.2% agarose gel electrophoresis was done and a positive amplication was observed at 192 bp when compared to 100 bp standards. With the advancement in molecular biology techniques, PCR based identification and quantification of the bacterial load can be done within hours using species-specific primers and DNA probes. Thus, this technique may reduce the laboratory time spend in conventional culture methods, reduces the possibility of colony identification errors and is more sensitive to culture techniques.

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.

Raman scattering spectroscopy for explosives identification

NASA Astrophysics Data System (ADS)

Nagli, L.; Gaft, M.

2007-04-01

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

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

PubMed

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

2013-01-01

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

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.

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.

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

PubMed

Hertrampf, A; Sousa, R M; Menezes, J C; Herdling, T

2016-05-30

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

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

2015-12-01

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

Raman spectroscopy-based identification of nosocomial outbreaks of the clonal bacterium Escherichia coli.

PubMed

Kusters, J G; van Leeuwen, W B; Maquelin, K; Blok, H E M; Willemse, H F M; de Graaf-Miltenburg, L A M; Fluit, A C; Troelstra, A

2016-01-01

DNA-based techniques are frequently used to confirm the relatedness of putative outbreak isolates. These techniques often lack the discriminatory power when analyzing closely related microbes such as E. coli. Here the value of Raman spectroscopy as a typing tool for E. coli in a clinical setting was retrospectively evaluated.

Encrypted data stream identification using randomness sparse representation and fuzzy Gaussian mixture model

NASA Astrophysics Data System (ADS)

Zhang, Hong; Hou, Rui; Yi, Lei; Meng, Juan; Pan, Zhisong; Zhou, Yuhuan

2016-07-01

The accurate identification of encrypted data stream helps to regulate illegal data, detect network attacks and protect users' information. In this paper, a novel encrypted data stream identification algorithm is introduced. The proposed method is based on randomness characteristics of encrypted data stream. We use a l1-norm regularized logistic regression to improve sparse representation of randomness features and Fuzzy Gaussian Mixture Model (FGMM) to improve identification accuracy. Experimental results demonstrate that the method can be adopted as an effective technique for encrypted data stream identification.

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

NASA Astrophysics Data System (ADS)

Ghosal, Sayan; Pradhan, Sourav; Salapaka, Murti

2018-05-01

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

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.

From laptop to benchtop to bedside: Structure-based Drug Design on Protein Targets

PubMed Central

Chen, Lu; Morrow, John K.; Tran, Hoang T.; Phatak, Sharangdhar S.; Du-Cuny, Lei; Zhang, Shuxing

2013-01-01

As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. PMID:22316152

Wheeze sound analysis using computer-based techniques: a systematic review.

PubMed

Ghulam Nabi, Fizza; Sundaraj, Kenneth; Chee Kiang, Lam; Palaniappan, Rajkumar; Sundaraj, Sebastian

2017-10-31

Wheezes are high pitched continuous respiratory acoustic sounds which are produced as a result of airway obstruction. Computer-based analyses of wheeze signals have been extensively used for parametric analysis, spectral analysis, identification of airway obstruction, feature extraction and diseases or pathology classification. While this area is currently an active field of research, the available literature has not yet been reviewed. This systematic review identified articles describing wheeze analyses using computer-based techniques on the SCOPUS, IEEE Xplore, ACM, PubMed and Springer and Elsevier electronic databases. After a set of selection criteria was applied, 41 articles were selected for detailed analysis. The findings reveal that 1) computerized wheeze analysis can be used for the identification of disease severity level or pathology, 2) further research is required to achieve acceptable rates of identification on the degree of airway obstruction with normal breathing, 3) analysis using combinations of features and on subgroups of the respiratory cycle has provided a pathway to classify various diseases or pathology that stem from airway obstruction.

Detection and identification of concealed weapons using matrix pencil

NASA Astrophysics Data System (ADS)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

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.

Current genetic methodologies in the identification of disaster victims and in forensic analysis.

PubMed

Ziętkiewicz, Ewa; Witt, Magdalena; Daca, Patrycja; Zebracka-Gala, Jadwiga; Goniewicz, Mariusz; Jarząb, Barbara; Witt, Michał

2012-02-01

This review presents the basic problems and currently available molecular techniques used for genetic profiling in disaster victim identification (DVI). The environmental conditions of a mass disaster often result in severe fragmentation, decomposition and intermixing of the remains of victims. In such cases, traditional identification based on the anthropological and physical characteristics of the victims is frequently inconclusive. This is the reason why DNA profiling became the gold standard for victim identification in mass-casualty incidents (MCIs) or any forensic cases where human remains are highly fragmented and/or degraded beyond recognition. The review provides general information about the sources of genetic material for DNA profiling, the genetic markers routinely used during genetic profiling (STR markers, mtDNA and single-nucleotide polymorphisms [SNP]) and the basic statistical approaches used in DNA-based disaster victim identification. Automated technological platforms that allow the simultaneous analysis of a multitude of genetic markers used in genetic identification (oligonucleotide microarray techniques and next-generation sequencing) are also presented. Forensic and population databases containing information on human variability, routinely used for statistical analyses, are discussed. The final part of this review is focused on recent developments, which offer particularly promising tools for forensic applications (mRNA analysis, transcriptome variation in individuals/populations and genetic profiling of specific cells separated from mixtures).

A combined qualitative-quantitative approach for the identification of highly co-creative technology-driven firms

NASA Astrophysics Data System (ADS)

Milyakov, Hristo; Tanev, Stoyan; Ruskov, Petko

2011-03-01

Value co-creation, is an emerging business and innovation paradigm, however, there is not enough clarity on the distinctive characteristics of value co-creation as compared to more traditional value creation approaches. The present paper summarizes the results from an empirically-derived research study focusing on the development of a systematic procedure for the identification of firms that are active in value co-creation. The study is based on a sample 273 firms that were selected for being representative of the breadth of their value co-creation activities. The results include: i) the identification of the key components of value co-creation based on a research methodology using web search and Principal Component Analysis techniques, and ii) the comparison of two different classification techniques identifying the firms with the highest degree of involvement in value co-creation practices. To the best of our knowledge this is the first study using sophisticated data collection techniques to provide a classification of firms according to the degree of their involvement in value co-creation.

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.

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

PubMed

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

2016-08-01

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

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.

Use of 16S-23S rRNA spacer-region (SR)-PCR for identification of intestinal clostridia.

PubMed

Song, Yuli; Liu, Chengxu; Molitoris, Denise; Tomzynski, Thomas J; Mc Teague, Maureen; Read, Erik; Finegold, Sydney M

2002-12-01

The suitability of a species identification technique based on PCR analysis of 16S-23S rRNA spacer region (SR) polymorphism for human intestinal Clostridium species was evaluated. This SR-PCR based technique is highly reproducible and successfully differentiated the strains tested, which included 17 ATCC type strains of Clostridium and 152 human stool Clostridium isolates, at the species or intraspecies level. Ninety-eight of 152 stool isolates, including C. bifermentans, C. butyricum, C. cadaveris, C. orbiscindens, C. paraputrificum, C. pefringens, C. ramosum, C. scindens, C. spiroforme, C. symbiosum and C. tertium, were identified to species level by SR-PCR patterns that were identical to those of their corresponding ATCC type strains. The other 54 stool isolates distributed among ten SR-PCR patterns that are unique and possibly represent ten novel Clostridium species or subspecies. The species identification obtained by SR-PCR pattern analysis completely agreed with that obtained by 16S rRNA sequencing, and led to identification that clearly differed from that obtained by cellular fatty acid analysis for 23/152 strains (15%). These results indicate that SR-PCR provides an accurate and rapid molecular method for the identification of human intestinal Clostridium species.

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

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

PubMed

Kaneko, Takamasa

2011-01-01

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

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.

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.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Pattern recognition tool based on complex network-based approach

NASA Astrophysics Data System (ADS)

Casanova, Dalcimar; Backes, André Ricardo; Martinez Bruno, Odemir

2013-02-01

This work proposed a generalization of the method proposed by the authors: 'A complex network-based approach for boundary shape analysis'. Instead of modelling a contour into a graph and use complex networks rules to characterize it, here, we generalize the technique. This way, the work proposes a mathematical tool for characterization signals, curves and set of points. To evaluate the pattern description power of the proposal, an experiment of plat identification based on leaf veins image are conducted. Leaf vein is a taxon characteristic used to plant identification proposes, and one of its characteristics is that these structures are complex, and difficult to be represented as a signal or curves and this way to be analyzed in a classical pattern recognition approach. Here, we model the veins as a set of points and model as graphs. As features, we use the degree and joint degree measurements in a dynamic evolution. The results demonstrates that the technique has a good power of discrimination and can be used for plant identification, as well as other complex pattern recognition tasks.

Separation techniques: Chromatography

PubMed Central

Coskun, Ozlem

2016-01-01

Chromatography is an important biophysical technique that enables the separation, identification, and purification of the components of a mixture for qualitative and quantitative analysis. Proteins can be purified based on characteristics such as size and shape, total charge, hydrophobic groups present on the surface, and binding capacity with the stationary phase. Four separation techniques based on molecular characteristics and interaction type use mechanisms of ion exchange, surface adsorption, partition, and size exclusion. Other chromatography techniques are based on the stationary bed, including column, thin layer, and paper chromatography. Column chromatography is one of the most common methods of protein purification. PMID:28058406

Molecular diagnosis of bloodstream infections: planning to (physically) reach the bedside.

PubMed

Leggieri, N; Rida, A; François, P; Schrenzel, Jacques

2010-08-01

Faster identification of infecting microorganisms and treatment options is a first-ranking priority in the infectious disease area, in order to prevent inappropriate treatment and overuse of broad-spectrum antibiotics. Standard bacterial identification is intrinsically time-consuming, and very recently there has been a burst in the number of commercially available nonphenotype-based techniques and in the documentation of a possible clinical impact of these techniques. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is now a standard diagnostic procedure on cultures and hold promises on spiked blood. Meanwhile, commercial PCR-based techniques have improved with the use of bacterial DNA enrichment methods, the diversity of amplicon analysis techniques (melting curve analysis, microarrays, gel electrophoresis, sequencing and analysis by mass spectrometry) leading to the ability to challenge bacterial culture as the gold standard for providing earlier diagnosis with a better 'clinical' sensitivity and additional prognostic information. Laboratory practice has already changed with MALDI-TOF MS, but a change in clinical practice, driven by emergent nucleic acid-based techniques, will need the demonstration of real-life applicability as well as robust clinical-impact-oriented studies.

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

PubMed

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

2018-02-01

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

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

NASA Technical Reports Server (NTRS)

Stry, Greselda I.; Mook, D. Joseph

1991-01-01

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

Remote sensing based on hyperspectral data analysis

NASA Astrophysics Data System (ADS)

Sharifahmadian, Ershad

In remote sensing, accurate identification of far objects, especially concealed objects is difficult. In this study, to improve object detection from a distance, the hyperspecral imaging and wideband technology are employed with the emphasis on wideband radar. As the wideband data includes a broad range of frequencies, it can reveal information about both the surface of the object and its content. Two main contributions are made in this study: 1) Developing concept of return loss for target detection: Unlike typical radar detection methods which uses radar cross section to detect an object, it is possible to enhance the process of detection and identification of concealed targets using the wideband radar based on the electromagnetic characteristics --conductivity, permeability, permittivity, and return loss-- of materials. During the identification process, collected wideband data is evaluated with information from wideband signature library which has already been built. In fact, several classes (e.g. metal, wood, etc.) and subclasses (ex. metals with high conductivity) have been defined based on their electromagnetic characteristics. Materials in a scene are then classified based on these classes. As an example, materials with high electrical conductivity can be conveniently detected. In fact, increasing relative conductivity leads to a reduction in the return loss. Therefore, metals with high conductivity (ex. copper) shows stronger radar reflections compared with metals with low conductivity (ex. stainless steel). Thus, it is possible to appropriately discriminate copper from stainless steel. 2) Target recognition techniques: To detect and identify targets, several techniques have been proposed, in particular the Multi-Spectral Wideband Radar Image (MSWRI) which is able to localize and identify concealed targets. The MSWRI is based on the theory of robust capon beamformer. During identification process, information from wideband signature library is utilized. The WB signature library includes such parameters as conductivity, permeability, permittivity, and return loss at different frequencies for possible materials related to a target. In the MSWRI approach, identification procedure is performed by calculating the RLs at different selected frequencies. Based on similarity of the calculated RLs and RL from WB signature library, targets are detected and identified. Based on the simulation and experimental results, it is concluded that the MSWRI technique is a promising approach for standoff target detection.

Novel Application of FTIR Spectroscopy for the Passive Standoff Detection of Radiological Materials

DTIC Science & Technology

2006-08-01

possibility of applying the long-wave passive standoff detection technique to the identification of radiological materials. This work is based on...infrared (FTIR) radiometry is a well-known technique for detecting and identifying chemical warfare agents. In addition to these potential threats...necessary tools and techniques available for detecting and identifying radioactive products. At present, the main detection techniques depend on methods

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.

DNA barcoding and wing morphometrics to distinguish three Aedes vectors in Thailand.

PubMed

Sumruayphol, Suchada; Apiwathnasorn, Chamnarn; Ruangsittichai, Jiraporn; Sriwichai, Patchara; Attrapadung, Siriluck; Samung, Yudthana; Dujardin, Jean-Pierre

2016-07-01

Aedes aegypti (Diptera: Culicidae) (L.), Ae. albopictus (Skuse), and Ae. scutellaris (Walker) are important mosquito vectors of dengue and chikungunya viruses. They are morphologically similar and sympatric in some parts of their distribution; therefore, there is a risk of incorrect morphological identification. Any confusion could have a negative impact on epidemiological studies or control strategies. Therefore, we explored two modern tools to supplement current morphological identification: DNA barcoding and geometric morphometric analyses. Field larvae were reared to adults and carefully classified based on morphological traits. The genetic analysis was based on the 658bp each of 30COI sequences. Some Culex spp., Mansonia bonneae, were included as outgroups, and inclusion of a few other Aedes spp. facilitated phylogenetic inference of the relationship between Ae. albopictus and Ae. scutellaris. The two species were separated by an average interspecific divergence of 0.123 (0.119-0.127). Morphometric examination included landmark- (392 specimens) and outline-based (317 specimens) techniques. The shape of the wing showed different discriminating power based on sex and digitizing technique. This is the first time that Ae. scutellaris and Ae. albopictus have been compared using these two techniques. We confirm that these morphologically close species are valid, and that geometric morphometrics can considerably increase the reliability of morphological identification. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications

USDA-ARS?s Scientific Manuscript database

Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylat...

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

PubMed

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

2017-11-01

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

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applied to virus identification

PubMed Central

Calderaro, Adriana; Arcangeletti, Maria-Cristina; Rodighiero, Isabella; Buttrini, Mirko; Gorrini, Chiara; Motta, Federica; Germini, Diego; Medici, Maria-Cristina; Chezzi, Carlo; De Conto, Flora

2014-01-01

Virus detection and/or identification traditionally rely on methods based on cell culture, electron microscopy and antigen or nucleic acid detection. These techniques are good, but often expensive and/or time-consuming; furthermore, they not always lead to virus identification at the species and/or type level. In this study, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) was tested as an innovative tool to identify human polioviruses and to identify specific viral protein biomarkers in infected cells. The results revealed MALDI-TOF MS to be an effective and inexpensive tool for the identification of the three poliovirus serotypes. The method was firstly applied to Sabin reference strains, and then to isolates from different clinical samples, highlighting its value as a time-saving, sensitive and specific technique when compared to the gold standard neutralization assay and casting new light on its possible application to virus detection and/or identification. PMID:25354905

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.

Semantic Image Based Geolocation Given a Map (Author’s Initial Manuscript)

DTIC Science & Technology

2016-09-01

novel technique for detection and identification of building facades from geo-tagged reference view using the map and geometry of the building facades. We...2D map of the environment, and geometry of building facades. We evaluate our approach for building identification and geo-localization on a new...location recognition and building identification is done by matching the query view to a reference set, followed by estimation of 3D building facades

Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses

NASA Astrophysics Data System (ADS)

Le, Thien-Phu

2017-10-01

The frequency-scale domain decomposition technique has recently been proposed for operational modal analysis. The technique is based on the Cauchy mother wavelet. In this paper, the approach is extended to the Morlet mother wavelet, which is very popular in signal processing due to its superior time-frequency localization. Based on the regressive form and an appropriate norm of the Morlet mother wavelet, the continuous wavelet transform of the power spectral density of ambient responses enables modes in the frequency-scale domain to be highlighted. Analytical developments first demonstrate the link between modal parameters and the local maxima of the continuous wavelet transform modulus. The link formula is then used as the foundation of the proposed modal identification method. Its practical procedure, combined with the singular value decomposition algorithm, is presented step by step. The proposition is finally verified using numerical examples and a laboratory test.

Rapid identification of single microbes by various Raman spectroscopic techniques

NASA Astrophysics Data System (ADS)

Rösch, Petra; Harz, Michaela; Schmitt, Michael; Peschke, Klaus-Dieter; Ronneberger, Olaf; Burkhardt, Hans; Motzkus, Hans-Walter; Lankers, Markus; Hofer, Stefan; Thiele, Hans; Popp, Jürgen

2006-02-01

A fast and unambiguous identification of microorganisms is necessary not only for medical purposes but also in technical processes such as the production of pharmaceuticals. Conventional microbiological identification methods are based on the morphology and the ability of microbes to grow under different conditions on various cultivation media depending on their biochemical properties. These methods require pure cultures which need cultivation of at least 6 h but normally much longer. Recently also additional methods to identify bacteria are established e.g. mass spectroscopy, polymerase chain reaction (PCR), flow cytometry or fluorescence spectroscopy. Alternative approaches for the identification of microorganisms are vibrational spectroscopic techniques. With Raman spectroscopy a spectroscopic fingerprint of the microorganisms can be achieved. Using UV-resonance Raman spectroscopy (UVRR) macromolecules like DNA/RNA and proteins are resonantly enhanced. With an excitation wavelength of e.g. 244 nm it is possible to determine the ratio of guanine/cytosine to all DNA bases which allows a genotypic identification of microorganisms. The application of UVRR requires a large amount of microorganisms (> 10 6 cells) e.g. at least a micro colony. For the analysis of single cells micro-Raman spectroscopy with an excitation wavelength of 532 nm can be used. Here, the obtained information is from all type of molecules inside the cells which lead to a chemotaxonomic identification. In this contribution we show how wavelength dependent Raman spectroscopy yields significant molecular information applicable for the identification of microorganisms on a single cell level.

Identification of terpenes and essential oils by means of static headspace gas chromatography-ion mobility spectrometry.

PubMed

Rodríguez-Maecker, Roman; Vyhmeister, Eduardo; Meisen, Stefan; Rosales Martinez, Antonio; Kuklya, Andriy; Telgheder, Ursula

2017-11-01

Static headspace gas chromatography-ion mobility spectrometry (SHS GC-IMS) is a relatively new analytical technique that has considerable potential for analysis of volatile organic compounds (VOCs). In this study, SHS GC-IMS was used for the identification of the major terpene components of various essential oils (EOs). Based on the data obtained from 25 terpene standards and 50 EOs, a database for fingerprint identification of characteristic terpenes and EOs was generated utilizing SHS GC-IMS for authenticity testing of fragrances in foods, cosmetics, and personal care products. This database contains specific normalized IMS drift times and GC retention indices for 50 terpene components of EOs. Initially, the SHS GC-IMS parameters, e.g., drift gas and carrier gas flow rates, drift tube, and column temperatures, were evaluated to determine suitable operating conditions for terpene separation and identification. Gas chromatography-mass spectrometry (GC-MS) was used as a reference method for the identification of terpenes in EOs. The fingerprint pattern based on the normalized IMS drift times and retention indices of 50 terpenes is presented for 50 EOs. The applicability of the method was proven on examples of ten commercially available food, cosmetic, and personal care product samples. The results confirm the suitability of SHS GC-IMS as a powerful analytical technique for direct identification of terpene components in solid and liquid samples without any pretreatment. Graphical abstract Fingerprint pattern identification of terpenes and essential oils using static headspace gas chromatography-ion mobility spectrometry.

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

PubMed

Yu, Dongchuan; Frasca, Mattia; Liu, Fang

2008-10-01

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

Rapid Multi-Damage Identification for Health Monitoring of Laminated Composites Using Piezoelectric Wafer Sensor Arrays

PubMed Central

Si, Liang; Wang, Qian

2016-01-01

Through the use of the wave reflection from any damage in a structure, a Hilbert spectral analysis-based rapid multi-damage identification (HSA-RMDI) technique with piezoelectric wafer sensor arrays (PWSA) is developed to monitor and identify the presence, location and severity of damage in carbon fiber composite structures. The capability of the rapid multi-damage identification technique to extract and estimate hidden significant information from the collected data and to provide a high-resolution energy-time spectrum can be employed to successfully interpret the Lamb waves interactions with single/multiple damage. Nevertheless, to accomplish the precise positioning and effective quantification of multiple damage in a composite structure, two functional metrics from the RMDI technique are proposed and used in damage identification, which are the energy density metric and the energy time-phase shift metric. In the designed damage experimental tests, invisible damage to the naked eyes, especially delaminations, were detected in the leftward propagating waves as well as in the selected sensor responses, where the time-phase shift spectra could locate the multiple damage whereas the energy density spectra were used to quantify the multiple damage. The increasing damage was shown to follow a linear trend calculated by the RMDI technique. All damage cases considered showed completely the developed RMDI technique potential as an effective online damage inspection and assessment tool. PMID:27153070

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.

Molecular tools for cryptic Candida species identification with applications in a clinical laboratory.

PubMed

Gamarra, Soledad; Dudiuk, Catiana; Mancilla, Estefanía; Vera Garate, María Verónica; Guerrero, Sergio; Garcia-Effron, Guillermo

2013-01-01

Candida spp. includes more than 160 species but only 20 species pose clinical problems. C. albicans and C. parapsilosis account for more than 75% of all the fungemias worldwide. In 1995 and 2005, one C. albicans and two C. parapsilosis-related species were described, respectively. Using phenotypic traits, the identification of these newly described species is inconclusive or impossible. Thus, molecular-based procedures are mandatory. In the proposed educational experiment we have adapted different basic molecular biology techniques designed to identify these species including PCR, multiplex PCR, PCR-based restriction endonuclease analysis and nuclear ribosomal RNA amplification. During the classes, students acquired the ability to search and align gene sequences, design primers, and use bioinformatics software. Also, in the performed experiments, fungal molecular taxonomy concepts were introduced and the obtained results demonstrated that classic identification (phenotypic) in some cases needs to be complemented with molecular-based techniques. As a conclusion we can state that we present an inexpensive and well accepted group of classes involving important concepts that can be recreated in any laboratory. Copyright © 2013 International Union of Biochemistry and Molecular Biology, Inc.

Cloud-based adaptive exon prediction for DNA analysis.

PubMed

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

2018-02-01

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

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 Species and Sources of Cryptosporidium Oocysts in Storm Waters with a Small-Subunit rRNA-Based Diagnostic and Genotyping Tool

PubMed Central

Xiao, Lihua; Alderisio, Kerri; Limor, Josef; Royer, Michael; Lal, Altaf A.

2000-01-01

The identification of Cryptosporidium oocysts in environmental samples is largely made by the use of an immunofluorescent assay. In this study, we have used a small-subunit rRNA-based PCR-restriction fragment length polymorphism technique to identify species and sources of Cryptosporidium oocysts present in 29 storm water samples collected from a stream in New York. A total of 12 genotypes were found in 27 positive samples; for 4 the species and probable origins were identified by sequence analysis, whereas the rest represent new genotypes from wildlife. Thus, this technique provides an alternative method for the detection and differentiation of Cryptosporidium parasites in environmental samples. PMID:11097935

Robust volcano plot: identification of differential metabolites in the presence of outliers.

PubMed

Kumar, Nishith; Hoque, Md Aminul; Sugimoto, Masahiro

2018-04-11

The identification of differential metabolites in metabolomics is still a big challenge and plays a prominent role in metabolomics data analyses. Metabolomics datasets often contain outliers because of analytical, experimental, and biological ambiguity, but the currently available differential metabolite identification techniques are sensitive to outliers. We propose a kernel weight based outlier-robust volcano plot for identifying differential metabolites from noisy metabolomics datasets. Two numerical experiments are used to evaluate the performance of the proposed technique against nine existing techniques, including the t-test and the Kruskal-Wallis test. Artificially generated data with outliers reveal that the proposed method results in a lower misclassification error rate and a greater area under the receiver operating characteristic curve compared with existing methods. An experimentally measured breast cancer dataset to which outliers were artificially added reveals that our proposed method produces only two non-overlapping differential metabolites whereas the other nine methods produced between seven and 57 non-overlapping differential metabolites. Our data analyses show that the performance of the proposed differential metabolite identification technique is better than that of existing methods. Thus, the proposed method can contribute to analysis of metabolomics data with outliers. The R package and user manual of the proposed method are available at https://github.com/nishithkumarpaul/Rvolcano .

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Checking of individuality by DNA profiling.

PubMed

Brdicka, R; Nürnberg, P

1993-08-25

A review of methods of DNA analysis used in forensic medicine for identification, paternity testing, etc. is provided. Among other techniques, DNA fingerprinting using different probes and polymerase chain reaction-based techniques such as amplified sequence polymorphisms and minisatellite variant repeat mapping are thoroughly described and both theoretical and practical aspects are discussed.

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.

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.

Blood meal identification and parasite detection in laboratory-fed and field-captured Lutzomyia longipalpis by PCR using FTA databasing paper

PubMed Central

Sant’Anna, Mauricio R.V.; Jones, Nathaniel G.; Hindley, Jonathan A.; Mendes-Sousa, Antonio F.; Dillon, Rod J.; Cavalcante, Reginaldo R.; Alexander, Bruce; Bates, Paul A.

2008-01-01

The phlebotomine sand fly Lutzomyia longipalpis takes blood from a variety of wild and domestic animals and transmits Leishmania (Leishmania) infantum chagasi, etiological agent of American visceral leishmaniasis. Blood meal identification in sand flies has depended largely on serological methods but a new protocol described here uses filter-based technology to stabilise and store blood meal DNA, allowing subsequent PCR identification of blood meal sources, as well as parasite detection, in blood-fed sand flies. This technique revealed that 53.6% of field-collected sand flies captured in the back yards of houses in Teresina (Brazil) had fed on chickens. The potential applications of this technique in epidemiological studies and strategic planning for leishmaniasis control programmes are discussed. PMID:18606150

Particle identification using the time-over-threshold measurements in straw tube detectors

NASA Astrophysics Data System (ADS)

Jowzaee, S.; Fioravanti, E.; Gianotti, P.; Idzik, M.; Korcyl, G.; Palka, M.; Przyborowski, D.; Pysz, K.; Ritman, J.; Salabura, P.; Savrie, M.; Smyrski, J.; Strzempek, P.; Wintz, P.

2013-08-01

The identification of charged particles based on energy losses in straw tube detectors has been simulated. The response of a new front-end chip developed for the PANDA straw tube tracker was implemented in the simulations and corrections for track distance to sense wire were included. Separation power for p - K, p - π and K - π pairs obtained using the time-over-threshold technique was compared with the one based on the measurement of collected charge.

Identification of modal strains using sub-microstrain FBG data and a novel wavelength-shift detection algorithm

NASA Astrophysics Data System (ADS)

Anastasopoulos, Dimitrios; Moretti, Patrizia; Geernaert, Thomas; De Pauw, Ben; Nawrot, Urszula; De Roeck, Guido; Berghmans, Francis; Reynders, Edwin

2017-03-01

The presence of damage in a civil structure alters its stiffness and consequently its modal characteristics. The identification of these changes can provide engineers with useful information about the condition of a structure and constitutes the basic principle of the vibration-based structural health monitoring. While eigenfrequencies and mode shapes are the most commonly monitored modal characteristics, their sensitivity to structural damage may be low relative to their sensitivity to environmental influences. Modal strains or curvatures could offer an attractive alternative but current measurement techniques encounter difficulties in capturing the very small strain (sub-microstrain) levels occurring during ambient, or operational excitation, with sufficient accuracy. This paper investigates the ability to obtain sub-microstrain accuracy with standard fiber-optic Bragg gratings using a novel optical signal processing algorithm that identifies the wavelength shift with high accuracy and precision. The novel technique is validated in an extensive experimental modal analysis test on a steel I-beam which is instrumented with FBG sensors at its top and bottom flange. The raw wavelength FBG data are processed into strain values using both a novel correlation-based processing technique and a conventional peak tracking technique. Subsequently, the strain time series are used for identifying the beam's modal characteristics. Finally, the accuracy of both algorithms in identification of modal characteristics is extensively investigated.

[Isolation and identification methods of enterobacteria group and its technological advancement].

PubMed

Furuta, Itaru

2007-08-01

In the last half-century, isolation and identification methods of enterobacteria groups have markedly improved by technological advancement. Clinical microbiology tests have changed overtime from tube methods to commercial identification kits and automated identification. Tube methods are the original method for the identification of enterobacteria groups, that is, a basically essential method to recognize bacterial fermentation and biochemical principles. In this paper, traditional tube tests are discussed, such as the utilization of carbohydrates, indole, methyl red, and citrate and urease tests. Commercial identification kits and automated instruments by computer based analysis as current methods are also discussed, and those methods provide rapidity and accuracy. Nonculture techniques of nucleic acid typing methods using PCR analysis, and immunochemical methods using monoclonal antibodies can be further developed.

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

A minimally invasive technique to assess several life-history characteristics of the endangered great hammerhead shark Sphyrna mokarran.

PubMed

O'Connell, C P; Leurs, G

2016-03-01

A dorsal-fin photo-identification technique paired with a non-invasive parallel laser photogrammetry technique was used to non-invasively identify individual Sphyrna mokarran over time. Based on the data collected over a duration of 59 days, 16 different S. mokarran (mean ± S.D. pre-caudal length: 220·82 ± 13·66 cm; mean ± S.D. cephalofoil width: 71·38 ± 7·94 cm) were identified using dorsal-fin photo-identification, with a mean ± S.D. shark re-sighting frequency of 4·05 ± 3·06 at-sea days. The results illustrate a high S. mokarran sighting rate and therefore, the utilization of parallel laser photogrammetry and dorsal-fin photo-identification may be a plausible multi-year approach to aid in non-invasively determining the growth rate and inter-annual site fidelity of these animals. © 2016 The Fisheries Society of the British Isles.

Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks

PubMed Central

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

2015-01-01

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

A TaqMan real-time PCR-based assay for the identification of Fasciola spp.

PubMed

Alasaad, Samer; Soriguer, Ramón C; Abu-Madi, Marawan; El Behairy, Ahmed; Jowers, Michael J; Baños, Pablo Díez; Píriz, Ana; Fickel, Joerns; Zhu, Xing-Quan

2011-06-30

Real time quantitative PCR (qPCR) is one of the key technologies of the post-genome era, with clear advantages compared to normal end-point PCR. In this paper, we report the first qPCR-based assay for the identification of Fasciola spp. Based on sequences of the second internal transcribed spacers (ITS-2) of the ribosomal rRNA gene, we used a set of genus-specific primers for Fasciola ITS-2 amplification, and we designed species-specific internal TaqMan probes to identify F. hepatica and F. gigantica, as well as the hybrid 'intermediate'Fasciola. These primers and probes were used for the highly specific, sensitive, and simple identification of Fasciola species collected from different animal host from China, Spain, Niger and Egypt. The novel qPCR-based technique for the identification of Fasciola spp. may provide a useful tool for the epidemiological investigation of Fasciola infection, including their intermediate snail hosts. Copyright © 2011 Elsevier B.V. All rights reserved.

Level-set techniques for facies identification in reservoir modeling

NASA Astrophysics Data System (ADS)

Iglesias, Marco A.; McLaughlin, Dennis

2011-03-01

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

Privacy-protected biometric templates: acoustic ear identification

NASA Astrophysics Data System (ADS)

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

2004-08-01

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

Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review

PubMed Central

Santos, Rui; Pombo, Nuno; Flórez-Revuelta, Francisco

2018-01-01

An increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT), Mel-frequency cepstrum coefficients (MFCC), Principal Component Analysis (PCA), Fast Fourier Transform (FFT), Gaussian mixture models (GMM), likelihood estimation, logarithmic moduled complex lapped transform (LMCLT), support vector machine (SVM), constant Q transform (CQT), symmetric pairwise boosting (SPB), Philips robust hash (PRH), linear discriminant analysis (LDA) and discrete cosine transform (DCT). PMID:29315232

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2015-04-01

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

Characterization of Sorolla's gouache pigments by means of spectroscopic techniques

NASA Astrophysics Data System (ADS)

Roldán, Clodoaldo; Juanes, David; Ferrazza, Livio; Carballo, Jorgelina

2016-02-01

This paper presents the characterization of the Joaquín Sorolla's gouache sketches for the oil on canvas series "Vision of Spain" commissioned by A. M. Huntington to decorate the library of the Hispanic Society of America in New York. The analyses were focused on the identification of the elemental composition of the gouache pigments by means of portable EDXRF spectrometry in a non-destructive mode. Additionally, SEM-EDX and FTIR analyses of a selected set of micro-samples were carried out to identify completely the pigments, the paint technique and the binding media. The obtained results have confirmed the identification of lead and zinc white, vermillion, earth pigments, ochre, zinc yellow, chrome yellow, ultramarine, Prussian blue, chromium based and copper-arsenic based green pigments, bone black and carbon based black pigments, and the use of gum arabic as binding media in the gouache pigments.

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

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2013-04-01

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

Cloud-based adaptive exon prediction for DNA analysis

PubMed Central

Putluri, Srinivasareddy; Fathima, Shaik Yasmeen

2018-01-01

Cloud computing offers significant research and economic benefits to healthcare organisations. Cloud services provide a safe place for storing and managing large amounts of such sensitive data. Under conventional flow of gene information, gene sequence laboratories send out raw and inferred information via Internet to several sequence libraries. DNA sequencing storage costs will be minimised by use of cloud service. In this study, the authors put forward a novel genomic informatics system using Amazon Cloud Services, where genomic sequence information is stored and accessed for processing. True identification of exon regions in a DNA sequence is a key task in bioinformatics, which helps in disease identification and design drugs. Three base periodicity property of exons forms the basis of all exon identification techniques. Adaptive signal processing techniques found to be promising in comparison with several other methods. Several adaptive exon predictors (AEPs) are developed using variable normalised least mean square and its maximum normalised variants to reduce computational complexity. Finally, performance evaluation of various AEPs is done based on measures such as sensitivity, specificity and precision using various standard genomic datasets taken from National Center for Biotechnology Information genomic sequence database. PMID:29515813

Damage detection and quantification in a structural model under seismic excitation using time-frequency analysis

NASA Astrophysics Data System (ADS)

Chan, Chun-Kai; Loh, Chin-Hsiung; Wu, Tzu-Hsiu

2015-04-01

In civil engineering, health monitoring and damage detection are typically carry out by using a large amount of sensors. Typically, most methods require global measurements to extract the properties of the structure. However, some sensors, like LVDT, cannot be used due to in situ limitation so that the global deformation remains unknown. An experiment is used to demonstrate the proposed algorithms: a one-story 2-bay reinforce concrete frame under weak and strong seismic excitation. In this paper signal processing techniques and nonlinear identification are used and applied to the response measurements of seismic response of reinforced concrete structures subject to different level of earthquake excitations. Both modal-based and signal-based system identification and feature extraction techniques are used to study the nonlinear inelastic response of RC frame using both input and output response data or output only measurement. From the signal-based damage identification method, which include the enhancement of time-frequency analysis of acceleration responses and the estimation of permanent deformation using directly from acceleration response data. Finally, local deformation measurement from dense optical tractor is also use to quantify the damage of the RC frame structure.

Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers

PubMed Central

Shattuck-Hufnagel, S.; Choi, J. Y.; Moro-Velázquez, L.; Gómez-García, J. A.

2017-01-01

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting. PMID:29240814

An adaptive deep learning approach for PPG-based identification.

PubMed

Jindal, V; Birjandtalab, J; Pouyan, M Baran; Nourani, M

2016-08-01

Wearable biosensors have become increasingly popular in healthcare due to their capabilities for low cost and long term biosignal monitoring. This paper presents a novel two-stage technique to offer biometric identification using these biosensors through Deep Belief Networks and Restricted Boltzman Machines. Our identification approach improves robustness in current monitoring procedures within clinical, e-health and fitness environments using Photoplethysmography (PPG) signals through deep learning classification models. The approach is tested on TROIKA dataset using 10-fold cross validation and achieved an accuracy of 96.1%.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

[Different wavelengths selection methods for identification of early blight on tomato leaves by using hyperspectral imaging technique].

PubMed

Cheng, Shu-Xi; Xie, Chuan-Qi; Wang, Qiao-Nan; He, Yong; Shao, Yong-Ni

2014-05-01

Identification of early blight on tomato leaves by using hyperspectral imaging technique based on different effective wavelengths selection methods (successive projections algorithm, SPA; x-loading weights, x-LW; gram-schmidt orthogonaliza-tion, GSO) was studied in the present paper. Hyperspectral images of seventy healthy and seventy infected tomato leaves were obtained by hyperspectral imaging system across the wavelength range of 380-1023 nm. Reflectance of all pixels in region of interest (ROI) was extracted by ENVI 4. 7 software. Least squares-support vector machine (LS-SVM) model was established based on the full spectral wavelengths. It obtained an excellent result with the highest identification accuracy (100%) in both calibration and prediction sets. Then, EW-LS-SVM and EW-LDA models were established based on the selected wavelengths suggested by SPA, x-LW and GSO, respectively. The results showed that all of the EW-LS-SVM and EW-LDA models performed well with the identification accuracy of 100% in EW-LS-SVM model and 100%, 100% and 97. 83% in EW-LDA model, respectively. Moreover, the number of input wavelengths of SPA-LS-SVM, x-LW-LS-SVM and GSO-LS-SVM models were four (492, 550, 633 and 680 nm), three (631, 719 and 747 nm) and two (533 and 657 nm), respectively. Fewer input variables were beneficial for the development of identification instrument. It demonstrated that it is feasible to identify early blight on tomato leaves by using hyperspectral imaging, and SPA, x-LW and GSO were effective wavelengths selection methods.

Dry Stream Reaches in Carbonate Terranes: Surface Indicators of Ground-Water Reservoirs

USGS Publications Warehouse

Brahana, J.V.; Hollyday, E.F.

1988-01-01

In areas where dry stream reaches occur, subsurface drainage successfully competes with surface drainage, and sheet-like dissolution openings have developed parallel to bedding creating the ground-water reservoir. Union Hollow in south-central Tennessee is the setting for a case study that illustrates the application of the dry stream reach technique. In this technique, dry stream reach identification is based on two types of readily acquired information: remotely sensed black and white infrared aerial photography; and surface reconnaissance of stream channel characteristics. Test drilling in Union Hollow subsequent to identification of the dry reach proved that a localized ground-water reservoir was present.

Techniques for the recovery and identification of Cryptosporidium oocysts from stool specimens.

PubMed

Garcia, L S; Bruckner, D A; Brewer, T C; Shimizu, R Y

1983-07-01

Due to increasing numbers of patients with documented infections with Cryptosporidium and other coccidia, it is important for the physician and clinical laboratory to be aware of the appropriate diagnostic techniques necessary for organism recovery and identification. Although Cryptosporidium is found in the gastrointestinal tract, tissue biopsies may be insufficient for organism recovery; the examination of stool specimens is a noninvasive procedure and will provide better overall opportunities for organism recovery. Human clinical specimens were examined from 45 patients with confirmed cryptosporidiosis or suspected of having the infection. Tissue biopsy sections, fecal wet preparations, and permanent stained smears were examined. Stool specimens were submitted in 10% Formalin, 2.5% potassium dichromate, and polyvinyl alcohol and were examined for oocysts by using 15 different methods: phase-contrast and light microscopy; Sheather's sugar flotation; Formalin concentration techniques; 10% potassium hydroxide; Giemsa; trichrome; periodic acid-Schiff; modified periodic acid-Schiff; silver methenamine; acridine orange; auramine-rhodamine; Kinyoun acid-fast; Ziehl-Neelsen carbolfuchsin; and a modified acid-fast procedure. Each technique or combination of techniques was assessed by organism quantitation, organism morphology, and ease of visual recognition. Based on these comparative studies, the modified Ziehl-Neelsen carbolfuchsin stain on 10% Formalin-preserved stool is recommended for the recovery and identification of Cryptosporidium.

Techniques for the recovery and identification of Cryptosporidium oocysts from stool specimens.

PubMed Central

Garcia, L S; Bruckner, D A; Brewer, T C; Shimizu, R Y

1983-01-01

Due to increasing numbers of patients with documented infections with Cryptosporidium and other coccidia, it is important for the physician and clinical laboratory to be aware of the appropriate diagnostic techniques necessary for organism recovery and identification. Although Cryptosporidium is found in the gastrointestinal tract, tissue biopsies may be insufficient for organism recovery; the examination of stool specimens is a noninvasive procedure and will provide better overall opportunities for organism recovery. Human clinical specimens were examined from 45 patients with confirmed cryptosporidiosis or suspected of having the infection. Tissue biopsy sections, fecal wet preparations, and permanent stained smears were examined. Stool specimens were submitted in 10% Formalin, 2.5% potassium dichromate, and polyvinyl alcohol and were examined for oocysts by using 15 different methods: phase-contrast and light microscopy; Sheather's sugar flotation; Formalin concentration techniques; 10% potassium hydroxide; Giemsa; trichrome; periodic acid-Schiff; modified periodic acid-Schiff; silver methenamine; acridine orange; auramine-rhodamine; Kinyoun acid-fast; Ziehl-Neelsen carbolfuchsin; and a modified acid-fast procedure. Each technique or combination of techniques was assessed by organism quantitation, organism morphology, and ease of visual recognition. Based on these comparative studies, the modified Ziehl-Neelsen carbolfuchsin stain on 10% Formalin-preserved stool is recommended for the recovery and identification of Cryptosporidium. Images PMID:6193138

On the spot damage detection methodology for highway bridges during natural crises : tech transfer summary.

DOT National Transportation Integrated Search

2010-07-01

The objective of this work was to develop a : low-cost portable damage detection tool to : assess and predict damage areas in highway : bridges. : The proposed tool was based on standard : vibration-based damage identification (VBDI) : techniques but...

SQUIDs vs. Induction Coils for Ultra-Low Field Nuclear Magnetic Resonance: Experimental and Simulation Comparison

PubMed Central

Matlashov, Andrei N.; Schultz, Larry J.; Espy, Michelle A.; Kraus, Robert H.; Savukov, Igor M.; Volegov, Petr L.; Wurden, Caroline J.

2011-01-01

Nuclear magnetic resonance (NMR) is widely used in medicine, chemistry and industry. One application area is magnetic resonance imaging (MRI). Recently it has become possible to perform NMR and MRI in the ultra-low field (ULF) regime requiring measurement field strengths of the order of only 1 Gauss. This technique exploits the advantages offered by superconducting quantum interference devices or SQUIDs. Our group has built SQUID based MRI systems for brain imaging and for liquid explosives detection at airport security checkpoints. The requirement for liquid helium cooling limits potential applications of ULF MRI for liquid identification and security purposes. Our experimental comparative investigation shows that room temperature inductive magnetometers may provide enough sensitivity in the 3–10 kHz range and can be used for fast liquid explosives detection based on ULF NMR technique. We describe experimental and computer-simulation results comparing multichannel SQUID based and induction coils based instruments that are capable of performing ULF MRI for liquid identification. PMID:21747638

Resistance Curves in the Tensile and Compressive Longitudinal Failure of Composites

NASA Technical Reports Server (NTRS)

Camanho, Pedro P.; Catalanotti, Giuseppe; Davila, Carlos G.; Lopes, Claudio S.; Bessa, Miguel A.; Xavier, Jose C.

2010-01-01

This paper presents a new methodology to measure the crack resistance curves associated with fiber-dominated failure modes in polymer-matrix composites. These crack resistance curves not only characterize the fracture toughness of the material, but are also the basis for the identification of the parameters of the softening laws used in the analytical and numerical simulation of fracture in composite materials. The method proposed is based on the identification of the crack tip location by the use of Digital Image Correlation and the calculation of the J-integral directly from the test data using a simple expression derived for cross-ply composite laminates. It is shown that the results obtained using the proposed methodology yield crack resistance curves similar to those obtained using FEM-based methods in compact tension carbon-epoxy specimens. However, it is also shown that the Digital Image Correlation based technique can be used to extract crack resistance curves in compact compression tests for which FEM-based techniques are inadequate.

Development of DNA-based Identification methods to track the ...

EPA Pesticide Factsheets

The ability to track the identity and abundance of larval fish, which are ubiquitous during spawning season, may lead to a greater understanding of fish species distributions in Great Lakes nearshore areas including early-detection of invasive fish species before they become established. However, larval fish are notoriously hard to identify using traditional morphological techniques. While DNA-based identification methods could increase the ability of aquatic resource managers to determine larval fish composition, use of these methods in aquatic surveys is still uncommon and presents many challenges. In response to this need, we have been working with the U. S. Fish and Wildlife Service to develop field and laboratory methods to facilitate the identification of larval fish using DNA-meta-barcoding. In 2012, we initiated a pilot-project to develop a workflow for conducting DNA-based identification, and compared the species composition at sites within the St. Louis River Estuary of Lake Superior using traditional identification versus DNA meta-barcoding. In 2013, we extended this research to conduct DNA-identification of fish larvae collected from multiple nearshore areas of the Great Lakes by the USFWS. The species composition of larval fish generally mirrored that of fish species known from the same areas, but was influenced by the timing and intensity of sampling. Results indicate that DNA-based identification needs only very low levels of biomass to detect pre

Whale Identification

NASA Technical Reports Server (NTRS)

1991-01-01

R:BASE for DOS, a computer program developed under NASA contract, has been adapted by the National Marine Mammal Laboratory and the College of the Atlantic to provide and advanced computerized photo matching technique for identification of humpback whales. The program compares photos with stored digitized descriptions, enabling researchers to track and determine distribution and migration patterns. R:BASE is a spinoff of RIM (Relational Information Manager), which was used to store data for analyzing heat shielding tiles on the Space Shuttle Orbiter. It is now the world's second largest selling line of microcomputer database management software.

Application of MALDI-TOF MS for the Identification of Food Borne Bacteria

PubMed Central

Pavlovic, Melanie; Huber, Ingrid; Konrad, Regina; Busch, Ulrich

2013-01-01

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently emerged as a powerful tool for the routine identification of clinical isolates. MALDI-TOF MS based identification of bacteria has been shown to be more rapid, accurate and cost-efficient than conventional phenotypic techniques or molecular methods. Rapid and reliable identification of food-associated bacteria is also of crucial importance for food processing and product quality. This review is concerned with the applicability of MALDI-TOF MS for routine identification of foodborne bacteria taking the specific requirements of food microbiological laboratories and the food industry into account. The current state of knowledge including recent findings and new approaches are discussed. PMID:24358065

Performance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap Instrument

PubMed Central

Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2016-01-01

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. To date, these different MS2 strategies and the optimal data interpretation approach for each have not been adequately evaluated. This study comprehensively investigated the four MS2 strategies: HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection), HCD-IT (HCD with ion trap, IT), CID-IT (collision-induced-dissociation with IT) and CID-OT on Orbitrap Fusion. To achieve extensive comparison and identify the optimal data interpretation method for each technique, several search engines (SEQUEST and Mascot) and post-processing methods (score-based, PeptideProphet, and Percolator) were assessed for all techniques for the analysis of a human cell proteome. It was found that divergent conclusions could be made from the same dataset when different data interpretation approaches were used and therefore requiring a relatively fair comparison among techniques. Percolator was chosen for comparison of techniques because it performs the best among all search engines and MS2 strategies. For the analysis of human cell proteome using individual MS2 strategies, the highest number of identifications was achieved by HCD-OT, followed by HCD-IT and CID-IT. Based on these results, we concluded that a relatively fair platform for data interpretation is necessary to avoid divergent conclusions from the same dataset, and HCD-OT and HCD-IT may be preferable for protein/peptide identification using Orbitrap Fusion. PMID:27472422

Consistent detection and identification of individuals in a large camera network

NASA Astrophysics Data System (ADS)

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

2007-10-01

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

Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases.

PubMed

Ahmed, Towfiq; Haraldsen, Jason T; Rehr, John J; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V

2014-03-28

Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new 'multi-point cross-correlation' technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.

A novel and efficient technique for identification and classification of GPCRs.

PubMed

Gupta, Ravi; Mittal, Ankush; Singh, Kuldip

2008-07-01

G-protein coupled receptors (GPCRs) play a vital role in different biological processes, such as regulation of growth, death, and metabolism of cells. GPCRs are the focus of significant amount of current pharmaceutical research since they interact with more than 50% of prescription drugs. The dipeptide-based support vector machine (SVM) approach is the most accurate technique to identify and classify the GPCRs. However, this approach has two major disadvantages. First, the dimension of dipeptide-based feature vector is equal to 400. The large dimension makes the classification task computationally and memory wise inefficient. Second, it does not consider the biological properties of protein sequence for identification and classification of GPCRs. In this paper, we present a novel-feature-based SVM classification technique. The novel features are derived by applying wavelet-based time series analysis approach on protein sequences. The proposed feature space summarizes the variance information of seven important biological properties of amino acids in a protein sequence. In addition, the dimension of the feature vector for proposed technique is equal to 35. Experiments were performed on GPCRs protein sequences available at GPCRs Database. Our approach achieves an accuracy of 99.9%, 98.06%, 97.78%, and 94.08% for GPCR superfamily, families, subfamilies, and subsubfamilies (amine group), respectively, when evaluated using fivefold cross-validation. Further, an accuracy of 99.8%, 97.26%, and 97.84% was obtained when evaluated on unseen or recall datasets of GPCR superfamily, families, and subfamilies, respectively. Comparison with dipeptide-based SVM technique shows the effectiveness of our approach.

Rapid and automatic chemical identification of the medicinal flower buds of Lonicera plants by the benchtop and hand-held Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Jianbo; Guo, Baolin; Yan, Rui; Sun, Suqin; Zhou, Qun

2017-07-01

With the utilization of the hand-held equipment, Fourier transform infrared (FT-IR) spectroscopy is a promising analytical technique to minimize the time cost for the chemical identification of herbal materials. This research examines the feasibility of the hand-held FT-IR spectrometer for the on-site testing of herbal materials, using Lonicerae Japonicae Flos (LJF) and Lonicerae Flos (LF) as examples. Correlation-based linear discriminant models for LJF and LF are established based on the benchtop and hand-held FT-IR instruments. The benchtop FT-IR models can exactly recognize all articles of LJF and LF. Although a few LF articles are misjudged at the sub-class level, the hand-held FT-IR models are able to exactly discriminate LJF and LF. As a direct and label-free analytical technique, FT-IR spectroscopy has great potential in the rapid and automatic chemical identification of herbal materials either in laboratories or in fields. This is helpful to prevent the spread and use of adulterated herbal materials in time.

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.

Aircraft applications of fault detection and isolation techniques

NASA Astrophysics Data System (ADS)

Marcos Esteban, Andres

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

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.

Dental radiographic indicators, a key to age estimation

PubMed Central

Panchbhai, AS

2011-01-01

Objective The present review article is aimed at describing the radiological methods utilized for human age identification. Methods The application and importance of radiological methods in human age assessment was discussed through the literature survey. Results Following a literature search, 46 articles were included in the study and the relevant information is depicted in the article. Dental tissue is often preserved indefinitely after death. Implementation of radiography is based on the assessment of the extent of calcification of teeth and in turn the degree of formation of crown and root structures, along with the sequence and the stages of eruption. Several radiological techniques can be used to assist in both individual and general identification, including determination of gender, ethnic group and age. The radiographic method is a simpler and cheaper method of age identification compared with histological and biochemical methods. Radiographic and tomographic images have become an essential aid for human identification in forensic dentistry, particularly with the refinement of techniques and the incorporation of information technology resources. Conclusion Based on an appropriate knowledge of the available methods, forensic dentists can choose the most appropriate since the validity of age estimation crucially depends on the method used and its proper application. The multifactorial approach will lead to optimum age assessment. The legal requirements also have to be considered. PMID:21493876

Modal parameter identification based on combining transmissibility functions and blind source separation techniques

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Sánchez, Jesús Antonio García; Andersen, Palle

2018-05-01

Transmissibility-based operational modal analysis is a recent and alternative approach used to identify the modal parameters of structures under operational conditions. This approach is advantageous compared with traditional operational modal analysis because it does not make any assumptions about the excitation spectrum (i.e., white noise with a flat spectrum). However, common methodologies do not include a procedure to extract closely spaced modes with low signal-to-noise ratios. This issue is relevant when considering that engineering structures generally have closely spaced modes and that their measured responses present high levels of noise. Therefore, to overcome these problems, a new combined method for modal parameter identification is proposed in this work. The proposed method combines blind source separation (BSS) techniques and transmissibility-based methods. Here, BSS techniques were used to recover source signals, and transmissibility-based methods were applied to estimate modal information from the recovered source signals. To achieve this combination, a new method to define a transmissibility function was proposed. The suggested transmissibility function is based on the relationship between the power spectral density (PSD) of mixed signals and the PSD of signals from a single source. The numerical responses of a truss structure with high levels of added noise and very closely spaced modes were processed using the proposed combined method to evaluate its ability to identify modal parameters in these conditions. Colored and white noise excitations were used for the numerical example. The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes. The results showed that the proposed combined method is capable of identifying very closely spaced modes in the presence of noise and, thus, may be potentially applied to improve the identification of damping ratios.

Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network.

PubMed

Bobin, C; Bichler, O; Lourenço, V; Thiam, C; Thévenin, M

2016-03-01

Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes' rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra ((241)Am, (133)Ba, (207)Bi, (60)Co, (137)Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat. Copyright © 2015 Elsevier Ltd. All rights reserved.

Full-envelope aerodynamic modeling of the Harrier aircraft

NASA Technical Reports Server (NTRS)

Mcnally, B. David

1986-01-01

A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.

16S-ARDRA and MALDI-TOF mass spectrometry as tools for identification of Lactobacillus bacteria isolated from poultry.

PubMed

Dec, Marta; Puchalski, Andrzej; Urban-Chmiel, Renata; Wernicki, Andrzej

2016-06-13

The objective of our study is to evaluate the potential use of Amplified 16S Ribosomal DNA Restriction Analysis (16S-ARDRA) and MALDI-TOF mass spectrometry (MS) as methods for species identification of Lactobacillus strains in poultry. A total of 80 Lactobacillus strains isolated from the cloaca of chicken, geese and turkeys were identified to the species level by MALDI-TOF MS (on-plate extraction method) and 16S-ARDRA. The two techniques produced comparable classification results, some of which were additionally confirmed by sequencing of 16S rDNA. MALDI-TOF MS enabled rapid species identification but produced more than one reliable identification result for 16.25 % of examined strains (mainly of the species L. johnsonii). For 30 % of isolates intermediate log(scores) of 1.70-1.99 were obtained, indicating correct genus identification but only presumptive species identification. The 16S-ARDRA protocol was based on digestion of 16S rDNA with the restriction enzymes MseI, HinfI, MboI and AluI. This technique was able to distinguish 17 of the 19 Lactobacillus reference species tested and enabled identification of all 80 wild isolates. L. salivarius dominated among the 15 recognized species, followed by L. johnsonii and L. ingluviei. The MALDI-TOF MS and 16S-ARDRA assays are valuable tools for the identification of avian lactobacilli to the species level. MALDI-TOF MS is a fast, simple and cost-effective technique, and despite generating a high percentage of results with a log(score) <2.00, the on-plate extraction method is characterized by high-performance. For samples for which Biotyper produces more than one reliable result, MALDI-TOF MS must be used in combination with genotypic techniques to achieve unambiguous results. 16S-ARDRA is simple, repetitive method with high power of discrimination, whose sole limitation is its inability to discriminate between species with very high 16S rDNA sequence homology, such as L. casei and L. zeae. The assays can be used for discrimination of Lactobacillus bacteria from different habitats.

Forensic identification of resampling operators: A semi non-intrusive approach.

PubMed

Cao, Gang; Zhao, Yao; Ni, Rongrong

2012-03-10

Recently, several new resampling operators have been proposed and successfully invalidate the existing resampling detectors. However, the reliability of such anti-forensic techniques is unaware and needs to be investigated. In this paper, we focus on the forensic identification of digital image resampling operators including the traditional type and the anti-forensic type which hides the trace of traditional resampling. Various resampling algorithms involving geometric distortion (GD)-based, dual-path-based and postprocessing-based are investigated. The identification is achieved in the manner of semi non-intrusive, supposing the resampling software could be accessed. Given an input pattern of monotone signal, polarity aberration of GD-based resampled signal's first derivative is analyzed theoretically and measured by effective feature metric. Dual-path-based and postprocessing-based resampling can also be identified by feeding proper test patterns. Experimental results on various parameter settings demonstrate the effectiveness of the proposed approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2018-05-01

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

Target identification for small bioactive molecules: finding the needle in the haystack.

PubMed

Ziegler, Slava; Pries, Verena; Hedberg, Christian; Waldmann, Herbert

2013-03-04

Identification and confirmation of bioactive small-molecule targets is a crucial, often decisive step both in academic and pharmaceutical research. Through the development and availability of several new experimental techniques, target identification is, in principle, feasible, and the number of successful examples steadily grows. However, a generic methodology that can successfully be applied in the majority of the cases has not yet been established. Herein we summarize current methods for target identification of small molecules, primarily for a chemistry audience but also the biological community, for example, the chemist or biologist attempting to identify the target of a given bioactive compound. We describe the most frequently employed experimental approaches for target identification and provide several representative examples illustrating the state-of-the-art. Among the techniques currently available, protein affinity isolation using suitable small-molecule probes (pulldown) and subsequent mass spectrometric analysis of the isolated proteins appears to be most powerful and most frequently applied. To provide guidance for rapid entry into the field and based on our own experience we propose a typical workflow for target identification, which centers on the application of chemical proteomics as the key step to generate hypotheses for potential target proteins. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

Liao, Yabin; Wells, Valana

2011-10-01

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

[Neurophysiological identification of the cranial nerves in endoscopic endonasal surgery of skull base tumors].

PubMed

Shkarubo, A N; Ogurtsova, A A; Moshchev, D A; Lubnin, A Yu; Andreev, D N; Koval', K V; Chernov, I V

2016-01-01

Intraoperative identification of the cranial nerves is a useful technique in removal of skull base tumors through the endoscopic endonasal approach. Searching through the scientific literature found one pilot study on the use of triggered electromyography (t-EMG) for identification of the VIth nerve in endonasal endoscopic surgery of skull base tumors (D. San-Juan, et al, 2014). The study objective was to prevent iatrogenic injuries to the cranial nerves without reducing the completeness of tumor tissue resection. In 2014, 5 patients were operated on using the endoscopic endonasal approach. Surgeries were performed for large skull base chordomas (2 cases) and trigeminal nerve neurinomas located in the cavernous sinus (3). Intraoperatively, identification of the cranial nerves was performed by triggered electromyography using a bipolar electrode (except 1 case of chordoma where a monopolar electrode was used). Evaluation of the functional activity of the cranial nerves was carried out both preoperatively and postoperatively. Tumor resection was total in 4 out of 5 cases and subtotal (chordoma) in 1 case. Intraoperatively, the IIIrd (2 patients), Vth (2), and VIth (4) cranial nerves were identified. No deterioration in the function of the intraoperatively identified nerves was observed in the postoperative period. In one case, no responses from the VIth nerve on the right (in the cavernous sinus region) were intraoperatively obtained, and deep paresis (up to plegia) of the nerve-innervated muscles developed in the postoperative period. The nerve function was not impaired before surgery. The t-EMG technique is promising and requires further research.

Targeting Anti-Cancer Active Compounds: Affinity-Based Chromatographic Assays

PubMed Central

de Moraes, Marcela Cristina; Cardoso, Carmen Lucia; Seidl, Claudia; Moaddel, Ruin; Cass, Quezia Bezerra

2016-01-01

Affinity-based chromatography assays encompass the use of solid supports containing immobilized biological targets to monitor binding events in the isolation , identification and/or characterization of bioactive compounds. This powerful bioanalytical technique allows the screening of potential binders through fast analyses that can be directly performed using isolated substances or complex matrices. An overview of the recent researches in frontal and zonal affinity-based chromatography screening assays, which has been used as a tool in the identification and characterization of new anti-cancer agents, is discussed. In addition, a critical evaluation of the recently emerged ligands fishing assays in complex mixtures is also discussed. PMID:27306095

The Identification of Reasons, Solutions, and Techniques Informing a Theory-Based Intervention Targeting Recreational Sports Participation

ERIC Educational Resources Information Center

St Quinton, Tom; Brunton, Julie A.

2018-01-01

Purpose: This study is the 3rd piece of formative research utilizing the theory of planned behavior to inform the development of a behavior change intervention. Focus groups were used to identify reasons for and solutions to previously identified key beliefs in addition to potentially effective behavior change techniques. Method: A purposive…

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

A Historical Perspective on the Identification of Cell Types in Pancreatic Islets of Langerhans by Staining and Histochemical Techniques

PubMed Central

2015-01-01

Before the middle of the previous century, cell types of the pancreatic islets of Langerhans were identified primarily on the basis of their color reactions with histological dyes. At that time, the chemical basis for the staining properties of islet cells in relation to the identity, chemistry and structure of their hormones was not fully understood. Nevertheless, the definitive islet cell types that secrete glucagon, insulin, and somatostatin (A, B, and D cells, respectively) could reliably be differentiated from each other with staining protocols that involved variations of one or more tinctorial techniques, such as the Mallory-Heidenhain azan trichrome, chromium hematoxylin and phloxine, aldehyde fuchsin, and silver impregnation methods, which were popularly used until supplanted by immunohistochemical techniques. Before antibody-based staining methods, the most bona fide histochemical techniques for the identification of islet B cells were based on the detection of sulfhydryl and disulfide groups of insulin. The application of the classical islet tinctorial staining methods for pathophysiological studies and physiological experiments was fundamental to our understanding of islet architecture and the physiological roles of A and B cells in glucose regulation and diabetes. PMID:26216133

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

PubMed Central

2018-01-01

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

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

PubMed

Illias, Hazlee Azil; Zhao Liang, Wee

2018-01-01

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

Bioanalytical Applications of Fluorescence Line-Narrowing and Non-Line-Narrowing Spectroscopy Interfaced with Capillary Electrophoresis and High-Performance Liquid Chromatography

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

Roberts, Kenneth Paul

Capillary electrophoresis (CE) and high-performance liquid chromatography (HPLC) are widely used analytical separation techniques with many applications in chemical, biochemical, and biomedical sciences. Conventional analyte identification in these techniques is based on retention/migration times of standards; requiring a high degree of reproducibility, availability of reliable standards, and absence of coelution. From this, several new information-rich detection methods (also known as hyphenated techniques) are being explored that would be capable of providing unambiguous on-line identification of separating analytes in CE and HPLC. As further discussed, a number of such on-line detection methods have shown considerable success, including Raman, nuclear magnetic resonancemore » (NMR), mass spectrometry (MS), and fluorescence line-narrowing spectroscopy (FLNS). In this thesis, the feasibility and potential of combining the highly sensitive and selective laser-based detection method of FLNS with analytical separation techniques are discussed and presented. A summary of previously demonstrated FLNS detection interfaced with chromatography and electrophoresis is given, and recent results from on-line FLNS detection in CE (CE-FLNS), and the new combination of HPLC-FLNS, are shown.« less

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Identification of astaxanthin diglucoside diesters from snow alga Chlamydomonas nivalis by liquid chromatography-atmospheric pressure chemical ionization mass spectrometry.

PubMed

Rezanka, Tomás; Nedbalová, Linda; Sigler, Karel; Cepák, Vladislav

2008-01-01

A method is described for the identification of astaxanthin glucoside esters from snow alga Chlamydomonas nivalis by means of liquid chromatography-mass spectrometry with atmospheric pressure chemical ionization (LC-MS/APCI). The method is based on the use of preparative HPLC and subsequent identification of astaxanthin diglucoside diesters by microbore LC-MS/APCI. The combination of these two techniques was used to identify more than 100 molecular species. The astaxanthin diglucoside diester, i.e. (all-E)-[di-(6-O-oleoyl-beta-D-glucopyranosyloxy)]-astaxanthin, was also synthesized to unambiguously confirm its structure.

The Identification and Tracking of Uterine Contractions Using Template Based Cross-Correlation.

PubMed

McDonald, Sarah C; Brooker, Graham; Phipps, Hala; Hyett, Jon

2017-09-01

The purpose of this paper is to outline a novel method of using template based cross-correlation to identify and track uterine contractions during labour. A purpose built six-channel Electromyography (EMG) device was used to collect data from consenting women during labour and birth. A range of templates were constructed for the purpose of identifying and tracking uterine activity when cross-correlated with the EMG signal. Peak finding techniques were applied on the cross-correlated result to simplify and automate the identification and tracking of contractions. The EMG data showed a unique pattern when a woman was contracting with key features of the contraction signal remaining consistent and identifiable across subjects. Contraction profiles across subjects were automatically identified using template based cross-correlation. Synthetic templates from a rectangular function with a duration of between 5 and 10 s performed best at identifying and tracking uterine activity across subjects. The successful application of this technique provides opportunity for both simple and accurate real-time analysis of contraction data while enabling investigations into the application of techniques such as machine learning which could enable automated learning from contraction data as part of real-time monitoring and post analysis.

Performance of wavelet analysis and neural networks for pathological voices identification

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

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

PubMed

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

2017-12-01

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

Color and Contour Based Identification of Stem of Coconut Bunch

NASA Astrophysics Data System (ADS)

Kannan Megalingam, Rajesh; Manoharan, Sakthiprasad K.; Reddy, Rajesh G.; Sriteja, Gone; Kashyap, Ashwin

2017-08-01

Vision is the key component of Artificial Intelligence and Automated Robotics. Sensors or Cameras are the sight organs for a robot. Only through this, they are able to locate themselves or identify the shape of a regular or an irregular object. This paper presents the method of Identification of an object based on color and contour recognition using a camera through digital image processing techniques for robotic applications. In order to identify the contour, shape matching technique is used, which takes the input data from the database provided, and uses it to identify the contour by checking for shape match. The shape match is based on the idea of iterating through each contour of the threshold image. The color is identified on HSV Scale, by approximating the desired range of values from the database. HSV data along with iteration is used for identifying a quadrilateral, which is our required contour. This algorithm could also be used in a non-deterministic plane, which only uses HSV values exclusively.

Comparing the landcapes of common retroviral insertion sites across tumor models

NASA Astrophysics Data System (ADS)

Weishaupt, Holger; Čančer, Matko; Engström, Cristopher; Silvestrov, Sergei; Swartling, Fredrik J.

2017-01-01

Retroviral tagging represents an important technique, which allows researchers to screen for candidate cancer genes. The technique is based on the integration of retroviral sequences into the genome of a host organism, which might then lead to the artificial inhibition or expression of proximal genetic elements. The identification of potential cancer genes in this framework involves the detection of genomic regions (common insertion sites; CIS) which contain a number of such viral integration sites that is greater than expected by chance. During the last two decades, a number of different methods have been discussed for the identification of such loci and the respective techniques have been applied to a variety of different retroviruses and/or tumor models. We have previously established a retrovirus driven brain tumor model and reported the CISs which were found based on a Monte Carlo statistics derived detection paradigm. In this study, we consider a recently proposed alternative graph theory based method for identifying CISs and compare the resulting CIS landscape in our brain tumor dataset to those obtained when using the Monte Carlo approach. Finally, we also employ the graph-based method to compare the CIS landscape in our brain tumor model with those of other published retroviral tumor models.

Decoupling Identification for Serial Two-Link Two-Inertia System

NASA Astrophysics Data System (ADS)

Oaki, Junji; Adachi, Shuichi

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

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

PubMed Central

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

2016-01-01

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

Identification of illicit drugs by a combination of liquid chromatography and surface-enhanced Raman scattering spectroscopy

NASA Astrophysics Data System (ADS)

Sägmüller, Bernd; Schwarze, Bernd; Brehm, Georg; Trachta, Gerd; Schneider, Siegfried

2003-12-01

We have developed a new analysis procedure based upon High-Performance Liquid Chromatography (HPLC) in combination with surface-enhanced Raman scattering (SERS) spectroscopy as detection technique to meet todays need for an additional unique and reliable identification method of the ingredients of illicitly sold drugs or other pharmaceutical compounds. Separation of the individual components of a sample was preferentially achieved by employing an acetonitrile free eluent. The fractions of interest were collected as microliter volumes in the wells of a microtiter plate, which contained a home-made, matrix-stabilized silver halide dispersion. The latter functions as the precursor for the SERS-active surface generated by the probing laser beam. The limits of detection can be as low as 1 μg of analyte per one well of the microtiter plate. The recorded SERS spectra of the drugs Cocaine, Heroine and Amphetamine or the pharmaceuticals (Nor-) Papaverine and Procaine promise the possibility of a unique identification, especially if compared with the spectra of reference samples, and, therefore, can support the conclusions drawn by other identification techniques, if requested for example during a law suit.

Current and Prospective Methods for Plant Disease Detection

PubMed Central

Fang, Yi; Ramasamy, Ramaraja P.

2015-01-01

Food losses due to crop infections from pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. In order to minimize the disease induced damage in crops during growth, harvest and postharvest processing, as well as to maximize productivity and ensure agricultural sustainability, advanced disease detection and prevention in crops are imperative. This paper reviews the direct and indirect disease identification methods currently used in agriculture. Laboratory-based techniques such as polymerase chain reaction (PCR), immunofluorescence (IF), fluorescence in-situ hybridization (FISH), enzyme-linked immunosorbent assay (ELISA), flow cytometry (FCM) and gas chromatography-mass spectrometry (GC-MS) are some of the direct detection methods. Indirect methods include thermography, fluorescence imaging and hyperspectral techniques. Finally, the review also provides a comprehensive overview of biosensors based on highly selective bio-recognition elements such as enzyme, antibody, DNA/RNA and bacteriophage as a new tool for the early identification of crop diseases. PMID:26287253

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

PubMed

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

2017-05-01

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

Perceptual Audio Hashing Functions

NASA Astrophysics Data System (ADS)

Özer, Hamza; Sankur, Bülent; Memon, Nasir; Anarım, Emin

2005-12-01

Perceptual hash functions provide a tool for fast and reliable identification of content. We present new audio hash functions based on summarization of the time-frequency spectral characteristics of an audio document. The proposed hash functions are based on the periodicity series of the fundamental frequency and on singular-value description of the cepstral frequencies. They are found, on one hand, to perform very satisfactorily in identification and verification tests, and on the other hand, to be very resilient to a large variety of attacks. Moreover, we address the issue of security of hashes and propose a keying technique, and thereby a key-dependent hash function.

Spotting Cheetahs: Identifying Individuals by Their Footprints.

PubMed

Jewell, Zoe C; Alibhai, Sky K; Weise, Florian; Munro, Stuart; Van Vuuren, Marlice; Van Vuuren, Rudie

2016-05-01

The cheetah (Acinonyx jubatus) is Africa's most endangered large felid and listed as Vulnerable with a declining population trend by the IUCN(1). It ranges widely over sub-Saharan Africa and in parts of the Middle East. Cheetah conservationists face two major challenges, conflict with landowners over the killing of domestic livestock, and concern over range contraction. Understanding of the latter remains particularly poor(2). Namibia is believed to support the largest number of cheetahs of any range country, around 30%, but estimates range from 2,905(3) to 13,520(4). The disparity is likely a result of the different techniques used in monitoring. Current techniques, including invasive tagging with VHF or satellite/GPS collars, can be costly and unreliable. The footprint identification technique(5) is a new tool accessible to both field scientists and also citizens with smartphones, who could potentially augment data collection. The footprint identification technique analyzes digital images of footprints captured according to a standardized protocol. Images are optimized and measured in data visualization software. Measurements of distances, angles, and areas of the footprint images are analyzed using a robust cross-validated pairwise discriminant analysis based on a customized model. The final output is in the form of a Ward's cluster dendrogram. A user-friendly graphic user interface (GUI) allows the user immediate access and clear interpretation of classification results. The footprint identification technique algorithms are species specific because each species has a unique anatomy. The technique runs in a data visualization software, using its own scripting language (jsl) that can be customized for the footprint anatomy of any species. An initial classification algorithm is built from a training database of footprints from that species, collected from individuals of known identity. An algorithm derived from a cheetah of known identity is then able to classify free-ranging cheetahs of unknown identity. The footprint identification technique predicts individual cheetah identity with an accuracy of >90%.

Spotting Cheetahs: Identifying Individuals by Their Footprints

PubMed Central

Jewell, Zoe C.; Alibhai, Sky K.; Weise, Florian; Munro, Stuart; Van Vuuren, Marlice; Van Vuuren, Rudie

2016-01-01

The cheetah (Acinonyx jubatus) is Africa's most endangered large felid and listed as Vulnerable with a declining population trend by the IUCN1. It ranges widely over sub-Saharan Africa and in parts of the Middle East. Cheetah conservationists face two major challenges, conflict with landowners over the killing of domestic livestock, and concern over range contraction. Understanding of the latter remains particularly poor2. Namibia is believed to support the largest number of cheetahs of any range country, around 30%, but estimates range from 2,9053 to 13,5204. The disparity is likely a result of the different techniques used in monitoring. Current techniques, including invasive tagging with VHF or satellite/GPS collars, can be costly and unreliable. The footprint identification technique5 is a new tool accessible to both field scientists and also citizens with smartphones, who could potentially augment data collection. The footprint identification technique analyzes digital images of footprints captured according to a standardized protocol. Images are optimized and measured in data visualization software. Measurements of distances, angles, and areas of the footprint images are analyzed using a robust cross-validated pairwise discriminant analysis based on a customized model. The final output is in the form of a Ward's cluster dendrogram. A user-friendly graphic user interface (GUI) allows the user immediate access and clear interpretation of classification results. The footprint identification technique algorithms are species specific because each species has a unique anatomy. The technique runs in a data visualization software, using its own scripting language (jsl) that can be customized for the footprint anatomy of any species. An initial classification algorithm is built from a training database of footprints from that species, collected from individuals of known identity. An algorithm derived from a cheetah of known identity is then able to classify free-ranging cheetahs of unknown identity. The footprint identification technique predicts individual cheetah identity with an accuracy of >90%. PMID:27167035

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.

A manual and an automatic TERS based virus discrimination

NASA Astrophysics Data System (ADS)

Olschewski, Konstanze; Kämmer, Evelyn; Stöckel, Stephan; Bocklitz, Thomas; Deckert-Gaudig, Tanja; Zell, Roland; Cialla-May, Dana; Weber, Karina; Deckert, Volker; Popp, Jürgen

2015-02-01

Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%.Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr07033j

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

NASA Astrophysics Data System (ADS)

Wada, Daichi; Sugimoto, Yohei

2017-04-01

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

A novel neural network based image reconstruction model with scale and rotation invariance for target identification and classification for Active millimetre wave imaging

NASA Astrophysics Data System (ADS)

Agarwal, Smriti; Bisht, Amit Singh; Singh, Dharmendra; Pathak, Nagendra Prasad

2014-12-01

Millimetre wave imaging (MMW) is gaining tremendous interest among researchers, which has potential applications for security check, standoff personal screening, automotive collision-avoidance, and lot more. Current state-of-art imaging techniques viz. microwave and X-ray imaging suffers from lower resolution and harmful ionizing radiation, respectively. In contrast, MMW imaging operates at lower power and is non-ionizing, hence, medically safe. Despite these favourable attributes, MMW imaging encounters various challenges as; still it is very less explored area and lacks suitable imaging methodology for extracting complete target information. Keeping in view of these challenges, a MMW active imaging radar system at 60 GHz was designed for standoff imaging application. A C-scan (horizontal and vertical scanning) methodology was developed that provides cross-range resolution of 8.59 mm. The paper further details a suitable target identification and classification methodology. For identification of regular shape targets: mean-standard deviation based segmentation technique was formulated and further validated using a different target shape. For classification: probability density function based target material discrimination methodology was proposed and further validated on different dataset. Lastly, a novel artificial neural network based scale and rotation invariant, image reconstruction methodology has been proposed to counter the distortions in the image caused due to noise, rotation or scale variations. The designed neural network once trained with sample images, automatically takes care of these deformations and successfully reconstructs the corrected image for the test targets. Techniques developed in this paper are tested and validated using four different regular shapes viz. rectangle, square, triangle and circle.

Fingerprinting and quantification of GMOs in the agro-food sector.

PubMed

Taverniers, I; Van Bockstaele, E; De Loose, M

2003-01-01

Most strategies for analyzing GMOs in plants and derived food and feed products, are based on the polymerase chain reaction (PCR) technique. In conventional PCR methods, a 'known' sequence between two specific primers is amplified. To the contrary, with the 'anchor PCR' technique, unknown sequences adjacent to a known sequence, can be amplified. Because T-DNA/plant border sequences are being amplified, anchor PCR is the perfect tool for unique identification of transgenes, including non-authorized GMOs. In this work, anchor PCR was applied to characterize the 'transgene locus' and to clarify the complete molecular structure of at least six different commercial transgenic plants. Based on sequences of T-DNA/plant border junctions, obtained by anchor PCR, event specific primers were developed. The junction fragments, together with endogeneous reference gene targets, were cloned in plasmids. The latter were then used as event specific calibrators in real-time PCR, a new technique for the accurate relative quantification of GMOs. We demonstrate here the importance of anchor PCR for identification and the usefulness of plasmid DNA calibrators in quantification strategies for GMOs, throughout the agro-food sector.

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

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.

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.

Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library.

PubMed

Lachaud, Laurence; Fernández-Arévalo, Anna; Normand, Anne-Cécile; Lami, Patrick; Nabet, Cécile; Donnadieu, Jean Luc; Piarroux, Martine; Djenad, Farid; Cassagne, Carole; Ravel, Christophe; Tebar, Silvia; Llovet, Teresa; Blanchet, Denis; Demar, Magalie; Harrat, Zoubir; Aoun, Karim; Bastien, Patrick; Muñoz, Carmen; Gállego, Montserrat; Piarroux, Renaud

2017-10-01

Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-based application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani , L. guyanensis , and L. braziliensis complexes was observed, as previously reported for other techniques. The tested application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers. Copyright © 2017 American Society for Microbiology.

Description and detection of burst events in turbulent flows

NASA Astrophysics Data System (ADS)

Schmid, P. J.; García-Gutierrez, A.; Jiménez, J.

2018-04-01

A mathematical and computational framework is developed for the detection and identification of coherent structures in turbulent wall-bounded shear flows. In a first step, this data-based technique will use an embedding methodology to formulate the fluid motion as a phase-space trajectory, from which state-transition probabilities can be computed. Within this formalism, a second step then applies repeated clustering and graph-community techniques to determine a hierarchy of coherent structures ranked by their persistencies. This latter information will be used to detect highly transitory states that act as precursors to violent and intermittent events in turbulent fluid motion (e.g., bursts). Used as an analysis tool, this technique allows the objective identification of intermittent (but important) events in turbulent fluid motion; however, it also lays the foundation for advanced control strategies for their manipulation. The techniques are applied to low-dimensional model equations for turbulent transport, such as the self-sustaining process (SSP), for varying levels of complexity.

Electromigration techniques--a fast and economical tool for differentiation of similar strains of microorganisms.

PubMed

Horká, Marie; Horký, Jaroslav; Kubesová, Anna; Mazanec, Karel; Matousková, Hana; Slais, Karel

2010-07-01

The detection and identification of pathogens currently relies upon a very diverse range of techniques and skills, from traditional cultivation and taxonomic procedures to modern rapid and sensitive diagnostic methods. Real-time PCR is now exploited as a front line diagnostic screening tool in human, animal and plant health as well as bio-security. Nevertheless, new techniques for pathogen identification, particularly of unknown samples, are needed. In this study we propose the combination of electrophoresis-based procedures for the fast differentiation of microorganisms. The method feasibility is proved on the model of seven similar strains of Pseudomonas syringae pathovars from 37 sources, identified by gas chromatography of fatty acid methyl esters. The results from the routine laboratory were compared with results of the combination of the developed capillary and gel electrophoresis as well as mass spectrometry. According to our experiments appropriate combination of electromigration techniques appears to be useful for the fast and economical differentiation of unknown microorganisms.

Development of techniques for producing static strata maps and development of photointerpretation methods based on multitemporal LANDSAT data

NASA Technical Reports Server (NTRS)

Colwell, R. N. (Principal Investigator); Hay, C. M.; Thomas, R. W.; Benson, A. S.

1976-01-01

The progress of research conducted in support of the Large Area Crop Inventory Experiment (LACIE) is documented. Specific tasks include (1) evaluation of the static stratification procedure and modification of that procedure if warranted, and (2) the development of alternative photointerpretative techniques to the present LACIE procedures for the identification and selection of training fields (areas).

Development of techniques for producing static strata maps and development of photointerpretive methods based on multitemporal LANDSAT data

NASA Technical Reports Server (NTRS)

Colwell, R. N. (Principal Investigator); Hay, C. M.; Thomas, R. W.; Benson, A. S.

1977-01-01

Progress in the evaluation of the static stratification procedure and the development of alternative photointerpretive techniques to the present LACIE procedure for the identification of training fields is reported. Statistically significant signature controlling variables were defined for use in refining the stratification procedure. A subset of the 1973-74 Kansas LACIE segments for wheat was analyzed.

Polydiacetylene-Based Liposomes: An "Optical Tongue" for Bacteria Detection and Identification

ERIC Educational Resources Information Center

West, Matthew R.; Hanks, Timothy W.; Watson, Rhett T.

2009-01-01

Food- and water-borne bacteria are a major health concern worldwide. Current detection methods are time-consuming and require sophisticated equipment that is not always readily available. However, new techniques based on nanotechnology are under development that will result in a new generation of sensors. In this experiment, liposomes are…

Laser-Induced Breakdown Spectroscopy: A Review of Applied Explosive Detection

DTIC Science & Technology

2013-09-01

Based Techniques ..........................................................................................7 2.5 Ion Mobility and Mass Spectrometry...proximal trace detection. We show that the algorithms for material identification could be improved by including the critical signatures (e.g., C2...IMS), desorption electrospray ionization (DESI), laser electrospray mass spectrometry (LEMS), emerging efforts like antibody/antigen-based efforts

SQUIDs vs. Faraday coils for ultlra-low field nuclear magnetic resonance: experimental and simulation comparison

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

Matlashov, Andrei N; Espy, Michelle A; Kraus, Robert H

2010-01-01

Nuclear magnetic resonance (NMR) methods are widely used in medicine, chemistry and industry. One application area is magnetic resonance imaging or MRI. Recently it has become possible to perform NMR and MRI in ultra-low field (ULF) regime that requires measurement field strengths only of the order of 1 Gauss. These techniques exploit the advantages offered by superconducting quantum interference devices or SQUIDs. Our group at LANL has built SQUID based MRI systems for brain imaging and for liquid explosives detection at airports security checkpoints. The requirement for liquid helium cooling limits potential applications of ULF MRI for liquid identification andmore » security purposes. Our experimental comparative investigation shows that room temperature inductive magnetometers provide enough sensitivity in the 3-10 kHz range and can be used for fast liquid explosives detection based on ULF NMR/MRI technique. We describe an experimental and computer simulation comparison of the world's first multichannel SQUID based and Faraday coils based instruments that are capable of performing ULF MRI for liquids identification.« less

Tumor or abnormality identification from magnetic resonance images using statistical region fusion based segmentation.

PubMed

Subudhi, Badri Narayan; Thangaraj, Veerakumar; Sankaralingam, Esakkirajan; Ghosh, Ashish

2016-11-01

In this article, a statistical fusion based segmentation technique is proposed to identify different abnormality in magnetic resonance images (MRI). The proposed scheme follows seed selection, region growing-merging and fusion of multiple image segments. In this process initially, an image is divided into a number of blocks and for each block we compute the phase component of the Fourier transform. The phase component of each block reflects the gray level variation among the block but contains a large correlation among them. Hence a singular value decomposition (SVD) technique is adhered to generate a singular value of each block. Then a thresholding procedure is applied on these singular values to identify edgy and smooth regions and some seed points are selected for segmentation. By considering each seed point we perform a binary segmentation of the complete MRI and hence with all seed points we get an equal number of binary images. A parcel based statistical fusion process is used to fuse all the binary images into multiple segments. Effectiveness of the proposed scheme is tested on identifying different abnormalities: prostatic carcinoma detection, tuberculous granulomas identification and intracranial neoplasm or brain tumor detection. The proposed technique is established by comparing its results against seven state-of-the-art techniques with six performance evaluation measures. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-12-22

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

Further Validation of Simulated Dynamic Interface Testing Techniques as a Tool in the Forecasting of Air Vehicle Deck Limits

DTIC Science & Technology

2010-01-01

UAV Autonomy program which includes intelligent reasoning for autonomy, technologies to enhance see and avoid capabilities, object identification ...along the ship’s base recovery course (BRC). The pilot then flies toward the stern of the ship, aligning his approach path with the ship’s lineup line...quiescent point identification . CONCLUSIONS The primary goal for conducting dynamic interface analysis is to expand existing operating envelopes and

Measuring the Electronic Properties of DNA-Specific Schottky Diodes Towards Detecting and Identifying Basidiomycetes DNA

PubMed Central

Periasamy, Vengadesh; Rizan, Nastaran; Al-Ta’ii, Hassan Maktuff Jaber; Tan, Yee Shin; Tajuddin, Hairul Annuar; Iwamoto, Mitsumasa

2016-01-01

The discovery of semiconducting behavior of deoxyribonucleic acid (DNA) has resulted in a large number of literatures in the study of DNA electronics. Sequence-specific electronic response provides a platform towards understanding charge transfer mechanism and therefore the electronic properties of DNA. It is possible to utilize these characteristic properties to identify/detect DNA. In this current work, we demonstrate a novel method of DNA-based identification of basidiomycetes using current-voltage (I-V) profiles obtained from DNA-specific Schottky barrier diodes. Electronic properties such as ideality factor, barrier height, shunt resistance, series resistance, turn-on voltage, knee-voltage, breakdown voltage and breakdown current were calculated and used to quantify the identification process as compared to morphological and molecular characterization techniques. The use of these techniques is necessary in order to study biodiversity, but sometimes it can be misleading and unreliable and is not sufficiently useful for the identification of fungi genera. Many of these methods have failed when it comes to identification of closely related species of certain genus like Pleurotus. Our electronics profiles, both in the negative and positive bias regions were however found to be highly characteristic according to the base-pair sequences. We believe that this simple, low-cost and practical method could be useful towards identifying and detecting DNA in biotechnology and pathology. PMID:27435636

Measuring the Electronic Properties of DNA-Specific Schottky Diodes Towards Detecting and Identifying Basidiomycetes DNA

NASA Astrophysics Data System (ADS)

Periasamy, Vengadesh; Rizan, Nastaran; Al-Ta'Ii, Hassan Maktuff Jaber; Tan, Yee Shin; Tajuddin, Hairul Annuar; Iwamoto, Mitsumasa

2016-07-01

The discovery of semiconducting behavior of deoxyribonucleic acid (DNA) has resulted in a large number of literatures in the study of DNA electronics. Sequence-specific electronic response provides a platform towards understanding charge transfer mechanism and therefore the electronic properties of DNA. It is possible to utilize these characteristic properties to identify/detect DNA. In this current work, we demonstrate a novel method of DNA-based identification of basidiomycetes using current-voltage (I-V) profiles obtained from DNA-specific Schottky barrier diodes. Electronic properties such as ideality factor, barrier height, shunt resistance, series resistance, turn-on voltage, knee-voltage, breakdown voltage and breakdown current were calculated and used to quantify the identification process as compared to morphological and molecular characterization techniques. The use of these techniques is necessary in order to study biodiversity, but sometimes it can be misleading and unreliable and is not sufficiently useful for the identification of fungi genera. Many of these methods have failed when it comes to identification of closely related species of certain genus like Pleurotus. Our electronics profiles, both in the negative and positive bias regions were however found to be highly characteristic according to the base-pair sequences. We believe that this simple, low-cost and practical method could be useful towards identifying and detecting DNA in biotechnology and pathology.

Identification of exhumed remains of fire tragedy victims using conventional methods and autosomal/Y-chromosomal short tandem repeat DNA profiling.

PubMed

Calacal, Gayvelline C; Delfin, Frederick C; Tan, Michelle Music M; Roewer, Lutz; Magtanong, Danilo L; Lara, Myra C; Fortun, Raquel dR; De Ungria, Maria Corazon A

2005-09-01

In a fire tragedy in Manila in December 1998, one of the worst tragic incidents which resulted in the reported death of 23 children, identity could not be established initially resulting in the burial of still unidentified bodies. Underscoring the importance of identifying each of the human remains, the bodies were exhumed 3 months after the tragedy. We describe here our work, which was the first national case handled by local laboratories wherein conventional and molecular-based techniques were successfully applied in forensic identification. The study reports analysis of DNA obtained from skeletal remains exposed to conditions of burning, burial, and exhumation. DNA typing methods using autosomal and Y-chromosomal short tandem repeat (Y-STR) markers reinforced postmortem examinations using conventional identification techniques. The strategy resulted in the identification of 18 out of the 21 human remains analyzed, overcoming challenges encountered due to the absence of established procedures for the recovery of mass disaster remains. There was incomplete antemortem information to match the postmortem data obtained from the remains of 3 female child victims. Two victims were readily identified due to the availability of antemortem tissues. In the absence of this biologic material, parentage testing was performed using reference blood samples collected from parents and relatives. Data on patrilineal lineage based on common Y-STR haplotypes augmented autosomal DNA typing, particularly in deficiency cases.

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.

On-the-spot damage detection methodology for highway bridges.

DOT National Transportation Integrated Search

2010-07-01

Vibration-based damage identification (VBDI) techniques have been developed in part to address the problems associated with an aging civil infrastructure. To assess the potential of VBDI as it applies to highway bridges in Iowa, three applications of...

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

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

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

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

NASA Astrophysics Data System (ADS)

Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest AGB retrieval showed R2 value of 0.5, RMSE of 62.73 (t ha-1) and a percent accuracy of 51%. TSI based PolInSAR inversion modeling showed the most accurate result for forest height estimation. The correlation between the field measured forest height and the estimated tree height using TSI technique is 62% with an average accuracy of 91.56% and RMSE of 2.28 m. The study suggested that PolInSAR coherence based modeling approach has significant potential for retrieval of forest biophysical parameters.

New encoded single-indicator sequences based on physico-chemical parameters for efficient exon identification.

PubMed

Meher, J K; Meher, P K; Dash, G N; Raval, M K

2012-01-01

The first step in gene identification problem based on genomic signal processing is to convert character strings into numerical sequences. These numerical sequences are then analysed spectrally or using digital filtering techniques for the period-3 peaks, which are present in exons (coding areas) and absent in introns (non-coding areas). In this paper, we have shown that single-indicator sequences can be generated by encoding schemes based on physico-chemical properties. Two new methods are proposed for generating single-indicator sequences based on hydration energy and dipole moments. The proposed methods produce high peak at exon locations and effectively suppress false exons (intron regions having greater peak than exon regions) resulting in high discriminating factor, sensitivity and specificity.

Spectrometric microbiological analyzer

NASA Astrophysics Data System (ADS)

Schlager, Kenneth J.; Meissner, Ken E.

1996-04-01

Currently, there are four general approaches to microbiological analysis, i.e., the detection, identification and quantification of micro-organisms: (1) Traditional culturing and staining procedures, metabolic fermentations and visual morphological characteristics; (2) Immunological approaches employing microbe-specific antibodies; (3) Biotechnical techniques employing DNA probes and related genetic engineering methods; and (4) Physical measurement techniques based on the biophysical properties of micro-organisms. This paper describes an instrumentation development in the fourth of the above categories, physical measurement, that uses a combination of fluorometric and light scatter spectra to detect and identify micro-organisms at the species level. A major advantage of this approach is the rapid turnaround possible in medical diagnostic or water testing applications. Fluorometric spectra serve to define the biochemical characteristics of the microbe, and light scatter spectra the size and shape morphology. Together, the two spectra define a 'fingerprint' for each species of microbe for detection, identification and quantification purposes. A prototype instrument has been developed and tested under NASA sponsorship based on fluorometric spectra alone. This instrument demonstrated identification and quantification capabilities at the species level. The paper reports on test results using this instrument, and the benefits of employing a combination of fluorometric and light scatter spectra.

Molecular ecology of hydrothermal vent microbial communities.

PubMed

Jeanthon, C

2000-02-01

The study of the structure and diversity of hydrothermal vent microbial communities has long been restricted to the morphological description of microorganisms and the use of enrichment culture-based techniques. Until recently the identification of the culturable fraction required the isolation of pure cultures followed by testing for multiple physiological and biochemical traits. However, peculiar inhabitants of the hydrothermal ecosystem such as the invertebrate endosymbionts and the dense microbial mat filaments have eluded laboratory cultivation. Substantial progress has been achieved in recent years in techniques for the identification of microorganisms in natural environments. Application of molecular approaches has revealed the existence of unique and previously unrecognized microorganisms. These have provided fresh insight into the ecology, diversity and evolution of mesophilic and thermophilic microbial communities from the deep-sea hydrothermal ecosystem. This review reports the main discoveries made through the introduction of these powerful techniques in the study of deep-sea hydrothermal vent microbiology.

Molecular identification of Aspergillus and Eurotium species isolated from rice and their toxin-producing ability.

PubMed

Yazdani, D; Zainal Abidin, M A; Tan, Y H; Kamaruzaman, S

2011-01-01

Thirty milled rice samples were collected from retailers in 4 provinces of Malaysia. These samples were evaluated for Aspergillus spp. infection by direct plating on malt extract salt agar (MESA). All Aspergillus holomorphs were isolated and identified using nucleotide sequences of ITS 1 and ITS 2 of rDNA. Five anamorphs (Aspergillus flavus, A. oryzae, A. tamarii, A. fumigatus and A. niger) and 5 teleomorphs (Eurotium rubrum, E. amstelodami, E. chevalieri, E. cristatum and E. tonophilum) were identified. The PCR-sequencing based technique for sequences of ITS 1 and ITS 2 is a fast technique for identification of Aspergillus and Eurotium species, although it doesn't work flawlessly for differentiation of Eurotium species. All Aspergillus and Eurotium isolates were screened for their ability to produce aflatoxin and ochratoxin A (OTA) by HPLC and TLC techniques. Only A. flavus isolate UPM 89 was able to produce aflatoxins B1 and B2.

Creation of hybrid optoelectronic systems for document identification

NASA Astrophysics Data System (ADS)

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

2001-06-01

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

Molecular diagnosis of rhino-orbito-cerebral mucormycosis from fresh tissue samples.

PubMed

Zaman, Kamran; Rudramurthy, Shivaprakash Mandya; Das, Ashim; Panda, Naresh; Honnavar, Prasanna; Kaur, Harsimran; Chakrabarti, Arunaloke

2017-08-01

We aimed to evaluate a PCR-based technique for the diagnosis of mucormycosis and the identification of fungi from fresh tissue specimens in patients with rhino-orbito-cerebral-mucormycosis (ROCM). Fifty cases of ROCM were included in the study. Conventional identification was performed using microscopy and culture. Molecular diagnosis was performed by amplifying the ribosomal DNA using pan-fungal ITS primers and semi-nested Mucorales-specific primers of the 18S region. The amplified products were sequenced to identify the agents. The utility of PCR-RFLP of the 18S region of rDNA was evaluated to identify the Mucorales. The ROCM cases were diagnosed by the demonstration of aseptate ribbon-like hyphae in biopsy specimens collected from the patients. Isolation was possible in 24 (48 %) samples. The ITS2 PCR confirmed mucormycosis in 27 cases (54 %; CI 59.4-68.2). By comparison, Mucorales-specific PCR was able to amplify DNA and the sequence enabled the identification of Mucorales speciesin all the patients. PCR-RFLP of the 18S region of rDNA could only identify the agent to genus level. The molecular technique was able to identify Mucorales species in 26 (42 %) cases that were negative by culture. Mucorales-specific semi-nested PCR targeting the 18S region is a better technique than ITS2 PCR for diagnosis. PCR-RFLP of the 18S region helps in identification to genus level.

Molecular identification of Amazonian stingless bees using polymerase chain reaction single-strand conformation polymorphism.

PubMed

Souza, M T; Carvalho-Zilse, G A

2014-07-25

In countries containing a mega diversity of wildlife, such as Brazil, identifying and characterizing biological diversity is a continuous process for the scientific community, even in face of technological and scientific advances. This activity demands initiatives for the taxonomic identification of highly diverse groups, such as stingless bees, including molecular analysis strategies. This type of bee is distributed in all of the Brazilian states, with the highest species diversity being found in the State of Amazônia. However, the estimated number of species diverges among taxonomists. These bees are considered the main pollinators in the Amazon rainforest, in which they obtain food and shelter; however, their persistence is constantly threatened by deforestation pressure. Hence, it is important to classify the number and abundance of bee specie, to measure their decline and implement meaningful, priority conservation strategies. This study aims to maximize the implementation of more direct, economic and successful techniques for the taxonomic identification of stingless bees. Specifically, the genes 16S rRNA and COI from mitochondrial DNA were used as molecular markers to differentiate 9 species of Amazonian stingless bees based on DNA polymorphism, using the polymerase chain reaction-single-strand conformation polymorphism technique. We registered different, exclusive SSCP haplotypes for both genes in all species analyzed. These results demonstrate that SSCP is a simple and cost-effective technique that is applicable to the molecular identification of stingless bee species.

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

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

Recombinant blood group proteins for use in antibody screening and identification tests.

PubMed

Seltsam, Axel; Blasczyk, Rainer

2009-11-01

The present review elucidates the potentials of recombinant blood group proteins (BGPs) for red blood cell (RBC) antibody detection and identification in pretransfusion testing and the achievements in this field so far. Many BGPs have been eukaryotically and prokaryotically expressed in sufficient quantity and quality for RBC antibody testing. Recombinant BGPs can be incorporated in soluble protein reagents or solid-phase assays such as ELISA, color-coded microsphere and protein microarray chip-based techniques. Because novel recombinant protein-based assays use single antigens, a positive reaction of a serum with the recombinant protein directly indicates the presence and specificity of the target antibody. Inversely, conventional RBC-based assays use panels of human RBCs carrying a huge number of blood group antigens at the same time and require negative reactions of samples with antigen-negative cells for indirect determination of antibody specificity. Because of their capacity for single-step, direct RBC antibody determination, recombinant protein-based assays may greatly facilitate and accelerate the identification of common and rare RBC antibodies.

Modeling and managing risk early in software development

NASA Technical Reports Server (NTRS)

Briand, Lionel C.; Thomas, William M.; Hetmanski, Christopher J.

1993-01-01

In order to improve the quality of the software development process, we need to be able to build empirical multivariate models based on data collectable early in the software process. These models need to be both useful for prediction and easy to interpret, so that remedial actions may be taken in order to control and optimize the development process. We present an automated modeling technique which can be used as an alternative to regression techniques. We show how it can be used to facilitate the identification and aid the interpretation of the significant trends which characterize 'high risk' components in several Ada systems. Finally, we evaluate the effectiveness of our technique based on a comparison with logistic regression based models.

Hazard identification by methods of animal-based toxicology.

PubMed

Barlow, S M; Greig, J B; Bridges, J W; Carere, A; Carpy, A J M; Galli, C L; Kleiner, J; Knudsen, I; Koëter, H B W M; Levy, L S; Madsen, C; Mayer, S; Narbonne, J-F; Pfannkuch, F; Prodanchuk, M G; Smith, M R; Steinberg, P

2002-01-01

This paper is one of several prepared under the project "Food Safety In Europe: Risk Assessment of Chemicals in Food and Diet" (FOSIE), a European Commission Concerted Action Programme, organised by the International Life Sciences Institute, Europe (ILSI). The aim of the FOSIE project is to review the current state of the science of risk assessment of chemicals in food and diet, by consideration of the four stages of risk assessment, that is, hazard identification, hazard characterisation, exposure assessment and risk characterisation. The contribution of animal-based methods in toxicology to hazard identification of chemicals in food and diet is discussed. The importance of first applying existing technical and chemical knowledge to the design of safety testing programs for food chemicals is emphasised. There is consideration of the presently available and commonly used toxicity testing approaches and methodologies, including acute and repeated dose toxicity, reproductive and developmental toxicity, neurotoxicity, genotoxicity, carcinogenicity, immunotoxicity and food allergy. They are considered from the perspective of whether they are appropriate for assessing food chemicals and whether they are adequate to detect currently known or anticipated hazards from food. Gaps in knowledge and future research needs are identified; research on these could lead to improvements in the methods of hazard identification for food chemicals. The potential impact of some emerging techniques and toxicological issues on hazard identification for food chemicals, such as new measurement techniques, the use of transgenic animals, assessment of hormone balance and the possibilities for conducting studies in which common human diseases have been modelled, is also considered.

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

DOEpatents

Sommer, Edward J.; Rich, John T.

2001-01-01

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

Application of identification techniques to remote manipulator system flight data

NASA Technical Reports Server (NTRS)

Shepard, G. D.; Lepanto, J. A.; Metzinger, R. W.; Fogel, E.

1983-01-01

This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.

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.

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.

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

NASA Astrophysics Data System (ADS)

Suresh, Pooja

2014-05-01

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

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

PubMed

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

2016-01-01

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

Single-molecule detection: applications to ultrasensitive biochemical analysis

NASA Astrophysics Data System (ADS)

Castro, Alonso; Shera, E. Brooks

1995-06-01

Recent developments in laser-based detection of fluorescent molecules have made possible the implementation of very sensitive techniques for biochemical analysis. We present and discuss our experiments on the applications of our recently developed technique of single-molecule detection to the analysis of molecules of biological interest. These newly developed methods are capable of detecting and identifying biomolecules at the single-molecule level of sensitivity. In one case, identification is based on measuring fluorescence brightness from single molecules. In another, molecules are classified by determining their electrophoretic velocities.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Teaching Cardiac Examination Skills

PubMed Central

Smith, Christopher A; Hart, Avery S; Sadowski, Laura S; Riddle, Janet; Evans, Arthur T; Clarke, Peter M; Ganschow, Pamela S; Mason, Ellen; Sequeira, Winston; Wang, Yue

2006-01-01

OBJECTIVE To determine if structured teaching of bedside cardiac examination skills improves medical residents' examination technique and their identification of key clinical findings. DESIGN Firm-based single-blinded controlled trial. SETTING Inpatient service at a university-affiliated public teaching hospital. PARTICIPANTS Eighty Internal Medicine residents. METHODS The study assessed 2 intervention groups that received 3-hour bedside teaching sessions during their 4-week rotation using either: (1) a traditional teaching method, “demonstration and practice” (DP) (n=26) or (2) an innovative method, “collaborative discovery” (CD) (n=24). The control group received their usual ward teaching sessions (n=25). The main outcome measures were scores on examination technique and correct identification of key clinical findings on an objective structured clinical examination (OSCE). RESULTS All 3 groups had similar scores for both their examination technique and identification of key findings in the preintervention OSCE. After teaching, both intervention groups significantly improved their technical examination skills compared with the control group. The increase was 10% (95% confidence interval [CI] 4% to 17%) for CD versus control and 12% (95% CI 6% to 19%) for DP versus control (both P<.005) equivalent to an additional 3 to 4 examination skills being correctly performed. Improvement in key findings was limited to a 5% (95% CI 2% to 9%) increase for the CD teaching method, CD versus control P=.046, equivalent to the identification of an additional 2 key clinical findings. CONCLUSIONS Both programs of bedside teaching increase the technical examination skills of residents but improvements in the identification of key clinical findings were modest and only demonstrated with a new method of teaching. PMID:16423116

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space.

PubMed

Akbar, Shahid; Hayat, Maqsood; Iqbal, Muhammad; Jan, Mian Ahmad

2017-06-01

Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to perilous impact of cancer, the development of an accurate and highly efficient intelligent computational model is desirable for identification of anticancer peptides. In this paper, evolutionary intelligent genetic algorithm-based ensemble model, 'iACP-GAEnsC', is proposed for the identification of anticancer peptides. In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition. The performance of the extracted feature spaces are investigated separately and then merged to exhibit the significance of hybridization. In addition, the predicted results of individual classifiers are combined together, using optimized genetic algorithm and simple majority technique in order to enhance the true classification rate. It is observed that genetic algorithm-based ensemble classification outperforms than individual classifiers as well as simple majority voting base ensemble. The performance of genetic algorithm-based ensemble classification is highly reported on hybrid feature space, with an accuracy of 96.45%. In comparison to the existing techniques, 'iACP-GAEnsC' model has achieved remarkable improvement in terms of various performance metrics. Based on the simulation results, it is observed that 'iACP-GAEnsC' model might be a leading tool in the field of drug design and proteomics for researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

ChiloKey, an interactive identification tool for the geophilomorph centipedes of Europe (Chilopoda, Geophilomorpha).

PubMed

Bonato, Lucio; Minelli, Alessandro; Lopresti, Massimo; Cerretti, Pierfilippo

2014-01-01

ChiloKey is a matrix-based, interactive key to all 179 species of Geophilomorpha (Chilopoda) recorded from Europe, including species of uncertain identity and those whose morphology is known partially only. The key is intended to assist in identification of subadult and adult specimens, by means of microscopy and simple dissection techniques whenever necessary. The key is freely available through the web at: http://www.biologia.unipd.it/chilokey/ and at http://www.interactive-keys.eu/chilokey/.

Chaotic Time Series Analysis Method Developed for Stall Precursor Identification in High-Speed Compressors

NASA Technical Reports Server (NTRS)

1997-01-01

A new technique for rotating stall precursor identification in high-speed compressors has been developed at the NASA Lewis Research Center. This pseudo correlation integral method uses a mathematical algorithm based on chaos theory to identify nonlinear dynamic changes in the compressor. Through a study of four various configurations of a high-speed compressor stage, a multistage compressor rig, and an axi-centrifugal engine test, this algorithm, using only a single pressure sensor, has consistently predicted the onset of rotating stall.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

2016-10-18

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G; Ward, David C; Bray-Ward, Patricia

2015-03-10

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

2010-02-23

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Laser micro-etching of metal prostheses for personal identification

PubMed Central

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

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

Laser micro-etching of metal prostheses for personal identification.

PubMed

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

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

Raman spectroscopic studies on bacteria

NASA Astrophysics Data System (ADS)

Maquelin, Kees; Choo-Smith, Lin-P'ing; Endtz, Hubert P.; Bruining, Hajo A.; Puppels, Gerwin J.

2000-11-01

Routine clinical microbiological identification of pathogenic micro-organisms is largely based on nutritional and biochemical tests. Laboratory results can be presented to a clinician after 2 - 3 days for most clinically relevant micro- organisms. Most of this time is required to obtain pure cultures and enough biomass for the tests to be performed. In the case of severely ill patients, this unavoidable time delay associated with such identification procedures can be fatal. A novel identification method based on confocal Raman microspectroscopy will be presented. With this method it is possible to obtain Raman spectra directly from microbial microcolonies on the solid culture medium, which have developed after only 6 hours of culturing for most commonly encountered organisms. Not only does this technique enable rapid (same day) identifications, but also preserves the sample allowing it to be double-checked with traditional tests. This, combined with the speed and minimal sample handling indicate that confocal Raman microspectroscopy has much potential as a powerful new tool in clinical diagnostic microbiology.

An overview of recent advances in system identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1994-01-01

This paper presents an overview of the recent advances in system identification for modal testing and control of large flexible structures. Several techniques are discussed including the Observer/Kalman Filter Identification, the Observer/Controller Identification, and the State-Space System Identification in the Frequency Domain. The System/Observer/Controller Toolbox developed at NASA Langley Research Center is used to show the applications of these techniques to real aerospace structures such as the Hubble spacecraft telescope and the active flexible aircraft wing.

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

PubMed

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

2014-01-01

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

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

PubMed

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

2016-01-01

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

Forensic use of photo response non-uniformity of imaging sensors and a counter method.

PubMed

Dirik, Ahmet Emir; Karaküçük, Ahmet

2014-01-13

Analogous to use of bullet scratches in forensic science, the authenticity of a digital image can be verified through the noise characteristics of an imaging sensor. In particular, photo-response non-uniformity noise (PRNU) has been used in source camera identification (SCI). However, this technique can be used maliciously to track or inculpate innocent people. To impede such tracking, PRNU noise should be suppressed significantly. Based on this motivation, we propose a counter forensic method to deceive SCI. Experimental results show that it is possible to impede PRNU-based camera identification for various imaging sensors while preserving the image quality.

Developments in the Identification of Glycan Biomarkers for the Detection of Cancer

PubMed Central

Ruhaak, L. Renee; Miyamoto, Suzanne; Lebrilla, Carlito B.

2013-01-01

Changes in glycosylation readily occur in cancer and other disease states. Thanks to recent advances in the development of analytical techniques and instrumentation, especially in mass spectrometry, it is now possible to identify blood-derived glycan-based biomarkers using glycomics strategies. This review is an overview of the developments made in the search for glycan-based cancer biomarkers and the technologies currently in use. It is anticipated that the progressing instrumental and bioinformatics developments will allow the identification of relevant glycan biomarkers for the diagnosis, early detection, and monitoring of cancer treatment with sufficient sensitivity and specificity for clinical use. PMID:23365456

Road sign recognition using Viapix module and correlation

NASA Astrophysics Data System (ADS)

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

2015-03-01

In this paper, we propose and validate a new system used to explore road assets. In this work we are interested on the vertical road signs. To do this, we are based on the combination of road signs detection, recognition and identification using data provides by sensors. The proposed approach consists on using panoramic views provided by the innovative device, VIAPIX®1, developed by our company ACTRIS2. We are based also on the optimized correlation technique for road signs recognition and identification on pictures. Obtained results shows the interest on using panoramic views compared to results obtained using images provided using only one camera.

Videogrammetric Model Deformation Measurement Technique

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Kernelized Locality-Sensitive Hashing for Fast Image Landmark Association

DTIC Science & Technology

2011-03-24

based Simultaneous Localization and Mapping ( SLAM ). The problem, however, is that vision-based navigation techniques can re- quire excessive amounts of...up and optimizing the data association process in vision-based SLAM . Specifically, this work studies the current methods that algorithms use to...required for location identification than that of other methods. This work can then be extended into a vision- SLAM implementation to subsequently

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modeling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-07-01

Ground magnetic anomaly separation using reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prosepecting area in NW Iran. The geophysical survey that resulted in the ground magnetic data was conducted for magnetic elements exploration. Firstly, RTP technique was applied for recognizing underground magnetic anomalies. RTP anomalies was classified to different populations based on this method. For this reason, drilling points determination with RTP technique was complicated. Next, C-A method was applied on the RTP-Magnetic-Anomalies (RTP-MA) for demonstrating magnetic susceptibility concentration. This identification was appropriate for increasing the resolution of the drilling points determination and decreasing the drilling risk, due to the economic costs of underground prospecting. In this study, the results of C-A Modeling on the RTP-MA are compared with 8 borehole data. The results show there is good correlation between anomalies derived via C-A method and log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentration, based on multifractal modeling data analyses, between 63 533.1 and 66 296 nT. Drilling results show appropriate magnetite thickness with the grades greater than 20 % Fe total. Also, anomalies associated with andesite units host iron mineralization.

[Modern bacterial taxonomy: techniques review--application to bacteria that nodulate leguminous plants (BNL)].

PubMed

Zakhia, Frédéric; de Lajudie, Philippe

2006-03-01

Taxonomy is the science that studies the relationships between organisms. It comprises classification, nomenclature, and identification. Modern bacterial taxonomy is polyphasic. This means that it is based on several molecular techniques, each one retrieving the information at different cellular levels (proteins, fatty acids, DNA...). The obtained results are combined and analysed to reach a "consensus taxonomy" of a microorganism. Until 1970, a small number of classification techniques were available for microbiologists (mainly phenotypic characterization was performed: a legume species nodulation ability for a Rhizobium, for example). With the development of techniques based on polymerase chain reaction for characterization, the bacterial taxonomy has undergone great changes. In particular, the classification of the legume nodulating bacteria has been repeatedly modified over the last 20 years. We present here a review of the currently used molecular techniques in bacterial characterization, with examples of application of these techniques for the study of the legume nodulating bacteria.

IDENTIFICATION OF SEDIMENT SOURCE AREAS WITHIN A WATERSHED

EPA Science Inventory

Two methods, one using a travel time approach and the other based on optimization techniques, were developed to identify sediment generating areas within a watershed. Both methods rely on hydrograph and sedimentograph data collected at the mouth of the watershed. Data from severa...

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.

3D matching techniques using OCT fingerprint point clouds

NASA Astrophysics Data System (ADS)

Gutierrez da Costa, Henrique S.; Silva, Luciano; Bellon, Olga R. P.; Bowden, Audrey K.; Czovny, Raphael K.

2017-02-01

Optical Coherence Tomography (OCT) makes viable acquisition of 3D fingerprints from both dermis and epidermis skin layers and their interfaces, exposing features that can be explored to improve biometric identification such as the curvatures and distinctive 3D regions. Scanned images from eleven volunteers allowed the construction of the first OCT 3D fingerprint database, to our knowledge, containing epidermal and dermal fingerprints. 3D dermal fingerprints can be used to overcome cases of Failure to Enroll (FTE) due to poor ridge image quality and skin alterations, cases that affect 2D matching performance. We evaluate three matching techniques, including the well-established Iterative Closest Points algorithm (ICP), Surface Interpenetration Measure (SIM) and the well-known KH Curvature Maps, all assessed using a 3D OCT fingerprint database, the first one for this purpose. Two of these techniques are based on registration techniques and one on curvatures. These were evaluated, compared and the fusion of matching scores assessed. We applied a sequence of steps to extract regions of interest named (ROI) minutiae clouds, representing small regions around distinctive minutia, usually located at ridges/valleys endings or bifurcations. The obtained ROI is acquired from the epidermis and dermis-epidermis interface by OCT imaging. A comparative analysis of identification accuracy was explored using different scenarios and the obtained results shows improvements for biometric identification. A comparison against 2D fingerprint matching algorithms is also presented to assess the improvements.

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.

Identification of Synthetic Fluids Utilizing Pyrolysis Gas Liquid Chromatographic Techniques

DTIC Science & Technology

1981-09-01

Base Stock No. 6327 Di-isodecyl Azelate II 7 Synthetic Base Stock No. 6318 Di-2-ethylhexyl Azelate I 8 Synthetic Base Stock No. 6323 l)i-2-ethylhexyl...Adipatc 13 9 Synthetic Base Stock No. 6321 Di-2-cthylhexyl Sebacattk 14 10 Synthetic Base Stock No. 6326 Di-tridecyl Azelate 15 11 Synthetic Base...Stock No. 6319 Di-tridecyl Adipate 16 12 Synthetic Base Stock No. 6320 Di-iso-octyl Azelate 17 13 Synthetic Base Stock No. 6516 TMP Triheptanoate 18 14

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.

Ground Vibration Test Planning and Pre-Test Analysis for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Bedrossian, Herand; Tinker, Michael L.; Hidalgo, Homero

2000-01-01

This paper describes the results of the modal test planning and the pre-test analysis for the X-33 vehicle. The pre-test analysis included the selection of the target modes, selection of the sensor and shaker locations and the development of an accurate Test Analysis Model (TAM). For target mode selection, four techniques were considered, one based on the Modal Cost technique, one based on Balanced Singular Value technique, a technique known as the Root Sum Squared (RSS) method, and a Modal Kinetic Energy (MKE) approach. For selecting sensor locations, four techniques were also considered; one based on the Weighted Average Kinetic Energy (WAKE), one based on Guyan Reduction (GR), one emphasizing engineering judgment, and one based on an optimum sensor selection technique using Genetic Algorithm (GA) search technique combined with a criteria based on Hankel Singular Values (HSV's). For selecting shaker locations, four techniques were also considered; one based on the Weighted Average Driving Point Residue (WADPR), one based on engineering judgment and accessibility considerations, a frequency response method, and an optimum shaker location selection based on a GA search technique combined with a criteria based on HSV's. To evaluate the effectiveness of the proposed sensor and shaker locations for exciting the target modes, extensive numerical simulations were performed. Multivariate Mode Indicator Function (MMIF) was used to evaluate the effectiveness of each sensor & shaker set with respect to modal parameter identification. Several TAM reduction techniques were considered including, Guyan, IRS, Modal, and Hybrid. Based on a pre-test cross-orthogonality checks using various reduction techniques, a Hybrid TAM reduction technique was selected and was used for all three vehicle fuel level configurations.

Identifying High-Rate Flows Based on Sequential Sampling

NASA Astrophysics Data System (ADS)

Zhang, Yu; Fang, Binxing; Luo, Hao

We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling, TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.

ActiviTree: interactive visual exploration of sequences in event-based data using graph similarity.

PubMed

Vrotsou, Katerina; Johansson, Jimmy; Cooper, Matthew

2009-01-01

The identification of significant sequences in large and complex event-based temporal data is a challenging problem with applications in many areas of today's information intensive society. Pure visual representations can be used for the analysis, but are constrained to small data sets. Algorithmic search mechanisms used for larger data sets become expensive as the data size increases and typically focus on frequency of occurrence to reduce the computational complexity, often overlooking important infrequent sequences and outliers. In this paper we introduce an interactive visual data mining approach based on an adaptation of techniques developed for web searching, combined with an intuitive visual interface, to facilitate user-centred exploration of the data and identification of sequences significant to that user. The search algorithm used in the exploration executes in negligible time, even for large data, and so no pre-processing of the selected data is required, making this a completely interactive experience for the user. Our particular application area is social science diary data but the technique is applicable across many other disciplines.

Multi-level damage identification with response reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

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

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

PubMed

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

2016-06-23

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

Virus detection and quantification using electrical parameters

NASA Astrophysics Data System (ADS)

Ahmad, Mahmoud Al; Mustafa, Farah; Ali, Lizna M.; Rizvi, Tahir A.

2014-10-01

Here we identify and quantitate two similar viruses, human and feline immunodeficiency viruses (HIV and FIV), suspended in a liquid medium without labeling, using a semiconductor technique. The virus count was estimated by calculating the impurities inside a defined volume by observing the change in electrical parameters. Empirically, the virus count was similar to the absolute value of the ratio of the change of the virus suspension dopant concentration relative to the mock dopant over the change in virus suspension Debye volume relative to mock Debye volume. The virus type was identified by constructing a concentration-mobility relationship which is unique for each kind of virus, allowing for a fast (within minutes) and label-free virus quantification and identification. For validation, the HIV and FIV virus preparations were further quantified by a biochemical technique and the results obtained by both approaches corroborated well. We further demonstrate that the electrical technique could be applied to accurately measure and characterize silica nanoparticles that resemble the virus particles in size. Based on these results, we anticipate our present approach to be a starting point towards establishing the foundation for label-free electrical-based identification and quantification of an unlimited number of viruses and other nano-sized particles.

Toxicophore exploration as a screening technology for drug design and discovery: techniques, scope and limitations.

PubMed

Singh, Pankaj Kumar; Negi, Arvind; Gupta, Pawan Kumar; Chauhan, Monika; Kumar, Raj

2016-08-01

Toxicity is a common drawback of newly designed chemotherapeutic agents. With the exception of pharmacophore-induced toxicity (lack of selectivity at higher concentrations of a drug), the toxicity due to chemotherapeutic agents is based on the toxicophore moiety present in the drug. To date, methodologies implemented to determine toxicophores may be broadly classified into biological, bioanalytical and computational approaches. The biological approach involves analysis of bioactivated metabolites, whereas the computational approach involves a QSAR-based method, mapping techniques, an inverse docking technique and a few toxicophore identification/estimation tools. Being one of the major steps in drug discovery process, toxicophore identification has proven to be an essential screening step in drug design and development. The paper is first of its kind, attempting to cover and compare different methodologies employed in predicting and determining toxicophores with an emphasis on their scope and limitations. Such information may prove vital in the appropriate selection of methodology and can be used as screening technology by researchers to discover the toxicophoric potentials of their designed and synthesized moieties. Additionally, it can be utilized in the manipulation of molecules containing toxicophores in such a manner that their toxicities might be eliminated or removed.

[Evaluation of mass spectrometry: MALDI-TOF MS for fast and reliable yeast identification].

PubMed

Relloso, María S; Nievas, Jimena; Fares Taie, Santiago; Farquharson, Victoria; Mujica, María T; Romano, Vanesa; Zarate, Mariela S; Smayevsky, Jorgelina

2015-01-01

The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technique known as MALDI-TOF MS is a tool used for the identification of clinical pathogens by generating a protein spectrum that is unique for a given species. In this study we assessed the identification of clinical yeast isolates by MALDI-TOF MS in a university hospital from Argentina and compared two procedures for protein extraction: a rapid method and a procedure based on the manufacturer's recommendations. A short protein extraction procedure was applied in 100 isolates and the rate of correct identification at genus and species level was 98.0%. In addition, we analyzed 201 isolates, previously identified by conventional methods, using the methodology recommended by the manufacturer and there was 95.38% coincidence in the identification at species level. MALDI TOF MS showed to be a fast, simple and reliable tool for yeast identification. Copyright © 2014 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Identification of Enterococcus, Streptococcus, and Staphylococcus by Multivariate Analysis of Proton Magnetic Resonance Spectroscopic Data from Plate Cultures

PubMed Central

Bourne, Roger; Himmelreich, Uwe; Sharma, Ansuiya; Mountford, Carolyn; Sorrell, Tania

2001-01-01

A new fingerprinting technique with the potential for rapid identification of bacteria was developed by combining proton magnetic resonance spectroscopy (1H MRS) with multivariate statistical analysis. This resulted in an objective identification strategy for common clinical isolates belonging to the bacterial species Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Streptococcus pneumoniae, Streptococcus pyogenes, Streptococcus agalactiae, and the Streptococcus milleri group. Duplicate cultures of 104 different isolates were examined one or more times using 1H MRS. A total of 312 cultures were examined. An optimized classifier was developed using a bootstrapping process and a seven-group linear discriminant analysis to provide objective classification of the spectra. Identification of isolates was based on consistent high-probability classification of spectra from duplicate cultures and achieved 92% agreement with conventional methods of identification. Fewer than 1% of isolates were identified incorrectly. Identification of the remaining 7% of isolates was defined as indeterminate. PMID:11474013

Development of advanced techniques for rotorcraft state estimation and parameter identification

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Molecular Techniques for the Detection and Differentiation of Host and Parasitoid Species and the Implications for Fruit Fly Management

PubMed Central

Jenkins, Cheryl; Chapman, Toni A.; Micallef, Jessica L.; Reynolds, Olivia L.

2012-01-01

Parasitoid detection and identification is a necessary step in the development and implementation of fruit fly biological control strategies employing parasitoid augmentive release. In recent years, DNA-based methods have been used to identify natural enemies of pest species where morphological differentiation is problematic. Molecular techniques also offer a considerable advantage over traditional morphological methods of fruit fly and parasitoid discrimination as well as within-host parasitoid identification, which currently relies on dissection of immature parasitoids from the host, or lengthy and labour-intensive rearing methods. Here we review recent research focusing on the use of molecular strategies for fruit fly and parasitoid detection and differentiation and discuss the implications of these studies on fruit fly management. PMID:26466628

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.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-05-09

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

Inquiry-Based Approach to a Carbohydrate Analysis Experiment

NASA Astrophysics Data System (ADS)

Senkbeil, Edward G.

1999-01-01

The analysis of an unknown carbohydrate in an inquiry-based learning format has proven to be a valuable and interesting undergraduate biochemistry laboratory experiment. Students are given a list of carbohydrates and a list of references for carbohydrate analysis. The references contain a variety of well-characterized wet chemistry and instrumental techniques for carbohydrate identification, but the students must develop an appropriate sequential protocol for unknown identification. The students are required to provide a list of chemicals and procedures and a flow chart for identification before the lab. During the 3-hour laboratory period, they utilize their accumulated information and knowledge to classify and identify their unknown. Advantages of the inquiry-based format are (i) students must be well prepared in advance to be successful in the laboratory, (ii) students feel a sense of accomplishment in both designing and carrying out a successful experiment, and (iii) the carbohydrate background information digested by the students significantly decreases the amount of lecture time required for this topic.

Use of PCR-restriction fragment length polymorphism analysis for identification of yeast species isolated from bovine intramammary infection.

PubMed

Fadda, M E; Pisano, M B; Scaccabarozzi, L; Mossa, V; Deplano, M; Moroni, P; Liciardi, M; Cosentino, S

2013-01-01

This study reports a rapid PCR-based technique using a one-enzyme RFLP for discrimination of yeasts isolated from bovine clinical and subclinical mastitis milk samples. We analyzed a total of 1,486 milk samples collected over 1 yr in south Sardinia and northern Italy, and 142 yeast strains were preliminarily grouped based on their cultural morphology and physiological characteristics. Assimilation tests were conducted using the identification kit API ID 32C and APILAB Plus software (bioMérieux, Marcy l'Etoile, France). For PCR-RFLP analysis, the 18S-ITS1-5.8S ribosomal(r)DNA region was amplified and then digested with HaeIII, and dendrogram analysis of RFLP fragments was carried out. Furthermore, within each of the groups identified by the API or PCR-RFLP methods, the identification of isolates was confirmed by sequencing of the D1/D2 region using an ABI Prism 310 automatic sequencer (Applied Biosystems, Foster City, CA). The combined phenotypic and molecular approach enabled the identification of 17 yeast species belonging to the genera Candida (47.9%), Cryptococcus (21.1%), Trichosporon (19.7%), Geotrichum (7.1%), and Rhodotorula (4.2%). All Candida species were correctly identified by the API test and their identification confirmed by sequencing. All strains identified with the API system as Geotrichum candidum, Cryptococcus uniguttulatus, and Rhodotorula glutinis also produced characteristic restriction patterns and were confirmed as Galactomyces geotrichum (a teleomorph of G. candidum), Filobasidium uniguttulatum (teleomorph of Crypt. uniguttulatus), and R. glutinis, respectively, by D1/D2 rDNA sequencing. With regard to the genus Trichosporon, preliminary identification by API was problematic, whereas the RFLP technique used in this study gave characteristic restriction profiles for each species. Moreover, sequencing of the D1/D2 region allowed not only successful identification of Trichosporon gracile where API could not, but also correct identification of misidentified isolates. In conclusion, the 18S-ITS1-5.8S region appears to be useful in detecting genetic variability among yeast species, which is valuable for taxonomic purposes and for species identification. We have established an RFLP database for yeast species identified in milk samples using the software GelCompar II and the RFLP database constitutes an initial method for veterinary yeast identification. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Context-Based Intent Understanding for Autonomous Systems in Naval and Collaborative Robot Applications

DTIC Science & Technology

2013-10-29

COVERED (From - To) 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d...based on contextual information, 3) develop vision-based techniques for learning of contextual information, and detection and identification of...that takes into account many possible contexts. The probability distributions of these contexts will be learned from existing databases on common sense

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

DTIC Science & Technology

1991-07-01

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

An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

NASA Astrophysics Data System (ADS)

Su, Zhongqing; Ye, Lin

2004-08-01

The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

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.

Development of an Adolescent Alcohol Misuse Intervention Based on the Prototype Willingness Model: A Delphi Study

ERIC Educational Resources Information Center

Davies, Emma; Martin, Jilly; Foxcroft, David

2016-01-01

Purpose: The purpose of this paper is to report on the use of the Delphi method to gain expert feedback on the identification of behaviour change techniques (BCTs) and development of a novel intervention to reduce adolescent alcohol misuse, based on the Prototype Willingness Model (PWM) of health risk behaviour. Design/methodology/approach: Four…

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

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2015-02-01

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

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.

Dynamic Parameter Identification of Subject-Specific Body Segment Parameters Using Robotics Formalism: Case Study Head Complex.

PubMed

Díaz-Rodríguez, Miguel; Valera, Angel; Page, Alvaro; Besa, Antonio; Mata, Vicente

2016-05-01

Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.

Mass spectrometry-based cDNA profiling as a potential tool for human body fluid identification.

PubMed

Donfack, Joseph; Wiley, Anissa

2015-05-01

Several mRNA markers have been exhaustively evaluated for the identification of human venous blood, saliva, and semen in forensic genetics. As new candidate human body fluid specific markers are discovered, evaluated, and reported in the scientific literature, there is an increasing trend toward determining the ideal markers for cDNA profiling of body fluids of forensic interest. However, it has not been determined which molecular genetics-based technique(s) should be utilized to assess the performance of these markers. In recent years, only a few confirmatory, mRNA/cDNA-based methods have been evaluated for applications in body fluid identification. The most frequently described methods tested to date include quantitative polymerase chain reaction (qPCR) and capillary electrophoresis (CE). However these methods, in particular qPCR, often favor narrow multiplex PCR due to the availability of a limited number of fluorescent dyes/tags. In an attempt to address this technological constraint, this study explored matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) for human body fluid identification via cDNA profiling of venous blood, saliva, and semen. Using cDNA samples at 20pg input phosphoglycerate kinase 1 (PGK1) amounts, body fluid specific markers for the candidate genes were amplified in their corresponding body fluid (i.e., venous blood, saliva, or semen) and absent in the remaining two (100% specificity). The results of this study provide an initial indication that MALDI-TOF MS is a potential fluorescent dye-free alternative method for body fluid identification in forensic casework. However, the inherent issues of low amounts of mRNA, and the damage caused to mRNA by environmental exposures, extraction processes, and storage conditions are important factors that significantly hinder the implementation of cDNA profiling into forensic casework. Published by Elsevier Ireland Ltd.

A water-soluble conjugated polymer for protein identification and denaturation detection.

PubMed

Xu, Qingling; Wu, Chunxian; Zhu, Chunlei; Duan, Xinrui; Liu, Libing; Han, Yuchun; Wang, Yilin; Wang, Shu

2010-12-03

Rapid and sensitive methods to detect proteins and protein denaturation have become increasingly needful in the field of proteomics, medical diagnostics, and biology. In this paper, we have reported the synthesis of a new cationic water-soluble conjugated polymer that contains fluorene and diene moieties in the backbone (PFDE) for protein identification by sensing an array of PFDE solutions in different ionic strengths using the linear discriminant analysis technique (LDA). The PFDE can form complexes with proteins by electrostatic and/or hydrophobic interactions and exhibits different fluorescence response. Three main factors contribute to the fluorescence response of PFDE, namely, the net charge density on the protein surface, the hydrophobic nature of the protein, and the metalloprotein characteristics. The denaturation of proteins can also be detected using PFDE as a fluorescent probe. The interactions between PFDE and proteins were also studied by dynamic light scattering (DLS) and isothermal titration microcalorimetry (ITC) techniques. In contrast to other methods based on conjugated polymers, the synthesis of a series of quencher or dye-labeled acceptors or protein substrates has been avoided in our method, which significantly reduces the cost and the synthetic complexity. Our method provides promising applications on protein identification and denaturation detection in a simple, fast, and label-free manner based on non-specific interaction-induced perturbation of PFDE fluorescence response.

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.

Causal gene identification using combinatorial V-structure search.

PubMed

Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng

2013-07-01

With the advances of biomedical techniques in the last decade, the costs of human genomic sequencing and genomic activity monitoring are coming down rapidly. To support the huge genome-based business in the near future, researchers are eager to find killer applications based on human genome information. Causal gene identification is one of the most promising applications, which may help the potential patients to estimate the risk of certain genetic diseases and locate the target gene for further genetic therapy. Unfortunately, existing pattern recognition techniques, such as Bayesian networks, cannot be directly applied to find the accurate causal relationship between genes and diseases. This is mainly due to the insufficient number of samples and the extremely high dimensionality of the gene space. In this paper, we present the first practical solution to causal gene identification, utilizing a new combinatorial formulation over V-Structures commonly used in conventional Bayesian networks, by exploring the combinations of significant V-Structures. We prove the NP-hardness of the combinatorial search problem under a general settings on the significance measure on the V-Structures, and present a greedy algorithm to find sub-optimal results. Extensive experiments show that our proposal is both scalable and effective, particularly with interesting findings on the causal genes over real human genome data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

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

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

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

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

2011-09-22

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

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

Fingerprint separation: an application of ICA

NASA Astrophysics Data System (ADS)

Singh, Meenakshi; Singh, Deepak Kumar; Kalra, Prem Kumar

2008-04-01

Among all existing biometric techniques, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications. Fingerprint-based identification is the most recognized tool in biometrics because of its reliability and accuracy. Fingerprint identification is done by matching questioned and known friction skin ridge impressions from fingers, palms, and toes to determine if the impressions are from the same finger (or palm, toe, etc.). There are many fingerprint matching algorithms which automate and facilitate the job of fingerprint matching, but for any of these algorithms matching can be difficult if the fingerprints are overlapped or mixed. In this paper, we have proposed a new algorithm for separating overlapped or mixed fingerprints so that the performance of the matching algorithms will improve when they are fed with these inputs. Independent Component Analysis (ICA) has been used as a tool to separate the overlapped or mixed fingerprints.

Private content identification based on soft fingerprinting

NASA Astrophysics Data System (ADS)

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

2011-02-01

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

The visible touch: in planta visualization of protein-protein interactions by fluorophore-based methods

PubMed Central

Bhat, Riyaz A; Lahaye, Thomas; Panstruga, Ralph

2006-01-01

Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this review, we address the individual strengths and weaknesses of both approaches and provide an outlook about new directions and possible future developments for both techniques. PMID:16800872

Establishing homologies in protein sequences

NASA Technical Reports Server (NTRS)

Dayhoff, M. O.; Barker, W. C.; Hunt, L. T.

1983-01-01

Computer-based statistical techniques used to determine homologies between proteins occurring in different species are reviewed. The technique is based on comparison of two protein sequences, either by relating all segments of a given length in one sequence to all segments of the second or by finding the best alignment of the two sequences. Approaches discussed include selection using printed tabulations, identification of very similar sequences, and computer searches of a database. The use of the SEARCH, RELATE, and ALIGN programs (Dayhoff, 1979) is explained; sample data are presented in graphs, diagrams, and tables and the construction of scoring matrices is considered.

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

Comparison of μ-ATR-FTIR spectroscopy and py-GCMS as identification tools for microplastic particles and fibers isolated from river sediments.

PubMed

Käppler, Andrea; Fischer, Marten; Scholz-Böttcher, Barbara M; Oberbeckmann, Sonja; Labrenz, Matthias; Fischer, Dieter; Eichhorn, Klaus-Jochen; Voit, Brigitte

2018-06-16

In recent years, many studies on the analysis of microplastics (MP) in environmental samples have been published. These studies are hardly comparable due to different sampling, sample preparation, as well as identification and quantification techniques. Here, MP identification is one of the crucial pitfalls. Visual identification approaches using morphological criteria alone often lead to significant errors, being especially true for MP fibers. Reliable, chemical structure-based identification methods are indispensable. In this context, the frequently used vibrational spectroscopic techniques but also thermoanalytical methods are established. However, no critical comparison of these fundamentally different approaches has ever been carried out with regard to analyzing MP in environmental samples. In this blind study, we investigated 27 single MP particles and fibers of unknown material isolated from river sediments. Successively micro-attenuated total reflection Fourier transform infrared spectroscopy (μ-ATR-FTIR) and pyrolysis gas chromatography-mass spectrometry (py-GCMS) in combination with thermochemolysis were applied. Both methods differentiated between plastic vs. non-plastic in the same way in 26 cases, with 19 particles and fibers (22 after re-evaluation) identified as the same polymer type. To illustrate the different approaches and emphasize the complementarity of their information content, we exemplarily provide a detailed comparison of four particles and three fibers and a critical discussion of advantages and disadvantages of both methods.

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

PubMed

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

2013-01-01

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

Species identification refined by molecular scatology in a community of sympatric carnivores in Xinjiang, China.

PubMed

Laguardia, Alice; Wang, Jun; Shi, Fang-Lei; Shi, Kun; Riordan, Philip

2015-03-18

Many ecological studies and conservation management plans employ noninvasive scat sampling based on the assumption that species' scats can be correctly identified in the field. However, in habitats with sympatric similarly sized carnivores, misidentification of scats is frequent and can lead to bias in research results. To address the scat identification dilemma, molecular scatology techniques have been developed to extract DNA from the donor cells present on the outer lining of the scat samples. A total of 100 samples were collected in the winter of 2009 and 2011 in Taxkorgan region of Xinjiang, China. DNA was extracted successfully from 88% of samples and genetic species identification showed that more than half the scats identified in the field as snow leopard (Panthera uncia) actually belonged to fox (Vulpes vulpes). Correlation between scat characteristics and species were investigated, showing that diameter and dry weight of the scat were significantly different between the species. However it was not possible to define a precise range of values for each species because of extensive overlap between the morphological values. This preliminary study confirms that identification of snow leopard feces in the field is misleading. Research that relies upon scat samples to assess distribution or diet of the snow leopard should therefore employ molecular scatology techniques. These methods are financially accessible and employ relatively simple laboratory procedures that can give an indisputable response to species identification from scats.

Demonstration of a single-wavelength spectral-imaging-based Thai jasmine rice identification

NASA Astrophysics Data System (ADS)

Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

2011-07-01

A single-wavelength spectral-imaging-based Thai jasmine rice breed identification is demonstrated. Our nondestructive identification approach relies on a combination of fluorescent imaging and simple image processing techniques. Especially, we apply simple image thresholding, blob filtering, and image subtracting processes to either a 545 or a 575nm image in order to identify our desired Thai jasmine rice breed from others. Other key advantages include no waste product and fast identification time. In our demonstration, UVC light is used as our exciting light, a liquid crystal tunable optical filter is used as our wavelength seclector, and a digital camera with 640activepixels×480activepixels is used to capture the desired spectral image. Eight Thai rice breeds having similar size and shape are tested. Our experimental proof of concept shows that by suitably applying image thresholding, blob filtering, and image subtracting processes to the selected fluorescent image, the Thai jasmine rice breed can be identified with measured false acceptance rates of <22.9% and <25.7% for spectral images at 545 and 575nm wavelengths, respectively. A measured fast identification time is 25ms, showing high potential for real-time applications.

A novel, multiplex, real-time PCR-based approach for the detection of the commonly occurring pathogenic fungi and bacteria.

PubMed

Horváth, Ádám; Pető, Zoltán; Urbán, Edit; Vágvölgyi, Csaba; Somogyvári, Ferenc

2013-12-23

Polymerase chain reaction (PCR)-based techniques are widely used to identify fungal and bacterial infections. There have been numerous reports of different, new, real-time PCR-based pathogen identification methods although the clinical practicability of such techniques is not yet fully clarified.The present study focuses on a novel, multiplex, real-time PCR-based pathogen identification system developed for rapid differentiation of the commonly occurring bacterial and fungal causative pathogens of bloodstream infections. A multiplex, real-time PCR approach is introduced for the detection and differentiation of fungi, Gram-positive (G+) and Gram-negative (G-) bacteria. The Gram classification is performed with the specific fluorescence resonance energy transfer (FRET) probes recommended for LightCycler capillary real-time PCR. The novelty of our system is the use of a non-specific SYBR Green dye instead of labelled anchor probes or primers, to excite the acceptor dyes on the FRET probes. In conjunction with this, the use of an intercalating dye allows the detection of fungal amplicons.With the novel pathogen detection system, fungi, G + and G- bacteria in the same reaction tube can be differentiated within an hour after the DNA preparation via the melting temperatures of the amplicons and probes in the same tube. This modified FRET technique is specific and more rapid than the gold-standard culture-based methods. The fact that fungi, G + and G- bacteria were successfully identified in the same tube within an hour after the DNA preparation permits rapid and early evidence-based management of bloodstream infections in clinical practice.

"ToothPIC": An Interactive Application for Teaching Oral Anatomy

ERIC Educational Resources Information Center

Javaid, Maria; Ashrafi, Seema; Zefran, Mil; Steinberg, Arnold D.

2016-01-01

This paper describes the development and evaluation of an interactive educational program, "Tooth" "P"lacement and "I"dentification "C"oach ("ToothPIC"). The program uses a game-based learning paradigm and 3D visualization techniques to allow first year dentistry and hygiene students to get…

Identifying Critical Issues and Problems in Technology Education Using a Modified-Delphi Technique.

ERIC Educational Resources Information Center

Wicklein, Robert C.

1993-01-01

Critical issues for technology education (TE) identified by a 25-member Delphi panel were identification of the knowledge base, curriculum development approaches, interdisciplinary approaches, and teacher education reform. Problems identified included inadequate marketing/public relations, teacher shortage, lack of content consensus, and…

Untangling Topic Threads in Chat-Based Communication: A Case Study

DTIC Science & Technology

2011-08-01

learning techniques such as clustering are very popular for analyzing text for topic identification (Anjewierden,, Kollöffel and Hulshof 2007; Adams...Anjewierden, A., Kollöffel, B., and Hulshof , C. (2007). Towards educational data mining: Using data mining methods for automated chat analysis to

Identification of particle-laden flow features from wavelet decomposition

NASA Astrophysics Data System (ADS)

Jackson, A.; Turnbull, B.

2017-12-01

A wavelet decomposition based technique is applied to air pressure data obtained from laboratory-scale powder snow avalanches. This technique is shown to be a powerful tool for identifying both repeatable and chaotic features at any frequency within the signal. Additionally, this technique is demonstrated to be a robust method for the removal of noise from the signal as well as being capable of removing other contaminants from the signal. Whilst powder snow avalanches are the focus of the experiments analysed here, the features identified can provide insight to other particle-laden gravity currents and the technique described is applicable to a wide variety of experimental signals.

A simple molecular technique for distinguishing species reveals frequent misidentification of Hawaiian corals in the genus Pocillopora

PubMed Central

Forsman, Zac H.; Toonen, Robert J.

2018-01-01

Species within the scleractinian genus Pocillopora Lamarck 1816 exhibit extreme phenotypic plasticity, making identification based on morphology difficult. However, the mitochondrial open reading frame (mtORF) marker provides a useful genetic tool for identification of most species in this genus, with a notable exception of P. eydouxi and P. meandrina. Based on recent genomic work, we present a quick and simple, gel-based restriction fragment length polymorphism (RFLP) method for the identification of all six Pocillopora species occurring in Hawai‘i by amplifying either the mtORF region, a newly discovered histone region, or both, and then using the restriction enzymes targeting diagnostic sequences we unambiguously identify each species. Using this approach, we documented frequent misidentification of Pocillopora species based on colony morphology. We found that P. acuta colonies are frequently mistakenly identified as P. damicornis in Kāne‘ohe Bay, O‘ahu. We also found that P. meandrina likely has a northern range limit in the Northwest Hawaiian Islands, above which P. ligulata was regularly mistaken for P. meandrina. PMID:29441239

Hemispheric specialization in quantification processes.

PubMed

Pasini, M; Tessari, A

2001-01-01

Three experiments were carried out to study hemispheric specialization for subitizing (the rapid enumeration of small patterns) and counting (the serial quantification process based on some formal principles). The experiments consist of numerosity identification of dot patterns presented in one visual field, with a tachistoscopic technique, or eye movements monitored through glasses, and comparison between centrally presented dot patterns and lateralized tachistoscopically presented digits. Our experiments show left visual field advantage in the identification and comparison tasks in the subitizing range, whereas right visual field advantage has been found in the comparison task for the counting range.

Note: Model identification and analysis of bivalent analyte surface plasmon resonance data.

PubMed

Tiwari, Purushottam Babu; Üren, Aykut; He, Jin; Darici, Yesim; Wang, Xuewen

2015-10-01

Surface plasmon resonance (SPR) is a widely used, affinity based, label-free biophysical technique to investigate biomolecular interactions. The extraction of rate constants requires accurate identification of the particular binding model. The bivalent analyte model involves coupled non-linear differential equations. No clear procedure to identify the bivalent analyte mechanism has been established. In this report, we propose a unique signature for the bivalent analyte model. This signature can be used to distinguish the bivalent analyte model from other biphasic models. The proposed method is demonstrated using experimentally measured SPR sensorgrams.

The Bone Black Pigment Identification by Noninvasive, In Situ Infrared Reflection Spectroscopy

PubMed Central

Malagodi, Marco; Vagnini, Manuela

2018-01-01

Two real case studies, an oil painting on woven paper and a cycle of mural paintings, have been presented to validate the use of infrared reflection spectroscopy as suitable technique for the identification of bone black pigment. By the use of the sharp weak band at 2013 cm−1, it has been possible to distinguish animal carbon-based blacks by a noninvasive method. Finally, an attempt for an eventual assignment for the widely used sharp band at 2013 cm−1 is discussed. PMID:29736290

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

PubMed

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

2015-12-08

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

Liquid chromatographic separation of terpenoid pigments in foods and food products.

PubMed

Cserháti, T; Forgács, E

2001-11-30

The newest achievements in the use of various liquid chromatographic techniques such as adsorption and reversed-phase thin-layer chromatography and HPLC employed for the separation and quantitative determination of terpenoid-based color substances in foods and food products are reviewed. The techniques applied for the analysis of individual pigments and pigments classes are surveyed and critically evaluated. Future trends in the separation and identification of pigments in foods and food products are delineated.

Determination of residual stresses in objects at their additive manufacturing by layer-by-layer photopolymerization method

NASA Astrophysics Data System (ADS)

Bychkov, P. S.; Chentsov, A. V.; Kozintsev, V. M.; Popov, A. L.

2018-04-01

A calculation-experimental technique is developed for identification of the shrinkage stresses generated in objects after their additive manufacturing by layer-by-layer photopolymerization. The technique is based on the analysis of shrinkage deformations at bending occurring in a series of samples in the form of plates-stripes with identical sizes, but with different time of polymerization which is predetermined during their production on the 3D printer.

Sound Source Identification Through Flow Density Measurement and Correlation With Far Field Noise

NASA Technical Reports Server (NTRS)

Panda, J.; Seasholtz, R. G.

2001-01-01

Sound sources in the plumes of unheated round jets, in the Mach number range 0.6 to 1.8, were investigated experimentally using "casuality" approach, where air density fluctuations in the plumes were correlated with the far field noise. The air density was measured using a newly developed Molecular Rayleigh scattering based technique, which did not require any seeding. The reference at the end provides a detailed description of the measurement technique.

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

PubMed

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

2017-02-05

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

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

ERIC Educational Resources Information Center

Hammonds, S. J.

1990-01-01

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

Comparison of modal identification techniques using a hybrid-data approach

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1986-01-01

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

Computerized multiple image analysis on mammograms: performance improvement of nipple identification for registration of multiple views using texture convergence analyses

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Sahiner, Berkman; Hadjiiski, Lubomir M.; Paramagul, Chintana

2004-05-01

Automated registration of multiple mammograms for CAD depends on accurate nipple identification. We developed two new image analysis techniques based on geometric and texture convergence analyses to improve the performance of our previously developed nipple identification method. A gradient-based algorithm is used to automatically track the breast boundary. The nipple search region along the boundary is then defined by geometric convergence analysis of the breast shape. Three nipple candidates are identified by detecting the changes along the gray level profiles inside and outside the boundary and the changes in the boundary direction. A texture orientation-field analysis method is developed to estimate the fourth nipple candidate based on the convergence of the tissue texture pattern towards the nipple. The final nipple location is determined from the four nipple candidates by a confidence analysis. Our training and test data sets consisted of 419 and 368 randomly selected mammograms, respectively. The nipple location identified on each image by an experienced radiologist was used as the ground truth. For 118 of the training and 70 of the test images, the radiologist could not positively identify the nipple, but provided an estimate of its location. These were referred to as invisible nipple images. In the training data set, 89.37% (269/301) of the visible nipples and 81.36% (96/118) of the invisible nipples could be detected within 1 cm of the truth. In the test data set, 92.28% (275/298) of the visible nipples and 67.14% (47/70) of the invisible nipples were identified within 1 cm of the truth. In comparison, our previous nipple identification method without using the two convergence analysis techniques detected 82.39% (248/301), 77.12% (91/118), 89.93% (268/298) and 54.29% (38/70) of the nipples within 1 cm of the truth for the visible and invisible nipples in the training and test sets, respectively. The results indicate that the nipple on mammograms can be detected accurately. This will be an important step towards automatic multiple image analysis for CAD techniques.

Subcritical flutter testing and system identification

NASA Technical Reports Server (NTRS)

Houbolt, J. C.

1974-01-01

Treatment is given of system response evaluation, especially in application to subcritical flight and wind tunnel flutter testing of aircraft. An evaluation is made of various existing techniques, in conjuction with a companion survey which reports theoretical and analog experiments made to study the identification of system response characteristics. Various input excitations are considered, and new techniques for analyzing response are explored, particularly in reference to the prevalent practical case where unwanted input noise is present, such as caused by gusts or wind tunnel turbulence. Further developments are also made of system parameter identification techniques.

Raman spectroscopy of CNC-and CNF-based nanocomposites

Treesearch

Umesh P. Agarwal

2017-01-01

In this chapter, applications of Raman spectroscopy to nanocelluloses and nanocellulose composites are reviewed, and it is shown how use of various techniques in Raman can provide unique information. Some of the most important uses consisted of identification of cellulose nanomaterials, estimation of cellulose crystallinity, study of dispersion of cellulose...

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

NASA Technical Reports Server (NTRS)

1979-01-01

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

Developing Public Education Policy through Policy-Impact Analysis.

ERIC Educational Resources Information Center

Hackett, E. Raymond; And Others

A model for analyzing policy impacts is presented that will assist state-level policy makers in education. The model comprises four stages: (1) monitoring, which includes the identification of relevant trends and issues and the development of a data base; (2) forecasting, which uses quantitative and qualitative techniques developed in futures…

A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

PubMed Central

Xie, Jin; Zhang, Lei; You, Jane; Zhang, David; Qu, Xiaofeng

2012-01-01

Human hand back skin texture (HBST) is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands). An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the l1 -minimization based sparse representation (SR) technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification. PMID:23012512

[Mass spectrometry in the clinical microbiology laboratory].

PubMed

Jordana-Lluch, Elena; Martró Català, Elisa; Ausina Ruiz, Vicente

2012-12-01

Infectious diseases are still a cause of high mortality and morbidity rates. Current microbiological diagnostic methods are based on culture and phenotypic identification of isolated microorganisms, which can be obtained in about 24-48 h. Given that the microbiological identification is of major importance for patient management, new diagnostic methods are needed in order to detect and identify microorganisms in a timely and accurate manner. Over the last few years, several molecular techniques based on the amplification of microbial nucleic acids have been developed with the aim of reducing the time needed for the identification of the microorganisms involved in different infectious processes. On the other hand, mass spectrometry has emerged as a rapid and consistent alternative to conventional methods for microorganism identification. This review describes the most widely used mass spectrometry technologies -matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and electrospray ionization time-of-flight (ESI-TOF)-, both for protein and nucleic acid analysis, as well as the commercial platforms available. Related publications of most interest in clinical microbiology are also reviewed. Copyright © 2011 Elsevier España, S.L. All rights reserved.

Estimation of hysteretic damping of structures by stochastic subspace identification

NASA Astrophysics Data System (ADS)

Bajrić, Anela; Høgsberg, Jan

2018-05-01

Output-only system identification techniques can estimate modal parameters of structures represented by linear time-invariant systems. However, the extension of the techniques to structures exhibiting non-linear behavior has not received much attention. This paper presents an output-only system identification method suitable for random response of dynamic systems with hysteretic damping. The method applies the concept of Stochastic Subspace Identification (SSI) to estimate the model parameters of a dynamic system with hysteretic damping. The restoring force is represented by the Bouc-Wen model, for which an equivalent linear relaxation model is derived. Hysteretic properties can be encountered in engineering structures exposed to severe cyclic environmental loads, as well as in vibration mitigation devices, such as Magneto-Rheological (MR) dampers. The identification technique incorporates the equivalent linear damper model in the estimation procedure. Synthetic data, representing the random vibrations of systems with hysteresis, validate the estimated system parameters by the presented identification method at low and high-levels of excitation amplitudes.

31P-edited diffusion-ordered 1H NMR spectroscopy for the spectral isolation and identification of organophosphorus compounds related to chemical weapons agents and their degradation products.

PubMed

Mayer, Brian P; Valdez, Carlos A; Hok, Saphon; Chinn, Sarah C; Hart, Bradley R

2012-12-04

Organophosphorus compounds represent a large class of molecules that include pesticides, flame-retardants, biologically relevant molecules, and chemical weapons agents (CWAs). The detection and identification of organophosphorus molecules, particularly in the cases of pesticides and CWAs, are paramount to the verification of international treaties by various organizations. To that end, novel analytical methodologies that can provide additional support to traditional analyses are important for unambiguous identification of these compounds. We have developed an NMR method that selectively edits for organophosphorus compounds via (31)P-(1)H heteronuclear single quantum correlation (HSQC) and provides an additional chromatographic-like separation based on self-diffusivities of the individual species via (1)H diffusion-ordered spectroscopy (DOSY): (1)H-(31)P HSQC-DOSY. The technique is first validated using the CWA VX (O-ethyl S-[2-(diisopropylamino)ethyl] methylphosphonothioate) by traditional two-dimensional DOSY spectra. We then extend this technique to a complex mixture of VX degradation products and identify all the main phosphorus-containing byproducts generated after exposure to a zinc-cyclen organometallic homogeneous catalyst.

Hyperspectral imager for components identification in the atmosphere

NASA Astrophysics Data System (ADS)

Dewandel, Jean-Luc; Beghuin, Didier; Dubois, Xavier; Antoine, Philippe

2017-11-01

Several applications require the identification of chemical elements during re-entry of material in the atmosphere. The materials can be from human origin or meteorites. The Automated Transfer Vehicle (ATV) re-entry has been filmed with conventional camera from airborne manual operation. In order to permit the identification of the separate elements from their glow, spectral analysis needs to be added to the video data. In a LET-SME contract with ESA, Lambda-X has built a Fourier Transform Imaging Spectrometer to permit, in a future work, to bring the technology to the readiness level required for the application. In this paper, the principles of the Fourier Transform Imaging spectroscopy are recalled, the different interferometers suitable for supporting the technique are reviewed and the selection process is explained. The final selection of the interferometer corresponds to a birefringent prism based common path shear interferometer. The design of the breadboard and its performances are presented in terms of spatial resolution, aperture, and spectral resolution. A discussion is open regarding perspective of the technique for other remote sensing applications compared to more usual push broom configurations.

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

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

2007-04-01

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

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

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Laser-induced breakdown spectroscopy (LIBS): An innovative tool for studying bacteria

NASA Astrophysics Data System (ADS)

Mohaidat, Qassem I.

Laser-induced breakdown spectroscopy (LIBS) has gained a reputation as a flexible and convenient technique for rapidly determining the elemental composition of samples with minimal or no sample preparation. In this dissertation, I will describe the benefits of using LIBS for the rapid discrimination and identification of bacteria (both pathogenic and non-pathogenic) based on the relative concentration of trace inorganic elements such as Mg, P, Ca, and Na. The speed, portability, and robustness of the technique suggest that LIBS may be applicable as a rapid point-of-care medical diagnostic technology. LIBS spectra of multiple genera of bacteria such as Escherichia, Streptococcus, Mycobacterium, and Staphylococcus were acquired and successfully analyzed using a computerized discriminant function analysis (DFA). It was shown that a LIBS-based bacterial identification might be insensitive to a wide range of biological changes that could occur in the bacterial cell due to a variety of environmental stresses that the cell may encounter. The effect of reducing the number of bacterial cells on the LIBS-based classification was also studied. These results showed that with 2500 bacteria, the identification of bacterial specimens was still possible. Importantly, it was shown that bacteria in mixed samples (more than one type of bacteria being present) were identifiable. The dominant or majority component of a two-component mixture was reliably identified as long as it comprised 70% of the mixture or more. Finally, to simulate a clinical specimen in a precursor to actual clinical tests, Staphylococcus epidermidis bacteria were collected from urine samples (to simulate a urinary tract infection specimen) and were tested via LIBS without washing. The analysis showed that these bacteria possessed exactly the same spectral fingerprint as control bacteria obtained from sterile deionized water, resulting in a 100% correct classification. This indicates that the presence of other trace background biochemicals from clinical fluids will not adversely disrupt a LIBS-based identification of bacteria.

A novel field method to distinguish between cryptic carcharhinid sharks, Australian blacktip shark Carcharhinus tilstoni and common blacktip shark C. limbatus, despite the presence of hybrids.

PubMed

Johnson, G J; Buckworth, R C; Lee, H; Morgan, J A T; Ovenden, J R; McMahon, C R

2017-01-01

Multivariate and machine-learning methods were used to develop field identification techniques for two species of cryptic blacktip shark. From 112 specimens, precaudal vertebrae (PCV) counts and molecular analysis identified 95 Australian blacktip sharks Carcharhinus tilstoni and 17 common blacktip sharks Carcharhinus limbatus. Molecular analysis also revealed 27 of the 112 were C. tilstoni × C. limbatus hybrids, of which 23 had C. tilstoni PCV counts and four had C. limbatus PCV counts. In the absence of further information about hybrid phenotypes, hybrids were assigned as either C. limbatus or C. tilstoni based on PCV counts. Discriminant analysis achieved 80% successful identification, but machine-learning models were better, achieving 100% successful identification, using six key measurements (fork length, caudal-fin peduncle height, interdorsal space, second dorsal-fin height, pelvic-fin length and pelvic-fin midpoint to first dorsal-fin insertion). Furthermore, pelvic-fin markings could be used for identification: C. limbatus has a distinct black mark >3% of the total pelvic-fin area, while C. tilstoni has markings with diffuse edges, or has smaller or no markings. Machine learning and pelvic-fin marking identification methods were field tested achieving 87 and 90% successful identification, respectively. With further refinement, the techniques developed here will form an important part of a multi-faceted approach to identification of C. tilstoni and C. limbatus and have a clear management and conservation application to these commercially important sharks. The methods developed here are broadly applicable and can be used to resolve species identities in many fisheries where cryptic species exist. © 2016 The Fisheries Society of the British Isles.

Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

PubMed Central

Chen, Yen-Lin; Liang, Wen-Yew; Chiang, Chuan-Yen; Hsieh, Tung-Ju; Lee, Da-Cheng; Yuan, Shyan-Ming; Chang, Yang-Lang

2011-01-01

This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions. PMID:22163990

Human tracking over camera networks: a review

NASA Astrophysics Data System (ADS)

Hou, Li; Wan, Wanggen; Hwang, Jenq-Neng; Muhammad, Rizwan; Yang, Mingyang; Han, Kang

2017-12-01

In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non-overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminative trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.

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

PubMed

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

2000-11-01

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

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.

Optimizations for the EcoPod field identification tool

PubMed Central

Manoharan, Aswath; Stamberger, Jeannie; Yu, YuanYuan; Paepcke, Andreas

2008-01-01

Background We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species. Results Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required. Conclusion Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing performed better for rare species than Simple Good-Turing, and that, contrary to expectation, the technique did not then adversely affect identification performance for frequently observed birds. PMID:18366649

[Research progress on identification and quality evaluation of glues medicines].

PubMed

Li, Hui-Hu; Ren, Gang; Chen, Li-Min; Zhong, Guo-Yue

2018-01-01

Glues medicines is a special kind of traditional Chinese medicine.As the market demand is large, the raw materials are in short supply and lacks proper quality evaluation technology, which causes inconsistent quality of products on the market. Its authentic identification and evaluation stay a problem to be solved. In this paper, the research progress of the methods and techniques of the evaluation of the identification and quality of glues medicines were reviewed. The researches of medicinal glue type identification and quality evaluation mainly concentrated in four aspects of medicinal materials of physical and chemical properties, trace elements, organic chemicals and biological genetic methods and techniques. The methods of physicochemical properties include thermal analysis, gel electrophoresis, isoelectric focusing electrophoresis, infrared spectroscopy, gel exclusion chromatography, and circular dichroism. The methods including atomic absorption spectrometry, X-ray fluorescence spectrometry, plasma emission spectrometry and visible spectrophotometry were used for the study of the trace elements of glues medicines. The organic chemical composition was studied by methods of composition of amino acids, content detection, odor detection, lipid soluble component, organic acid detection. Methods based on the characteristics of biogenetics include DNA, polypeptide and amino acid sequence difference analysis. Overall, because of relative components similarity of the glues medicines (such as amino acids, proteins and peptides), its authenticity and quality evaluation index is difficult to judge objectively, all sorts of identification evaluation methods have different characteristics, but also their limitations. It indicates that further study should focus on identification of evaluation index and various technology integrated application combining with the characteristics of the production process. Copyright© by the Chinese Pharmaceutical Association.

System Identification for the Clipper Liberty C96 Wind Turbine

NASA Astrophysics Data System (ADS)

Showers, Daniel

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

TOXICITY IDENTIFICATION EVALUATION (TIE) RESULTS FOR METAL CONTAMINATED SEDIMENTS

EPA Science Inventory

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

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.

Method and Apparatus for Reading Two Dimensional Identification Symbols Using Radar Techniques

NASA Technical Reports Server (NTRS)

Schramm, Harry F., Jr. (Inventor); Roxby, Donald L. (Inventor)

2003-01-01

A method and apparatus are provided for sensing two-dimensional identification marks provided on a substrate or embedded within a substrate below a surface of the substrate. Micropower impulse radar is used to transmit a high risetime, short duration pulse to a focussed radar target area of the substrate having the two dimensional identification marks. The method further includes the steps of listening for radar echoes returned from the identification marks during a short listening period window occurring a predetermined time after transmission of the radar pulse. If radar echoes are detected, an image processing step is carried out. If no radar echoes are detected, the method further includes sequentially transmitting further high risetime, short duration pulses, and listening for radar echoes from each of said further pulses after different elapsed times for each of the further pulses until radar echoes are detected. When radar echoes are detected, data based on the detected echoes is processed to produce an image of the identification marks.

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.

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

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

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun-Fat

2017-01-01

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

Development of techniques for producing static strata maps and development of photointerpretive methods based on multitemporal LANDSAT data

NASA Technical Reports Server (NTRS)

Colwell, R. N. (Principal Investigator)

1977-01-01

The results and progress of work conducted in support of the Large Area Crop Inventory Experiment (LACIE) are documented. Research was conducted for two tasks. These tasks include: (1) evaluation of the UCB static stratification procedure and modification of that procedure if warranted; and (2) the development of alternative photointerpretive techniques to the present LACIE procedure for the identification and selection of training areas for machine-processing of LACIE segments.

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

Security and matching of partial fingerprint recognition systems

NASA Astrophysics Data System (ADS)

Jea, Tsai-Yang; Chavan, Viraj S.; Govindaraju, Venu; Schneider, John K.

2004-08-01

Despite advances in fingerprint identification techniques, matching incomplete or partial fingerprints still poses a difficult challenge. While the introduction of compact silicon chip-based sensors that capture only a part of the fingerprint area have made this problem important from a commercial perspective, there is also considerable interest on the topic for processing partial and latent fingerprints obtained at crime scenes. Attempts to match partial fingerprints using singular ridge structures-based alignment techniques fail when the partial print does not include such structures (e.g., core or delta). We present a multi-path fingerprint matching approach that utilizes localized secondary features derived using only the relative information of minutiae. Since the minutia-based fingerprint representation, is an ANSI-NIST standard, our approach has the advantage of being directly applicable to already existing databases. We also analyze the vulnerability of partial fingerprint identification systems to brute force attacks. The described matching approach has been tested on one of FVC2002"s DB1 database11. The experimental results show that our approach achieves an equal error rate of 1.25% and a total error rate of 1.8% (with FAR at 0.2% and FRR at 1.6%).

Automated texture-based identification of ovarian cancer in confocal microendoscope images

NASA Astrophysics Data System (ADS)

Srivastava, Saurabh; Rodriguez, Jeffrey J.; Rouse, Andrew R.; Brewer, Molly A.; Gmitro, Arthur F.

2005-03-01

The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.

A new assay based on terminal restriction fragment length polymorphism of homocitrate synthase gene fragments for Candida species identification.

PubMed

Szemiako, Kasjan; Śledzińska, Anna; Krawczyk, Beata

2017-08-01

Candida sp. have been responsible for an increasing number of infections, especially in patients with immunodeficiency. Species-specific differentiation of Candida sp. is difficult in routine diagnosis. This identification can have a highly significant association in therapy and prophylaxis. This work has shown a new application of the terminal restriction fragment length polymorphism (t-RFLP) method in the molecular identification of six species of Candida, which are the most common causes of fungal infections. Specific for fungi homocitrate synthase gene was chosen as a molecular target for amplification. The use of three restriction enzymes, DraI, RsaI, and BglII, for amplicon digestion can generate species-specific fluorescence labeled DNA fragment profiles, which can be used to determine the diagnostic algorithm. The designed method can be a cost-efficient high-throughput molecular technique for the identification of six clinically important Candida species.

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.

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

NASA Astrophysics Data System (ADS)

Guesmi, Latifa; Menif, Mourad

2016-08-01

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

Molecular identification of Malassezia species isolated from dermatitis affections.

PubMed

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

2009-05-01

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

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.

Investigations on landmine detection by neutron-based techniques.

PubMed

Csikai, J; Dóczi, R; Király, B

2004-07-01

Principles and techniques of some neutron-based methods used to identify the antipersonnel landmines (APMs) are discussed. New results have been achieved in the field of neutron reflection, transmission, scattering and reaction techniques. Some conclusions are as follows: The neutron hand-held detector is suitable for the observation of anomaly caused by a DLM2-like sample in different soils with a scanning speed of 1m(2)/1.5 min; the reflection cross section of thermal neutrons rendered the determination of equivalent thickness of different soil components possible; a simple method was developed for the determination of the thermal neutron flux perturbation factor needed for multi-elemental analysis of bulky samples; unfolded spectra of elastically backscattered neutrons using broad-spectrum sources render the identification of APMs possible; the knowledge of leakage spectra of different source neutrons is indispensable for the determination of the differential and integrated reaction rates and through it the dimension of the interrogated volume; the precise determination of the C/O atom fraction requires the investigations on the angular distribution of the 6.13MeV gamma-ray emitted in the (16)O(n,n'gamma) reaction. These results, in addition to the identification of landmines, render the improvement of the non-intrusive neutron methods possible.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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

PubMed

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

2013-06-01

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

High-Throughput Block Optical DNA Sequence Identification.

PubMed

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

2018-01-01

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

NearSense - Advances Towards a Silicon-Based Terahertz Near-Field Imaging Sensor for Ex Vivo Breast Tumour Identification

NASA Astrophysics Data System (ADS)

Mavarani, Laven; Hillger, Philipp; Bücher, Thomas; Grzyb, Janusz; Pfeiffer, Ullrich R.; Cassar, Quentin; Al-Ibadi, Amel; Zimmer, Thomas; Guillet, Jean-Paul; Mounaix, Patrick; MacGrogan, Gaëtan

2018-03-01

Breast Cancer is one of the most frequently diagnosed cancer diseases worldwide, and the most common invasive tumour for women. As with all cancers, early detection plays a major role in reducing the mortality and morbidity rate. Currently, most breast cancers are detected due to clinical symptoms, or by screening mammography. The limitations of these techniques have resulted in research of alternative methods for imaging and detecting breast cancer. Apart from this, it is essential to define precise tumour margins during breast-conserving surgeries to reduce the re-excision rate. This study presents the advances in the development of a silicon-based THz sub-wavelength imager usable in life science applications, especially for tumour margin identification.

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.

Partial fingerprint identification algorithm based on the modified generalized Hough transform on mobile device

NASA Astrophysics Data System (ADS)

Qin, Jin; Tang, Siqi; Han, Congying; Guo, Tiande

2018-04-01

Partial fingerprint identification technology which is mainly used in device with small sensor area like cellphone, U disk and computer, has taken more attention in recent years with its unique advantages. However, owing to the lack of sufficient minutiae points, the conventional method do not perform well in the above situation. We propose a new fingerprint matching technique which utilizes ridges as features to deal with partial fingerprint images and combines the modified generalized Hough transform and scoring strategy based on machine learning. The algorithm can effectively meet the real-time and space-saving requirements of the resource constrained devices. Experiments on in-house database indicate that the proposed algorithm have an excellent performance.

A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

PubMed

Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

2017-08-15

Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

DNA barcoding: an efficient tool to overcome authentication challenges in the herbal market.

PubMed

Mishra, Priyanka; Kumar, Amit; Nagireddy, Akshitha; Mani, Daya N; Shukla, Ashutosh K; Tiwari, Rakesh; Sundaresan, Velusamy

2016-01-01

The past couple of decades have witnessed global resurgence of herbal-based health care. As a result, the trade of raw drugs has surged globally. Accurate and fast scientific identification of the plant(s) is the key to success for the herbal drug industry. The conventional approach is to engage an expert taxonomist, who uses a mix of traditional and modern techniques for precise plant identification. However, for bulk identification at industrial scale, the process is protracted and time-consuming. DNA barcoding, on the other hand, offers an alternative and feasible taxonomic tool box for rapid and robust species identification. For the success of DNA barcode, the barcode loci must have sufficient information to differentiate unambiguously between closely related plant species and discover new cryptic species. For herbal plant identification, matK, rbcL, trnH-psbA, ITS, trnL-F, 5S-rRNA and 18S-rRNA have been used as successful DNA barcodes. Emerging advances in DNA barcoding coupled with next-generation sequencing and high-resolution melting curve analysis have paved the way for successful species-level resolution recovered from finished herbal products. Further, development of multilocus strategy and its application has provided new vistas to the DNA barcode-based plant identification for herbal drug industry. For successful and acceptable identification of herbal ingredients and a holistic quality control of the drug, DNA barcoding needs to work harmoniously with other components of the systems biology approach. We suggest that for effectively resolving authentication challenges associated with the herbal market, DNA barcoding must be used in conjunction with metabolomics along with need-based transcriptomics and proteomics. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Microfluidic microscopy-assisted label-free approach for cancer screening: automated microfluidic cytology for cancer screening.

PubMed

Jagannadh, Veerendra Kalyan; Gopakumar, G; Subrahmanyam, Gorthi R K Sai; Gorthi, Sai Siva

2017-05-01

Each year, about 7-8 million deaths occur due to cancer around the world. More than half of the cancer-related deaths occur in the less-developed parts of the world. Cancer mortality rate can be reduced with early detection and subsequent treatment of the disease. In this paper, we introduce a microfluidic microscopy-based cost-effective and label-free approach for identification of cancerous cells. We outline a diagnostic framework for the same and detail an instrumentation layout. We have employed classical computer vision techniques such as 2D principal component analysis-based cell type representation followed by support vector machine-based classification. Analogous to criminal face recognition systems implemented with help of surveillance cameras, a signature-based approach for cancerous cell identification using microfluidic microscopy surveillance is demonstrated. Such a platform would facilitate affordable mass screening camps in the developing countries and therefore help decrease cancer mortality rate.

Evolution of transversus abdominis plane infiltration techniques for postsurgical analgesia following abdominal surgeries.

PubMed

Gadsden, Jeffrey; Ayad, Sabry; Gonzales, Jeffrey J; Mehta, Jaideep; Boublik, Jan; Hutchins, Jacob

2015-01-01

Transversus abdominis plane (TAP) infiltration is a regional anesthesia technique that has been demonstrated to be effective for management of postsurgical pain after abdominal surgery. There are several different clinical variations in the approaches used for achieving analgesia via TAP infiltration, and methods for identification of the TAP have evolved considerably since the landmark-guided technique was first described in 2001. There are many factors that impact the analgesic outcomes following TAP infiltration, and the various nuances of this technique have led to debate regarding procedural classification of TAP infiltration. Based on our current understanding of fascial and neuronal anatomy of the anterior abdominal wall, as well as available evidence from studies assessing local anesthetic spread and cutaneous sensory block following TAP infiltration, it is clear that TAP infiltration techniques are appropriately classified as field blocks. While the objective of peripheral nerve block and TAP infiltration are similar in that both approaches block sensory response in order to achieve analgesia, the technical components of the two procedures are different. Unlike peripheral nerve block, which involves identification or stimulation of a specific nerve or nerve plexus, followed by administration of a local anesthetic in close proximity, TAP infiltration involves administration and spread of local anesthetic within an anatomical plane of the surgical site.

Identification of beer-spoilage bacteria using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Wieme, Anneleen D; Spitaels, Freek; Aerts, Maarten; De Bruyne, Katrien; Van Landschoot, Anita; Vandamme, Peter

2014-08-18

Applicability of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for identification of beer-spoilage bacteria was examined. To achieve this, an extensive identification database was constructed comprising more than 4200 mass spectra, including biological and technical replicates derived from 273 acetic acid bacteria (AAB) and lactic acid bacteria (LAB), covering a total of 52 species, grown on at least three growth media. Sequence analysis of protein coding genes was used to verify aberrant MALDI-TOF MS identification results and confirmed the earlier misidentification of 34 AAB and LAB strains. In total, 348 isolates were collected from culture media inoculated with 14 spoiled beer and brewery samples. Peak-based numerical analysis of MALDI-TOF MS spectra allowed a straightforward species identification of 327 (94.0%) isolates. The remaining isolates clustered separately and were assigned through sequence analysis of protein coding genes either to species not known as beer-spoilage bacteria, and thus not present in the database, or to novel AAB species. An alternative, classifier-based approach for the identification of spoilage bacteria was evaluated by combining the identification results obtained through peak-based cluster analysis and sequence analysis of protein coding genes as a standard. In total, 263 out of 348 isolates (75.6%) were correctly identified at species level and 24 isolates (6.9%) were misidentified. In addition, the identification results of 50 isolates (14.4%) were considered unreliable, and 11 isolates (3.2%) could not be identified. The present study demonstrated that MALDI-TOF MS is well-suited for the rapid, high-throughput and accurate identification of bacteria isolated from spoiled beer and brewery samples, which makes the technique appropriate for routine microbial quality control in the brewing industry. Copyright © 2014 Elsevier B.V. All rights reserved.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Species identification refined by molecular scatology in a community of sympatric carnivores in Xinjiang, China

PubMed Central

LAGUARDIA, Alice; WANG, Jun; SHI, Fang-Lei; SHI, Kun; RIORDAN, Philip

2015-01-01

Many ecological studies and conservation management plans employ noninvasive scat sampling based on the assumption that species’ scats can be correctly identified in the field. However, in habitats with sympatric similarly sized carnivores, misidentification of scats is frequent and can lead to bias in research results. To address the scat identification dilemma, molecular scatology techniques have been developed to extract DNA from the donor cells present on the outer lining of the scat samples. A total of 100 samples were collected in the winter of 2009 and 2011 in Taxkorgan region of Xinjiang, China. DNA was extracted successfully from 88% of samples and genetic species identification showed that more than half the scats identified in the field as snow leopard (Panthera uncia) actually belonged to fox (Vulpes vulpes). Correlation between scat characteristics and species were investigated, showing that diameter and dry weight of the scat were significantly different between the species. However it was not possible to define a precise range of values for each species because of extensive overlap between the morphological values. This preliminary study confirms that identification of snow leopard feces in the field is misleading. Research that relies upon scat samples to assess distribution or diet of the snow leopard should therefore employ molecular scatology techniques. These methods are financially accessible and employ relatively simple laboratory procedures that can give an indisputable response to species identification from scats. PMID:25855225

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

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

PubMed

Khadka, Grishma; Hwang, Suk-Seung

2017-01-01

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

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

NASA Technical Reports Server (NTRS)

Schkolnik, Gerard S.

1993-01-01

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

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

NASA Technical Reports Server (NTRS)

Schkolnik, Gerald S.

1993-01-01

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

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

PubMed Central

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

2011-01-01

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

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to bemore » the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.« less

Damage detection in composite panels based on mode-converted Lamb waves sensed using 3D laser scanning vibrometer

NASA Astrophysics Data System (ADS)

Pieczonka, Łukasz; Ambroziński, Łukasz; Staszewski, Wiesław J.; Barnoncel, David; Pérès, Patrick

2017-12-01

This paper introduces damage identification approach based on guided ultrasonic waves and 3D laser Doppler vibrometry. The method is based on the fact that the symmetric and antisymmetric Lamb wave modes differ in amplitude of the in-plane and out-of-plane vibrations. Moreover, the modes differ also in group velocities and normally they are well separated in time. For a given time window both modes can occur simultaneously only close to the wave source or to a defect that leads to mode conversion. By making the comparison between the in-plane and out-of-plane wave vector components the detection of mode conversion is possible, allowing for superior and reliable damage detection. Experimental verification of the proposed damage identification procedure is performed on fuel tank elements of Reusable Launch Vehicles designed for space exploration. Lamb waves are excited using low-profile, surface-bonded piezoceramic transducers and 3D scanning laser Doppler vibrometer is used to characterize the Lamb wave propagation field. The paper presents theoretical background of the proposed damage identification technique as well as experimental arrangements and results.

The Design and Development of Test Platform for Wheat Precision Seeding Based on Image Processing Techniques

NASA Astrophysics Data System (ADS)

Li, Qing; Lin, Haibo; Xiu, Yu-Feng; Wang, Ruixue; Yi, Chuijie

The test platform of wheat precision seeding based on image processing techniques is designed to develop the wheat precision seed metering device with high efficiency and precision. Using image processing techniques, this platform gathers images of seeds (wheat) on the conveyer belt which are falling from seed metering device. Then these data are processed and analyzed to calculate the qualified rate, reseeding rate and leakage sowing rate, etc. This paper introduces the whole structure, design parameters of the platform and hardware & software of the image acquisition system were introduced, as well as the method of seed identification and seed-space measurement using image's threshold and counting the seed's center. By analyzing the experimental result, the measurement error is less than ± 1mm.

Automated designation of tie-points for image-to-image coregistration.

Treesearch

R.E. Kennedy; W.B. Cohen

2003-01-01

Image-to-image registration requires identification of common points in both images (image tie-points: ITPs). Here we describe software implementing an automated, area-based technique for identifying ITPs. The ITP software was designed to follow two strategies: ( I ) capitalize on human knowledge and pattern recognition strengths, and (2) favour robustness in many...

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Recording and cataloging hazards information, revision A

NASA Technical Reports Server (NTRS)

Stein, R. J.

1974-01-01

A data collection process is described for the purpose of discerning causation factors of accidents, and the establishment of boundaries or controls aimed at mitigating and eliminating accidents. A procedure is proposed that suggests a discipline approach to hazard identification based on energy interrelationships together with an integrated control technique which takes the form of checklists.

Screening and rapid identification of Campylobacter spp. DNA by FlaA PCR based method on chicken and human fecal samples in Egypt

USDA-ARS?s Scientific Manuscript database

Campylobacter is a foodborne pathogen which has a potential public health concern worldwide. Due to discriminatory problems encountered by conventional isolation of Campylobacter spp. and its genetic similarities, rapid molecular techniques for its genetic characterization are useful. In this study,...

Identification of Multiple Nonreturner Profiles to Inform the Development of Targeted College Retention Interventions

ERIC Educational Resources Information Center

Mattern, Krista D.; Marini, Jessica P.; Shaw, Emily J.

2015-01-01

Throughout the college retention literature, there is a recurring theme that students leave college for a variety of reasons making retention a difficult phenomenon to model. In the current study, cluster analysis techniques were employed to investigate whether multiple empirically based profiles of nonreturning students existed to more fully…

Estimating a Meaningful Point of Change: A Comparison of Exploratory Techniques Based on Nonparametric Regression

ERIC Educational Resources Information Center

Klotsche, Jens; Gloster, Andrew T.

2012-01-01

Longitudinal studies are increasingly common in psychological research. Characterized by repeated measurements, longitudinal designs aim to observe phenomena that change over time. One important question involves identification of the exact point in time when the observed phenomena begin to meaningfully change above and beyond baseline…

pH fractionation and identification of proteins: comparing column isoelectric focusing vs liquid based focusing techniques

USDA-ARS?s Scientific Manuscript database

In order to understand how bacteria react and adapt to changes in the environment, it is necessary to identify the proteins the bacteria produces under different environmental conditions. However, the proteomes of even simple organisms like bacteria can contain a significant number of proteins, mak...

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Efficacy of the FilmArray blood culture identification panel for direct molecular diagnosis of infectious diseases from samples other than blood.

PubMed

Micó, Miquel; Navarro, Ferran; de Miniac, Daniela; González, Yésica; Brell, Albert; López, Cristina; Sánchez-Reus, Ferran; Mirelis, Beatriz; Coll, Pere

2015-12-01

Molecular-based techniques reduce the delay in diagnosing infectious diseases and therefore contribute to better patient outcomes. We assessed the FilmArray blood culture identification (BCID) panel (Biofire Diagnostics/bioMérieux) directly on clinical specimens other than blood: cerebrospinal, joint, pleural and ascitic fluids, bronchoscopy samples and abscesses. We compared the results from 88 samples obtained by culture-based techniques. The percentage of agreement between the two methods was 75 % with a Cohen κ value of 0.51. Global sensitivity and specificity using the FilmArray BCID panel were 71 and 97 %, respectively. Sensitivity was poorer in samples with a low bacterial load, such as ascitic and pleural fluids (25 %), whereas the sensitivity for abscess samples was high (89 %). These findings suggest that the FilmArray BCID panel could be useful to perform microbiological diagnosis directly from samples other than positive blood cultures, as it offers acceptable sensitivity and moderate agreement with conventional microbiological methods. Nevertheless, cost-benefit studies should be performed before introducing this method into algorithms for microbiological diagnostics.

Near-infrared surface-enhanced-Raman-scattering (SERS) mediated identification of single optically trapped, bacterial spores

NASA Astrophysics Data System (ADS)

Alexander, Troy A.; Gillespie, James B.; Pellegrino, Paul M.; Fell, Nicholas F., Jr.; Wood, Gary L.; Salamo, Gregory J.

2003-03-01

A novel methodology has been developed for the investigation of bacterial spores. Specifically, this method has been used to probe the spore coat composition of several Bacillus species. This technique may be useful in many applications; most notably, development of novel detection schemes toward potentially harmful biological agents. This method would also be useful as an ancillary environmental monitoring system where sterility is of importance (i.e., food preparation areas as well as invasive and minimally invasive medical applications). This unique detection scheme is based on the near-infrared (NIR) Surface-Enhanced-Raman-Scattering (SERS) from single, optically trapped, bacterial spores. The SERS spectra of several bacterial spores in aqueous media have been measured using SERS substrates based on 60-nm diameter gold colloids bound to 3-Aminopropyltriethoxysilane derivatized glass. The light from a 785-nm laser diode was used to capture/manipulate as well as simultaneously excite the SERS of an individual bacterial spore. The collected SERS spectra were examined for uniqueness and the applicability of this technique for the species identification of bacterial spores.

Use of an ion mobility spectrometer for detecting uranium compounds

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

McLain, Derek R.; Steeb, Jennifer L.; Smith, Nicholas A.

The safeguards community currently lacks a method to rapidly determine the chemical form of radioactive and non-radioactive compounds in real time during inspection activities. Chemical speciation identification can provide important information on both the types of materials that are collected during environmental sampling and can inform inspectors as to where to focus efforts during inspections or complementary access visits. Ion Mobility Spectrometry (IMS) is an established field technique for the detection of explosives, narcotics, and other organic compounds. More recently, electrospray ionization (ESI) has been used to introduce inorganic compounds to IMS instruments for analysis. These techniques have shown themore » ability to supply chemical information about the compounds being analyzed. Although these laboratory based instruments use a liquid-based injection system, there is evidence in the literature of unaltered and intact pharmaceutical tablets being volatilized and ionized in open atmosphere using heat and a Ni-63 source. Lastly, this work determined that a commercial-off-the-shelf (COTS) IMS could be used for the identification of solid uranium compounds directly after sampling using a COTS sample swipe.« less

Indocyanine green fluorescence imaging in the surgical management of liver cancers: current facts and future implications.

PubMed

Lim, C; Vibert, E; Azoulay, D; Salloum, C; Ishizawa, T; Yoshioka, R; Mise, Y; Sakamoto, Y; Aoki, T; Sugawara, Y; Hasegawa, K; Kokudo, N

2014-04-01

Imaging detection of liver cancers and identification of the bile ducts during surgery, based on the fluorescence properties of indocyanine green, has recently been developed in liver surgery. The principle of this imaging technique relies on the intravenous administration of indocyanine green before surgery and the illumination of the surface of the liver by an infrared camera that simultaneously induces and collects the fluorescence. Detection by fluorescence is based on the contrast between the (fluorescent) tumoral or peri-tumoral tissues and the healthy (non-fluorescent) liver. Results suggest that indocyanine green fluorescence imaging is capable of identification of new liver cancers and enables the characterization of known hepatic lesions in real time during liver resection. The purpose of this paper is to present the fundamental principles of fluorescence imaging detection, to describe successively the practical and technical aspects of its use and the appearance of hepatic lesions in fluorescence, and to expose the diagnostic and therapeutic perspectives of this innovative imaging technique in liver surgery. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Use of an ion mobility spectrometer for detecting uranium compounds

DOE PAGES

McLain, Derek R.; Steeb, Jennifer L.; Smith, Nicholas A.

2018-03-09

The safeguards community currently lacks a method to rapidly determine the chemical form of radioactive and non-radioactive compounds in real time during inspection activities. Chemical speciation identification can provide important information on both the types of materials that are collected during environmental sampling and can inform inspectors as to where to focus efforts during inspections or complementary access visits. Ion Mobility Spectrometry (IMS) is an established field technique for the detection of explosives, narcotics, and other organic compounds. More recently, electrospray ionization (ESI) has been used to introduce inorganic compounds to IMS instruments for analysis. These techniques have shown themore » ability to supply chemical information about the compounds being analyzed. Although these laboratory based instruments use a liquid-based injection system, there is evidence in the literature of unaltered and intact pharmaceutical tablets being volatilized and ionized in open atmosphere using heat and a Ni-63 source. Lastly, this work determined that a commercial-off-the-shelf (COTS) IMS could be used for the identification of solid uranium compounds directly after sampling using a COTS sample swipe.« 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.

Quantitative Index and Abnormal Alarm Strategy Using Sensor-Dependent Vibration Data for Blade Crack Identification in Centrifugal Booster Fans

PubMed Central

Chen, Jinglong; Sun, Hailiang; Wang, Shuai; He, Zhengjia

2016-01-01

Centrifugal booster fans are important equipment used to recover blast furnace gas (BFG) for generating electricity, but blade crack faults (BCFs) in centrifugal booster fans can lead to unscheduled breakdowns and potentially serious accidents, so in this work quantitative fault identification and an abnormal alarm strategy based on acquired historical sensor-dependent vibration data is proposed for implementing condition-based maintenance for this type of equipment. Firstly, three group dependent sensors are installed to acquire running condition data. Then a discrete spectrum interpolation method and short time Fourier transform (STFT) are applied to preliminarily identify the running data in the sensor-dependent vibration data. As a result a quantitative identification and abnormal alarm strategy based on compound indexes including the largest Lyapunov exponent and relative energy ratio at the second harmonic frequency component is proposed. Then for validation the proposed blade crack quantitative identification and abnormality alarm strategy is applied to analyze acquired experimental data for centrifugal booster fans and it has successfully identified incipient blade crack faults. In addition, the related mathematical modelling work is also introduced to investigate the effects of mistuning and cracks on the vibration features of centrifugal impellers and to explore effective techniques for crack detection. PMID:27171083

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Different Sarcocystis spp. are present in bovine eosinophilic myositis.

PubMed

Vangeel, Lieve; Houf, Kurt; Geldhof, Peter; De Preter, Katleen; Vercruysse, Jozef; Ducatelle, Richard; Chiers, Koen

2013-11-08

It has been suggested that Sarcocystis species are associated with bovine eosinophilic myositis (BEM). To date, parasite identification in this myopathy has been based on morphological techniques. The aim of the present study was to use molecular techniques to identify Sarcocystis species inside lesions of BEM. Histologically, BEM lesions of 97 condemned carcasses were examined for the presence of Sarcocystis species. Intralesional and extralesional cysts were collected using laser capture microdissection and the species was determined with a PCR-based technique based on 18S rDNA. Intralesional sarcocysts or remnants were found in BEM lesions in 28% of the carcasses. The majority (82%) of intralesional Sarcocystis species were found to be S. hominis. However S. cruzi and S. hirsuta were also found, as well as an unidentified species. It can be concluded that Sarcocystis species present in lesions of BEM are not restricted to one species. Copyright © 2013 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

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

Comparative study of performance of neutral axis tracking based damage detection

NASA Astrophysics Data System (ADS)

Soman, R.; Malinowski, P.; Ostachowicz, W.

2015-07-01

This paper presents a comparative study of a novel SHM technique for damage isolation. The performance of the Neutral Axis (NA) tracking based damage detection strategy is compared to other popularly used vibration based damage detection methods viz. ECOMAC, Mode Shape Curvature Method and Strain Flexibility Index Method. The sensitivity of the novel method is compared under changing ambient temperature conditions and in the presence of measurement noise. Finite Element Analysis (FEA) of the DTU 10 MW Wind Turbine was conducted to compare the local damage identification capability of each method and the results are presented. Under the conditions examined, the proposed method was found to be robust to ambient condition changes and measurement noise. The damage identification in some is either at par with the methods mentioned in the literature or better under the investigated damage scenarios.

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 %.

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.

Analysis of pigments in polychromes by use of laser induced breakdown spectroscopy and Raman microscopy

NASA Astrophysics Data System (ADS)

Castillejo, M.; Martín, M.; Silva, D.; Stratoudaki, T.; Anglos, D.; Burgio, L.; Clark, R. J. H.

2000-09-01

Two laser-based analytical techniques, Laser Induced Breakdown Spectroscopy (LIBS) and Raman microscopy, have been used for the identification of pigments on a polychrome from the Rococo period. Detailed spectral data are presented from analyses performed on a fragment of a gilded altarpiece from the church of Escatrón, Zaragoza, Spain. LIBS measurements yielded elemental analytical data which suggest the presence of certain pigments and, in addition, provide information on the stratigraphy of the paint layers. Identification of most pigments and of the materials used in the preparation layer was performed by Raman microscopy.

Large protein as a potential target for use in rabies diagnostics.

PubMed

Santos Katz, I S; Dias, M H; Lima, I F; Chaves, L B; Ribeiro, O G; Scheffer, K C; Iwai, L K

Rabies is a zoonotic viral disease that remains a serious threat to public health worldwide. The rabies lyssavirus (RABV) genome encodes five structural proteins, multifunctional and significant for pathogenicity. The large protein (L) presents well-conserved genomic regions, which may be a good alternative to generate informative datasets for development of new methods for rabies diagnosis. This paper describes the development of a technique for the identification of L protein in several RABV strains from different hosts, demonstrating that MS-based proteomics is a potential method for antigen identification and a good alternative for rabies diagnosis.

Identification of cracks in thick beams with a cracked beam element model

NASA Astrophysics Data System (ADS)

Hou, Chuanchuan; Lu, Yong

2016-12-01

The effect of a crack on the vibration of a beam is a classical problem, and various models have been proposed, ranging from the basic stiffness reduction method to the more sophisticated model involving formulation based on the additional flexibility due to a crack. However, in the damage identification or finite element model updating applications, it is still common practice to employ a simple stiffness reduction factor to represent a crack in the identification process, whereas the use of a more realistic crack model is rather limited. In this paper, the issues with the simple stiffness reduction method, particularly concerning thick beams, are highlighted along with a review of several other crack models. A robust finite element model updating procedure is then presented for the detection of cracks in beams. The description of the crack parameters is based on the cracked beam flexibility formulated by means of the fracture mechanics, and it takes into consideration of shear deformation and coupling between translational and longitudinal vibrations, and thus is particularly suitable for thick beams. The identification procedure employs a global searching technique using Genetic Algorithms, and there is no restriction on the location, severity and the number of cracks to be identified. The procedure is verified to yield satisfactory identification for practically any configurations of cracks in a beam.

An overview of the essential differences and similarities of system identification techniques

NASA Technical Reports Server (NTRS)

Mehra, Raman K.

1991-01-01

Information is given in the form of outlines, graphs, tables and charts. Topics include system identification, Bayesian statistical decision theory, Maximum Likelihood Estimation, identification methods, structural mode identification using a stochastic realization algorithm, and identification results regarding membrane simulations and X-29 flutter flight test data.

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

NASA Astrophysics Data System (ADS)

Kenderi, Gábor; Fidlin, Alexander

2014-12-01

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

Identification of different species of Bacillus isolated from Nisargruna Biogas Plant by FTIR, UV-Vis and NIR spectroscopy

NASA Astrophysics Data System (ADS)

Ghosh, S. B.; Bhattacharya, K.; Nayak, S.; Mukherjee, P.; Salaskar, D.; Kale, S. P.

2015-09-01

Definitive identification of microorganisms, including pathogenic and non-pathogenic bacteria, is extremely important for a wide variety of applications including food safety, environmental studies, bio-terrorism threats, microbial forensics, criminal investigations and above all disease diagnosis. Although extremely powerful techniques such as those based on PCR and microarrays exist, they require sophisticated laboratory facilities along with elaborate sample preparation by trained researchers. Among different spectroscopic techniques, FTIR was used in the 1980s and 90s for bacterial identification. In the present study five species of Bacillus were isolated from the aerobic predigester chamber of Nisargruna Biogas Plant (NBP) and were identified to the species level by biochemical and molecular biological (16S ribosomal DNA sequence) methods. Those organisms were further checked by solid state spectroscopic absorbance measurements using a wide range of electromagnetic radiation (wavelength 200 nm to 25,000 nm) encompassing UV, visible, near Infrared and Infrared regions. UV-Vis and NIR spectroscopy was performed on dried bacterial cell suspension on silicon wafer in specular mode while FTIR was performed on KBr pellets containing the bacterial cells. Consistent and reproducible species specific spectra were obtained and sensitivity up to a level of 1000 cells was observed in FTIR with a DTGS detector. This clearly shows the potential of solid state spectroscopic techniques for simple, easy to implement, reliable and sensitive detection of bacteria from environmental samples.

Identification of species and geographical strains of Sitophilus oryzae and Sitophilus zeamais using the visible/near-infrared hyperspectral imaging technique.

PubMed

Cao, Yang; Zhang, Chaojie; Chen, Quansheng; Li, Yanyu; Qi, Shuai; Tian, Lin; Ren, YongLin

2015-08-01

Identifying stored-product insects is essential for granary management. Automated, computer-based classification methods are rapidly developing in many areas. A hyperspectral imaging technique could potentially be developed to identify stored-product insect species and geographical strains. This study tested and adapted the technique using four geographical strains of each of two insect species, the rice weevil and maize weevil, to collect and analyse the resultant hyperspectral data. Three characteristic images that corresponded to the dominant wavelengths, 505, 659 and 955 nm, were selected by multivariate image analysis. Each image was processed, and 22 morphological and textural features from regions of interest were extracted as the inputs for an identification model. We found the backpropagation neural network model to be the superior method for distinguishing between the insect species and geographical strains. The overall recognition rates of the classification model for insect species were 100 and 98.13% for the calibration and prediction sets respectively, while the rates of the model for geographical strains were 94.17 and 86.88% respectively. This study has demonstrated that hyperspectral imaging, together with the appropriate recognition method, could provide a potential instrument for identifying insects and could become a useful tool for identification of Sitophilus oryzae and Sitophilus zeamais to aid in the management of stored-product insects. © 2014 Society of Chemical Industry.

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

PubMed

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

2017-03-01

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

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Guillaume, Alexandre

2009-01-01

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

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.

Diagnosis of group A streptococcal infections directly from throat secretions.

PubMed Central

Edwards, E A; Phillips, I A; Suiter, W C

1982-01-01

The diagnosis of group A streptococcal disease still relies on isolation of group A streptococcal strains on sheep blood agar followed by presumptive identification based on bacitracin sensitivity or the results of the more precise serogrouping methods such as the Lancefield precipitin test. A technique that would permit rapid identification of streptococcal infections directly from throat secretions would allow immediate appropriate antimicrobial therapy for the management of streptococcal infections to be started. We have been able to identify soluble group A antigen directly from throat secretions by using a latex agglutination test. In a clinical trial in which latex (Streptex group A) and conventional culturing techniques were used, 53 throat secretion cultures were tested: 26 were positive by both procedures, 5 were positive by culture only, 3 were positive by the latex agglutination test only, and 19 were negative by both tests. Images PMID:7042747

Nocardia transvalensis Disseminated Infection in an Immunocompromised Patient with Idiopathic Thrombocytopenic Purpura

PubMed Central

García-Méndez, Jorge; Carrillo-Casas, Erika M.; Rangel-Cordero, Andrea; Leyva-Leyva, Margarita; Xicohtencatl-Cortes, Juan; Arenas, Roberto; Hernández-Castro, Rigoberto

2016-01-01

Nocardia transvalensis complex includes a wide range of microorganisms with specific antimicrobial resistance patterns. N. transvalensis is an unusual Nocardia species. However, it must be differentiated due to its natural resistance to aminoglycosides while other Nocardia species are susceptible. The present report describes a Nocardia species involved in an uncommon clinical case of a patient with idiopathic thrombocytopenic purpura and pulmonary nocardiosis. Microbiological and molecular techniques based on the sequencing of the 16S rRNA gene allowed diagnosis of Nocardia transvalensis sensu stricto. The successful treatment was based on trimethoprim-sulfamethoxazole and other drugs. We conclude that molecular identification of Nocardia species is a valuable technique to guide good treatment and prognosis and recommend its use for daily bases diagnosis. PMID:27313917

Nocardia transvalensis Disseminated Infection in an Immunocompromised Patient with Idiopathic Thrombocytopenic Purpura.

PubMed

García-Méndez, Jorge; Carrillo-Casas, Erika M; Rangel-Cordero, Andrea; Leyva-Leyva, Margarita; Xicohtencatl-Cortes, Juan; Arenas, Roberto; Hernández-Castro, Rigoberto

2016-01-01

Nocardia transvalensis complex includes a wide range of microorganisms with specific antimicrobial resistance patterns. N. transvalensis is an unusual Nocardia species. However, it must be differentiated due to its natural resistance to aminoglycosides while other Nocardia species are susceptible. The present report describes a Nocardia species involved in an uncommon clinical case of a patient with idiopathic thrombocytopenic purpura and pulmonary nocardiosis. Microbiological and molecular techniques based on the sequencing of the 16S rRNA gene allowed diagnosis of Nocardia transvalensis sensu stricto. The successful treatment was based on trimethoprim-sulfamethoxazole and other drugs. We conclude that molecular identification of Nocardia species is a valuable technique to guide good treatment and prognosis and recommend its use for daily bases diagnosis.

High-accuracy user identification using EEG biometrics.

PubMed

Koike-Akino, Toshiaki; Mahajan, Ruhi; Marks, Tim K; Ye Wang; Watanabe, Shinji; Tuzel, Oncel; Orlik, Philip

2016-08-01

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.

Characterization of the Hydrocarbon Potential and Non-Potential Zones Using Wavelet-Based Fractal Analysis

NASA Astrophysics Data System (ADS)

Mukherjee, Bappa; Roy, P. N. S.

The identification of prospective and dry zone is of major importance from well log data. Truthfulness in the identification of potential zone is a very crucial issue in hydrocarbon exploration. In this line, the problem has received considerable attention and many conventional techniques have been proposed. The purpose of this study is to recognize the hydrocarbon and non-hydrocarbon bearing portion within a reservoir by using the non-conventional technique. The wavelet based fractal analysis (WBFA) has been applied on the wire-line log data in order to obtain the pre-defined hydrocarbon (HC) and non-hydrocarbon (NHC) zones by their self-affine signal nature is demonstrated in this paper. The feasibility of the proposed technique is tested with the help of most commonly used logs, like self-potential, gamma ray, resistivity and porosity log responses. These logs are obtained from the industry to make out several HC and NHC zones of all wells in the study region belonging to the upper Assam basin. The results obtained in this study for a particular log response, where in the case of HC bearing zones, it is found that they are mainly situated in a variety of sandstones lithology which leads to the higher Hurst exponent. Further, the NHC zones found to be analogous to lithology with higher shale content having lower Hurst exponent. The above proposed technique can overcome the chance of miss interpretation in conventional reservoir characterization.

Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals.

PubMed

Sidek, Khairul; Khali, Ibrahim

2012-01-01

In this paper, a person identification mechanism implemented with Cardioid based graph using electrocardiogram (ECG) is presented. Cardioid based graph has given a reasonably good classification accuracy in terms of differentiating between individuals. However, the current feature extraction method using Euclidean distance could be further improved by using Mahalanobis distance measurement producing extracted coefficients which takes into account the correlations of the data set. Identification is then done by applying these extracted features to Radial Basis Function Network. A total of 30 ECG data from MITBIH Normal Sinus Rhythm database (NSRDB) and MITBIH Arrhythmia database (MITDB) were used for development and evaluation purposes. Our experimentation results suggest that the proposed feature extraction method has significantly increased the classification performance of subjects in both databases with accuracy from 97.50% to 99.80% in NSRDB and 96.50% to 99.40% in MITDB. High sensitivity, specificity and positive predictive value of 99.17%, 99.91% and 99.23% for NSRDB and 99.30%, 99.90% and 99.40% for MITDB also validates the proposed method. This result also indicates that the right feature extraction technique plays a vital role in determining the persistency of the classification accuracy for Cardioid based person identification mechanism.

A new surface fractal dimension for displacement mode shape-based damage identification of plate-type structures

NASA Astrophysics Data System (ADS)

Shi, Binkai; Qiao, Pizhong

2018-03-01

Vibration-based nondestructive testing is an area of growing interest and worthy of exploring new and innovative approaches. The displacement mode shape is often chosen to identify damage due to its local detailed characteristic and less sensitivity to surrounding noise. Requirement for baseline mode shape in most vibration-based damage identification limits application of such a strategy. In this study, a new surface fractal dimension called edge perimeter dimension (EPD) is formulated, from which an EPD-based window dimension locus (EPD-WDL) algorithm for irregularity or damage identification of plate-type structures is established. An analytical notch-type damage model of simply-supported plates is proposed to evaluate notch effect on plate vibration performance; while a sub-domain of notch cases with less effect is selected to investigate robustness of the proposed damage identification algorithm. Then, fundamental aspects of EPD-WDL algorithm in term of notch localization, notch quantification, and noise immunity are assessed. A mathematical solution called isomorphism is implemented to remove false peaks caused by inflexions of mode shapes when applying the EPD-WDL algorithm to higher mode shapes. The effectiveness and practicability of the EPD-WDL algorithm are demonstrated by an experimental procedure on damage identification of an artificially-induced notched aluminum cantilever plate using a measurement system of piezoelectric lead-zirconate (PZT) actuator and scanning laser Doppler vibrometer (SLDV). As demonstrated in both the analytical and experimental evaluations, the new surface fractal dimension technique developed is capable of effectively identifying damage in plate-type structures.

Repositioning the substrate activity screening (SAS) approach as a fragment-based method for identification of weak binders.

PubMed

Gladysz, Rafaela; Cleenewerck, Matthias; Joossens, Jurgen; Lambeir, Anne-Marie; Augustyns, Koen; Van der Veken, Pieter

2014-10-13

Fragment-based drug discovery (FBDD) has evolved into an established approach for "hit" identification. Typically, most applications of FBDD depend on specialised cost- and time-intensive biophysical techniques. The substrate activity screening (SAS) approach has been proposed as a relatively cheap and straightforward alternative for identification of fragments for enzyme inhibitors. We have investigated SAS for the discovery of inhibitors of oncology target urokinase (uPA). Although our results support the key hypotheses of SAS, we also encountered a number of unreported limitations. In response, we propose an efficient modified methodology: "MSAS" (modified substrate activity screening). MSAS circumvents the limitations of SAS and broadens its scope by providing additional fragments and more coherent SAR data. As well as presenting and validating MSAS, this study expands existing SAR knowledge for the S1 pocket of uPA and reports new reversible and irreversible uPA inhibitor scaffolds. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Experiments in automatic word class and word sense identification for information retrieval

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

Gauch, S.; Futrelle, R.P.

Automatic identification of related words and automatic detection of word senses are two long-standing goals of researchers in natural language processing. Word class information and word sense identification may enhance the performance of information retrieval system4ms. Large online corpora and increased computational capabilities make new techniques based on corpus linguisitics feasible. Corpus-based analysis is especially needed for corpora from specialized fields for which no electronic dictionaries or thesauri exist. The methods described here use a combination of mutual information and word context to establish word similarities. Then, unsupervised classification is done using clustering in the word space, identifying word classesmore » without pretagging. We also describe an extension of the method to handle the difficult problems of disambiguation and of determining part-of-speech and semantic information for low-frequency words. The method is powerful enough to produce high-quality results on a small corpus of 200,000 words from abstracts in a field of molecular biology.« less

Recent patents for detecting the species of origin in animal feedstuff, and raw and processed meat products.

PubMed

Rogberg-Muñoz, Andrés; Posik, Diego M; Rípoli, María V; Falomir Lockhart, Agustín H; Peral-García, Pilar; Giovambattista, Guillermo

2013-04-01

The value of the traceability and labeling of food is attributable to two main aspects: health safety and/or product or process certification. The identification of the species related to meat production is still a major concern for economic, religious and health reasons. Many approaches and technologies have been used for species identification in animal feedstuff and food. The early methods for meat products identification include physical, anatomical, histological and chemical. Since 1970, a variety of methods were developed, these include electrophoresis (i.e. isoelectrofocusing), chromatography (i.e. HPLC), immunological techniques (i.e. ELISA), Nuclear Magnetic Resonance, Mass Spectrometry and PCR (DNA and RNA based methods). The recent patents on species detection in animal feedstuffs, raw meat and meat processed products, listed in this work, are mainly based on monoclonal antibodies and PCR, especially RT-PCR. The new developments under research are looking for more sensible, specific, less time consuming and quantitatively detection methods, which can be used in highly processed or heated treated meat food.

Review of Detection of Brucella sp. by Polymerase Chain Reaction

PubMed Central

Yu, Wei Ling; Nielsen, Klaus

2010-01-01

Here we present a review of most of the currently used polymerase chain reaction (PCR)-based methods for identification of Brucella bacteria in biological samples. We focused in particular on methods using single-pair primers, multiplex primers, real-time PCRs, PCRs for marine Brucella, and PCRs for molecular biotyping. These methods are becoming very important tools for the identification of Brucella, at the species level and recently also at the biovar level. These techniques require minimum biological containment and can provide results in a very short time. In addition, genetic fingerprinting of isolates aid in epidemiological studies of the disease and its control. PCR-based methods are more useful and practical than conventional methods used to identify Brucella spp., and new methods for Brucella spp identification and typing are still being developed. However, the sensitivity, specificity, and issues of quality control and quality assurance using these methods must be fully validated on clinical samples before PCR can be used in routine laboratory testing for brucellosis. PMID:20718083

Optimum electrode configuration selection for electrical resistance change based damage detection in composites using an effective independence measure

NASA Astrophysics Data System (ADS)

Escalona, Luis; Díaz-Montiel, Paulina; Venkataraman, Satchi

2016-04-01

Laminated carbon fiber reinforced polymer (CFRP) composite materials are increasingly used in aerospace structures due to their superior mechanical properties and reduced weight. Assessing the health and integrity of these structures requires non-destructive evaluation (NDE) techniques to detect and measure interlaminar delamination and intralaminar matrix cracking damage. The electrical resistance change (ERC) based NDE technique uses the inherent changes in conductive properties of the composite to characterize internal damage. Several works that have explored the ERC technique have been limited to thin cross-ply laminates with simple linear or circular electrode arrangements. This paper investigates a method of optimum selection of electrode configurations for delamination detection in thick cross-ply laminates using ERC. Inverse identification of damage requires numerical optimization of the measured response with a model predicted response. Here, the electrical voltage field in the CFRP composite laminate is calculated using finite element analysis (FEA) models for different specified delamination size and locations, and location of ground and current electrodes. Reducing the number of sensor locations and measurements is needed to reduce hardware requirements, and computational effort needed for inverse identification. This paper explores the use of effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations of selecting a pair of electrodes among the n electrodes. To enable use of EI to ERC required, it is proposed in this research a singular value decomposition SVD to obtain a spectral representation of the resistance measurements in the laminate. The effectiveness of EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set of resistance measurements and the reduced set of measurements. The investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERC based damage detection.

Program risk analysis handbook

NASA Technical Reports Server (NTRS)

Batson, R. G.

1987-01-01

NASA regulations specify that formal risk analysis be performed on a program at each of several milestones. Program risk analysis is discussed as a systems analysis approach, an iterative process (identification, assessment, management), and a collection of techniques. These techniques, which range from extremely simple to complex network-based simulation, are described in this handbook in order to provide both analyst and manager with a guide for selection of the most appropriate technique. All program risk assessment techniques are shown to be based on elicitation and encoding of subjective probability estimates from the various area experts on a program. Techniques to encode the five most common distribution types are given. Then, a total of twelve distinct approaches to risk assessment are given. Steps involved, good and bad points, time involved, and degree of computer support needed are listed. Why risk analysis should be used by all NASA program managers is discussed. Tools available at NASA-MSFC are identified, along with commercially available software. Bibliography (150 entries) and a program risk analysis check-list are provided.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

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

Application Of The Wigner-Ville Distribution To The Identification Of Machine Noise

NASA Astrophysics Data System (ADS)

Boashash, Boualem; O'Shea, Peter

1988-02-01

The theory of signal detection using the Wigner-Ville Distribution (WVD) and the Cross Wagner-Ville Distribution (XWVD) is reviewed, and applied to the signaturing, detection, and identification of some specific machine sounds - the individual cylinder firings of a marine engine. For this task, a 4 step procedure has been devised. The Autocorrelation Function (ACF) is first employed for ascertaining the number of engine cylinders and the firing rate of the engine. Cross-correlation techniques are then used for detecting the occurrence of cylinder firing events. This is followed by the use WVD and XWVD based analyses to produce high resolution Time-Frequency signatures, and finally 2D correlations are employed for identification of the cylinders. The proposed methodology is applied to real data.

Full-field modal analysis during base motion excitation using high-speed 3D digital image correlation

NASA Astrophysics Data System (ADS)

Molina-Viedma, Ángel J.; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2017-10-01

In recent years, many efforts have been made to exploit full-field measurement optical techniques for modal identification. Three-dimensional digital image correlation using high-speed cameras has been extensively employed for this purpose. Modal identification algorithms are applied to process the frequency response functions (FRF), which relate the displacement response of the structure to the excitation force. However, one of the most common tests for modal analysis involves the base motion excitation of a structural element instead of force excitation. In this case, the relationship between response and excitation is typically based on displacements, which are known as transmissibility functions. In this study, a methodology for experimental modal analysis using high-speed 3D digital image correlation and base motion excitation tests is proposed. In particular, a cantilever beam was excited from its base with a random signal, using a clamped edge join. Full-field transmissibility functions were obtained through the beam and converted into FRF for proper identification, considering a single degree-of-freedom theoretical conversion. Subsequently, modal identification was performed using a circle-fit approach. The proposed methodology facilitates the management of the typically large amounts of data points involved in the DIC measurement during modal identification. Moreover, it was possible to determine the natural frequencies, damping ratios and full-field mode shapes without requiring any additional tests. Finally, the results were experimentally validated by comparing them with those obtained by employing traditional accelerometers, analytical models and finite element method analyses. The comparison was performed by using the quantitative indicator modal assurance criterion. The results showed a high level of correspondence, consolidating the proposed experimental methodology.

Thermal Skin fabrication technology

NASA Technical Reports Server (NTRS)

Milam, T. B.

1972-01-01

Advanced fabrication techniques applicable to Thermal Skin structures were investigated, including: (1) chemical machining; (2) braze bonding; (3) diffusion bonding; and (4) electron beam welding. Materials investigated were nickel and nickel alloys. Sample Thermal Skin panels were manufactured using the advanced fabrication techniques studied and were structurally tested. Results of the program included: (1) development of improved chemical machining processes for nickel and several nickel alloys; (2) identification of design geometry limits; (3) identification of diffusion bonding requirements; (4) development of a unique diffusion bonding tool; (5) identification of electron beam welding limits; and (6) identification of structural properties of Thermal Skin material.

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modelling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-10-01

Ground magnetic anomaly separation using the reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prospecting area in northwestern Iran. The geophysical survey resulting in the ground magnetic data was conducted for magnetic element exploration. Firstly, the RTP technique was applied to recognize underground magnetic anomalies. RTP anomalies were classified into different populations based on the current method. For this reason, drilling point area determination by the RTP technique was complicated for magnetic anomalies, which are in the center and north of the studied area. Next, the C-A method was applied to the RTP magnetic anomalies (RTP-MA) to demonstrate magnetic susceptibility concentrations. This identification was appropriate for increasing the resolution of the drilling point area determination and decreasing the drilling risk issue, due to the economic costs of underground prospecting. In this study, the results of C-A modelling on the RTP-MA are compared with 8 borehole data. The results show that there is a good correlation between anomalies derived via the C-A method and the log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentrations, based on multifractal modelling data analyses, between 63 533.1 and 66 296 nT. Drilling results showed appropriate magnetite thickness with grades greater than 20 % Fe. The total associated with anomalies containing andesite units hosts iron mineralization.

Demographic management in a federated healthcare environment.

PubMed

Román, I; Roa, L M; Reina-Tosina, J; Madinabeitia, G

2006-09-01

The purpose of this paper is to provide a further step toward the decentralization of identification and demographic information about persons by solving issues related to the integration of demographic agents in a federated healthcare environment. The aim is to identify a particular person in every system of a federation and to obtain a unified view of his/her demographic information stored in different locations. This work is based on semantic models and techniques, and pursues the reconciliation of several current standardization works including ITU-T's Open Distributed Processing, CEN's prEN 12967, OpenEHR's dual and reference models, CEN's General Purpose Information Components and CORBAmed's PID service. We propose a new paradigm for the management of person identification and demographic data, based on the development of an open architecture of specialized distributed components together with the incorporation of techniques for the efficient management of domain ontologies, in order to have a federated demographic service. This new service enhances previous correlation solutions sharing ideas with different standards and domains like semantic techniques and database systems. The federation philosophy enforces us to devise solutions to the semantic, functional and instance incompatibilities in our approach. Although this work is based on several models and standards, we have improved them by combining their contributions and developing a federated architecture that does not require the centralization of demographic information. The solution is thus a good approach to face integration problems and the applied methodology can be easily extended to other tasks involved in the healthcare organization.

Plasmonic improvement of microcavity biomedical sensor spectroscopic characteristics

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas; Ghadiri, Reza

2014-03-01

New opportunity to improve a sensetivity of a label-free biomolecule detection in sensing systems based on microcavity evanescent wave optical sensors has been recently found and is being under intensive development. Novel technique based on combination of optical resonance on microring structures with plasmon resonance. Recently developed tools based on neural network data processing can realize real-time identification of biological agents. So combining advantages of plasmon enhancing optical microcavity resonance with identification tools can give a new platform for ulta sensitive label-free biomedical sensor. Our developed technique used standard glass and polymer microspheres as sensetive elements. They are fixed in the solution flow by adhesive layer on the surface being in the field of evanescence wave. Sensitive layer have been treated by gold nanoparticel (GN) solution. Another technique used thin film gold layers deposited on the substrate below adhesive. The light from a tuneable diode laser is coupled into the microsphere through a prism and was sharply focussed on the single microsphere. Images were recorded by CMOS camera. Normalized by free spectral range resonance shift of whispering gallery mode (WGM) and a relative efficiency of their excitation were used as input data for biomolecule classification. Both biomolecules and NP injection was obtained caused WGM spectra modification. But after NP treatment spectral shift and intensity of WGM resonances in biomolecule solutions increased. WGM resonances in microspheres fixed on substrate with gold layer with optimized layer thickness in biomolecule solutions also had higher intensity and spectra modification then without gold layer.

Automated Identification and Shape Analysis of Chorus Elements in the Van Allen Radiation Belts

NASA Astrophysics Data System (ADS)

Sen Gupta, Ananya; Kletzing, Craig; Howk, Robin; Kurth, William; Matheny, Morgan

2017-12-01

An important goal of the Van Allen Probes mission is to understand wave-particle interaction by chorus emissions in terrestrial Van Allen radiation belts. To test models, statistical characterization of chorus properties, such as amplitude variation and sweep rates, is an important scientific goal. The Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite provides measurements of wave electric and magnetic fields as well as DC magnetic fields for the Van Allen Probes mission. However, manual inspection across terabytes of EMFISIS data is not feasible and as such introduces human confirmation bias. We present signal processing techniques for automated identification, shape analysis, and sweep rate characterization of high-amplitude whistler-mode chorus elements in the Van Allen radiation belts. Specifically, we develop signal processing techniques based on the radon transform that disambiguate chorus elements with a dominant sweep rate against hiss-like chorus. We present representative results validating our techniques and also provide statistical characterization of detected chorus elements across a case study of a 6 s epoch.

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Identification of unique repeated patterns, location of mutation in DNA finger printing using artificial intelligence technique.

PubMed

Mukunthan, B; Nagaveni, N

2014-01-01

In genetic engineering, conventional techniques and algorithms employed by forensic scientists to assist in identification of individuals on the basis of their respective DNA profiles involves more complex computational steps and mathematical formulae, also the identification of location of mutation in a genomic sequence in laboratories is still an exigent task. This novel approach provides ability to solve the problems that do not have an algorithmic solution and the available solutions are also too complex to be found. The perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

Techniques for air pollution source identification are reviewed, and some results obtained with them are evaluated. Described techniques include remote sensing from satellites and aircraft, on-site monitoring, and the use of injected tracers and pollutants themselves as tracers. The use of a large number of trace elements in ambient airborne particulate matter as a practical means of identifying sources is discussed in detail. Sampling and analysis techniques are described, and it is shown that elemental constituents can be related to specific source types such as those found in the earth's crust and those associated with specific industries. Source identification sytems are noted which utilize charged particle X-ray fluorescence analysis of original field data.

Rapid identification and source-tracking of Listeria monocytogenes using MALDI-TOF mass spectrometry.

PubMed

Jadhav, Snehal; Gulati, Vandana; Fox, Edward M; Karpe, Avinash; Beale, David J; Sevior, Danielle; Bhave, Mrinal; Palombo, Enzo A

2015-06-02

Listeria monocytogenes is an important foodborne pathogen responsible for the sometimes fatal disease listeriosis. Public health concerns and stringent regulations associated with the presence of this pathogen in food and food processing environments underline the need for rapid and reliable detection and subtyping techniques. In the current study, the application of matrix assisted laser desorption/ionisation-time-of-flight mass spectrometry (MALDI-TOF MS) as a single identification and source-tracking tool for a collection of L. monocytogenes isolates, obtained predominantly from dairy sources within Australia, was explored. The isolates were cultured on different growth media and analysed using MALDI-TOF MS at two incubation times (24 and 48 h). Whilst reliable genus-level identification was achieved from most media, identification at the species level was found to be dependent on culture conditions. Successful speciation was highest for isolates cultured on the chromogenic Agar Listeria Ottaviani Agosti agar (ALOA, 91% of isolates) and non-selective horse blood agar (HBA, 89%) for 24h. Chemometric statistical analysis of the MALDI-TOF MS data enabled source-tracking of L. monocytogenes isolates obtained from four different dairy sources. Strain-level discrimination was also observed to be influenced by culture conditions. In addition, t-test/analysis of variance (ANOVA) was used to identify potential biomarker peaks that differentiated the isolates according to their source of isolation. Source-tracking using MALDI-TOF MS was compared and correlated with the gold standard pulsed-field gel electrophoresis (PFGE) technique. The discriminatory index and the congruence between both techniques were compared using the Simpsons Diversity Index and adjusted Rand and Wallace coefficients. Overall, MALDI-TOF MS based source-tracking (using data obtained by culturing the isolates on HBA) and PFGE demonstrated good congruence with a Wallace coefficient of 0.71 and comparable discriminatory indices of 0.89 and 0.86, respectively. MALDI-TOF MS thus represents a rapid and cost-effective source-tracking technique for L. monocytogenes. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of body fluids for forensic purposes: from laboratory testing to non-destructive rapid confirmatory identification at a crime scene.

PubMed

Virkler, Kelly; Lednev, Igor K

2009-07-01

Body fluid traces recovered at crime scenes are among the most important types of evidence to forensic investigators. They contain valuable DNA evidence which can identify a suspect or victim as well as exonerate an innocent individual. The first step of identifying a particular body fluid is highly important since the nature of the fluid is itself very informative to the investigation, and the destructive nature of a screening test must be considered when only a small amount of material is available. The ability to characterize an unknown stain at the scene of the crime without having to wait for results from a laboratory is another very critical step in the development of forensic body fluid analysis. Driven by the importance for forensic applications, body fluid identification methods have been extensively developed in recent years. The systematic analysis of these new developments is vital for forensic investigators to be continuously educated on possible superior techniques. Significant advances in laser technology and the development of novel light detectors have dramatically improved spectroscopic methods for molecular characterization over the last decade. The application of this novel biospectroscopy for forensic purposes opens new and exciting opportunities for the development of on-field, non-destructive, confirmatory methods for body fluid identification at a crime scene. In addition, the biospectroscopy methods are universally applicable to all body fluids unlike the majority of current techniques which are valid for individual fluids only. This article analyzes the current methods being used to identify body fluid stains including blood, semen, saliva, vaginal fluid, urine, and sweat, and also focuses on new techniques that have been developed in the last 5-6 years. In addition, the potential of new biospectroscopic techniques based on Raman and fluorescence spectroscopy is evaluated for rapid, confirmatory, non-destructive identification of a body fluid at a crime scene.

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.

Not just fun and games: applications of virtual reality in the identification and rehabilitation of cognitive disorders of the elderly.

PubMed

Cherniack, E Paul

2011-01-01

To outline the evidence in the published medical literature suggesting the potential applications of virtual reality (VR) for the identification and rehabilitation of cognitive disorders of the elderly. Non-systematic literature review. VR, despite its more common usage by younger persons, is a potentially promising source of techniques useful in the identification and rehabilitation of cognitive disorders of the elderly. Systems employing VR can include desktop and head-mounted visual displays among other devices. Thus far, published studies have described VR-based applications in the identification and treatment of deficits in navigational skills in ambulation and driving. In addition, VR has been utilised to enhance the ability to perform activities of daily living in patients with dementia, stroke, and Parkinson's Disease. Such investigations have thus far been small, and unblinded. VR-based applications can potentially offer more versatile, comprehensive, and safer assessments of function. However, they also might be more expensive, complex and more difficult to use by elderly patients. Side effects of head-mounted visual displays include nausea and disorientation, but, have not been reported specifically in older subjects.

[Contribution of Leishmania identification using polymerase chain reaction--restriction fragment length polymerase for epidemiological studies of cutaneous leishmaniasis in Tunisia].

PubMed

Bousslimi, N; Ben Abda, I; Ben Mously, R; Siala, E; Harrat, Z; Zallagua, N; Bouratbine, A; Aoun, K

2014-02-01

Three forms of cutaneous leishmaniasis (CL) are endemic in Tunisia. The identification of the causative species is useful to complete epidemiological data and to manage the cases. The aim of this study is to assess PCR-RFLP technique in the identification of Leishmania species responsible of CL in Tunisia and to compare the results of this technique to those of isoenzyme analysis. Sixty-one CL lesions were sampled. Dermal samples were tested by culture on NNN medium and analyzed by PCR-RFLP assay targeting the ITS1 region of ribosomal DNA. Species identification was performed by both iso-enzymatic typing for positive cultures and analysis of restriction profiles after enzymatic digestion by HaeIII of the obtained amplicons. Thirty-eight (62%) samples were positive by culture. The iso-enzymatic typing of 32 isolates identified 3 L. infantum, 23 L. major MON-25 and 6 L. tropica MON-8. Sixty samples were positive by PCR. The PCR-RFLP digestion profiles of the 56 PCR products identified 12 L. infantum, 38 L. major and 6 L. tropica. The results of both techniques were concordant in the 32 strains identified by both techniques. Species identification correlated with the geographical distribution of CL forms endemic in Tunisia. Results of PCR-RFLP revealed highly concordant with those of isoenzyme electrophoresis. Thanks to its simplicity, rapidity and ability to be performed directly on biological samples, this technique appears as an interesting alternative for the identification of Leishmania strains responsible of CL in Tunisia. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Identification of superficial defects in reconstructed 3D objects using phase-shifting fringe projection

NASA Astrophysics Data System (ADS)

Madrigal, Carlos A.; Restrepo, Alejandro; Branch, John W.

2016-09-01

3D reconstruction of small objects is used in applications of surface analysis, forensic analysis and tissue reconstruction in medicine. In this paper, we propose a strategy for the 3D reconstruction of small objects and the identification of some superficial defects. We applied a technique of projection of structured light patterns, specifically sinusoidal fringes and an algorithm of phase unwrapping. A CMOS camera was used to capture images and a DLP digital light projector for synchronous projection of the sinusoidal pattern onto the objects. We implemented a technique based on a 2D flat pattern as calibration process, so the intrinsic and extrinsic parameters of the camera and the DLP were defined. Experimental tests were performed in samples of artificial teeth, coal particles, welding defects and surfaces tested with Vickers indentation. Areas less than 5cm were studied. The objects were reconstructed in 3D with densities of about one million points per sample. In addition, the steps of 3D description, identification of primitive, training and classification were implemented to recognize defects, such as: holes, cracks, roughness textures and bumps. We found that pattern recognition strategies are useful, when quality supervision of surfaces has enough quantities of points to evaluate the defective region, because the identification of defects in small objects is a demanding activity of the visual inspection.

Characterization and identification of microorganisms by FT-IR microspectrometry

NASA Astrophysics Data System (ADS)

Ngo-Thi, N. A.; Kirschner, C.; Naumann, D.

2003-12-01

We report on a novel FT-IR approach for microbial characterization/identification based on a light microscope coupled to an infrared spectrometer which offers the possibility to acquire IR-spectra of microcolonies containing only few hundred cells. Microcolony samples suitable for FT-IR microspectroscopic measurements were obtained by a replica technique with a stamping device that transfers spatially accurate cells of microcolonies growing on solid culture plates to a special, IR-transparent or reflecting stamping plate. High quality spectra could be recorded either by applying the transmission/absorbance or the reflectance/absorbance mode of the infrared microscope. Signal to noise ratios higher than 1000 were obtained for microcolonies as small as 40 μm in diameter. Reproducibility levels were established that allowed species and strain identification. The differentiation and classification capacity of the FT-IR microscopic technique was tested for different selected microorganisms. Cluster and factor analysis methods were used to evaluate the complex spectral data. Excellent discrimination between bacteria and yeasts, and at the same time Gram-negative and Gram-positive bacterial strains was obtained. Twenty-two selected strains of different species within the genus Staphylococcus were repetitively measured and could be grouped into correct species cluster. Moreover, the results indicated that the method allows also identifications at the subspecies level. Additionally, the new approach allowed spectral mapping analysis of single colonies which provided spatially resolved characterization of growth heterogeneity within complex microbial populations such as colonies.

Single Nucleobase Identification Using Biophysical Signatures from Nanoelectronic Quantum Tunneling.

PubMed

Korshoj, Lee E; Afsari, Sepideh; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-03-01

Nanoelectronic DNA sequencing can provide an important alternative to sequencing-by-synthesis by reducing sample preparation time, cost, and complexity as a high-throughput next-generation technique with accurate single-molecule identification. However, sample noise and signature overlap continue to prevent high-resolution and accurate sequencing results. Probing the molecular orbitals of chemically distinct DNA nucleobases offers a path for facile sequence identification, but molecular entropy (from nucleotide conformations) makes such identification difficult when relying only on the energies of lowest-unoccupied and highest-occupied molecular orbitals (LUMO and HOMO). Here, nine biophysical parameters are developed to better characterize molecular orbitals of individual nucleobases, intended for single-molecule DNA sequencing using quantum tunneling of charges. For this analysis, theoretical models for quantum tunneling are combined with transition voltage spectroscopy to obtain measurable parameters unique to the molecule within an electronic junction. Scanning tunneling spectroscopy is then used to measure these nine biophysical parameters for DNA nucleotides, and a modified machine learning algorithm identified nucleobases. The new parameters significantly improve base calling over merely using LUMO and HOMO frontier orbital energies. Furthermore, high accuracies for identifying DNA nucleobases were observed at different pH conditions. These results have significant implications for developing a robust and accurate high-throughput nanoelectronic DNA sequencing technique. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Testing isotopic labeling with [¹³C₆]glucose as a method of advanced glycation sites identification.

PubMed

Kielmas, Martyna; Kijewska, Monika; Stefanowicz, Piotr; Szewczuk, Zbigniew

2012-12-01

The Maillard reaction occurring between reducing sugars and reactive amino groups of biomolecules leads to the formation of a heterogeneous mixture of compounds: early, intermediate, and advanced glycation end products (AGEs). These compounds could be markers of certain diseases and of the premature aging process. Detection of Amadori products can be performed by various methods, including MS/MS techniques and affinity chromatography on immobilized boronic acid. However, the diversity of the structures of AGEs makes detection of these compounds more difficult. The aim of this study was to test a new method of AGE identification based on isotope (13)C labeling. The model protein (hen egg lysozyme) was modified with an equimolar mixture of [(12)C(6)]glucose and [(13)C(6)]glucose and then subjected to reduction of the disulfide bridges followed by tryptic hydrolysis. The digest obtained was analyzed by LC-MS. The glycation products were identified on the basis of characteristic isotopic patterns resulting from the use of isotopically labeled glucose. This method allowed identification of 38 early Maillard reaction products and five different structures of the end glycation products. This isotopic labeling technique combined with LC-MS is a sensitive method for identification of advanced glycation end products even if their chemical structure is unknown. Copyright © 2012 Elsevier Inc. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

PubMed

Oluwadare, Oluwatosin; Cheng, Jianlin

2017-11-14

With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function. Here, we formulate the TAD identification problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identification method called ClusterTAD. We introduce a novel method to represent chromosomal contacts as features to be used by the clustering algorithm. Our results show that ClusterTAD can accurately predict the TADs on a simulated Hi-C data. Our method is also largely complementary and consistent with existing methods on the real Hi-C datasets of two mouse cells. The validation with the chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) data shows that the domain boundaries identified by ClusterTAD have a high enrichment of CTCF binding sites, promoter-related marks, and enhancer-related histone modifications. As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a large array of clustering methods developed in the machine learning field to the TAD identification problem. The source code, the results, and the TADs generated for the simulated and real Hi-C datasets are available here: https://github.com/BDM-Lab/ClusterTAD .

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.

An analytical platform for mass spectrometry-based identification and chemical analysis of RNA in ribonucleoprotein complexes.

PubMed

Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Masaki, Shunpei; Nakayama, Hiroshi; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

2009-11-01

We describe here a mass spectrometry (MS)-based analytical platform of RNA, which combines direct nano-flow reversed-phase liquid chromatography (RPLC) on a spray tip column and a high-resolution LTQ-Orbitrap mass spectrometer. Operating RPLC under a very low flow rate with volatile solvents and MS in the negative mode, we could estimate highly accurate mass values sufficient to predict the nucleotide composition of a approximately 21-nucleotide small interfering RNA, detect post-transcriptional modifications in yeast tRNA, and perform collision-induced dissociation/tandem MS-based structural analysis of nucleolytic fragments of RNA at a sub-femtomole level. Importantly, the method allowed the identification and chemical analysis of small RNAs in ribonucleoprotein (RNP) complex, such as the pre-spliceosomal RNP complex, which was pulled down from cultured cells with a tagged protein cofactor as bait. We have recently developed a unique genome-oriented database search engine, Ariadne, which allows tandem MS-based identification of RNAs in biological samples. Thus, the method presented here has broad potential for automated analysis of RNA; it complements conventional molecular biology-based techniques and is particularly suited for simultaneous analysis of the composition, structure, interaction, and dynamics of RNA and protein components in various cellular RNP complexes.

Fractal dimension based damage identification incorporating multi-task sparse Bayesian learning

NASA Astrophysics Data System (ADS)

Huang, Yong; Li, Hui; Wu, Stephen; Yang, Yongchao

2018-07-01

Sensitivity to damage and robustness to noise are critical requirements for the effectiveness of structural damage detection. In this study, a two-stage damage identification method based on the fractal dimension analysis and multi-task Bayesian learning is presented. The Higuchi’s fractal dimension (HFD) based damage index is first proposed, directly examining the time-frequency characteristic of local free vibration data of structures based on the irregularity sensitivity and noise robustness analysis of HFD. Katz’s fractal dimension is then presented to analyze the abrupt irregularity change of the spatial curve of the displacement mode shape along the structure. At the second stage, the multi-task sparse Bayesian learning technique is employed to infer the final damage localization vector, which borrow the dependent strength of the two fractal dimension based damage indication information and also incorporate the prior knowledge that structural damage occurs at a limited number of locations in a structure in the absence of its collapse. To validate the capability of the proposed method, a steel beam and a bridge, named Yonghe Bridge, are analyzed as illustrative examples. The damage identification results demonstrate that the proposed method is capable of localizing single and multiple damages regardless of its severity, and show superior robustness under heavy noise as well.

Neurophysiological Identification of Cranial Nerves During Endoscopic Endonasal Surgery of Skull Base Tumors: Pilot Study Technical Report.

PubMed

Shkarubo, Alexey Nikolaevich; Chernov, Ilia Valerievich; Ogurtsova, Anna Anatolievna; Moshchev, Dmitry Aleksandrovich; Lubnin, Andrew Jurievich; Andreev, Dmitry Nicolaevich; Koval, Konstantin Vladimirovich

2017-02-01

Intraoperative identification of cranial nerves is crucial for safe surgery of skull base tumors. Currently, only a small number of published papers describe the technique of trigger electromyography (t-EMG) in endoscopic endonasal removal of such tumors. To assess the effectiveness of t-EMG in preventing intraoperative cranial nerve damage in endoscopic endonasal surgery of skull base tumors. Nine patients were operated on using the endoscopic endonasal approach within a 1-year period. The tumors included large skull base chordomas and trigeminal neurinomas localized in the cavernous sinus. During the surgical process, cranial nerve identification was carried out using monopolar and bipolar t-EMG methods. Assessment of cranial nerve functional activity was conducted both before and after tumor removal. We mapped 17 nerves in 9 patients. Third, fifth, and sixth cranial nerves were identified intraoperatively. There were no cases of postoperative functional impairment of the mapped cranial nerves. In one case we were unable to get an intraoperative response from the fourth cranial nerve and observed its postoperative transient plegia (the function was normal before surgery). t-EMG allows surgeons to control the safety of cranial nerves both during and after skull base tumor removal. Copyright © 2016 Elsevier Inc. All rights reserved.

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

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

PubMed Central

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

2017-01-01

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

The discrimination of 72 nitrate, chlorate and perchlorate salts using IR and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Zapata, Félix; García-Ruiz, Carmen

2018-01-01

Inorganic oxidizing energetic salts including nitrates, chlorates and perchlorates are widely used in the manufacture of not only licit pyrotechnic compositions, but also illicit homemade explosive mixtures. Their identification in forensic laboratories is usually accomplished by either capillary electrophoresis or ion chromatography, with the disadvantage of dissociating the salt into its ions. On the contrary, vibrational spectroscopy, including IR and Raman, enables the non-invasive identification of the salt, i.e. avoiding its dissociation. This study focuses on the discrimination of all nitrate, chlorate and perchlorate salts that are commercially available, using both Raman and IR spectroscopy, with the aim of testing whether every salt can be unequivocally identified. Besides the visual spectra comparison by assigning every band with the corresponding molecular vibrational mode, a statistical analysis based on Pearson correlation was performed to ensure an objective identification, either using Raman, IR or both. Positively, 25 salts (out of 72) were unequivocally identified using Raman, 30 salts when using IR and 44 when combining both techniques. Negatively, some salts were undistinguishable even using both techniques demonstrating there are some salts that provide very similar Raman and IR spectra.

Logical Framework of Forensic Identification: Ability to Resist Fabricated DNA.

PubMed

Wang, Zheng; Zhou, Di; Zhang, Suhua; Bian, Yingnan; Hu, Zhen; Zhu, Ruxin; Lu, Daru; Li, Chengtao

2015-12-01

Over the past 30 years, DNA analysis has revolutionized forensic science and has become the most useful single tool in the multifaceted fight against crime. Today, DNA profiling with sets of highly polymorphic autosomal short tandem repeat markers is widely employed and accepted in the courts due to its high discriminating power and reliability. However, an artificial bloodstain purposefully created using molecular biology techniques succeeded in tricking a leading forensic DNA laboratory. The disturbing possibility that a forensic DNA profile can be faked shocked the general public and the mass media, and generated serious discussion about the credibility of DNA evidence. Herein, we present two exemplary assays based on tissue-specific methylation patterns and cell-specific mRNA expression, respectively. These two assays can be integrated into the DNA analysis pipelines without consumption of additional samples. We show that the two assays can not only distinguish between artificial and genuine samples, but also provide information on tissue origin. The two assays were tested on natural and artificial bloodstains (generated by polymerase chain reaction and whole genome amplification technique) and the results illustrated that the logical framework of forensic identification is still useful for forensic identification with the high credibility.

Evaluation of a multi-fibre needle Raman probe for tissue analysis

NASA Astrophysics Data System (ADS)

Fullwood, Leanne M.; Iping Petterson, Ingeborg E.; Dudgeon, Alexander P.; Lloyd, Gavin R.; Kendall, Catherine; Hall, Charlie; Day, John C. C.; Stone, Nick

2016-03-01

Raman spectroscopy is a rapid technique for the identification of cancers. Its coupling with a hypodermic needle provides a minimally invasive instrument with the potential to aid real time assessment of suspicious lesions in vivo and guide surgery. A fibre optic Raman needle probe was utilised in this study to evaluate the classification ability of the instrument as a diagnostic tool together with multivariate analysis, through measurements of tissues from different animal species as well as various different porcine tissue types. Cross validation was performed and preliminary classification accuracies were calculated as 100% for the identification of tissue type and 97.5% for the identification of animal species. A lymph node sample was also measured using the needle probe to assess the use of the technique for human tissue and hence its efficiency as a clinical instrument. This needle probe has been demonstrated to have the capabilities to classify tissue samples based on their biochemical components. The Raman needle probe also has the potential to act as a diagnostic and surgical tool to delineate cancerous from non-cancerous cells in real time, thus assisting complete removal of a tumour.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Meteorological Techniques (Revision 26 Apr 2006)

DTIC Science & Technology

2003-06-13

OVV Graph ------------------------------------------------------------------------ 2-11 Figure 2-26 Dissipation of Stratus Using Mixing Ratio and...2-51 Figure 2-70 Bright Band Identification Using the WSR-88D. ------------------------------------------ 2-52 Figure 2-71 Example of Visible...R2, and R3 relative humidity values and cloud amounts ------------------------- 2-7 Table 2-4 Base of convective clouds using surface dew-point

Using Evidence-Based Decision Trees Instead of Formulas to Identify At-Risk Readers. REL 2014-036

ERIC Educational Resources Information Center

Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R.

2014-01-01

This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…

Development of quantitative PCR assays targeting 16S rRNA gene of Enterococcus spp. and their application to the identification of Enterococcus species in environmental samples

EPA Science Inventory

The detection of environmental enterococci has primarily been determined using culture-based techniques that might exclude some enterococci species as well as those that are nonculturable. To address this, the relative abundance of enterococci was examined by challenging fecal an...

Evaluation of the Technical Adequacy of Three Methods for Identifying Specific Learning Disabilities Based on Cognitive Discrepancies

ERIC Educational Resources Information Center

Stuebing, Karla K.; Fletcher, Jack M.; Branum-Martin, Lee; Francis, David J.

2012-01-01

This study used simulation techniques to evaluate the technical adequacy of three methods for the identification of specific learning disabilities via patterns of strengths and weaknesses in cognitive processing. Latent and observed data were generated and the decision-making process of each method was applied to assess concordance in…

Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies

ERIC Educational Resources Information Center

Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Burke, Mack D.; Camargo, Siglia P.

2012-01-01

Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not…

Project-Based Learning: A Student Investigation of the Turtle Trade in Guangzhou, People's Republic of China

ERIC Educational Resources Information Center

Cheung, Sze Man; Chow, Alex T.

2011-01-01

This article describes a survey conducted by 20 university students in Guangzhou, China since January 2008 on the live turtle trade in markets. Lectures on the Asian turtle conservation problem, turtle identification skills and survey techniques were given to the students before on-site surveys. After guided observation with teachers, students…

Identification of Highly Prized Commercial Fish Using a PCR-Based Methodology

ERIC Educational Resources Information Center

Moran, Paloma; Garcia-Vasquez, Eva

2006-01-01

We report a practical class designed for undergraduate students of Marine Sciences as a part of the Genetics course. The class can also be included in undergraduate studies of food technology. The exercise was designed to emphasize the application of molecular biology techniques to fish species authentication and traceability. After a simple and…

Problem Identification Survey Handbook for Parish Rural Development Committees.

ERIC Educational Resources Information Center

Koch, Kenneth A.

The Task Force on Resource Development of the Cooperative Extension Service, Louisiana State University, decided to utilize the leader identification technique as a means of assisting the parish rural development committees in the rural development process. The technique is a procedure to stimulate effective citizen participation to identify…

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

UV gated Raman spectroscopy for standoff detection of explosives

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2008-07-01

Real-time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called improvised explosive devices (IED). It is recognized that the only method, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We have applied gated Raman spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 m.

A comparative study on book shelf structure based on different domain modal analysis

NASA Astrophysics Data System (ADS)

Sabamehr, Ardalan; Roy, Timir Baran; Bagchi, Ashutosh

2017-04-01

Structural Health Monitoring (SHM) based on the vibration of structures has been very attractive topic for researchers in different fields such as: civil, aeronautical and mechanical engineering. The aim of this paper is to compare three most common modal identification techniques such as Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) to find modal properties (such as natural frequency, mode shape and damping ratio) of three story book shelf steel structure which was built in Concordia University Lab. The modified Complex Morlet wavelet have been selected for wavelet in order to use asymptotic signal rather than real one with variable bandwidth and wavelet central frequency. So, CWT is able to detect instantaneous modulus and phase by use of local maxima ridge detection.

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

An investigation of hydrogenized amorphous Si structures with Doppler broadening positron annihilation techniques

NASA Astrophysics Data System (ADS)

Petkov, M. P.; Marek, T.; Asoka-Kumar, P.; Lynn, K. G.; Crandall, R. S.; Mahan, A. H.

1998-07-01

In this letter, we examine the feasibility of applying positron annihilation spectroscopy to the study of hydrogenized amorphous silicon (a-Si:H)-based structures produced by chemical vapor deposition techniques. The positron probe, sensitive to open volume formations, is used to characterize neutral and negatively charged silicon dangling bonds, typical for undoped and n-doped a-Si:H, respectively. Using depth profiling along the growth direction a difference was observed in the electronic environment of these defects, which enables their identification in a p-i-n device.

Evaluation of the class II region of the major histocompatibility complex of the greyhound with the genomic matching technique and sequence-based typing.

PubMed

Fliegner, R A; Holloway, S A; Lester, S; McLure, C A; Dawkins, R L

2008-08-01

The class II region of the major histocompatibility complex was evaluated in 25 greyhounds by sequence-based typing and the genomic matching technique (GMT). Two new DLA-DRB1 alleles were identified. Twenty-four dogs carried the DLA-DRB1*01201/DQA1*00401/DQB1*01303/DQB1*01701 haplotype, which carries two DQB1 alleles. One haplotype was identified from which DQB1 and DQA1 appeared to be deleted. The GMT enabled detection of DQB1 copy number, discrimination of the different class II haplotypes and the identification of new, possibly biologically relevant polymorphisms.

Mass spectrometry: a revolution in clinical microbiology?

PubMed

Lavigne, Jean-Philippe; Espinal, Paula; Dunyach-Remy, Catherine; Messad, Nourredine; Pantel, Alix; Sotto, Albert

2013-02-01

Recently, different bacteriological laboratory interventions that decrease reporting time have been developed. These promising new broad-based techniques have merit, based on their ability to identify rapidly many bacteria, organisms difficult to grow or newly emerging strains, as well as their capacity to track disease transmission. The benefit of rapid reporting of identification and/or resistance of bacteria can greatly impact patient outcomes, with an improvement in the use of antibiotics, in the reduction of the emergence of multidrug resistant bacteria and in mortality rates. Different techniques revolve around mass spectrometry (MS) technology: matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR combined with electrospray ionization-mass spectrometry (PCR/ESIMS), iPLEX MassArray system and other new evolutions combining different techniques. This report emphasizes the (r)evolution of these technologies in clinical microbiology.

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Identification of Scleractinian Coral Recruits Using Fluorescent Censusing and DNA Barcoding Techniques

PubMed Central

Hsu, Chia-Min; de Palmas, Stéphane; Kuo, Chao-Yang; Denis, Vianney; Chen, Chaolun Allen

2014-01-01

The identification of coral recruits has been problematic due to a lack of definitive morphological characters being available for higher taxonomic resolution. In this study, we tested whether fluorescent detection of coral recruits used in combinations of different DNA-barcoding markers (cytochrome oxidase I gene [COI], open reading frame [ORF], and nuclear Pax-C intron [PaxC]) could be useful for increasing the resolution of coral spat identification in ecological studies. One hundred and fifty settlement plates were emplaced at nine sites on the fringing reefs of Kenting National Park in southern Taiwan between April 2011 and September 2012. A total of 248 living coral spats and juveniles (with basal areas ranging from 0.21 to 134.57 mm2) were detected on the plates with the aid of fluorescent light and collected for molecular analyses. Using the COI DNA barcoding technique, 90.3% (224/248) of coral spats were successfully identified into six genera, including Acropora, Isopora, Montipora, Pocillopora, Porites, and Pavona. PaxC further separated I. cuneata and I. palifera of Isopora from Acropora, and ORF successfully identified the species of Pocillopora (except P. meandrina and P. eydouxi). Moreover, other cnidarian species such as actinarians, zoanthids, and Millepora species were visually found using fluorescence and identified by COI DNA barcoding. This combination of existing approaches greatly improved the taxonomic resolution of early coral life stages, which to date has been mainly limited to the family level based on skeletal identification. Overall, this study suggests important improvements for the identification of coral recruits in ecological studies. PMID:25211345

Identification of scleractinian coral recruits using fluorescent censusing and DNA barcoding techniques.

PubMed

Hsu, Chia-Min; de Palmas, Stéphane; Kuo, Chao-Yang; Denis, Vianney; Chen, Chaolun Allen

2014-01-01

The identification of coral recruits has been problematic due to a lack of definitive morphological characters being available for higher taxonomic resolution. In this study, we tested whether fluorescent detection of coral recruits used in combinations of different DNA-barcoding markers (cytochrome oxidase I gene [COI], open reading frame [ORF], and nuclear Pax-C intron [PaxC]) could be useful for increasing the resolution of coral spat identification in ecological studies. One hundred and fifty settlement plates were emplaced at nine sites on the fringing reefs of Kenting National Park in southern Taiwan between April 2011 and September 2012. A total of 248 living coral spats and juveniles (with basal areas ranging from 0.21 to 134.57 mm(2)) were detected on the plates with the aid of fluorescent light and collected for molecular analyses. Using the COI DNA barcoding technique, 90.3% (224/248) of coral spats were successfully identified into six genera, including Acropora, Isopora, Montipora, Pocillopora, Porites, and Pavona. PaxC further separated I. cuneata and I. palifera of Isopora from Acropora, and ORF successfully identified the species of Pocillopora (except P. meandrina and P. eydouxi). Moreover, other cnidarian species such as actinarians, zoanthids, and Millepora species were visually found using fluorescence and identified by COI DNA barcoding. This combination of existing approaches greatly improved the taxonomic resolution of early coral life stages, which to date has been mainly limited to the family level based on skeletal identification. Overall, this study suggests important improvements for the identification of coral recruits in ecological studies.

Oral mark in the application of an individual identification: From ashes to truth.

PubMed

Chugh, Anshul; Narwal, Anumeha

2017-01-01

Forensic odontology is the branch of dentistry which deals with the proper handling, examination, evaluation and presentation of dental findings in the interest of justice. After major disasters and perimortem assaults such as earthquakes, fires, severe head and neck trauma or gross decomposition, accurate and early identification of dead and injured becomes important. In the absence of other records in such cases, identification is based on restorations, missing teeth and prosthetic devices such as partial and complete removable/fixed prosthesis or implant retained devices. This brings out the major role of prosthodontics to investigate the identity of suspects in the criminal cases as well as the deceased human beings in traumatic injuries or in disasters. Denture identification systems are being used as means of postmortem identification of edentulous persons which has evolved from the inclusion of some form of printed label in a denture to more high-tech methods. The provision of implant retained complete lower denture, antemortem, and postmortem radiographs of edentulous persons and correlation of bite marks using special impression techniques provide another potential source of evidence for human identification. Hence, this literature review throws some light on the role played by prosthodontist in forensic odontology.

Dynamic neural networks based on-line identification and control of high performance motor drives

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Kotaru, Raj

1995-01-01

In the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.

An automated cross-correlation based event detection technique and its application to surface passive data set

USGS Publications Warehouse

Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

2013-01-01

In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

Real-time flutter identification

NASA Technical Reports Server (NTRS)

Roy, R.; Walker, R.

1985-01-01

The techniques and a FORTRAN 77 MOdal Parameter IDentification (MOPID) computer program developed for identification of the frequencies and damping ratios of multiple flutter modes in real time are documented. Physically meaningful model parameterization was combined with state of the art recursive identification techniques and applied to the problem of real time flutter mode monitoring. The performance of the algorithm in terms of convergence speed and parameter estimation error is demonstrated for several simulated data cases, and the results of actual flight data analysis from two different vehicles are presented. It is indicated that the algorithm is capable of real time monitoring of aircraft flutter characteristics with a high degree of reliability.

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

PubMed

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

2014-03-01

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

Estimating Ocean Currents from Automatic Identification System Based Ship Drift Measurements

NASA Astrophysics Data System (ADS)

Jakub, Thomas D.

Ship drift is a technique that has been used over the last century and a half to estimate ocean currents. Several of the shortcomings of the ship drift technique include obtaining the data from multiple ships, the time delay in getting those ship positions to a data center for processing and the limited resolution based on the amount of time between position measurements. These shortcomings can be overcome through the use of the Automatic Identification System (AIS). AIS enables more precise ocean current estimates, the option of finer resolution and more timely estimates. In this work, a demonstration of the use of AIS to compute ocean currents is performed. A corresponding error and sensitivity analysis is performed to help identify under which conditions errors will be smaller. A case study in San Francisco Bay with constant AIS message updates was compared against high frequency radar and demonstrated ocean current magnitude residuals of 19 cm/s for ship tracks in a high signal to noise environment. These ship tracks were only minutes long compared to the normally 12 to 24 hour ship tracks. The Gulf of Mexico case study demonstrated the ability to estimate ocean currents over longer baselines and identified the dependency of the estimates on the accuracy of time measurements. Ultimately, AIS measurements when combined with ship drift can provide another method of estimating ocean currents, particularly when other measurements techniques are not available.

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

PubMed

Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

2015-11-04

European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

Rapid characterization of chlorogenic acids in Duhaldea nervosa based on ultra-high-performance liquid chromatography-linear trap quadropole-Orbitrap-mass spectrometry and mass spectral trees similarity filter technique.

PubMed

Liu, Lianghong; Zhang, Jiayu; Zheng, Binjie; Guan, Ying; Wang, Liting; Chen, Lei; Cai, Wei

2018-04-01

Duhaldea nervosa (Wallich ex Candolle) A. Anderberg has been traditionally used as a food spice and also in folk medicine for treating traumatic injury and relieving rheumatism, especially accelerating the healing of a fracture. However, so far as we are aware, the chemical constituents have not been fully investigated. In this study, a practical method of mass spectral trees similarity filter, a data-mining technique, was developed and evaluated for the rapid detection and identification complicated constituents based on ultra-high-performance liquid chromatography-linear trap quadropole-Orbitrap-mass spectrometry. Finally, a total of 47 chlorogenic acids, including 19 monoacyl-quinic acids, 22 diacyl-quinic acids, and six triacyl-quinic acids, were unambiguously or tentatively identified based on their accurate mass measurement, chromatographic retention, MS n spectra, and bibliography data. To our best knowledge, it is the first time to report the chlorogenic acids of D. nervosa, which would be beneficial for the further material basis and quality research. Meanwhile, this mass spectral trees similarity filter method could be envisioned to exhibit a wide application for the identification of complicated components from botanical extracts. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

PubMed Central

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis. PMID:25705672

The novel quantitative technique for assessment of gait symmetry using advanced statistical learning algorithm.

PubMed

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

Model correlation and damage location for large space truss structures: Secant method development and evaluation

NASA Technical Reports Server (NTRS)

Smith, Suzanne Weaver; Beattie, Christopher A.

1991-01-01

On-orbit testing of a large space structure will be required to complete the certification of any mathematical model for the structure dynamic response. The process of establishing a mathematical model that matches measured structure response is referred to as model correlation. Most model correlation approaches have an identification technique to determine structural characteristics from the measurements of the structure response. This problem is approached with one particular class of identification techniques - matrix adjustment methods - which use measured data to produce an optimal update of the structure property matrix, often the stiffness matrix. New methods were developed for identification to handle problems of the size and complexity expected for large space structures. Further development and refinement of these secant-method identification algorithms were undertaken. Also, evaluation of these techniques is an approach for model correlation and damage location was initiated.

Bench-to-bedside review: Rapid molecular diagnostics for bloodstream infection - a new frontier?

PubMed Central

2012-01-01

Among critically ill patients, the diagnosis of bloodstream infection poses a major challenge. Current standard bacterial identification based on blood culture platforms is intrinsically time-consuming and slow. The continuous evolvement of molecular techniques has the potential of providing a faster, more sensitive and direct identification of causative pathogens without prior need for cultivation. This may ultimately impact clinical decision-making and antimicrobial treatment. This review summarises the currently available technologies, their strengths and limitations and the obstacles that have to be overcome in order to develop a satisfactory bedside point-of-care diagnostic tool for detection of bloodstream infection. PMID:22647543

The Use of AIS Data for Identifying and Mapping Calcareous Soils in Western Nebraska

NASA Technical Reports Server (NTRS)

Samson, S. A.

1985-01-01

The identification of calcareous soils, through unique spectral responses of the vegetation to the chemical nature of calcareous soils, can improve the accuracy of delineating the boundaries of soil mapping units over conventional field techniques. The objective of this experiment is to evaluate the use of the Airborne Imaging Spectrometer (AIS) in the identification and delineation of calcareous soils in the western Sandhills of Nebraska. Based upon statistical differences found in separating the spectral curves below 1.3 microns, calcareous and non-calcareous soils may be identified by differences in species of vegetation. Additional work is needed to identify biogeochemical differences between the two soils.

Edge detection techniques for iris recognition system

NASA Astrophysics Data System (ADS)

Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

2013-12-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

Identification of pilot-vehicle dynamics from simulation and flight test

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1990-01-01

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

Spectral algorithm for non-destructive damage localisation: Application to an ancient masonry arch model

NASA Astrophysics Data System (ADS)

Masciotta, Maria-Giovanna; Ramos, Luís F.; Lourenço, Paulo B.; Vasta, Marcello

2017-02-01

Structural monitoring and vibration-based damage identification methods are fundamental tools for condition assessment and early-stage damage identification, especially when dealing with the conservation of historical constructions and the maintenance of strategic civil structures. However, although the substantial advances in the field, several issues must still be addressed to broaden the application range of such tools and to assert their reliability. This study deals with the experimental validation of a novel method for non-destructive damage identification purposes. This method is based on the use of spectral output signals and has been recently validated by the authors through a numerical simulation. After a brief insight into the basic principles of the proposed approach, the spectral-based technique is applied to identify the experimental damage induced on a masonry arch through statically increasing loading. Once the direct and cross spectral density functions of the nodal response processes are estimated, the system's output power spectrum matrix is built and decomposed in eigenvalues and eigenvectors. The present study points out how the extracted spectral eigenparameters contribute to the damage analysis allowing to detect the occurrence of damage and to locate the target points where the cracks appear during the experimental tests. The sensitivity of the spectral formulation to the level of noise in the modal data is investigated and discussed. As a final evaluation criterion, the results from the spectrum-driven method are compared with the ones obtained from existing non-model based damage identification methods.

Magnetic bead based immuno-detection of Listeria monocytogenes and Listeria ivanovii from infant formula and leafy green vegetables using the Bio-Plex suspension array system.

PubMed

Day, J B; Basavanna, U

2015-04-01

Listeriosis, a disease contracted via the consumption of foods contaminated with pathogenic Listeria species, can produce severe symptoms and high mortality in susceptible people and animals. The development of molecular methods and immuno-based techniques for detection of pathogenic Listeria in foods has been challenging due to the presence of assay inhibiting food components. In this study, we utilize a macrophage cell culture system for the isolation and enrichment of Listeria monocytogenes and Listeria ivanovii from infant formula and leafy green vegetables for subsequent identification using the Luminex xMAP technique. Macrophage monolayers were exposed to infant formula, lettuce and celery contaminated with L. monocytogenes or L. ivanovii. Magnetic microspheres conjugated to Listeria specific antibody were used to capture Listeria from infected macrophages and then analyzed using the Bio-Plex 200 analyzer. As few as 10 CFU/mL or g of L. monocytogenes was detected in all foods tested. The detection limit for L. ivanovii was 10 CFU/mL in infant formula and 100 CFU/g in leafy greens. Microsphere bound Listeria obtained from infected macrophage lysates could also be isolated on selective media for subsequent confirmatory identification. This method presumptively identifies L. monocytogenes and L. ivanovii from infant formula, lettuce and celery in less than 28 h with confirmatory identifications completed in less than 48 h. Published by Elsevier Ltd.

Individual identification via electrocardiogram analysis.

PubMed

Fratini, Antonio; Sansone, Mario; Bifulco, Paolo; Cesarelli, Mario

2015-08-14

During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations.

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.

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.

[Hallucinogenic fungi (psilocybe). Part II. Identification of Psilocybe semilanceata by PCR].

PubMed

Adamczyk, Aldona; Sadakierska-Chudy, Anna; Janoszka, Jerzy; Rymkiewicz, Apoloniusz; Dobosz, Tadeusz

2007-01-01

Psilocybe semilanceata belongs to the genus of Psilocybe; it is a hallucinogenic fungus, frequently found in regions with high rainfall, in the grass and moss. There are estimated to be as many as eight Psilocybe hallucinogenic species containing psychoactive alkaloids, such as psilocybin and psilocin, which may cause visual, auditory and other hallucinations, as well as profound changes in the perception of time and space. Since identification of P semilanceata in a form different than a fresh mushroom is almost impossible, the authors made an attempt at developing a method of fungi identification based on the PCR technique, which could be helpful in a fight against dangerous consumption of these hallucinogens by the youth. Detection of the specific DNA sequence for P semilanceata brought good results; the test may be commonly employed in forensic practice in the future.

Minimalist identification system based on venous map for security applications

NASA Astrophysics Data System (ADS)

Jacinto G., Edwar; Martínez S., Fredy; Martínez S., Fernando

2015-07-01

This paper proposes a technique and an algorithm used to build a device for people identification through the processing of a low resolution camera image. The infrared channel is the only information needed, sensing the blood reaction with the proper wave length, and getting a preliminary snapshot of the vascular map of the back side of the hand. The software uses this information to extract the characteristics of the user in a limited area (region of interest, ROI), unique for each user, which applicable to biometric access control devices. This kind of recognition prototypes functions are expensive, but in this case (minimalist design), the biometric equipment only used a low cost camera and the matrix of IR emitters adaptation to construct an economic and versatile prototype, without neglecting the high level of effectiveness that characterizes this kind of identification method.

DNA-based identification of invasive alien species in relation to Canadian federal policy and law, and the basis of rapid-response management.

PubMed

Thomas, Vernon G; Hanner, Robert H; Borisenko, Alex V

2016-11-01

Managing invasive alien species in Canada requires reliable taxonomic identification as the basis of rapid-response management. This can be challenging, especially when organisms are small and lack morphological diagnostic features. DNA-based techniques, such as DNA barcoding, offer a reliable, rapid, and inexpensive toolkit for taxonomic identification of individual or bulk samples, forensic remains, and even environmental DNA. Well suited for this requirement, they could be more broadly deployed and incorporated into the operating policy and practices of Canadian federal departments and should be authorized under these agencies' articles of law. These include Fisheries and Oceans Canada, Canadian Food Inspection Agency, Transport Canada, Environment Canada, Parks Canada, and Health Canada. These efforts should be harmonized with the appropriate provisions of provincial jurisdictions, for example, the Ontario Invasive Species Act. This approach necessitates that a network of accredited, certified laboratories exists, and that updated DNA reference libraries are readily accessible. Harmonizing this approach is vital among Canadian federal agencies, and between the federal and provincial levels of government. Canadian policy and law must also be harmonized with that of the USA when detecting, and responding to, invasive species in contiguous lands and waters. Creating capacity in legislation for use of DNA-based identifications brings the authority to fund, train, deploy, and certify staff, and to refine further developments in this molecular technology.

Highlights of DNA Barcoding in identification of salient microorganisms like fungi.

PubMed

Dulla, E L; Kathera, C; Gurijala, H K; Mallakuntla, T R; Srinivasan, P; Prasad, V; Mopati, R D; Jasti, P K

2016-12-01

Fungi, the second largest kingdom of eukaryotic life, are diverse and widespread. Fungi play a distinctive role in the production of different products on industrial scale, like fungal enzymes, antibiotics, fermented foods, etc., to give storage stability and improved health to meet major global challenges. To utilize algae perfectly for human needs, and to pave the way for getting a healthy relationship with fungi, it is important to identify them in a quick and robust manner with molecular-based identification system. So, there is a technique that aims to provide a well-organized method for species level identifications and to contribute powerfully to taxonomic and biodiversity research is DNA Barcoding. DNA Barcoding is generally achieved by the retrieval of a short DNA sequence - the 'barcode' - from a standard part of the genome and that barcode is then compared with a library of reference barcode sequences derived from individuals of known identity for identification. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Positive dental identification using tooth anatomy and digital superimposition.

PubMed

Johansen, Raymond J; Michael Bowers, C

2013-03-01

Dental identification of unknown human remains continues to be a relevant and reliable adjunct to forensic investigations. The advent of genomic and mitochondrial DNA procedures has not displaced the practical use of dental and related osseous structures remaining after destructive incidents that can render human remains unrecognizable, severely burned, and fragmented. The ability to conclusively identify victims of accident and homicide is based on the availability of antemortem records containing substantial and unambiguous proof of dental and related osseous characteristics. This case report documents the use of digital comparative analysis of antemortem dental models and postmortem dentition, to determine a dental identification. Images of dental models were digitally analyzed using Adobe Photoshop(TM) software. Individual tooth anatomy was compared between the antemortem and postmortem images. Digital superimposition techniques were also used for the comparison. With the absence of antemortem radiographs, this method proved useful to reach a positive identification in this case. © 2012 American Academy of Forensic Sciences.

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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