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.

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.

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.

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

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.

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.

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.

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

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

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

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

[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.

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.

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.

Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

PubMed

Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

2018-04-25

Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

[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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

Gender identification of Grasshopper Sparrows comparing behavioral, morphological, and molecular techniques

USGS Publications Warehouse

Ammer, F.K.; Wood, P.B.; McPherson, R.J.

2008-01-01

Correct gender identification in monomorphic species is often difficult especially if males and females do not display obvious behavioral and breeding differences. We compared gender specific morphology and behavior with recently developed DNA techniques for gender identification in the monomorphic Grasshopper Sparrow (Ammodramus savannarum). Gender was ascertained with DNA in 213 individuals using the 2550F/2718R primer set and 3% agarose gel electrophoresis. Field observations using behavior and breeding characteristics to identify gender matched DNA analyses with 100% accuracy for adult males and females. Gender was identified with DNA for all captured juveniles that did not display gender specific traits or behaviors in the field. The molecular techniques used offered a high level of accuracy and may be useful in studies of dispersal mechanisms and winter assemblage composition in monomorphic species.

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.

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.

How automated image analysis techniques help scientists in species identification and classification?

PubMed

Yousef Kalafi, Elham; Town, Christopher; Kaur Dhillon, Sarinder

2017-09-04

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification increased over the last two decades. Automation of data classification is primarily focussed on images, incorporating and analysing image data has recently become easier due to developments in computational technology. Research efforts in identification of species include specimens' image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, categorizing and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies.

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.

Automated Coronal Loop Identification Using Digital Image Processing Techniques

NASA Technical Reports Server (NTRS)

Lee, Jong K.; Gary, G. Allen; Newman, Timothy S.

2003-01-01

The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

Line identification studies using traditional techniques and wavelength coincidence statistics

NASA Technical Reports Server (NTRS)

Cowley, Charles R.; Adelman, Saul J.

1990-01-01

Traditional line identification techniques result in the assignment of individual lines to an atomic or ionic species. These methods may be supplemented by wavelength coincidence statistics (WCS). The strength and weakness of these methods are discussed using spectra of a number of normal and peculiar B and A stars that have been studied independently by both methods. The present results support the overall findings of some earlier studies. WCS would be most useful in a first survey, before traditional methods have been applied. WCS can quickly make a global search for all species and in this way may enable identifications of an unexpected spectrum that could easily be omitted entirely from a traditional study. This is illustrated by O I. WCS is a subject to well known weakness of any statistical technique, for example, a predictable number of spurious results are to be expected. The danger of small number statistics are illustrated. WCS is at its best relative to traditional methods in finding a line-rich atomic species that is only weakly present in a complicated stellar spectrum.

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.

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.

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.

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.

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.

Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

PubMed

Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

2017-01-01

Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

Phytophthora-ID.org: A sequence-based Phytophthora identification tool

Treesearch

N.J. Grünwald; F.N. Martin; M.M. Larsen; C.M. Sullivan; C.M. Press; M.D. Coffey; E.M. Hansen; J.L. Parke

2010-01-01

Contemporary species identification relies strongly on sequence-based identification, yet resources for identification of many fungal and oomycete pathogens are rare. We developed two web-based, searchable databases for rapid identification of Phytophthora spp. based on sequencing of the internal transcribed spacer (ITS) or the cytochrome oxidase...

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.

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

PubMed

Cheng, Ching-Min; Hwang, Sheue-Ling

2015-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

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.

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.

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.

Chemical Detection and Identification Techniques for Exobiology Flight Experiments

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Modal identification of dynamic mechanical systems

NASA Astrophysics Data System (ADS)

Srivastava, R. K.; Kundra, T. K.

1992-07-01

This paper reviews modal identification techniques which are now helping designers all over the world to improve the dynamic behavior of vibrating engineering systems. In this context the need to develop more accurate and faster parameter identification is ever increasing. A new dynamic stiffness matrix based identification method which is highly accurate, fast and system-dynamic-modification compatible is presented. The technique is applicable to all those multidegree-of-freedom systems where full receptance matrix can be experimentally measured.

Effective techniques for the identification and accommodation of disturbances

NASA Technical Reports Server (NTRS)

Johnson, C. D.

1989-01-01

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

Identification of inelastic parameters based on deep drawing forming operations using a global-local hybrid Particle Swarm approach

NASA Astrophysics Data System (ADS)

Vaz, Miguel; Luersen, Marco A.; Muñoz-Rojas, Pablo A.; Trentin, Robson G.

2016-04-01

Application of optimization techniques to the identification of inelastic material parameters has substantially increased in recent years. The complex stress-strain paths and high nonlinearity, typical of this class of problems, require the development of robust and efficient techniques for inverse problems able to account for an irregular topography of the fitness surface. Within this framework, this work investigates the application of the gradient-based Sequential Quadratic Programming method, of the Nelder-Mead downhill simplex algorithm, of Particle Swarm Optimization (PSO), and of a global-local PSO-Nelder-Mead hybrid scheme to the identification of inelastic parameters based on a deep drawing operation. The hybrid technique has shown to be the best strategy by combining the good PSO performance to approach the global minimum basin of attraction with the efficiency demonstrated by the Nelder-Mead algorithm to obtain the minimum itself.

[Molecular techniques applied in species identification of Toxocara].

PubMed

Fogt, Renata

2006-01-01

Toxocarosis is still an important and actual problem in human medicine. It can manifest as visceral (VLM), ocular (OLM) or covert (CT) larva migrans syndroms. Complicated life cycle of Toxocara, lack of easy and practical methods of species differentiation of the adult nematode and embarrassing in recognition of the infection in definitive hosts create difficulties in fighting with the infection. Although studies on human toxocarosis have been continued for over 50 years there is no conclusive answer, which of species--T. canis or T. cati constitutes a greater risk of transmission of the nematode to man. Neither blood serological examinations nor microscopic observations of the morphological features of the nematode give the satisfied answer on the question. Since the 90-ths molecular methods were developed for species identification and became useful tools being widely applied in parasitological diagnosis. This paper cover the survey of methods of DNA analyses used for identification of Toxocara species. The review may be helpful for researchers focused on Toxocara and toxocarosis as well as on detection of new species. The following techniques are described: PCR (Polymerase Chain Reaction), RFLP (Restriction Fragment Length Polymorphism), RAPD (Random Amplified Polymorphic DNA) and SSCP (Single Strand Conformation Polymorphism).

[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.

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.

Speaker gender identification based on majority vote classifiers

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Identification of Species in Tripterygium (Celastraceae) Based on DNA Barcoding.

PubMed

Zhang, Xiaomei; Li, Na; Yao, Yuanyuan; Liang, Xuming; Qu, Xianyou; Liu, Xiang; Zhu, Yingjie; Yang, Dajian; Sun, Wei

2016-11-01

Species of genus Tripterygium (Celastraceae) have attracted much attention owing to their excellent effect on treating autoimmune and inflammatory diseases. However, due to high market demand causing overexploitation, natural populations of genus Tripterygium have rapidly declined. Tripterygium medicinal materials are mainly collected from the wild, making the quality of medicinal materials unstable. Additionally, identification of herbal materials from Tripterygium species and their adulterants is difficult based on morphological characters. Therefore, an accurate, convenient, and stability method is urgently needed. In this wok, we developed a DNA barcoding technique to distinguish T. wilfordii HOOK. f., T. hypoglaucum (LÉVL.) HUTCH, and T. regelii SPRAGUE et TAKEDA and their adulterants based on four uniform and standard DNA regions (internal transcribed spacer 2 (ITS2), matK, rbcL, and psbA-trnH). DNA was extracted from 26 locations of fresh leaves. Phylogenetic tree was constructed with Neighbor-Joining (NJ) method, while barcoding gap was analyzed to assess identification efficiency. Compared with the other DNA barcodes applied individually or in combination, ITS2+psbA-trnH was demonstrated as the optimal barcode. T. hypoglaucum and T. wilfordii can be considered as conspecific, while T. regelii was recognized as a separate species. Furthermore, identification of commercial Tripterygium samples was conducted using BLAST against GenBank and Species Identification System for Traditional Chinese Medicine. Our results indicated that DNA barcoding is a convenient, effective, and stability method to identify and distinguish Tripterygium and its adulterants, and could be applied as the quality control for Tripterygium medicinal preparations and monitoring of the medicinal herb trade in markets.

Experimental evaluation of a recursive model identification technique for type 1 diabetes.

PubMed

Finan, Daniel A; Doyle, Francis J; Palerm, Cesar C; Bevier, Wendy C; Zisser, Howard C; Jovanovic, Lois; Seborg, Dale E

2009-09-01

A model-based controller for an artificial beta cell requires an accurate model of the glucose-insulin dynamics in type 1 diabetes subjects. To ensure the robustness of the controller for changing conditions (e.g., changes in insulin sensitivity due to illnesses, changes in exercise habits, or changes in stress levels), the model should be able to adapt to the new conditions by means of a recursive parameter estimation technique. Such an adaptive strategy will ensure that the most accurate model is used for the current conditions, and thus the most accurate model predictions are used in model-based control calculations. In a retrospective analysis, empirical dynamic autoregressive exogenous input (ARX) models were identified from glucose-insulin data for nine type 1 diabetes subjects in ambulatory conditions. Data sets consisted of continuous (5-minute) glucose concentration measurements obtained from a continuous glucose monitor, basal insulin infusion rates and times and amounts of insulin boluses obtained from the subjects' insulin pumps, and subject-reported estimates of the times and carbohydrate content of meals. Two identification techniques were investigated: nonrecursive, or batch methods, and recursive methods. Batch models were identified from a set of training data, whereas recursively identified models were updated at each sampling instant. Both types of models were used to make predictions of new test data. For the purpose of comparison, model predictions were compared to zero-order hold (ZOH) predictions, which were made by simply holding the current glucose value constant for p steps into the future, where p is the prediction horizon. Thus, the ZOH predictions are model free and provide a base case for the prediction metrics used to quantify the accuracy of the model predictions. In theory, recursive identification techniques are needed only when there are changing conditions in the subject that require model adaptation. Thus, the identification and

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.

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.

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.

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.

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

[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.

System identification and model reduction using modulating function techniques

NASA Technical Reports Server (NTRS)

Shen, Yan

1993-01-01

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

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.

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

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.

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.

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.

System Identification of Mistuned Bladed Disks from Traveling Wave Response Measurements

NASA Technical Reports Server (NTRS)

Feiner, D. M.; Griffin, J. H.; Jones, K. W.; Kenyon, J. A.; Mehmed, O.; Kurkov, A. P.

2003-01-01

A new approach to modal analysis is presented. By applying this technique to bladed disk system identification methods, one can determine the mistuning in a rotor based on its response to a traveling wave excitation. This allows system identification to be performed under rotating conditions, and thus expands the applicability of existing mistuning identification techniques from integrally bladed rotors to conventional bladed disks.

[Identification of Pummelo Cultivars Based on Hyperspectral Imaging Technology].

PubMed

Li, Xun-lan; Yi, Shi-lai; He, Shao-lan; Lü, Qiang; Xie, Rang-jin; Zheng, Yong-qiang; Deng, Lie

2015-09-01

Existing methods for the identification of pummelo cultivars are usually time-consuming and costly, and are therefore inconvenient to be used in cases that a rapid identification is needed. This research was aimed at identifying different pummelo cultivars by hyperspectral imaging technology which can achieve a rapid and highly sensitive measurement. A total of 240 leaf samples, 60 for each of the four cultivars were investigated. Samples were divided into two groups such as calibration set (48 samples of each cultivar) and validation set (12 samples of each cultivar) by a Kennard-Stone-based algorithm. Hyperspectral images of both adaxial and abaxial surfaces of each leaf were obtained, and were segmented into a region of interest (ROI) using a simple threshold. Spectra of leaf samples were extracted from ROI. To remove the absolute noises of the spectra, only the date of spectral range 400~1000 nm was used for analysis. Multiplicative scatter correction (MSC) and standard normal variable (SNV) were utilized for data preprocessing. Principal component analysis (PCA) was used to extract the best principal components, and successive projections algorithm (SPA) was used to extract the effective wavelengths. Least squares support vector machine (LS-SVM) was used to obtain the discrimination model of the four different pummelo cultivars. To find out the optimal values of σ2 and γ which were important parameters in LS-SVM modeling, Grid-search technique and Cross-Validation were applied. The first 10 and 11 principal components were extracted by PCA for the hyperspectral data of adaxial surface and abaxial surface, respectively. There were 31 and 21 effective wavelengths selected by SPA based on the hyperspectral data of adaxial surface and abaxial surface, respectively. The best principal components and the effective wavelengths were used as inputs of LS-SVM models, and then the PCA-LS-SVM model and the SPA-LS-SVM model were built. The results showed that 99.46% and

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%.

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.

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.

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.

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.

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

Dynamic programming-based hot spot identification approach for pedestrian crashes.

PubMed

Medury, Aditya; Grembek, Offer

2016-08-01

Network screening techniques are widely used by state agencies to identify locations with high collision concentration, also referred to as hot spots. However, most of the research in this regard has focused on identifying highway segments that are of concern to automobile collisions. In comparison, pedestrian hot spot detection has typically focused on analyzing pedestrian crashes in specific locations, such as at/near intersections, mid-blocks, and/or other crossings, as opposed to long stretches of roadway. In this context, the efficiency of the some of the widely used network screening methods has not been tested. Hence, in order to address this issue, a dynamic programming-based hot spot identification approach is proposed which provides efficient hot spot definitions for pedestrian crashes. The proposed approach is compared with the sliding window method and an intersection buffer-based approach. The results reveal that the dynamic programming method generates more hot spots with a higher number of crashes, while providing small hot spot segment lengths. In comparison, the sliding window method is shown to suffer from shortcomings due to a first-come-first-serve approach vis-à-vis hot spot identification and a fixed hot spot window length assumption. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Research on gait-based human identification

NASA Astrophysics Data System (ADS)

Li, Youguo

Gait recognition refers to automatic identification of individual based on his/her style of walking. This paper proposes a gait recognition method based on Continuous Hidden Markov Model with Mixture of Gaussians(G-CHMM). First, we initialize a Gaussian mix model for training image sequence with K-means algorithm, then train the HMM parameters using a Baum-Welch algorithm. These gait feature sequences can be trained and obtain a Continuous HMM for every person, therefore, the 7 key frames and the obtained HMM can represent each person's gait sequence. Finally, the recognition is achieved by Front algorithm. The experiments made on CASIA gait databases obtain comparatively high correction identification ratio and comparatively strong robustness for variety of bodily angle.

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.

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

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.

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.

Arabic writer identification based on diacritic's features

NASA Astrophysics Data System (ADS)

Maliki, Makki; Al-Jawad, Naseer; Jassim, Sabah A.

2012-06-01

Natural languages like Arabic, Kurdish, Farsi (Persian), Urdu, and any other similar languages have many features, which make them different from other languages like Latin's script. One of these important features is diacritics. These diacritics are classified as: compulsory like dots which are used to identify/differentiate letters, and optional like short vowels which are used to emphasis consonants. Most indigenous and well trained writers often do not use all or some of these second class of diacritics, and expert readers can infer their presence within the context of the writer text. In this paper, we investigate the use of diacritics shapes and other characteristic as parameters of feature vectors for Arabic writer identification/verification. Segmentation techniques are used to extract the diacritics-based feature vectors from examples of Arabic handwritten text. The results of evaluation test will be presented, which has been carried out on an in-house database of 50 writers. Also the viability of using diacritics for writer recognition will be demonstrated.

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.

Two-dimensional PCA-based human gait identification

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

Automated Coronal Loop Identification using Digital Image Processing Techniques

NASA Astrophysics Data System (ADS)

Lee, J. K.; Gary, G. A.; Newman, T. S.

2003-05-01

The results of a Master's thesis study of computer algorithms for automatic extraction and identification (i.e., collectively, "detection") of optically-thin, 3-dimensional, (solar) coronal-loop center "lines" from extreme ultraviolet and X-ray 2-dimensional images will be presented. The center lines, which can be considered to be splines, are proxies of magnetic field lines. Detecting the loops is challenging because there are no unique shapes, the loop edges are often indistinct, and because photon and detector noise heavily influence the images. Three techniques for detecting the projected magnetic field lines have been considered and will be described in the presentation. The three techniques used are (i) linear feature recognition of local patterns (related to the inertia-tensor concept), (ii) parametric space inferences via the Hough transform, and (iii) topological adaptive contours (snakes) that constrain curvature and continuity. Since coronal loop topology is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information that has also been incorporated into the detection process. Synthesized images have been generated to benchmark the suitability of the three techniques, and the performance of the three techniques on both synthesized and solar images will be presented and numerically evaluated in the presentation. The process of automatic detection of coronal loops is important in the reconstruction of the coronal magnetic field where the derived magnetic field lines provide a boundary condition for magnetic models ( cf. , Gary (2001, Solar Phys., 203, 71) and Wiegelmann & Neukirch (2002, Solar Phys., 208, 233)). . This work was supported by NASA's Office of Space Science - Solar and Heliospheric Physics Supporting Research and Technology Program.

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.

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.

Personal identification based on prescription eyewear.

PubMed

Berg, Gregory E; Collins, Randall S

2007-03-01

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

Aerodynamic measurement techniques. [laser based diagnostic techniques

NASA Technical Reports Server (NTRS)

Hunter, W. W., Jr.

1976-01-01

Laser characteristics of intensity, monochromatic, spatial coherence, and temporal coherence were developed to advance laser based diagnostic techniques for aerodynamic related research. Two broad categories of visualization and optical measurements were considered, and three techniques received significant attention. These are holography, laser velocimetry, and Raman scattering. Examples of the quantitative laser velocimeter and Raman scattering measurements of velocity, temperature, and density indicated the potential of these nonintrusive techniques.

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.

Comparison of perioperative outcomes between endoscope-assisted technique and handheld acoustic Doppler for perforator identification in fasciocutaneous flaps.

PubMed

Huang, Jen-Wu; Huang, Chih-Sheng; Shih, Yu-Chung; Perng, Cherng-Kang; Lin, Yi-Ying; Wu, Szu-Hsien

2018-06-01

The endoscopic technique has been utilized to harvest muscle flaps and detect perforators of fasciocutaneous flaps. This study aimed to compare the perioperative outcomes between the endoscope-assisted technique and handheld acoustic Doppler for perforator identification in fasciocutaneous flaps.This retrospective case-control study included patients who underwent fasciocutaneous flap reconstruction for traumatic soft tissue defects. In the case group, perforator identification was assisted by the endoscope-assisted technique. In the control group, age- and sex-matched patients received handheld acoustic Doppler to detect perforators. Perioperative outcomes, flap characteristics, and postoperative complications were compared.There were 12 patients in the case group and 12 in the control group. Compared with the control group, the case group had a significantly shorter length of donor-site wounds (9 cm vs 12 cm, P = .023) and a significantly smaller proportion of patients receiving skin grafting at the donor sites (0% vs 41.7%, P = .037). The case group had a longer operative time, but the difference was not statistically significant (180 minutes vs 150 minutes, P = .367). The amount of blood loss, the time length of postoperative drainage, and complications did not significantly differ between the 2 groups.The endoscope-assisted technique for perforator identification of fasciocutaneous flaps provided less donor-site morbidity and a significantly shorter length of donor-site wounds than the conventional handheld acoustic Doppler, which suggests that this technique could be a valuable alternative when a precise design is indicated.

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.

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

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.

Fast identification of the conduction-type of nanomaterials by field emission technique.

PubMed

Yang, Xun; Gan, Haibo; Tian, Yan; Peng, Luxi; Xu, Ningsheng; Chen, Jun; Chen, Huanjun; Deng, Shaozhi; Liang, Shi-Dong; Liu, Fei

2017-10-12

There are more or less dopants or defects existing in nanomaterials, so they usually have different conduct-types even for the same substrate. Therefore, fast identification of the conduction-type of nanomaterials is very essential for their practical application in functional nanodevices. Here we use the field emission (FE) technique to research nanomaterials and establish a generalized Schottky-Nordheim (SN) model, in which an important parameter λ (the image potential factor) is first introduced to describe the effective image potential. By regarding λ as the criterion, their energy-band structure can be identified: (a) λ = 1: metal; (b) 0.5 < λ < 1: n-type semiconductor; (c) 0 < λ < 0.5: p-type semiconductor. Moreover, this method can be utilized to qualitatively evaluate the doping-degree for a given semiconductor. We test numerically and experimentally a group of nanomaterial emitters and all results agree with our theoretical results very well, which suggests that our method based on FE measurements should be an ideal and powerful tool to fast ascertain the conduction-type of nanomaterials.

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

NASA Astrophysics Data System (ADS)

Porwal, Utkarsh; Rajan, Sreeranga; Govindaraju, Venu

2012-01-01

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

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 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

Air versus saline in the loss of resistance technique for identification of the epidural space.

PubMed

Antibas, Pedro L; do Nascimento Junior, Paulo; Braz, Leandro G; Vitor Pereira Doles, João; Módolo, Norma S P; El Dib, Regina

2014-07-18

The success of epidural anaesthesia depends on correct identification of the epidural space. For several decades, the decision of whether to use air or physiological saline during the loss of resistance technique for identification of the epidural space has been governed by the personal experience of the anaesthesiologist. Epidural block remains one of the main regional anaesthesia techniques. It is used for surgical anaesthesia, obstetrical analgesia, postoperative analgesia and treatment of chronic pain and as a complement to general anaesthesia. The sensation felt by the anaesthesiologist from the syringe plunger with loss of resistance is different when air is compared with saline (fluid). Frequently fluid allows a rapid change from resistance to non-resistance and increased movement of the plunger. However, the ideal technique for identification of the epidural space remains unclear. • To evaluate the efficacy and safety of both air and saline in the loss of resistance technique for identification of the epidural space.• To evaluate complications related to the air or saline injected. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (2013, Issue 9), MEDLINE, EMBASE and the Latin American and Caribbean Health Science Information Database (LILACS) (from inception to September 2013). We applied no language restrictions. The date of the most recent search was 7 September 2013. We included randomized controlled trials (RCTs) and quasi-randomized controlled trials (quasi-RCTs) on air and saline in the loss of resistance technique for identification of the epidural space. Two review authors independently assessed trial quality and extracted data. We included in the review seven studies with a total of 852 participants. The methodological quality of the included studies was generally ranked as showing low risk of bias in most domains, with the exception of one study, which did not mask participants. We were able to include data from 838

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

NASA Astrophysics Data System (ADS)

Fanos, Ali Mutar; Pradhan, Biswajeet

2018-04-01

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

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.

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.

Non-Halal biomarkers identification based on Fourier Transform Infrared Spectroscopy (FTIR) and Gas Chromatography-Time of Flight Mass Spectroscopy (GC-TOF MS) techniques

NASA Astrophysics Data System (ADS)

Witjaksono, Gunawan; Saputra, Irwan; Latief, Marsad; Jaswir, Irwandi; Akmeliawati, Rini; Abdelkreem Saeed Rabih, Almur

2017-11-01

Consumption of meat from halal (lawful) sources is essential for Muslims. The identification of non-halal meat is one of the main issues that face consumers in meat markets, especially in non-Islamic countries. Pig is one of the non-halal sources of meat, and hence pig meat and its derivatives are forbidden for Muslims to consume. Although several studies have been conducted to identify the biomarkers for nonhalal meats like pig meat, these studies are still in their infancy stages, and as a result there is no universal biomarker which could be used for clear cut identification. The purpose of this paper is to use Fourier Transform Infrared Spectroscopy (FTIR) and Gas Chromatography-Time of Flight Mass Spectroscopy (GC-TOF MS) techniques to study fat of pig, cow, lamb and chicken to find possible biomarkers for pig fat (lard) identification. FTIR results showed that lard and chicken fat have unique peaks at wavenumbers 1159.6 cm-1, 1743.4 cm-1, 2853.1 cm-1 and 2922.5 cm-1 compared to lamb and beef fats which did not show peaks at these wavenumbers. On the other hand, GC/MS-TOF results showed that the concentration of 1,2,3-trimethyl-Benzene, Indane, and Undecane in lard are 250, 14.5 and 1.28 times higher than their concentrations in chicken fat, respectively, and 91.4, 2.3 and 1.24 times higher than their concentrations in cow fat, respectively. These initial results clearly indicate that there is a possibility to find biomarkers for non-halal identification.

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

NASA Technical Reports Server (NTRS)

Innocenti, M.; Napolitano, M.

2003-01-01

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

A 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.

WE-G-204-08: Optimized Digital Radiographic Technique for Lost Surgical Devices/Needle Identification

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

Gorman, A; Seabrook, G; Brakken, A

Purpose: Small surgical devices and needles are used in many surgical procedures. Conventionally, an x-ray film is taken to identify missing devices/needles if post procedure count is incorrect. There is no data to indicate smallest surgical devices/needles that can be identified with digital radiography (DR), and its optimized acquisition technique. Methods: In this study, the DR equipment used is a Canon RadPro mobile with CXDI-70c wireless DR plate, and the same DR plate on a fixed Siemens Multix unit. Small surgical devices and needles tested include Rubber Shod, Bulldog, Fogarty Hydrogrip, and needles with sizes 3-0 C-T1 through 8-0 BV175-6.more » They are imaged with PMMA block phantoms with thickness of 2–8 inch, and an abdomen phantom. Various DR techniques are used. Images are reviewed on the portable x-ray acquisition display, a clinical workstation, and a diagnostic workstation. Results: all small surgical devices and needles are visible in portable DR images with 2–8 inch of PMMA. However, when they are imaged with the abdomen phantom plus 2 inch of PMMA, needles smaller than 9.3 mm length can not be visualized at the optimized technique of 81 kV and 16 mAs. There is no significant difference in visualization with various techniques, or between mobile and fixed radiography unit. However, there is noticeable difference in visualizing the smallest needle on a diagnostic reading workstation compared to the acquisition display on a portable x-ray unit. Conclusion: DR images should be reviewed on a diagnostic reading workstation. Using optimized DR techniques, the smallest needle that can be identified on all phantom studies is 9.3 mm. Sample DR images of various small surgical devices/needles available on diagnostic workstation for comparison may improve their identification. Further in vivo study is needed to confirm the optimized digital radiography technique for identification of lost small surgical devices and needles.« less

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

NASA Astrophysics Data System (ADS)

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

2000-06-01

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

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.

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

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

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

PubMed

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

2017-09-06

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

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.

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.

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.

Metamodel-based inverse method for parameter identification: elastic-plastic damage model

NASA Astrophysics Data System (ADS)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

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.

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.

MS-Based Analytical Techniques: Advances in Spray-Based Methods and EI-LC-MS Applications

PubMed Central

Medina, Isabel; Cappiello, Achille; Careri, Maria

2018-01-01

Mass spectrometry is the most powerful technique for the detection and identification of organic compounds. It can provide molecular weight information and a wealth of structural details that give a unique fingerprint for each analyte. Due to these characteristics, mass spectrometry-based analytical methods are showing an increasing interest in the scientific community, especially in food safety, environmental, and forensic investigation areas where the simultaneous detection of targeted and nontargeted compounds represents a key factor. In addition, safety risks can be identified at the early stage through online and real-time analytical methodologies. In this context, several efforts have been made to achieve analytical instrumentation able to perform real-time analysis in the native environment of samples and to generate highly informative spectra. This review article provides a survey of some instrumental innovations and their applications with particular attention to spray-based MS methods and food analysis issues. The survey will attempt to cover the state of the art from 2012 up to 2017. PMID:29850370

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.

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.

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.

MID Plot: a new lithology technique. [Matrix identification plot

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

Clavier, C.; Rust, D.H.

1976-01-01

Lithology interpretation by the Litho-Porosity (M-N) method has been used for years, but is evidently too cumbersome and ambiguous for widespread acceptance as a field technique. To set aside these objections, another method has been devised. Instead of the log-derived parameters M and N, the MID Plot uses quasi-physical quantities, (rho/sub ma/)/sub a/ and (..delta..t/sub ma/)/sub a/, as its porosity-independent variables. These parameters, taken from suitably scaled Neutron-Density and Sonic-Neutron crossplots, define a unique matrix mineral or mixture for each point on the logs. The matrix points on the MID Plot thus remain constant in spite of changes in mudmore » filtrate, porosity, or neutron tool types (all of which significantly affect the M-N Plot). This new development is expected to bring welcome relief in areas where lithology identification is a routine part of log analysis.« less

Using Web-Based Key Character and Classification Instruction for Teaching Undergraduate Students Insect Identification

NASA Astrophysics Data System (ADS)

Golick, Douglas A.; Heng-Moss, Tiffany M.; Steckelberg, Allen L.; Brooks, David. W.; Higley, Leon G.; Fowler, David

2013-08-01

The purpose of the study was to determine whether undergraduate students receiving web-based instruction based on traditional, key character, or classification instruction differed in their performance of insect identification tasks. All groups showed a significant improvement in insect identifications on pre- and post-two-dimensional picture specimen quizzes. The study also determined student performance on insect identification tasks was not as good as for family-level identification as compared to broader insect orders and arthropod classification identification tasks. Finally, students erred significantly more by misidentification than misspelling specimen names on prepared specimen quizzes. Results of this study support that short web-based insect identification exercises can improve insect identification performance. Also included is a discussion of how these results can be used in teaching and future research on biological identification.

Identification of Potential Fishing Grounds Using Geospatial Technique

NASA Astrophysics Data System (ADS)

Abdullah, Muhammad

2016-07-01

Fishery resources surveys using actual sampling and data collection methods require extensive ship time and sampling time. Informative data from satellite plays a vital role in fisheries application. Satellite Remote Sensing techniques can be used to detect fish aggregation just like visual fish identification ultimately these techniques can be used to predict the potential fishing zones by measuring the parameters which affect the distribution of fishes. Remote sensing is a time saving technique to locate fishery resources along the coast. Pakistan has a continental shelf area of 50,270 km2 and coastline length of 1,120 km. The total maritime zone of Pakistan is over 30 percent of the land area. Fishery plays an important role in the national economy. The marine fisheries sector is the main component, contributing about 57 percent in terms of production. Fishery is the most important economic activity in the villages and towns along the coast, and in most of the coastal villages and settlements it is the sole source of employment and income generation. Fishing by fishermen is done on the sole basis of repeated experiments and collection of information from other fishermen. Often they are in doubt about the location of potential fishing zones. This leads to waste of time and money, adversely affecting fishermen incomes and over or under-exploitation of fishing zones. The main purpose of this study was to map potential fishing grounds by identifying various environmental parameters which impact fish aggregation along the Pakistan coastline. The primary reason of this study is the fact that the fishing communities of Pakistan's coastal regions are extremely poor and lack knowledge of the modern tools and techniques that may be incorporated to enhance their yield and thus, improve their livelihood. Using geospatial techniques in order to accurately map the potential fishing zones based on sea surface temperature (SST) and chlorophyll -a content, in conjunction with

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

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.

Spatial assessment and source identification of heavy metals pollution in surface water using several chemometric techniques.

PubMed

Ismail, Azimah; Toriman, Mohd Ekhwan; Juahir, Hafizan; Zain, Sharifuddin Md; Habir, Nur Liyana Abdul; Retnam, Ananthy; Kamaruddin, Mohd Khairul Amri; Umar, Roslan; Azid, Azman

2016-05-15

This study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time. The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

A biometric identification system based on eigenpalm and eigenfinger features.

PubMed

Ribaric, Slobodan; Fratric, Ivan

2005-11-01

This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

Broad spectrum microarray for fingerprint-based bacterial species identification

PubMed Central

2010-01-01

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

Satellite angular velocity estimation based on star images and optical flow techniques.

PubMed

Fasano, Giancarmine; Rufino, Giancarlo; Accardo, Domenico; Grassi, Michele

2013-09-25

An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

Satellite Angular Velocity Estimation Based on Star Images and Optical Flow Techniques

PubMed Central

Fasano, Giancarmine; Rufino, Giancarlo; Accardo, Domenico; Grassi, Michele

2013-01-01

An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components. PMID:24072023

Writers Identification Based on Multiple Windows Features Mining

NASA Astrophysics Data System (ADS)

Fadhil, Murad Saadi; Alkawaz, Mohammed Hazim; Rehman, Amjad; Saba, Tanzila

2016-03-01

Now a days, writer identification is at high demand to identify the original writer of the script at high accuracy. The one of the main challenge in writer identification is how to extract the discriminative features of different authors' scripts to classify precisely. In this paper, the adaptive division method on the offline Latin script has been implemented using several variant window sizes. Fragments of binarized text a set of features are extracted and classified into clusters in the form of groups or classes. Finally, the proposed approach in this paper has been tested on various parameters in terms of text division and window sizes. It is observed that selection of the right window size yields a well positioned window division. The proposed approach is tested on IAM standard dataset (IAM, Institut für Informatik und angewandte Mathematik, University of Bern, Bern, Switzerland) that is a constraint free script database. Finally, achieved results are compared with several techniques reported in the literature.

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.…

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

Collaborative identification method for sea battlefield target based on deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Zheng, Guangdi; Pan, Mingbo; Liu, Wei; Wu, Xuetong

2018-03-01

The target identification of the sea battlefield is the prerequisite for the judgment of the enemy in the modern naval battle. In this paper, a collaborative identification method based on convolution neural network is proposed to identify the typical targets of sea battlefields. Different from the traditional single-input/single-output identification method, the proposed method constructs a multi-input/single-output co-identification architecture based on optimized convolution neural network and weighted D-S evidence theory. The simulation results show that

Model identification methodology for fluid-based inerters

NASA Astrophysics Data System (ADS)

Liu, Xiaofu; Jiang, Jason Zheng; Titurus, Branislav; Harrison, Andrew

2018-06-01

Inerter is the mechanical dual of the capacitor via the force-current analogy. It has the property that the force across the terminals is proportional to their relative acceleration. Compared with flywheel-based inerters, fluid-based forms have advantages of improved durability, inherent damping and simplicity of design. In order to improve the understanding of the physical behaviour of this fluid-based device, especially caused by the hydraulic resistance and inertial effects in the external tube, this work proposes a comprehensive model identification methodology. Firstly, a modelling procedure is established, which allows the topological arrangement of the mechanical networks to be obtained by mapping the damping, inertance and stiffness effects directly to their respective hydraulic counterparts. Secondly, an experimental sequence is followed, which separates the identification of friction, stiffness and various damping effects. Furthermore, an experimental set-up is introduced, where two pressure gauges are used to accurately measure the pressure drop across the external tube. The theoretical models with improved confidence are obtained using the proposed methodology for a helical-tube fluid inerter prototype. The sources of remaining discrepancies are further analysed.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

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.

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

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

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

Adding Personality to Gifted Identification: Relationships among Traditional and Personality-Based Constructs

ERIC Educational Resources Information Center

Carman, Carol A.

2011-01-01

One of the underutilized tools in gifted identification is personality-based measures. A multiple confirmatory factor analysis was utilized to examine the relationships between traditional identification methods and personality-based measures. The pattern of correlations indicated this model could be measuring two constructs, one related to…

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.

The public health impact of a new simple practical technique for collection and transfer of toxic jellyfish specimens and for nematocyst identification.

PubMed

Thaikruea, Lakkana; Santidherakul, Sineenart

2018-05-01

Our team aimed to create a new, simple, and inexpensive technique for collecting and transferring of toxic jellyfish specimens and for nematocysts identification. We collected tentacles of Chironex spp., Morbakka spp., and Physalia spp., and transferred them from the beaches by standard and by 'vacuum sticky tape' (VST) techniques. For the VST technique, our team placed the sticky tape on a tentacle and then folded it over to seal the tentacle in the equivalent of a vacuum. We kept the VST in room temperature. For nematocyst identification, we placed the VST on a glass microscope slide and took photographs down the microscope's eye piece using a mobile phone camera. The image quality was as good as when produced by standard techniques. Different classes of toxic jellyfish could be identified. Thus, VST is a potential public health breakthrough because it is practical, durable, inexpensive, allows good discrimination. It enables early warning of danger to health and rapid response via social network.

Energy Partitioning of Seismic Phases: Current Datasets and Techniques Aimed at Improving the Future of Event Identification

NASA Astrophysics Data System (ADS)

Bonner, J.

2006-05-01

Differences in energy partitioning of seismic phases from earthquakes and explosions provide the opportunity for event identification. In this talk, I will briefly review teleseismic Ms:mb and P/S ratio techniques that help identify events based on differences in compressional, shear, and surface wave energy generation from explosions and earthquakes. With the push to identify smaller yield explosions, the identification process has become increasingly complex as varied types of explosions, including chemical, mining, and nuclear, must be identified at regional distances. Thus, I will highlight some of the current views and problems associated with the energy partitioning of seismic phases from single- and delay-fired chemical explosions. One problem yet to have a universally accepted answer is whether the explosion and earthquake populations, based on the Ms:mb discriminants, should be separated at smaller magnitudes. I will briefly describe the datasets and theory that support either converging or parallel behavior of these populations. Also, I will discuss improvement to the currently used methods that will better constrain this problem in the future. I will also discuss the role of regional P/S ratios in identifying explosions. In particular, recent datasets from South Africa, Scandinavia, and the Western United States collected from earthquakes, single-fired chemical explosions, and/or delay-fired mining explosions have provide new insight into regional P, S, Lg, and Rg energy partitioning. Data from co-located mining and chemical explosions suggest that some mining explosions may be used for limited calibration of regional discriminants in regions where no historic explosion data is available.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-01-01

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

Initial planetary base construction techniques and machine implementation

NASA Technical Reports Server (NTRS)

Crockford, William W.

1987-01-01

Conceptual designs of (1) initial planetary base structures, and (2) an unmanned machine to perform the construction of these structures using materials local to the planet are presented. Rock melting is suggested as a possible technique to be used by the machine in fabricating roads, platforms, and interlocking bricks. Identification of problem areas in machine design and materials processing is accomplished. The feasibility of the designs is contingent upon favorable results of an analysis of the engineering behavior of the product materials. The analysis requires knowledge of several parameters for solution of the constitutive equations of the theory of elasticity. An initial collection of these parameters is presented which helps to define research needed to perform a realistic feasibility study. A qualitative approach to estimating power and mass lift requirements for the proposed machine is used which employs specifications of currently available equipment. An initial, unmanned mission scenario is discussed with emphasis on identifying uncompleted tasks and suggesting design considerations for vehicles and primitive structures which use the products of the machine processing.

Research of mine water source identification based on LIF technology

NASA Astrophysics Data System (ADS)

Zhou, Mengran; Yan, Pengcheng

2016-09-01

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

Village Building Identification Based on Ensemble Convolutional Neural Networks

PubMed Central

Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

2017-01-01

In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

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.

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.

Identification and quantitation of semi-crystalline microplastics using image analysis and differential scanning calorimetry.

PubMed

Rodríguez Chialanza, Mauricio; Sierra, Ignacio; Pérez Parada, Andrés; Fornaro, Laura

2018-06-01

There are several techniques used to analyze microplastics. These are often based on a combination of visual and spectroscopic techniques. Here we introduce an alternative workflow for identification and mass quantitation through a combination of optical microscopy with image analysis (IA) and differential scanning calorimetry (DSC). We studied four synthetic polymers with environmental concern: low and high density polyethylene (LDPE and HDPE, respectively), polypropylene (PP), and polyethylene terephthalate (PET). Selected experiments were conducted to investigate (i) particle characterization and counting procedures based on image analysis with open-source software, (ii) chemical identification of microplastics based on DSC signal processing, (iii) dependence of particle size on DSC signal, and (iv) quantitation of microplastics mass based on DSC signal. We describe the potential and limitations of these techniques to increase reliability for microplastic analysis. Particle size demonstrated to have particular incidence in the qualitative and quantitative performance of DSC signals. Both, identification (based on characteristic onset temperature) and mass quantitation (based on heat flow) showed to be affected by particle size. As a result, a proper sample treatment which includes sieving of suspended particles is particularly required for this analytical approach.

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.

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.

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

Various extraction and analytical techniques for isolation and identification of secondary metabolites from Nigella sativa seeds.

PubMed

Liu, X; Abd El-Aty, A M; Shim, J-H

2011-10-01

Nigella sativa L. (black cumin), commonly known as black seed, is a member of the Ranunculaceae family. This seed is used as a natural remedy in many Middle Eastern and Far Eastern countries. Extracts prepared from N. sativa have, for centuries, been used for medical purposes. Thus far, the organic compounds in N. sativa, including alkaloids, steroids, carbohydrates, flavonoids, fatty acids, etc. have been fairly well characterized. Herein, we summarize some new extraction techniques, including microwave assisted extraction (MAE) and supercritical extraction techniques (SFE), in addition to the classical method of hydrodistillation (HD), which have been employed for isolation and various analytical techniques used for the identification of secondary metabolites in black seed. We believe that some compounds contained in N. sativa remain to be identified, and that high-throughput screening could help to identify new compounds. A study addressing environmentally-friendly techniques that have minimal or no environmental effects is currently underway in our laboratory.

Analysis of Culture-Dependent versus Culture-Independent Techniques for Identification of Bacteria in Clinically Obtained Bronchoalveolar Lavage Fluid

PubMed Central

Dickson, Robert P.; Erb-Downward, John R.; Prescott, Hallie C.; Martinez, Fernando J.; Curtis, Jeffrey L.; Lama, Vibha N.

2014-01-01

The diagnosis and management of pneumonia are limited by the use of culture-based techniques of microbial identification, which may fail to identify unculturable, fastidious, and metabolically active viable but unculturable bacteria. Novel high-throughput culture-independent techniques hold promise but have not been systematically compared to conventional culture. We analyzed 46 clinically obtained bronchoalveolar lavage (BAL) fluid specimens from symptomatic and asymptomatic lung transplant recipients both by culture (using a clinical microbiology laboratory protocol) and by bacterial 16S rRNA gene pyrosequencing. Bacteria were identified in 44 of 46 (95.7%) BAL fluid specimens by culture-independent sequencing, significantly more than the number of specimens in which bacteria were detected (37 of 46, 80.4%, P ≤ 0.05) or “pathogen” species reported (18 of 46, 39.1%, P ≤ 0.0001) via culture. Identification of bacteria by culture was positively associated with culture-independent indices of infection (total bacterial DNA burden and low bacterial community diversity) (P ≤ 0.01). In BAL fluid specimens with no culture growth, the amount of bacterial DNA was greater than that in reagent and rinse controls, and communities were markedly dominated by select Gammaproteobacteria, notably Escherichia species and Pseudomonas fluorescens. Culture growth above the threshold of 104 CFU/ml was correlated with increased bacterial DNA burden (P < 0.01), decreased community diversity (P < 0.05), and increased relative abundance of Pseudomonas aeruginosa (P < 0.001). We present two case studies in which culture-independent techniques identified a respiratory pathogen missed by culture and clarified whether a cultured “oral flora” species represented a state of acute infection. In summary, we found that bacterial culture of BAL fluid is largely effective in discriminating acute infection from its absence and identified some specific limitations of BAL fluid culture in

Analysis of culture-dependent versus culture-independent techniques for identification of bacteria in clinically obtained bronchoalveolar lavage fluid.

PubMed

Dickson, Robert P; Erb-Downward, John R; Prescott, Hallie C; Martinez, Fernando J; Curtis, Jeffrey L; Lama, Vibha N; Huffnagle, Gary B

2014-10-01

The diagnosis and management of pneumonia are limited by the use of culture-based techniques of microbial identification, which may fail to identify unculturable, fastidious, and metabolically active viable but unculturable bacteria. Novel high-throughput culture-independent techniques hold promise but have not been systematically compared to conventional culture. We analyzed 46 clinically obtained bronchoalveolar lavage (BAL) fluid specimens from symptomatic and asymptomatic lung transplant recipients both by culture (using a clinical microbiology laboratory protocol) and by bacterial 16S rRNA gene pyrosequencing. Bacteria were identified in 44 of 46 (95.7%) BAL fluid specimens by culture-independent sequencing, significantly more than the number of specimens in which bacteria were detected (37 of 46, 80.4%, P ≤ 0.05) or "pathogen" species reported (18 of 46, 39.1%, P ≤ 0.0001) via culture. Identification of bacteria by culture was positively associated with culture-independent indices of infection (total bacterial DNA burden and low bacterial community diversity) (P ≤ 0.01). In BAL fluid specimens with no culture growth, the amount of bacterial DNA was greater than that in reagent and rinse controls, and communities were markedly dominated by select Gammaproteobacteria, notably Escherichia species and Pseudomonas fluorescens. Culture growth above the threshold of 10(4) CFU/ml was correlated with increased bacterial DNA burden (P < 0.01), decreased community diversity (P < 0.05), and increased relative abundance of Pseudomonas aeruginosa (P < 0.001). We present two case studies in which culture-independent techniques identified a respiratory pathogen missed by culture and clarified whether a cultured "oral flora" species represented a state of acute infection. In summary, we found that bacterial culture of BAL fluid is largely effective in discriminating acute infection from its absence and identified some specific limitations of BAL fluid culture in the

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

PubMed

Sufi, Fahim; Khalil, Ibrahim; Mahmood, Abdun

2011-12-01

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

FVID: Fishing Vessel Type Identification Based on VMS Trajectories

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

WiFi-based person identification

NASA Astrophysics Data System (ADS)

Yuan, Jing

2016-10-01

There has been increased interest in WIFI devices equipped with multiple antennas, which brings various wireless sensing applications such as localization, gesture identification and motion tracking. WIFI-based sensing has a lot of benefits such as device Free, which has shown great potential in smart scenarios. In this paper, we present WIP, a system that can distinguish a person from a small group of people. We prove that Channel State Information (CSI) can identify a person's gait. From the related-work, different people have different gait features. Thus the CSI-based gait features can be used to identify a person. We then proposed a machine-learning model-ANN to classify different person. The results show that ANN has a good performance in our scenario.

Fragment-based hit identification: thinking in 3D.

PubMed

Morley, Andrew D; Pugliese, Angelo; Birchall, Kristian; Bower, Justin; Brennan, Paul; Brown, Nathan; Chapman, Tim; Drysdale, Martin; Gilbert, Ian H; Hoelder, Swen; Jordan, Allan; Ley, Steven V; Merritt, Andy; Miller, David; Swarbrick, Martin E; Wyatt, Paul G

2013-12-01

The identification of high-quality hits during the early phases of drug discovery is essential if projects are to have a realistic chance of progressing into clinical development and delivering marketed drugs. As the pharmaceutical industry goes through unprecedented change, there are increasing opportunities to collaborate via pre-competitive networks to marshal multifunctional resources and knowledge to drive impactful, innovative science. The 3D Fragment Consortium is developing fragment-screening libraries with enhanced 3D characteristics and evaluating their effect on the quality of fragment-based hit identification (FBHI) projects. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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.

Molecular-Based Optical Measurement Techniques for Transition and Turbulence in High-Speed Flow

NASA Technical Reports Server (NTRS)

Bathel, Brett F.; Danehy, Paul M.; Cutler, Andrew D.

2013-01-01

High-speed laminar-to-turbulent transition and turbulence affect the control of flight vehicles, the heat transfer rate to a flight vehicle's surface, the material selected to protect such vehicles from high heating loads, the ultimate weight of a flight vehicle due to the presence of thermal protection systems, the efficiency of fuel-air mixing processes in high-speed combustion applications, etc. Gaining a fundamental understanding of the physical mechanisms involved in the transition process will lead to the development of predictive capabilities that can identify transition location and its impact on parameters like surface heating. Currently, there is no general theory that can completely describe the transition-to-turbulence process. However, transition research has led to the identification of the predominant pathways by which this process occurs. For a truly physics-based model of transition to be developed, the individual stages in the paths leading to the onset of fully turbulent flow must be well understood. This requires that each pathway be computationally modeled and experimentally characterized and validated. This may also lead to the discovery of new physical pathways. This document is intended to describe molecular based measurement techniques that have been developed, addressing the needs of the high-speed transition-to-turbulence and high-speed turbulence research fields. In particular, we focus on techniques that have either been used to study high speed transition and turbulence or techniques that show promise for studying these flows. This review is not exhaustive. In addition to the probe-based techniques described in the previous paragraph, several other classes of measurement techniques that are, or could be, used to study high speed transition and turbulence are excluded from this manuscript. For example, surface measurement techniques such as pressure and temperature paint, phosphor thermography, skin friction measurements and

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.

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

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

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

2011-09-23

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

Yangon River Geomorphology Identification and its Enviromental Imapacts Analsysi by Optical and Radar Sensing Techniques

NASA Astrophysics Data System (ADS)

Lwin, A.; Khaing, M. M.

2012-07-01

The Yangon river, also known as the Rangoon river, is about 40 km long (25miles), and flows from southern Myanmar as an outlet of the Irrawaddy (Ayeyarwady) river into the Ayeyarwady delta. The Yangon river drains the Pegu Mountains; both the Yangon and the Pathein rivers enter the Ayeyarwady at the delta. Fluvial geomorphology is based primarily on rivers of manageable dimensions. The emphasis is on geomorphology, sedimentology of Yangon river and techniques for their identification and management. Present techniques such as remote sensing have made it easier to investigate and interpret in details analysis of river geomorphology. In this paper, attempt has been made the complicated issues of geomorphology, sedimentation patterns and management of river system and evolution studied. The analysis was carried out for the impact of land use/ land cover (LULC) changes on stream flow patterns. The hydrologic response to intense, flood producing rainfall events bears the signatures of the geomorphic structure of the channel network and of the characteristic slope lengths defining the drainage density of the basin. The interpretation of the hydrologic response as the travel time distribution of a water particle randomly injected in a distributed manner across the landscape inspired many geomorphic insights. In 2008, Cyclone Nargis was seriously damaged to mangrove area and its biodiversity system in and around of Yangon river terraces. A combination of digital image processing techniques was employed for enhancement and classification process. It is observed from the study that middle infra red band (0.77mm - 0.86mm) is highly suitable for mapping mangroves. Two major classes of mangroves, dense and open mangroves were delineated from the digital data.

Rapid identification of red-flesh loquat cultivars using EST-SSR markers based on manual cultivar identification diagram strategy.

PubMed

Li, X Y; Xu, H X; Chen, J W

2014-04-29

Manual cultivar identification diagram is a new strategy for plant cultivar identification based on DNA markers, providing information to efficiently separate cultivars. We tested 25 pairs of apple EST-SSR primers for amplification of PCR products from loquat cultivars. These EST-SSR primers provided clear amplification products from the loquat cultivars, with a relatively high transferability rate of 84% to loquat; 11 pairs of primers amplified polymorphic products. After analysis of 24 red-fleshed loquat accessions, we found that only 7 pairs of primers could clearly separate all of them. A cultivar identification diagram of the 24 cultivars was constructed using polymorphic bands from the DNA fingerprints and EST-SSR primers. Any two of the 24 cultivars could be rapidly separated from each other, according to the polymorphic bands from the cultivars; the corresponding primers were marked in the correct position on the cultivar identification diagram. This red-flesh loquat cultivar identification diagram can separate the 24 red-flesh loquat cultivars, which is of benefit for loquat cultivar identification for germplasm management and breeding programs.

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

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.

White blood cells identification system based on convolutional deep neural learning networks.

PubMed

Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

2017-11-16

White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

A randomised approach for NARX model identification based on a multivariate Bernoulli distribution

NASA Astrophysics Data System (ADS)

Bianchi, F.; Falsone, A.; Prandini, M.; Piroddi, L.

2017-04-01

The identification of polynomial NARX models is typically performed by incremental model building techniques. These methods assess the importance of each regressor based on the evaluation of partial individual models, which may ultimately lead to erroneous model selections. A more robust assessment of the significance of a specific model term can be obtained by considering ensembles of models, as done by the RaMSS algorithm. In that context, the identification task is formulated in a probabilistic fashion and a Bernoulli distribution is employed to represent the probability that a regressor belongs to the target model. Then, samples of the model distribution are collected to gather reliable information to update it, until convergence to a specific model. The basic RaMSS algorithm employs multiple independent univariate Bernoulli distributions associated to the different candidate model terms, thus overlooking the correlations between different terms, which are typically important in the selection process. Here, a multivariate Bernoulli distribution is employed, in which the sampling of a given term is conditioned by the sampling of the others. The added complexity inherent in considering the regressor correlation properties is more than compensated by the achievable improvements in terms of accuracy of the model selection process.

The crash of Colgan Air flight 3407: Advanced techniques in victim identification.

PubMed

Bush, Mary; Miller, Raymond

2011-12-01

Identifying disaster victims by means of dental records is a well-established technique. In cases in which high temperatures are involved, destruction of the structural relationship of the dentition necessitates that adjunctive aids be used in the identification process. Analysis of tooth fragments by means of scanning electron microscopy with energy dispersive x-ray spectroscopy can reveal evidence of restorative procedures, as well as trace amounts of dental materials remaining on tooth surfaces. In addition, dental materials can be analyzed and identified according to brand, even if the materials have been cremated. The authors describe the identification of three victims from the crash of Colgan Air flight 3407, a commuter airplane flying between Newark, N.J., and Buffalo, N.Y. The crash involved a fire, and a portion of the airplane burned for nearly 11 hours. Dental fragments that had restorative material adhering to them were recovered and analyzed. These fragments contained corroborative information that helped confirm the identity of the victims. Detailed record keeping is part of clinical practice. The level of detail present in dental records can affect the ability of forensic odontologists to determine the identity of a victim's remains. Documenting the brand names of dental materials used in restorative procedures can make the difference between identifying and not identifying a victim's remains.

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.

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.

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.

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.

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

PubMed

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

2015-04-01

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

DNA barcode-based molecular identification system for fish species.

PubMed

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

2010-12-01

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

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

PubMed

St Quinton, Tom; Brunton, Julie A

2018-06-01

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. A purposive sample of 22 first-year undergraduate students (n = 8 men; M age  = 19.8 years, SD = 1.3 years) attending a university in the North of England was used. Focus groups were audio-recorded; recordings were transcribed verbatim, analyzed thematically, and coded for recurrent themes. The data revealed 14 reasons regarding enjoyment, 11 reasons for friends' approval, 11 reasons for friends' own participation, 14 reasons for the approval of family members, and 10 solutions to time constraints. Twelve distinct techniques were suggested to attend to these reasons and solutions. This qualitative research will be used to inform the development of a theory-based intervention to increase students' participation in university recreational sports.

Thermoluminescence of Antarctic meteorites: A rapid screening technique for terrestrial age estimation, pairing studies and identification of specimens with unusual prefall histories

NASA Technical Reports Server (NTRS)

Sutton, S. R.; Walker, R. M.

1986-01-01

Thermoluminescence (TL) is a promising technique for rapid screening of the large numbers of Antarctic meteorites, permitting identification of interesting specimens that can then be studied in detail by other, more definite techniques. Specifically, TL permits determination of rough terrestrial age, identification of potential paired groups and location of specimens with unusual pre-fall histories. Meteorites with long terrestrial ages are particularly valuable for studying transport and weathering mechanisms. Pairing studies are possible because TL variations among meteorites are large compared to variations within individual objects, especially for natural TL. Available TL data for several L3 fragments, three of which were paired by other techniques, are presented as an example of the use of TL parameters in pairing studies. Additional TL measurements, specifically a blind test, are recommended to satisfactorily establish the reliability of this pairing property. The TL measurements also identify fragments with unusual pre-fall histories, such an near-Sun orbits.

Identification of provenance rocks based on EPMA analyses of heavy minerals

NASA Astrophysics Data System (ADS)

Shimizu, M.; Sano, N.; Ueki, T.; Yonaga, Y.; Yasue, K. I.; Masakazu, N.

2017-12-01

Information on mountain building is significant in the field of geological disposal of high-level radioactive waste, because this affects long-term stability in groundwater flow system. Provenance analysis is one of effective approaches for understanding building process of mountains. Chemical compositions of heavy minerals, as well as their chronological data, can be an index for identification of provenance rocks. The accurate identification requires the measurement of as many grains as possible. In order to achieve an efficient provenance analysis, we developed a method for quick identification of heavy minerals using an Electron Probe Micro Analyzer (EPMA). In this method, heavy mineral grains extracted from a sample were aligned on a glass slide and mounted in a resin. Concentration of 28 elements was measured for 300-500 grains per sample using EPMA. To measure as many grains as possible, we prioritized swiftness of measurement over precision, configuring measurement time of about 3.5 minutes for each grain. Identification of heavy minerals was based on their chemical composition. We developed a Microsoft® Excel® spread sheet input criteria of mineral identification using a typical range of chemical compositions for each mineral. The grains of <80 wt.% or >110 wt.% total were rejected. The criteria of mineral identification were revised through the comparison between mineral identification by optical microscopy and chemical compositions of grains classified as "unknown minerals". Provenance rocks can be identified based on abundance ratio of identified minerals. If no significant difference of the abundance ratio was found among source rocks, chemical composition of specific minerals was used as another index. This method was applied to the sediments of some regions in Japan where provenance rocks had lithological variations but similar formation ages. Consequently, the provenance rocks were identified based on chemical compositions of heavy minerals

Implementation options for DNA-based identification into ecological status assessment under the European Water Framework Directive.

PubMed

Hering, Daniel; Borja, Angel; Jones, J Iwan; Pont, Didier; Boets, Pieter; Bouchez, Agnes; Bruce, Kat; Drakare, Stina; Hänfling, Bernd; Kahlert, Maria; Leese, Florian; Meissner, Kristian; Mergen, Patricia; Reyjol, Yorick; Segurado, Pedro; Vogler, Alfried; Kelly, Martyn

2018-07-01

Assessment of ecological status for the European Water Framework Directive (WFD) is based on "Biological Quality Elements" (BQEs), namely phytoplankton, benthic flora, benthic invertebrates and fish. Morphological identification of these organisms is a time-consuming and expensive procedure. Here, we assess the options for complementing and, perhaps, replacing morphological identification with procedures using eDNA, metabarcoding or similar approaches. We rate the applicability of DNA-based identification for the individual BQEs and water categories (rivers, lakes, transitional and coastal waters) against eleven criteria, summarised under the headlines representativeness (for example suitability of current sampling methods for DNA-based identification, errors from DNA-based species detection), sensitivity (for example capability to detect sensitive taxa, unassigned reads), precision of DNA-based identification (knowledge about uncertainty), comparability with conventional approaches (for example sensitivity of metrics to differences in DNA-based identification), cost effectiveness and environmental impact. Overall, suitability of DNA-based identification is particularly high for fish, as eDNA is a well-suited sampling approach which can replace expensive and potentially harmful methods such as gill-netting, trawling or electrofishing. Furthermore, there are attempts to replace absolute by relative abundance in metric calculations. For invertebrates and phytobenthos, the main challenges include the modification of indices and completing barcode libraries. For phytoplankton, the barcode libraries are even more problematic, due to the high taxonomic diversity in plankton samples. If current assessment concepts are kept, DNA-based identification is least appropriate for macrophytes (rivers, lakes) and angiosperms/macroalgae (transitional and coastal waters), which are surveyed rather than sampled. We discuss general implications of implementing DNA-based identification

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.

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.

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.

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.

Identification of species with DNA-based technology: current progress and challenges.

PubMed

Pereira, Filipe; Carneiro, João; Amorim, António

2008-01-01

One of the grand challenges of modern biology is to develop accurate and reliable technologies for a rapid screening of DNA sequence variation. This topic of research is of prime importance for the detection and identification of species in numerous fields of investigation, such as taxonomy, epidemiology, forensics, archaeology or ecology. Molecular identification is also central for the diagnosis, treatment and control of infections caused by different pathogens. In recent years, a variety of DNA-based approaches have been developed for the identification of individuals in a myriad of taxonomic groups. Here, we provide an overview of most commonly used assays, with emphasis on those based on DNA hybridizations, restriction enzymes, random PCR amplifications, species-specific PCR primers and DNA sequencing. A critical evaluation of all methods is presented focusing on their discriminatory power, reproducibility and user-friendliness. Having in mind that the current trend is to develop small-scale devices with a high-throughput capacity, we briefly review recent technological achievements for DNA analysis that offer great potentials for the identification of species.

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.

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.

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].

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.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

TL and ESR based identification of gamma-irradiated frozen fish using different hydrolysis techniques

NASA Astrophysics Data System (ADS)

Ahn, Jae-Jun; Akram, Kashif; Shahbaz, Hafiz Muhammad; Kwon, Joong-Ho

2014-12-01

Frozen fish fillets (walleye Pollack and Japanese Spanish mackerel) were selected as samples for irradiation (0-10 kGy) detection trials using different hydrolysis methods. Photostimulated luminescence (PSL)-based screening analysis for gamma-irradiated frozen fillets showed low sensitivity due to limited silicate mineral contents on the samples. Same limitations were found in the thermoluminescence (TL) analysis on mineral samples isolated by density separation method. However, acid (HCl) and alkali (KOH) hydrolysis methods were effective in getting enough minerals to carry out TL analysis, which was reconfirmed through the normalization step by calculating the TL ratios (TL1/TL2). For improved electron spin resonance (ESR) analysis, alkali and enzyme (alcalase) hydrolysis methods were compared in separating minute-bone fractions. The enzymatic method provided more clear radiation-specific hydroxyapatite radicals than that of the alkaline method. Different hydrolysis methods could extend the application of TL and ESR techniques in identifying the irradiation history of frozen fish fillets.

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

NASA Astrophysics Data System (ADS)

Ran, Chunjiang; Yang, Haitian; Zhang, Guoqing

2018-02-01

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

Development of a multilocus-based approach for sponge (phylum Porifera) identification: refinement and limitations.

PubMed

Yang, Qi; Franco, Christopher M M; Sorokin, Shirley J; Zhang, Wei

2017-02-02

For sponges (phylum Porifera), there is no reliable molecular protocol available for species identification. To address this gap, we developed a multilocus-based Sponge Identification Protocol (SIP) validated by a sample of 37 sponge species belonging to 10 orders from South Australia. The universal barcode COI mtDNA, 28S rRNA gene (D3-D5), and the nuclear ITS1-5.8S-ITS2 region were evaluated for their suitability and capacity for sponge identification. The highest Bit Score was applied to infer the identity. The reliability of SIP was validated by phylogenetic analysis. The 28S rRNA gene and COI mtDNA performed better than the ITS region in classifying sponges at various taxonomic levels. A major limitation is that the databases are not well populated and possess low diversity, making it difficult to conduct the molecular identification protocol. The identification is also impacted by the accuracy of the morphological classification of the sponges whose sequences have been submitted to the database. Re-examination of the morphological identification further demonstrated and improved the reliability of sponge identification by SIP. Integrated with morphological identification, the multilocus-based SIP offers an improved protocol for more reliable and effective sponge identification, by coupling the accuracy of different DNA markers.

Development of a multilocus-based approach for sponge (phylum Porifera) identification: refinement and limitations

PubMed Central

Yang, Qi; Franco, Christopher M. M.; Sorokin, Shirley J.; Zhang, Wei

2017-01-01

For sponges (phylum Porifera), there is no reliable molecular protocol available for species identification. To address this gap, we developed a multilocus-based Sponge Identification Protocol (SIP) validated by a sample of 37 sponge species belonging to 10 orders from South Australia. The universal barcode COI mtDNA, 28S rRNA gene (D3–D5), and the nuclear ITS1-5.8S-ITS2 region were evaluated for their suitability and capacity for sponge identification. The highest Bit Score was applied to infer the identity. The reliability of SIP was validated by phylogenetic analysis. The 28S rRNA gene and COI mtDNA performed better than the ITS region in classifying sponges at various taxonomic levels. A major limitation is that the databases are not well populated and possess low diversity, making it difficult to conduct the molecular identification protocol. The identification is also impacted by the accuracy of the morphological classification of the sponges whose sequences have been submitted to the database. Re-examination of the morphological identification further demonstrated and improved the reliability of sponge identification by SIP. Integrated with morphological identification, the multilocus-based SIP offers an improved protocol for more reliable and effective sponge identification, by coupling the accuracy of different DNA markers. PMID:28150727

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.

Using Web-Based Key Character and Classification Instruction for Teaching Undergraduate Students Insect Identification

ERIC Educational Resources Information Center

Golick, Douglas A.; Heng-Moss, Tiffany M.; Steckelberg, Allen L.; Brooks, David. W.; Higley, Leon G.; Fowler, David

2013-01-01

The purpose of the study was to determine whether undergraduate students receiving web-based instruction based on traditional, key character, or classification instruction differed in their performance of insect identification tasks. All groups showed a significant improvement in insect identifications on pre- and post-two-dimensional picture…

Competency-Based Occupational Programs: Identification, Structuring, and Evaluation.

ERIC Educational Resources Information Center

Pensacola Junior Coll., FL.

This publication presents results of the third phase of a Pensacola Junior College project to develop certain vocational programs as competency-based education. A brief narrative discusses the entire project--especially phase 3, which involved identification and definition of those competencies expected by an employer using input from an advisory…

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.

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

PubMed

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

2013-07-18

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

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

PubMed Central

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

2013-01-01

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

DNA-based techniques for authentication of processed food and food supplements.

PubMed

Lo, Yat-Tung; Shaw, Pang-Chui

2018-02-01

Authentication of food or food supplements with medicinal values is important to avoid adverse toxic effects, provide consumer rights, as well as for certification purpose. Compared to morphological and spectrometric techniques, molecular authentication is found to be accurate, sensitive and reliable. However, DNA degradation and inclusion of inhibitors may lead to failure in PCR amplification. This paper reviews on the existing DNA extraction and PCR protocols, and the use of small size DNA markers with sufficient discriminative power for molecular authentication. Various emerging new molecular techniques such as isothermal amplification for on-site diagnosis, next-generation sequencing for high-throughput species identification, high resolution melting analysis for quick species differentiation, DNA array techniques for rapid detection and quantitative determination in food products are also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.

PubMed

Schultheiss, Sebastian J; Busch, Wolfgang; Lohmann, Jan U; Kohlbacher, Oliver; Rätsch, Gunnar

2009-08-15

Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor (TF) binding sites in promoter regions of potential TF target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling, or heuristics to extend seed oligos. Such algorithms succeed in identifying single, relatively well-conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites, as those often found in cis-regulatory modules. We propose a new algorithm that combines the benefits of existing motif finding with the ones of support vector machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana, we were able to show that the newly developed strategy significantly improves the recognition of TF targets. The python source code (open source-licensed under GPL), the data for the experiments and a Galaxy-based web service are available at http://www.fml.mpg.de/raetsch/suppl/kirmes/.

Identification of metal elements by time-resolved LIBS technique in sediments lake the “Cisne”

NASA Astrophysics Data System (ADS)

Pacheco, P.; Arregui, E.; Álvarez, J.; Rangel, N.; Sarmiento, R.

2017-01-01

Laser induced breakdown spectroscopy (LIBS), is a kind of spectral method of atomic emission that uses pulses of radiation high energy laser as excitation source. One of the advantages of technical LIBS lies in the possibility of analyse the substances in any State of aggregation, already is solid, liquid or gaseous, even in colloids as aerosols, gels and others. Another advantage over other conventional techniques is the simultaneous analysis of elements present in a sample of multielement. This work is made in the use of this technique for the identification of metal pollutants in the Swan Lake sediment samples, collected by drilling cores. Plasmas were generated by focusing the radiation of Nd: YAG laser with an energy per pulse 13mJ and 4ns duration, wavelength of 532nm. The spectra of radiation from the plasmas of sediment were recorded with an Echelle spectrograph type coupled to an ICCD camera. The delay times were between 0.5μs and 7μs, while the gate width was of 2μs. To ensure the homogeneity of the plasmas, the sediment sample was placed in a positioning system of linear and rotary adjustment of smooth step synchronized with the trigger of the laser pulse. The registration of the spectra of the sediment to different times of delay, allowed to identify the lines prominent of the different elements present in the sample. The analysis of the Spectra allowed the identification of some elements in the sample as if, Ca, Na, Mg, and Al through the measurement of wavelengths of the prominent peaks.

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

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

DOE PAGES

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

2015-09-14

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

Health monitoring system for transmission shafts based on adaptive parameter identification

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

Tree Identification. Competency Based Teaching Materials in Horticulture.

ERIC Educational Resources Information Center

Legacy, Jim; And Others

This competency-based curriculum unit on tree identification is one of five developed for classroom use in teaching the landscape/nursery area of horticulture. The three sections are each divided into teaching content (in a question-and-answer format) and student skills that outline steps and factors for consideration. Topics covered include…

Identification of natural images and computer-generated graphics based on statistical and textural features.

PubMed

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Biometric identification based on novel frequency domain facial asymmetry measures

NASA Astrophysics Data System (ADS)

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

2005-03-01

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

Modulation format identification enabled by the digital frequency-offset loading technique for hitless coherent transceiver.

PubMed

Fu, Songnian; Xu, Zuying; Lu, Jianing; Jiang, Hexun; Wu, Qiong; Hu, Zhouyi; Tang, Ming; Liu, Deming; Chan, Calvin Chun-Kit

2018-03-19

We propose a blind and fast modulation format identification (MFI) enabled by the digital frequency-offset (FO) loading technique for hitless coherent transceiver. Since modulation format information is encoded to the FO distribution during digital signal processing (DSP) at the transmitter side (Tx), we can use the fast Fourier transformation based FO estimation (FFT-FOE) method to obtain the FO distribution of individual data block after constant modulus algorithm (CMA) pre-equalization at the receiver side, in order to realize non-data-aided (NDA) and fast MFI. The obtained FO can be also used for subsequent FO compensation (FOC), without additional complexity. We numerically investigate and experimentally verify the proposed MFI with high accuracy and fast format switching among 28 Gbaud dual-polarization (DP)-4/8/16/64QAM, time domain hybrid-4/16QAM, and set partitioning (SP)-128QAM. In particular, the proposed MFI brings no performance degradation, in term of tolerance of amplified spontaneous emission (ASE) noise, laser linewidth, and fiber nonlinearity. Finally, a hitless coherent transceiver enabled by the proposed MFI with switching-block of only 2048 symbols is demonstrated over 1500 km standard single mode fiber (SSMF) transmission.

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.

Community-Based Efforts to Increase the Identification of the Number of Gifted Minority Children.

ERIC Educational Resources Information Center

Davis, Paul I.

The document reports on a study of community-based identification of gifted and talented Black middle-school students, as an adjunct to formal identification procedures. A developmental framework for the identification of the gifted minority child was distributed to 17 known leaders in the Black community (including ministers, youth leaders in…

APRICOT: an integrated computational pipeline for the sequence-based identification and characterization of RNA-binding proteins.

PubMed

Sharan, Malvika; Förstner, Konrad U; Eulalio, Ana; Vogel, Jörg

2017-06-20

RNA-binding proteins (RBPs) have been established as core components of several post-transcriptional gene regulation mechanisms. Experimental techniques such as cross-linking and co-immunoprecipitation have enabled the identification of RBPs, RNA-binding domains (RBDs) and their regulatory roles in the eukaryotic species such as human and yeast in large-scale. In contrast, our knowledge of the number and potential diversity of RBPs in bacteria is poorer due to the technical challenges associated with the existing global screening approaches. We introduce APRICOT, a computational pipeline for the sequence-based identification and characterization of proteins using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences using position-specific scoring matrices and Hidden Markov Models of the functional domains and statistically scores them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them by several biological properties. Here we demonstrate the application and adaptability of the pipeline on large-scale protein sets, including the bacterial proteome of Escherichia coli. APRICOT showed better performance on various datasets compared to other existing tools for the sequence-based prediction of RBPs by achieving an average sensitivity and specificity of 0.90 and 0.91 respectively. The command-line tool and its documentation are available at https://pypi.python.org/pypi/bio-apricot. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Molecular markers for identification of P. ramorum and other Phytophthora species from diseased tissue

Treesearch

Frank N. Martin; Paul W. Tooley

2006-01-01

Molecular techniques have been developed for detection and identification of P. ramorum and other Phytophthora species that are based on the mitochondrially encoded sequences. One technique uses a Phytophthora genus specific primer to determine if a Phytophthora species is present, followed by...

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.

[Adverse Effect Predictions Based on Computational Toxicology Techniques and Large-scale Databases].

PubMed

Uesawa, Yoshihiro

2018-01-01

　Understanding the features of chemical structures related to the adverse effects of drugs is useful for identifying potential adverse effects of new drugs. This can be based on the limited information available from post-marketing surveillance, assessment of the potential toxicities of metabolites and illegal drugs with unclear characteristics, screening of lead compounds at the drug discovery stage, and identification of leads for the discovery of new pharmacological mechanisms. This present paper describes techniques used in computational toxicology to investigate the content of large-scale spontaneous report databases of adverse effects, and it is illustrated with examples. Furthermore, volcano plotting, a new visualization method for clarifying the relationships between drugs and adverse effects via comprehensive analyses, will be introduced. These analyses may produce a great amount of data that can be applied to drug repositioning.

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

PubMed

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

Identification of propulsion systems

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Constitutive error based parameter estimation technique for plate structures using free vibration signatures

NASA Astrophysics Data System (ADS)

Guchhait, Shyamal; Banerjee, Biswanath

2018-04-01

In this paper, a variant of constitutive equation error based material parameter estimation procedure for linear elastic plates is developed from partially measured free vibration sig-natures. It has been reported in many research articles that the mode shape curvatures are much more sensitive compared to mode shape themselves to localize inhomogeneity. Complying with this idea, an identification procedure is framed as an optimization problem where the proposed cost function measures the error in constitutive relation due to incompatible curvature/strain and moment/stress fields. Unlike standard constitutive equation error based procedure wherein a solution of a couple system is unavoidable in each iteration, we generate these incompatible fields via two linear solves. A simple, yet effective, penalty based approach is followed to incorporate measured data. The penalization parameter not only helps in incorporating corrupted measurement data weakly but also acts as a regularizer against the ill-posedness of the inverse problem. Explicit linear update formulas are then developed for anisotropic linear elastic material. Numerical examples are provided to show the applicability of the proposed technique. Finally, an experimental validation is also provided.

Identification Reduces Stigma of Mental Ill-Health: A Community-Based Study.

PubMed

Kearns, Michelle; Muldoon, Orla T; Msetfi, Rachel M; Surgenor, Paul W G

2018-03-01

The stigma surrounding mental ill-health is an important issue that affects likelihood of diagnosis and uptake of services, as those affected may work to avoid exposure, judgment, or any perceived loss in status associated with their mental ill-health. In this study, we drew upon social identity theory to examine how social group membership might influence the stigma surrounding mental ill-health. Participants from two urban centers in Ireland (N = 626) completed a survey measuring stigma of mental health, perceived social support as well as identification with two different social groups (community and religion). Mediation analysis showed that subjective identification with religious and community groups led to greater perceived social support and consequently lower perceived stigma of mental ill-health. Furthermore, findings indicated that high identification with more than one social group can lead to enhanced social resources, and that identification with a religious group was associated with greater community identification. This study thus extends the evidence base of group identification by demonstrating its relationship with stigma of mental ill-health, while also reinforcing how multiple identities can interact to enhance social resources crucial for well-being. © Society for Community Research and Action 2017.

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.

Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.; Pappa, R. S.

1985-01-01

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

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.

[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.

Applying knowledge compilation techniques to model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1991-01-01

Researchers in the area of knowledge compilation are developing general purpose techniques for improving the efficiency of knowledge-based systems. In this article, an attempt is made to define knowledge compilation, to characterize several classes of knowledge compilation techniques, and to illustrate how some of these techniques can be applied to improve the performance of model-based reasoning systems.

DNA-Based Identification of Forensically Important Blow Flies (Diptera: Calliphoridae) From India.

PubMed

Bharti, Meenakshi; Singh, Baneshwar

2017-09-01

Correct species identification is the first and the most important criteria in entomological evidence-based postmortem interval (PMI) estimation. Although morphological keys are available for species identification of adult blow flies, keys for immature stages are either lacking or are incomplete. In this study, cytochrome oxidase subunit 1 (COI) reference data were developed from nine species (belonging to three subfamilies, namely, Calliphorinae, Luciliinae, and Chrysomyinae) of blow flies from India. Seven of the nine species included in this study were found suitable for DNA-based identification using COI gene, because they showed nonoverlapping intra- (0.0-0.3%) and inter-(1.96-18.14%) specific diversity, and formed well-supported monophyletic clade in phylogenetic analysis. The remaining two species (i.e., Chrysomya megacephala (Fabricius) and Chrysomya chani Kurahashi) cannot be distinguished reliably using our database because they had a very low interspecific diversity (0.11%), and Ch. megacephala was paraphyletic with respect to Ch. chani in the phylogenetic analysis. We conclude that the COI gene is a useful marker for DNA-based identification of blow flies from India. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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.

[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.

Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA).

PubMed

Salimi, Nima; Loh, Kar Hoe; Kaur Dhillon, Sarinder; Chong, Ving Ching

2016-01-01

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

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

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).

Techniques for Enhancing Web-Based Education.

ERIC Educational Resources Information Center

Barbieri, Kathy; Mehringer, Susan

The Virtual Workshop is a World Wide Web-based set of modules on high performance computing developed at the Cornell Theory Center (CTC) (New York). This approach reaches a large audience, leverages staff effort, and poses challenges for developing interesting presentation techniques. This paper describes the following techniques with their…

Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier.

PubMed

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Rao, A R

2016-11-05

DNA barcoding is a molecular diagnostic method that allows automated and accurate identification of species based on a short and standardized fragment of DNA. To this end, an attempt has been made in this study to develop a computational approach for identifying the species by comparing its barcode with the barcode sequence of known species present in the reference library. Each barcode sequence was first mapped onto a numeric feature vector based on k-mer frequencies and then Random forest methodology was employed on the transformed dataset for species identification. The proposed approach outperformed similarity-based, tree-based, diagnostic-based approaches and found comparable with existing supervised learning based approaches in terms of species identification success rate, while compared using real and simulated datasets. Based on the proposed approach, an online web interface SPIDBAR has also been developed and made freely available at http://cabgrid.res.in:8080/spidbar/ for species identification by the taxonomists. Copyright © 2016 Elsevier B.V. All rights reserved.

Beyond radio-displacement techniques for Identification of CB1 Ligands: The First Application of a Fluorescence-quenching Assay

PubMed Central

Bruno, Agostino; Lembo, Francesca; Novellino, Ettore; Stornaiuolo, Mariano; Marinelli, Luciana

2014-01-01

Cannabinoid type 1 Receptor (CB1) belongs to the GPCR family and it has been targeted, so far, for the discovery of drugs aimed at the treatment of neuropathic pain, nausea, vomit, and food intake disorders. Here, we present the development of the first fluorescent assay enabling the measurement of kinetic binding constants for CB1orthosteric ligands. The assay is based on the use of T1117, a fluorescent analogue of AM251. We prove that T1117 binds endogenous and recombinant CB1 receptors with nanomolar affinity. Moreover, T1117 binding to CB1 is sensitive to the allosteric ligand ORG27569 and thus it is applicable to the discovery of new allosteric drugs. The herein presented assay constitutes a sustainable valid alternative to the expensive and environmental impacting radiodisplacement techniques and paves the way for an easy, fast and cheap high-throughput drug screening toward CB1 for identification of new orthosteric and allosteric modulators. PMID:24441508

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.

Development of an assay for rapid identification of meat from yak and cattle using polymerase chain reaction technique.

PubMed

Yin, R H; Bai, W L; Wang, J M; Wu, C D; Dou, Q L; Yin, R L; He, J B; Luo, G B

2009-09-01

Yak meat is of good quality with fine texture, high protein and low fat content, and rich in amino acids compared with that of cattle, and it lacks anabolic steroids or other drugs. In general terms, however, the meat yield of yak is relatively low compared with that of the cattle. In order to prevent possible adulteration of yak meat with cattle meat, based on the sequence of mitochondrial 12S rRNA gene, a multiplex PCR-based approach was proposed for rapid identification of the meat from yak and cattle using three primers designed in this work. Through the combinatorial usage of three primers with a single reaction set, two fragments of 290 and 159bp were amplified from the cattle meat DNA, whereas only a fragment of 290bp was obtained from the yak meat DNA. Using the assay described, satisfactory amplification was accomplished in the analysis of raw and heat-treated binary meat mixtures of yak/cattle with a detection limit of 0.1% for cattle meat. The technique is fast and straightforward. It might be a useful tool in the quality control of yak meat and meat products.

Discovery and identification of quality markers of Chinese medicine based on pharmacokinetic analysis.

PubMed

He, Jun; Feng, Xinchi; Wang, Kai; Liu, Changxiao; Qiu, Feng

2018-02-28

Quality control of Chinese medicine (CM) is an effective measure to ensure the safety and efficacy of CM in clinical practice, which is also a key factor to restrict the modernization process of CM. Various chemical components exist in CM and the determination of several chemical components is the main approach for quality control of vast majority of CM in the present. However, many components determined lack not only specificity, but also biological activities. This is bound to greatly reduce the actual value of quality standard of CM. Professor Changxiao Liu proposed the "quality marker" (Q-marker) concept to ensure the standardization and rationalization for the quality control of CM. As we all know, CMs are taken orally in most cases and could be extensively metabolized in vivo. Both prototype components and the metabolites could be the actual therapeutic material basis. Pharmacokinetic studies could benefit the elucidation of actual therapeutic material basis which is closely related to the identification of Q-markers. Therefore, a new strategy about Q-marker was proposed based on the pharmacokinetic analysis of CM, hoping to provide some ideas for the discovery and identification of Q-marker. The relationship between pharmacokinetic studies and the identification of Q-markers was demonstrated in this review and a new strategy was proposed. Starting from the pharmacokinetic analysis, reverse tracing of the prototype active components and the potential prodrugs in CM were conducted first and the therapeutic material basis were identified as Q-markers. Then, modern analytical techniques and methods were applied to obtain comprehensive quality control for these constituents. Several CMs including gingko biloba, ginseng, Periplocae Cortex, Mori Cortex, Bupleuri Radix and Scutellariae Radix were listed as examples to clarify how the new strategy could be applied. Pharmacokinetic studies play an important role for the elucidation of therapeutic material basis of CM

Xylella fastidiosa: Host Range and Advance in Molecular Identification Techniques

PubMed Central

Baldi, Paolo; La Porta, Nicola

2017-01-01

In the never ending struggle against plant pathogenic bacteria, a major goal is the early identification and classification of infecting microorganisms. Xylella fastidiosa, a Gram-negative bacterium belonging to the family Xanthmonadaceae, is no exception as this pathogen showed a broad range of vectors and host plants, many of which may carry the pathogen for a long time without showing any symptom. Till the last years, most of the diseases caused by X. fastidiosa have been reported from North and South America, but recently a widespread infection of olive quick decline syndrome caused by this fastidious pathogen appeared in Apulia (south-eastern Italy), and several cases of X. fastidiosa infection have been reported in other European Countries. At least five different subspecies of X. fastidiosa have been reported and classified: fastidiosa, multiplex, pauca, sandyi, and tashke. A sixth subspecies (morus) has been recently proposed. Therefore, it is vital to develop fast and reliable methods that allow the pathogen detection during the very early stages of infection, in order to prevent further spreading of this dangerous bacterium. To this purpose, the classical immunological methods such as ELISA and immunofluorescence are not always sensitive enough. However, PCR-based methods exploiting specific primers for the amplification of target regions of genomic DNA have been developed and are becoming a powerful tool for the detection and identification of many species of bacteria. The aim of this review is to illustrate the application of the most commonly used PCR approaches to X. fastidiosa study, ranging from classical PCR, to several PCR-based detection methods: random amplified polymorphic DNA (RAPD), quantitative real-time PCR (qRT-PCR), nested-PCR (N-PCR), immunocapture PCR (IC-PCR), short sequence repeats (SSRs, also called VNTR), single nucleotide polymorphisms (SNPs) and multilocus sequence typing (MLST). Amplification and sequence analysis of specific

Sub-word based Arabic handwriting analysis for writer identification

NASA Astrophysics Data System (ADS)

Maliki, Makki; Al-Jawad, Naseer; Jassim, Sabah

2013-05-01

Analysing a text or part of it is key to handwriting identification. Generally, handwriting is learnt over time and people develop habits in the style of writing. These habits are embedded in special parts of handwritten text. In Arabic each word consists of one or more sub-word(s). The end of each sub-word is considered to be a connect stroke. The main hypothesis in this paper is that sub-words are essential reflection of Arabic writer's habits that could be exploited for writer identification. Testing this hypothesis will be based on experiments that evaluate writer's identification, mainly using K nearest neighbor from group of sub-words extracted from longer text. The experimental results show that using a group of sub-words could be used to identify the writer with a successful rate between 52.94 % to 82.35% when top1 is used, and it can go up to 100% when top5 is used based on K nearest neighbor. The results show that majority of writers are identified using 7 sub-words with a reliability confident of about 90% (i.e. 90% of the rejected templates have significantly larger distances to the tested example than the distance from the correctly identified template). However previous work, using a complete word, shows successful rate of at most 90% in top 10.

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.

[Identification of varieties of cashmere by Vis/NIR spectroscopy technology based on PCA-SVM].

PubMed

Wu, Gui-Fang; He, Yong

2009-06-01

One mixed algorithm was presented to discriminate cashmere varieties with principal component analysis (PCA) and support vector machine (SVM). Cashmere fiber has such characteristics as threadlike, softness, glossiness and high tensile strength. The quality characters and economic value of each breed of cashmere are very different. In order to safeguard the consumer's rights and guarantee the quality of cashmere product, quickly, efficiently and correctly identifying cashmere has significant meaning to the production and transaction of cashmere material. The present research adopts Vis/NIRS spectroscopy diffuse techniques to collect the spectral data of cashmere. The near infrared fingerprint of cashmere was acquired by principal component analysis (PCA), and support vector machine (SVM) methods were used to further identify the cashmere material. The result of PCA indicated that the score map made by the scores of PC1, PC2 and PC3 was used, and 10 principal components (PCs) were selected as the input of support vector machine (SVM) based on the reliabilities of PCs of 99.99%. One hundred cashmere samples were used for calibration and the remaining 75 cashmere samples were used for validation. A one-against-all multi-class SVM model was built, the capabilities of SVM with different kernel function were comparatively analyzed, and the result showed that SVM possessing with the Gaussian kernel function has the best identification capabilities with the accuracy of 100%. This research indicated that the data mining method of PCA-SVM has a good identification effect, and can work as a new method for rapid identification of cashmere material varieties.

Distinguishing institutional identification from academic goal pursuit: interactive effects of ethnic identification and race-based rejection sensitivity.

PubMed

Mendoza-Denton, Rodolfo; Pietrzak, Janina; Downey, Geraldine

2008-08-01

We examined the interactive effects of ethnic identification (EI) and race-based rejection sensitivity (RS-race) on institutional outcomes among African American college students. We distinguished between effects on institutional identification on the one hand and academic goal pursuit (e.g., staying in school, grade point average [GPA]) on the other. Supporting the utility of this distinction, we found that EI and RS-race interacted to predict these outcomes differently. Higher EI in combination with higher RS-race predicted reduced identification with the institution (Studies 1, 2, and 3a). This combination, however, did not lead to decreases in GPA over time. Moreover, EI was positively related to intentions to stay in school as well as to GPA increases among those lower in RS-race (Studies 1 and 3b). Implications for understanding identity negotiation vis-à-vis performance in institutional settings are discussed. (c) 2008 APA, all rights reserved

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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.

Magnetic immunoassay platform based on the planar frequency mixing magnetic technique.

PubMed

Kim, Chang-Beom; Lim, Eul-Gyoon; Shin, Sung Woong; Krause, Hans Joachim; Hong, Hyobong

2016-09-15

We represent the experimental results of our planar-frequency mixing magnetic detection (p-FMMD) technique to obtain 2D superparamagnetic images for magnetic immunoassay purpose. The imaging of magnetic beads is based on the nonlinear magnetic characteristics inherent in superparamagnetic materials. The p-FMMD records the sum-frequency components originating from both a high and a low frequency magnetic field incident on the magnetically nonlinear nanoparticles. In this study, we apply the p-FMMD technique to 2D scanning imaging of superparamagnetic iron oxide nanoparticles (SPIONs) in a microfluidic platform. Our p-FMMD system enables to acquire planar images of SPIONs filled in a microchannel as narrow as 30µm in width. The minimum detectable amount is ~1.0×10(8) beads of 100nm size. The system shows a spatial resolution enabling to distinguish between two distinct channels even 2mm apart from each other. Our p-FMMD system as a magnetic immunoassaying system has permitted the detection of amyloid beta 42 (Aβ42), a promising biomarker of Alzheimer's disease, at the minimum concentration of 23.8pg/ml. This may enable the identification of the Aβ42 levels for the early-stage of Alzheimer's disease with the assistance of the MPI using p-FMMD technique. The results show that the deployment of the p-FMMD can be an alternative to conventional biosensing analytical methods, and can be used as a fast and portable screening method. Copyright © 2016 Elsevier B.V. All rights reserved.

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 network identity authentication system based on Fingerprint identification technology

NASA Astrophysics Data System (ADS)

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

2005-10-01

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

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

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

On the Simultaneous Identification and Quantification of Microalgae Populations Based on Fluorometric Techniques.

PubMed

Gsponer, Natalia S; Rodríguez, María Claudia; Palacios, Rodrigo E; Chesta, Carlos A

2018-05-16

In this study, the phytoplankton structure of a freshwater reservoir located in central Argentina (Embalse Río Tercero) was analyzed using Beutler's method (Photosynthesis Research 72: 39-53, 2002), aiming to provide water quality control agencies with a reliable tool for early detection of algae blooms, particularly cyanobacteria. The method estimated the concentration of chlorophyll a (Chl a) contributed by individual algal groups in a real sample by fitting its fluorescence excitation spectrum to a linear combination of norm spectra of relevant algae groups. To this purpose, norm spectra for five algae genera usually found in Embalse Río Tercero, Microcystis, Chlorella, Cyclotella, Ceratium and Porphyridium, were constructed and posteriorly used to analyze samples collected in the reservoir in years 2014-2016. Results showed that the method worked well for the quick identification of the algae present in the samples, but it tended to overestimate its Chl a contents. This error was attributed to the large heterogeneity of the algal populations due to the aging of cells grown in environmental conditions. © 2018 The American Society of Photobiology.

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

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

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

PubMed

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

Gas Reservoir Identification Basing on Deep Learning of Seismic-print Characteristics

NASA Astrophysics Data System (ADS)

Cao, J.; Wu, S.; He, X.

2016-12-01

Reservoir identification based on seismic data analysis is the core task in oil and gas geophysical exploration. The essence of reservoir identification is to identify the properties of rock pore fluid. We developed a novel gas reservoir identification method named seismic-print analysis by imitation of the vocal-print analysis techniques in speaker identification. The term "seismic-print" is referred to the characteristics of the seismic waveform which can identify determinedly the property of the geological objectives, for instance, a nature gas reservoir. Seismic-print can be characterized by one or a few parameters named as seismic-print parameters. It has been proven that gas reservoirs are of characteristics of negative 1-order cepstrum coefficient anomaly and Positive 2-order cepstrum coefficient anomaly, concurrently. The method is valid for sandstone gas reservoir, carbonate reservoir and shale gas reservoirs, and the accuracy rate may reach up to 90%. There are two main problems to deal with in the application of seismic-print analysis method. One is to identify the "ripple" of a reservoir on the seismogram, and another is to construct the mapping relationship between the seismic-print and the gas reservoirs. Deep learning developed in recent years is of the ability to reveal the complex non-linear relationship between the attribute and the data, and of ability to extract automatically the features of the objective from the data. Thus, deep learning could been used to deal with these two problems. There are lots of algorithms to carry out deep learning. The algorithms can be roughly divided into two categories: Belief Networks Network (DBNs) and Convolutional Neural Network (CNN). DBNs is a probabilistic generative model, which can establish a joint distribution of the observed data and tags. CNN is a feedforward neural network, which can be used to extract the 2D structure feature of the input data. Both DBNs and CNN can be used to deal with seismic data

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

The application of NMR-based milk metabolite analysis in milk authenticity identification.

PubMed

Li, Qiangqiang; Yu, Zunbo; Zhu, Dan; Meng, Xianghe; Pang, Xiumei; Liu, Yue; Frew, Russell; Chen, He; Chen, Gang

2017-07-01

Milk is an important food component in the human diet and is a target for fraud, including many unsafe practices. For example, the unscrupulous adulteration of soymilk into bovine and goat milk or of bovine milk into goat milk in order to gain profit without declaration is a health risk, as the adulterant source and sanitary history are unknown. A robust and fit-for-purpose technique is required to enforce market surveillance and hence protect consumer health. Nuclear magnetic resonance (NMR) is a powerful technique for characterization of food products based on measuring the profile of metabolites. In this study, 1D NMR in conjunction with multivariate chemometrics as well as 2D NMR was applied to differentiate milk types and to identify milk adulteration. Ten metabolites were found which differed among milk types, hence providing characteristic markers for identifying the milk. These metabolites were used to establish mathematical models for milk type differentiation. The limit of quantification (LOQ) of adulteration was 2% (v/v) for soymilk in bovine milk, 2% (v/v) for soymilk in goat milk and 5% (v/v) for bovine milk in goat milk, with relative standard deviation (RSD) less than 10%, which can meet the needs of daily inspection. The NMR method described here is effective for milk authenticity identification, and the study demonstrates that the NMR-based milk metabolite analysis approach provides a means of detecting adulteration at expected levels and can be used for dairy quality monitoring. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

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

PubMed

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

2017-01-01

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

Construction of dynamic stochastic simulation models using knowledge-based techniques

NASA Technical Reports Server (NTRS)

Williams, M. Douglas; Shiva, Sajjan G.

1990-01-01

Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM).

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.

XRF map identification problems based on a PDE electrodeposition model

NASA Astrophysics Data System (ADS)

Sgura, Ivonne; Bozzini, Benedetto

2017-04-01

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

Material identification based on electrostatic sensing technology

NASA Astrophysics Data System (ADS)

Liu, Kai; Chen, Xi; Li, Jingnan

2018-04-01

When the robot travels on the surface of different media, the uncertainty of the medium will seriously affect the autonomous action of the robot. In this paper, the distribution characteristics of multiple electrostatic charges on the surface of materials are detected, so as to improve the accuracy of the existing electrostatic signal material identification methods, which is of great significance to help the robot optimize the control algorithm. In this paper, based on the electrostatic signal material identification method proposed by predecessors, the multi-channel detection circuit is used to obtain the electrostatic charge distribution at different positions of the material surface, the weights are introduced into the eigenvalue matrix, and the weight distribution is optimized by the evolutionary algorithm, which makes the eigenvalue matrix more accurately reflect the surface charge distribution characteristics of the material. The matrix is used as the input of the k-Nearest Neighbor (kNN)classification algorithm to classify the dielectric materials. The experimental results show that the proposed method can significantly improve the recognition rate of the existing electrostatic signal material recognition methods.

Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification.

PubMed

Kovalchuk, Sergey V; Funkner, Anastasia A; Metsker, Oleg G; Yakovlev, Aleksey N

2018-06-01

An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for combination of different techniques. The implementation of the proposed approach for simulation of the acute coronary syndrome (ACS) was developed and used in an experimental study. A combination of data, text, process mining techniques, and machine learning approaches for the analysis of electronic health records (EHRs) with discrete-event simulation (DES) and queueing theory for the simulation of patient flow was proposed. The performed analysis of EHRs for ACS patients enabled identification of several classes of clinical pathways (CPs) which were used to implement a more realistic simulation of the patient flow. The developed solution was implemented using Python libraries (SimPy, SciPy, and others). The proposed approach enables more a realistic and detailed simulation of the patient flow within a group of related departments. An experimental study shows an improved simulation of patient length of stay for ACS patient flow obtained from EHRs in Almazov National Medical Research Centre in Saint Petersburg, Russia. The proposed approach, methods, and solutions provide a conceptual, methodological, and programming framework for the implementation of a simulation of complex and diverse scenarios within a flow of patients for different purposes: decision making, training, management optimization, and others. Copyright © 2018 Elsevier Inc. All rights reserved.

Mock-juror evaluations of traditional and ratings-based eyewitness identification evidence.

PubMed

Sauer, James D; Palmer, Matthew A; Brewer, Neil

2017-08-01

Compared to categorical identifications, culprit likelihood ratings (having the witness rate, for each lineup member, the likelihood that the individual is the culprit) provide a promising alternative for assessing a suspect's likely guilt. Four experiments addressed 2 broad questions about the use of culprit likelihood ratings evidence by mock-jurors. First, are mock-jurors receptive to noncategorical forms of identification evidence? Second, does the additional information provided by ratings (relating to discrimination) affect jurors' evaluations of the identification evidence? Experiments 1 and 1A manipulated confidence (90% vs. 50%) and discrimination (good, poor, no information) between participants. Evaluations were influenced by confidence, but not discrimination. However, a within-participant manipulation of discrimination (Experiment 2) demonstrated that evidence of good discrimination enhanced the persuasiveness of moderate levels of confidence, while poor discrimination reduced the persuasiveness of high levels of confidence. Thus, participants can interpret ratings-based evidence, but may not intuit the discrimination information when evaluating ratings for a single identification procedure. Providing detailed instructions about interpreting ratings produced clear discrimination effects when evaluating a single identification procedure (Experiment 3). Across 4 experiments, we found no evidence that mock-jurors perceived noncategorical identification evidence to be less informative than categorical evidence. However, jurors will likely benefit from instruction when interpreting ratings provided by a single witness. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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.

[application of the analytical transmission electron microscopy techniques for detection, identification and visualization of localization of nanoparticles of titanium and cerium oxides in mammalian cells].

PubMed

Shebanova, A S; Bogdanov, A G; Ismagulova, T T; Feofanov, A V; Semenyuk, P I; Muronets, V I; Erokhina, M V; Onishchenko, G E; Kirpichnikov, M P; Shaitan, K V

2014-01-01

This work represents the results of the study on applicability of the modern methods of analytical transmission electron microscopy for detection, identification and visualization of localization of nanoparticles of titanium and cerium oxides in A549 cell, human lung adenocarcinoma cell line. A comparative analysis of images of the nanoparticles in the cells obtained in the bright field mode of transmission electron microscopy, under dark-field scanning transmission electron microscopy and high-angle annular dark field scanning transmission electron was performed. For identification of nanoparticles in the cells the analytical techniques, energy-dispersive X-ray spectroscopy and electron energy loss spectroscopy, were compared when used in the mode of obtaining energy spectrum from different particles and element mapping. It was shown that the method for electron tomography is applicable to confirm that nanoparticles are localized in the sample but not coated by contamination. The possibilities and fields of utilizing different techniques for analytical transmission electron microscopy for detection, visualization and identification of nanoparticles in the biological samples are discussed.

Spectral-decomposition techniques for the identification of periodic and anomalous phenomena in radon time-series.

NASA Astrophysics Data System (ADS)

Crockett, R. G. M.; Perrier, F.; Richon, P.

2009-04-01

Building on independent investigations by research groups at both IPGP, France, and the University of Northampton, UK, hourly-sampled radon time-series of durations exceeding one year have been investigated for periodic and anomalous phenomena using a variety of established and novel techniques. These time-series have been recorded in locations having no routine human behaviour and thus are effectively free of significant anthropogenic influences. With regard to periodic components, the long durations of these time-series allow, in principle, very high frequency resolutions for established spectral-measurement techniques such as Fourier and maximum-entropy. However, as has been widely observed, the stochastic nature of radon emissions from rocks and soils, coupled with sensitivity to a wide variety influences such as temperature, wind-speed and soil moisture-content has made interpretation of the results obtained by such techniques very difficult, with uncertain results, in many cases. We here report developments in the investigation of radon-time series for periodic and anomalous phenomena using spectral-decomposition techniques. These techniques, in variously separating ‘high', ‘middle' and ‘low' frequency components, effectively ‘de-noise' the data by allowing components of interest to be isolated from others which (might) serve to obscure weaker information-containing components. Once isolated, these components can be investigated using a variety of techniques. Whilst this is very much work in early stages of development, spectral decomposition methods have been used successfully to indicate the presence of diurnal and sub-diurnal cycles in radon concentration which we provisionally attribute to tidal influences. Also, these methods have been used to enhance the identification of short-duration anomalies, attributable to a variety of causes including, for example, earthquakes and rapid large-magnitude changes in weather conditions. Keywords: radon

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

NASA Astrophysics Data System (ADS)

Fu, Yan; Guo, Pei-yuan; Xiang, Ling-zi; Bao, Man; Chen, Xing-hai

2013-08-01

With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high- accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

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

NASA Astrophysics Data System (ADS)

Mahdavi, Seyed Hossein; Razak, Hashim Abdul

2016-06-01

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

Damage Identification of Piles Based on Vibration Characteristics

PubMed Central

Zhang, Xiaozhong; Yao, Wenjuan; Chen, Bo; Liu, Dewen

2014-01-01

A method of damage identification of piles was established by using vibration characteristics. The approach focused on the application of the element strain energy and sensitive modals. A damage identification equation of piles was deduced using the structural vibration equation. The equation contained three major factors: change rate of element modal strain energy, damage factor of pile, and sensitivity factor of modal damage. The sensitive modals of damage identification were selected by using sensitivity factor of modal damage firstly. Subsequently, the indexes for early-warning of pile damage were established by applying the change rate of strain energy. Then the technology of computational analysis of wavelet transform was used to damage identification for pile. The identification of small damage of pile was completely achieved, including the location of damage and the extent of damage. In the process of identifying the extent of damage of pile, the equation of damage identification was used in many times. Finally, a stadium project was used as an example to demonstrate the effectiveness of the proposed method of damage identification for piles. The correctness and practicability of the proposed method were verified by comparing the results of damage identification with that of low strain test. The research provided a new way for damage identification of piles. PMID:25506062

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.

The detection of bulk explosives using nuclear-based techniques

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

Morgado, R.E.; Gozani, T.; Seher, C.C.

1988-01-01

In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals;more » new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.« less

IDENTIFICATION AND QUANTIFICATION OF AEROSOL POLAR OXYGENATED COMPOUNDS BEARING CARBOXYLIC AND/OR HYDROXYL GROUPS. 1. METHOD DEVELOPMENT

EPA Science Inventory

In this study, a new analytical technique was developed for the identification and quantification of multi-functional compounds containing simultaneously at least one hydroxyl or one carboxylic group, or both. This technique is based on derivatizing first the carboxylic group(s) ...

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.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Automatic 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.

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

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.

Identification-While-Scanning of a Multi-Aircraft Formation Based on Sparse Recovery for Narrowband Radar.

PubMed

Jiang, Yuan; Xu, Jia; Peng, Shi-Bao; Mao, Er-Ke; Long, Teng; Peng, Ying-Ning

2016-11-23

It is known that the identification performance of a multi-aircraft formation (MAF) of narrowband radar mainly depends on the time on target (TOT). To realize the identification task in one rotated scan with limited TOT, the paper proposes a novel identification-while-scanning (IWS) method based on sparse recovery to maintain high rotating speed and super-resolution for MAF identification, simultaneously. First, a multiple chirp signal model is established for MAF in a single scan, where different aircraft may have different Doppler centers and Doppler rates. Second, based on the sparsity of MAF in the Doppler parameter space, a novel hierarchical basis pursuit (HBP) method is proposed to obtain satisfactory sparse recovery performance as well as high computational efficiency. Furthermore, the parameter estimation performance of the proposed IWS identification method is analyzed with respect to recovery condition, signal-to-noise ratio and TOT. It is shown that an MAF can be effectively identified via HBP with a TOT of only about one hundred microseconds for IWS applications. Finally, some numerical experiment results are provided to demonstrate the effectiveness of the proposed method based on both simulated and real measured data.

Mass spectrometry-based protein identification by integrating de novo sequencing with database searching.

PubMed

Wang, Penghao; Wilson, Susan R

2013-01-01

Mass spectrometry-based protein identification is a very challenging task. The main identification approaches include de novo sequencing and database searching. Both approaches have shortcomings, so an integrative approach has been developed. The integrative approach firstly infers partial peptide sequences, known as tags, directly from tandem spectra through de novo sequencing, and then puts these sequences into a database search to see if a close peptide match can be found. However the current implementation of this integrative approach has several limitations. Firstly, simplistic de novo sequencing is applied and only very short sequence tags are used. Secondly, most integrative methods apply an algorithm similar to BLAST to search for exact sequence matches and do not accommodate sequence errors well. Thirdly, by applying these methods the integrated de novo sequencing makes a limited contribution to the scoring model which is still largely based on database searching. We have developed a new integrative protein identification method which can integrate de novo sequencing more efficiently into database searching. Evaluated on large real datasets, our method outperforms popular identification methods.

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.

Three-dimensional electron diffraction as a complementary technique to powder X-ray diffraction for phase identification and structure solution of powders.

PubMed

Yun, Yifeng; Zou, Xiaodong; Hovmöller, Sven; Wan, Wei

2015-03-01

Phase identification and structure determination are important and widely used techniques in chemistry, physics and materials science. Recently, two methods for automated three-dimensional electron diffraction (ED) data collection, namely automated diffraction tomography (ADT) and rotation electron diffraction (RED), have been developed. Compared with X-ray diffraction (XRD) and two-dimensional zonal ED, three-dimensional ED methods have many advantages in identifying phases and determining unknown structures. Almost complete three-dimensional ED data can be collected using the ADT and RED methods. Since each ED pattern is usually measured off the zone axes by three-dimensional ED methods, dynamic effects are much reduced compared with zonal ED patterns. Data collection is easy and fast, and can start at any arbitrary orientation of the crystal, which facilitates automation. Three-dimensional ED is a powerful technique for structure identification and structure solution from individual nano- or micron-sized particles, while powder X-ray diffraction (PXRD) provides information from all phases present in a sample. ED suffers from dynamic scattering, while PXRD data are kinematic. Three-dimensional ED methods and PXRD are complementary and their combinations are promising for studying multiphase samples and complicated crystal structures. Here, two three-dimensional ED methods, ADT and RED, are described. Examples are given of combinations of three-dimensional ED methods and PXRD for phase identification and structure determination over a large number of different materials, from Ni-Se-O-Cl crystals, zeolites, germanates, metal-organic frameworks and organic compounds to intermetallics with modulated structures. It is shown that three-dimensional ED is now as feasible as X-ray diffraction for phase identification and structure solution, but still needs further development in order to be as accurate as X-ray diffraction. It is expected that three-dimensional ED methods

Applications of Electromigration Techniques: Applications of Electromigration Techniques in Food Analysis

NASA Astrophysics Data System (ADS)

Wieczorek, Piotr; Ligor, Magdalena; Buszewski, Bogusław

Electromigration techniques, including capillary electrophoresis (CE), are widely used for separation and identification of compounds present in food products. These techniques may also be considered as alternate and complementary with respect to commonly used analytical techniques, such as high-performance liquid chromatography (HPLC), or gas chromatography (GC). Applications of CE concern the determination of high-molecular compounds, like polyphenols, including flavonoids, pigments, vitamins, food additives (preservatives, antioxidants, sweeteners, artificial pigments) are presented. Also, the method developed for the determination of proteins and peptides composed of amino acids, which are basic components of food products, are studied. Other substances such as carbohydrates, nucleic acids, biogenic amines, natural toxins, and other contaminations including pesticides and antibiotics are discussed. The possibility of CE application in food control laboratories, where analysis of the composition of food and food products are conducted, is of great importance. CE technique may be used during the control of technological processes in the food industry and for the identification of numerous compounds present in food. Due to the numerous advantages of the CE technique it is successfully used in routine food analysis.

A voting-based star identification algorithm utilizing local and global distribution

NASA Astrophysics Data System (ADS)

Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

2018-03-01

A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

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

PubMed Central

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

2014-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Comparison between traditional strategies and classification technique (SIMCA) in the identification of old proteinaceous binders.

PubMed

Checa-Moreno, R; Manzano, E; Mirón, G; Capitan-Vallvey, L F

2008-05-15

In this paper, we performed a comparison between commonly used strategies amino acid ratios (Aa ratios), two-dimensional ratio plots (2D-Plot) and statistical correlation factor (SCF) and a classification technique, soft independent modelling of class analogy (SIMCA), to identify protein binders present in old artwork samples. To do this, we used a natural standard collection of proteinaceous binders prepared in our laboratory using old recipes and eleven samples coming from Cultural Heritage, such as mural and easel paintings, manuscripts and polychrome sculptures from the 15-18th centuries. Protein binder samples were hydrolyzed and their constitutive amino acids were determined as PITC-derivatives using HPLC-DAD. Amino acid profile data were used to perform the comparison between the four different strategies mentioned above. Traditional strategies can lead to ambiguous or non-conclusive results. With SIMCA, it is possible to provide a more robust and less subjective identification knowing the confidence level of identification. As a standard, we used proteinaceous albumin (whole egg, yolk and glair); casein (goat, cow and sheep) and collagen (mammalian and fish). The process results in a more robust understanding of proteinaceous binding media in old artworks that makes it possible to distinguish them according to their origin.

Large modal survey testing using the Ibrahim time domain /ITD/ identification technique

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.; Pappa, R. S.

1981-01-01

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

DNA based identification of medicinal materials in Chinese patent medicines

NASA Astrophysics Data System (ADS)

Chen, Rong; Dong, Juan; Cui, Xin; Wang, Wei; Yasmeen, Afshan; Deng, Yun; Zeng, Xiaomao; Tang, Zhuo

2012-12-01

Chinese patent medicines (CPM) are highly processed and easy to use Traditional Chinese Medicine (TCM). The market for CPM in China alone is tens of billions US dollars annually and some of the CPM are also used as dietary supplements for health augmentation in the western countries. But concerns continue to be raised about the legality, safety and efficacy of many popular CPM. Here we report a pioneer work of applying molecular biotechnology to the identification of CPM, particularly well refined oral liquids and injections. What's more, this PCR based method can also be developed to an easy to use and cost-effective visual chip by taking advantage of G-quadruplex based Hybridization Chain Reaction. This study demonstrates that DNA identification of specific Medicinal materials is an efficient and cost-effective way to audit highly processed CPM and will assist in monitoring their quality and legality.

Fault zone identification in the eastern part of the Persian Gulf based on combined seismic attributes

NASA Astrophysics Data System (ADS)

Mirkamali, M. S.; Keshavarz FK, N.; Bakhtiari, M. R.

2013-02-01

Faults, as main pathways for fluids, play a critical role in creating regions of high porosity and permeability, in cutting cap rock and in the migration of hydrocarbons into the reservoir. Therefore, accurate identification of fault zones is very important in maximizing production from petroleum traps. Image processing and modern visualization techniques are provided for better mapping of objects of interest. In this study, the application of fault mapping in the identification of fault zones within the Mishan and Aghajari formations above the Guri base unconformity surface in the eastern part of Persian Gulf is investigated. Seismic single- and multi-trace attribute analyses are employed separately to determine faults in a vertical section, but different kinds of geological objects cannot be identified using individual attributes only. A mapping model is utilized to improve the identification of the faults, giving more accurate results. This method is based on combinations of all individual relevant attributes using a neural network system to create combined attributes, which gives an optimal view of the object of interest. Firstly, a set of relevant attributes were separately calculated on the vertical section. Then, at interpreted positions, some example training locations were manually selected in each fault and non-fault class by an interpreter. A neural network was trained on combinations of the attributes extracted at the example training locations to generate an optimized fault cube. Finally, the results of the fault and nonfault probability cube were estimated, which the neural network applied to the entire data set. The fault probability cube was obtained with higher mapping accuracy and greater contrast, and with fewer disturbances in comparison with individual attributes. The computed results of this study can support better understanding of the data, providing fault zone mapping with reliable results.

Identification of Load Categories in Rotor System Based on Vibration Analysis

PubMed Central

Yang, Zhaojian

2017-01-01

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

Laser-based direct-write techniques for cell printing

PubMed Central

Schiele, Nathan R; Corr, David T; Huang, Yong; Raof, Nurazhani Abdul; Xie, Yubing; Chrisey, Douglas B

2016-01-01

Fabrication of cellular constructs with spatial control of cell location (±5 μm) is essential to the advancement of a wide range of applications including tissue engineering, stem cell and cancer research. Precise cell placement, especially of multiple cell types in co- or multi-cultures and in three dimensions, can enable research possibilities otherwise impossible, such as the cell-by-cell assembly of complex cellular constructs. Laser-based direct writing, a printing technique first utilized in electronics applications, has been adapted to transfer living cells and other biological materials (e.g., enzymes, proteins and bioceramics). Many different cell types have been printed using laser-based direct writing, and this technique offers significant improvements when compared to conventional cell patterning techniques. The predominance of work to date has not been in application of the technique, but rather focused on demonstrating the ability of direct writing to pattern living cells, in a spatially precise manner, while maintaining cellular viability. This paper reviews laser-based additive direct-write techniques for cell printing, and the various cell types successfully laser direct-written that have applications in tissue engineering, stem cell and cancer research are highlighted. A particular focus is paid to process dynamics modeling and process-induced cell injury during laser-based cell direct writing. PMID:20814088

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

PubMed

Nease, Beth M; Haney, Tina S

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

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

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.

Developing a hybrid dictionary-based bio-entity recognition technique.

PubMed

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Developing a hybrid dictionary-based bio-entity recognition technique

PubMed Central

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

Performance of tensor decomposition-based modal identification under nonstationary vibration

NASA Astrophysics Data System (ADS)

Friesen, P.; Sadhu, A.

2017-03-01

Health monitoring of civil engineering structures is of paramount importance when they are subjected to natural hazards or extreme climatic events like earthquake, strong wind gusts or man-made excitations. Most of the traditional modal identification methods are reliant on stationarity assumption of the vibration response and posed difficulty while analyzing nonstationary vibration (e.g. earthquake or human-induced vibration). Recently tensor decomposition based methods are emerged as powerful and yet generic blind (i.e. without requiring a knowledge of input characteristics) signal decomposition tool for structural modal identification. In this paper, a tensor decomposition based system identification method is further explored to estimate modal parameters using nonstationary vibration generated due to either earthquake or pedestrian induced excitation in a structure. The effects of lag parameters and sensor densities on tensor decomposition are studied with respect to the extent of nonstationarity of the responses characterized by the stationary duration and peak ground acceleration of the earthquake. A suite of more than 1400 earthquakes is used to investigate the performance of the proposed method under a wide variety of ground motions utilizing both complete and partial measurements of a high-rise building model. Apart from the earthquake, human-induced nonstationary vibration of a real-life pedestrian bridge is also used to verify the accuracy of the proposed method.

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

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

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 .

Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

NASA Astrophysics Data System (ADS)

Jena, D. P.; Panigrahi, S. N.

2016-03-01

Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

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

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

NASA Astrophysics Data System (ADS)

Schimmel, Andreas; Hübl, Johannes

2017-04-01

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

Precise identification of <1 0 0> directions on Si{0 0 1} wafer using a novel self-aligning pre-etched technique

NASA Astrophysics Data System (ADS)

Singh, S. S.; Veerla, S.; Sharma, V.; Pandey, A. K.; Pal, P.

2016-02-01

Micromirrors with a tilt angle of 45° are widely used in optical switching and interconnect applications which require 90° out of plane reflection. Silicon wet bulk micromachining based on surfactant added TMAH is usually employed to fabricate 45° slanted walls at the < 1 0 0> direction on Si≤ft\\{0 0 1\\right\\} wafers. These slanted walls are used as 45° micromirrors. However, the appearance of a precise 45° ≤ft\\{0 1 1\\right\\} wall is subject to the accurate identification of the < 1 0 0> direction. In this paper, we present a simple technique based on pre-etched patterns for the identification of < 1 0 0> directions on the Si≤ft\\{0 0 1\\right\\} surface. The proposed pre-etched pattern self-aligns itself at the < 1 0 0> direction while becoming misaligned at other directions. The < 1 0 0> direction is determined by a simple visual inspection of pre-etched patterns and does not need any kind of measurement. To test the accuracy of the proposed method, we fabricated a 32 mm long rectangular opening with its sides aligned along the < 1 0 0> direction, which is determined using the proposed technique. Due to the finite etch rate of the ≤ft\\{1 1 0\\right\\} plane, undercutting occurred, which was measured at 12 different locations along the longer edge of the rectangular strip. The mean of these undercutting lengths, measured perpendicular to the mask edge, is found to be 13.41 μm with a sub-micron standard deviation of 0.38 μm. This level of uniform undercutting indicates that our method of identifying the < 1 0 0> direction is precise and accurate. The developed method will be extremely useful in fabricating arrays of 45° micromirrors.

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.

Comparison of DNA-based techniques for differentiation of production strains of ale and lager brewing yeast.

PubMed

Kopecká, J; Němec, M; Matoulková, D

2016-06-01

Brewing yeasts are classified into two species-Saccharomyces pastorianus and Saccharomyces cerevisiae. Most of the brewing yeast strains are natural interspecies hybrids typically polyploids and their identification is thus often difficult giving heterogenous results according to the method used. We performed genetic characterization of a set of the brewing yeast strains coming from several yeast culture collections by combination of various DNA-based techniques. The aim of this study was to select a method for species-specific identification of yeast and discrimination of yeast strains according to their technological classification. A group of 40 yeast strains were characterized using PCR-RFLP analysis of ITS-5·8S, NTS, HIS4 and COX2 genes, multiplex PCR, RAPD-PCR of genomic DNA, mtDNA-RFLP and electrophoretic karyotyping. Reliable differentiation of yeast to the species level was achieved by PCR-RFLP of HIS4 gene. Numerical analysis of the obtained RAPD-fingerprints and karyotype revealed species-specific clustering corresponding with the technological classification of the strains. Taxonomic position and partial hybrid nature of strains were verified by multiplex PCR. Differentiation among species using the PCR-RFLP of ITS-5·8S and NTS region was shown to be unreliable. Karyotyping and RFLP of mitochondrial DNA evinced small inaccuracies in strain categorization. PCR-RFLP of HIS4 gene and RAPD-PCR of genomic DNA are reliable and suitable methods for fast identification of yeast strains. RAPD-PCR with primer 21 is a fast and reliable method applicable for differentiation of brewing yeasts with only 35% similarity of fingerprint profile between the two main technological groups (ale and lager) of brewing strains. It was proved that PCR-RFLP method of HIS4 gene enables precise discrimination among three technologically important Saccharomyces species. Differentiation of brewing yeast to the strain level can be achieved using the RAPD-PCR technique. © 2016 The

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 ...

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.

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

PubMed Central

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

2015-01-01

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

Development of acoustic model-based iterative reconstruction technique for thick-concrete imaging

NASA Astrophysics Data System (ADS)

Almansouri, Hani; Clayton, Dwight; Kisner, Roger; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

2016-02-01

Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.1

Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

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

Almansouri, Hani; Clayton, Dwight A; Kisner, Roger A

Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structuresmore » are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.« less

The Importance of Context: Risk-based De-identification of Biomedical Data.

PubMed

Prasser, Fabian; Kohlmayer, Florian; Kuhn, Klaus A

2016-08-05

Data sharing is a central aspect of modern biomedical research. It is accompanied by significant privacy concerns and often data needs to be protected from re-identification. With methods of de-identification datasets can be transformed in such a way that it becomes extremely difficult to link their records to identified individuals. The most important challenge in this process is to find an adequate balance between an increase in privacy and a decrease in data quality. Accurately measuring the risk of re-identification in a specific data sharing scenario is an important aspect of data de-identification. Overestimation of risks will significantly deteriorate data quality, while underestimation will leave data prone to attacks on privacy. Several models have been proposed for measuring risks, but there is a lack of generic methods for risk-based data de-identification. The aim of the work described in this article was to bridge this gap and to show how the quality of de-identified datasets can be improved by using risk models to tailor the process of de-identification to a concrete context. We implemented a generic de-identification process and several models for measuring re-identification risks into the ARX de-identification tool for biomedical data. By integrating the methods into an existing framework, we were able to automatically transform datasets in such a way that information loss is minimized while it is ensured that re-identification risks meet a user-defined threshold. We performed an extensive experimental evaluation to analyze the impact of using different risk models and assumptions about the goals and the background knowledge of an attacker on the quality of de-identified data. The results of our experiments show that data quality can be improved significantly by using risk models for data de-identification. On a scale where 100 % represents the original input dataset and 0 % represents a dataset from which all information has been removed, the

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

PubMed

Rieche, Marie; Komenský, Tomás; Husar, Peter

2011-01-01

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

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.

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.

Monitoring scale scores over time via quality control charts, model-based approaches, and time series techniques.

PubMed

Lee, Yi-Hsuan; von Davier, Alina A

2013-07-01

Maintaining a stable score scale over time is critical for all standardized educational assessments. Traditional quality control tools and approaches for assessing scale drift either require special equating designs, or may be too time-consuming to be considered on a regular basis with an operational test that has a short time window between an administration and its score reporting. Thus, the traditional methods are not sufficient to catch unusual testing outcomes in a timely manner. This paper presents a new approach for score monitoring and assessment of scale drift. It involves quality control charts, model-based approaches, and time series techniques to accommodate the following needs of monitoring scale scores: continuous monitoring, adjustment of customary variations, identification of abrupt shifts, and assessment of autocorrelation. Performance of the methodologies is evaluated using manipulated data based on real responses from 71 administrations of a large-scale high-stakes language assessment.

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.

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.

GIS-based identification of active lineaments within the Krasnokamensk Area, Transbaikalia, Russia

NASA Astrophysics Data System (ADS)

Petrov, V. A.; Lespinasse, M.; Ustinov, S. A.; Cialec, C.

2017-07-01

Lineament analysis was carried out using detailed digital elevation models (DEM) of the Krasnokamensk Area, southeastern Transbaikalia (Russia). The results of this research confirm the presence of already known faults, but also identify unknown fault zones. The primary focus was identifying small discontinuities and their relationship with extended fault zones. The developed technique allowed construction and identification of the active lineaments with their orientation of the compression and expansion axes in the horizontal plane, their direction of shear movement (right or left), and their geodynamic setting of formation (compression or stretching). The results of active faults identification and definition of their kinematics on digital elevation models were confirmed by measuring the velocities and directions of modern horizontal surface motions using a geodesic GPS, as well as identifying the principal stress axes directions of the modern stress field using modern-day earthquake data. The obtained results are deemed necessary for proper rational environmental management decisions.

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

NASA Astrophysics Data System (ADS)

Dube, Chioniso; Pedro, Jimoh O.

2018-05-01

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

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.

Identification of threats using linguistics-based knowledge extraction.

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

Chew, Peter A.

One of the challenges increasingly facing intelligence analysts, along with professionals in many other fields, is the vast amount of data which needs to be reviewed and converted into meaningful information, and ultimately into rational, wise decisions by policy makers. The advent of the world wide web (WWW) has magnified this challenge. A key hypothesis which has guided us is that threats come from ideas (or ideology), and ideas are almost always put into writing before the threats materialize. While in the past the 'writing' might have taken the form of pamphlets or books, today's medium of choice is themore » WWW, precisely because it is a decentralized, flexible, and low-cost method of reaching a wide audience. However, a factor which complicates matters for the analyst is that material published on the WWW may be in any of a large number of languages. In 'Identification of Threats Using Linguistics-Based Knowledge Extraction', we have sought to use Latent Semantic Analysis (LSA) and other similar text analysis techniques to map documents from the WWW, in whatever language they were originally written, to a common language-independent vector-based representation. This then opens up a number of possibilities. First, similar documents can be found across language boundaries. Secondly, a set of documents in multiple languages can be visualized in a graphical representation. These alone offer potentially useful tools and capabilities to the intelligence analyst whose knowledge of foreign languages may be limited. Finally, we can test the over-arching hypothesis--that ideology, and more specifically ideology which represents a threat, can be detected solely from the words which express the ideology--by using the vector-based representation of documents to predict additional features (such as the ideology) within a framework based on supervised learning. In this report, we present the results of a three-year project of the same name. We believe these results

A physiologically based nonhomogeneous Poisson counter model of visual identification.

PubMed

Christensen, Jeppe H; Markussen, Bo; Bundesen, Claus; Kyllingsbæk, Søren

2018-04-30

A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are mutually confusable and hard to see. The model assumes that the visual system's initial sensory response consists in tentative visual categorizations, which are accumulated by leaky integration of both transient and sustained components comparable with those found in spike density patterns of early sensory neurons. The sensory response (tentative categorizations) feeds independent Poisson counters, each of which accumulates tentative object categorizations of a particular type to guide overt identification performance. We tested the model's ability to predict the effect of stimulus duration on observed distributions of responses in a nonspeeded (pure accuracy) identification task with eight response alternatives. The time courses of correct and erroneous categorizations were well accounted for when the event-rates of competing Poisson counters were allowed to vary independently over time in a way that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model provided an explanation for Bloch's law. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Neutron-based nonintrusive inspection techniques

NASA Astrophysics Data System (ADS)

Gozani, Tsahi

1997-02-01

Non-intrusive inspection of large objects such as trucks, sea-going shipping containers, air cargo containers and pallets is gaining attention as a vital tool in combating terrorism, drug smuggling and other violation of international and national transportation and Customs laws. Neutrons are the preferred probing radiation when material specificity is required, which is most often the case. Great strides have been made in neutron based inspection techniques. Fast and thermal neutrons, whether in steady state or in microsecond, or even nanosecond pulses are being employed to interrogate, at high speeds, for explosives, drugs, chemical agents, and nuclear and many other smuggled materials. Existing neutron techniques will be compared and their current status reported.

DNA-based identification and phylogeny of North American Armillaria species

Treesearch

Amy L. Ross-Davis; John W. Hanna; Ned B. Klopfenstein

2011-01-01

Because Armillaria species display different ecological behaviors across diverse forest ecosystems, it is critical to identify Armillaria species accurately for any assessment of forest health. To further develop DNA-based identification methods, partial sequences of the translation elongation factor-1 alpha (EF-1α) gene were used to examine the phylogenetic...

Efficient techniques for wave-based sound propagation in interactive applications

NASA Astrophysics Data System (ADS)

Mehra, Ravish

Sound propagation techniques model the effect of the environment on sound waves and predict their behavior from point of emission at the source to the final point of arrival at the listener. Sound is a pressure wave produced by mechanical vibration of a surface that propagates through a medium such as air or water, and the problem of sound propagation can be formulated mathematically as a second-order partial differential equation called the wave equation. Accurate techniques based on solving the wave equation, also called the wave-based techniques, are too expensive computationally and memory-wise. Therefore, these techniques face many challenges in terms of their applicability in interactive applications including sound propagation in large environments, time-varying source and listener directivity, and high simulation cost for mid-frequencies. In this dissertation, we propose a set of efficient wave-based sound propagation techniques that solve these three challenges and enable the use of wave-based sound propagation in interactive applications. Firstly, we propose a novel equivalent source technique for interactive wave-based sound propagation in large scenes spanning hundreds of meters. It is based on the equivalent source theory used for solving radiation and scattering problems in acoustics and electromagnetics. Instead of using a volumetric or surface-based approach, this technique takes an object-centric approach to sound propagation. The proposed equivalent source technique generates realistic acoustic effects and takes orders of magnitude less runtime memory compared to prior wave-based techniques. Secondly, we present an efficient framework for handling time-varying source and listener directivity for interactive wave-based sound propagation. The source directivity is represented as a linear combination of elementary spherical harmonic sources. This spherical harmonic-based representation of source directivity can support analytical, data

Clones identification of Sequoia sempervirens (D. Don) Endl. in Chile by using PCR-RAPDs technique.

PubMed

Toral Ibañez, Manuel; Caru, Margarita; Herrera, Miguel A; Gonzalez, Luis; Martin, Luis M; Miranda, Jorge; Navarro-Cerrillo, Rafael M

2009-02-01

A protocol of polymerase chain reaction-random amplified polymorphic DNAs (PCR-RAPDs) was established to analyse the gene diversity and genotype identification for clones of Sequoia sempervirens (D. Don) Endl. in Chile. Ten (out of 34) clones from introduction trial located in Voipir-Villarrica, Chile, were studied. The PCR-RAPDs technique and a modified hexadecyltrimethylammonium bromide (CTAB) protocol were used for genomic DNA extraction. The PCR tests were carried out employing 10-mer random primers. The amplification products were detected by electrophoresis in agarose gels. Forty nine polymorphic bands were obtained with the selected primers (BG04, BF07, BF12, BF13, and BF14) and were ordered according to their molecular size. The genetic similarity between samples was calculated by the Jaccard index and a dendrogram was constructed using a cluster analysis of unweighted pair group method using arithmetic averages (UPGMA). Of the primers tested, 5 (out of 60) RAPD primers were selected for their reproducibility and high polymorphism. A total of 49 polymorphic RAPD bands were detected out of 252 bands. The genetic similarity analysis demonstrates an extensive genetic variability between the tested clones and the dendrogram depicts the genetic relationships among the clones, suggesting a geographic relationship. The results indicate that the RAPD markers permitted the identification of the assayed clones, although they are derived from the same geographic origin.

Clones identification of Sequoia sempervirens (D. Don) Endl. in Chile by using PCR-RAPDs technique*

PubMed Central

Toral Ibañez, Manuel; Caru, Margarita; Herrera, Miguel A.; Gonzalez, Luis; Martin, Luis M.; Miranda, Jorge; Navarro-Cerrillo, Rafael M.

2009-01-01

A protocol of polymerase chain reaction-random amplified polymorphic DNAs (PCR-RAPDs) was established to analyse the gene diversity and genotype identification for clones of Sequoia sempervirens (D. Don) Endl. in Chile. Ten (out of 34) clones from introduction trial located in Voipir-Villarrica, Chile, were studied. The PCR-RAPDs technique and a modified hexadecyltrimethylammonium bromide (CTAB) protocol were used for genomic DNA extraction. The PCR tests were carried out employing 10-mer random primers. The amplification products were detected by electrophoresis in agarose gels. Forty nine polymorphic bands were obtained with the selected primers (BG04, BF07, BF12, BF13, and BF14) and were ordered according to their molecular size. The genetic similarity between samples was calculated by the Jaccard index and a dendrogram was constructed using a cluster analysis of unweighted pair group method using arithmetic averages (UPGMA). Of the primers tested, 5 (out of 60) RAPD primers were selected for their reproducibility and high polymorphism. A total of 49 polymorphic RAPD bands were detected out of 252 bands. The genetic similarity analysis demonstrates an extensive genetic variability between the tested clones and the dendrogram depicts the genetic relationships among the clones, suggesting a geographic relationship. The results indicate that the RAPD markers permitted the identification of the assayed clones, although they are derived from the same geographic origin. PMID:19235269

Fusing modeling techniques to support domain analysis for reuse opportunities identification

NASA Technical Reports Server (NTRS)

Hall, Susan Main; Mcguire, Eileen

1993-01-01

Functional modeling techniques or object-oriented graphical representations, which are more useful to someone trying to understand the general design or high level requirements of a system? For a recent domain analysis effort, the answer was a fusion of popular modeling techniques of both types. By using both functional and object-oriented techniques, the analysts involved were able to lean on their experience in function oriented software development, while taking advantage of the descriptive power available in object oriented models. In addition, a base of familiar modeling methods permitted the group of mostly new domain analysts to learn the details of the domain analysis process while producing a quality product. This paper describes the background of this project and then provides a high level definition of domain analysis. The majority of this paper focuses on the modeling method developed and utilized during this analysis effort.

LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data.

PubMed

Koelmel, Jeremy P; Kroeger, Nicholas M; Ulmer, Candice Z; Bowden, John A; Patterson, Rainey E; Cochran, Jason A; Beecher, Christopher W W; Garrett, Timothy J; Yost, Richard A

2017-07-10

Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry

BioCluster: tool for identification and clustering of Enterobacteriaceae based on biochemical data.

PubMed

Abdullah, Ahmed; Sabbir Alam, S M; Sultana, Munawar; Hossain, M Anwar

2015-06-01

Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI) tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC) and the Improved Hierarchical Clustering (IHC), a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1-47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

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.

Ultrabroadband Phased-Array Receivers Based on Optical Techniques

DTIC Science & Technology

2016-02-26

AFRL-AFOSR-VA-TR-2016-0121 Ultrabroadband Phased- array Receivers Based on Optical Techniques Christopher Schuetz UNIVERSITY OF DELAWARE Final Report...Jul 15 4. TITLE AND SUBTITLE Ultrabroadband Phased- Array Receivers Based on Optical Techniques 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...receiver that enables us to capture and convert signals across an array using photonic modulators, routing these signals to a central location using

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.

Gait Characteristic Analysis and Identification Based on the iPhone's Accelerometer and Gyrometer

PubMed Central

Sun, Bing; Wang, Yang; Banda, Jacob

2014-01-01

Gait identification is a valuable approach to identify humans at a distance. In this paper, gait characteristics are analyzed based on an iPhone's accelerometer and gyrometer, and a new approach is proposed for gait identification. Specifically, gait datasets are collected by the triaxial accelerometer and gyrometer embedded in an iPhone. Then, the datasets are processed to extract gait characteristic parameters which include gait frequency, symmetry coefficient, dynamic range and similarity coefficient of characteristic curves. Finally, a weighted voting scheme dependent upon the gait characteristic parameters is proposed for gait identification. Four experiments are implemented to validate the proposed scheme. The attitude and acceleration solutions are verified by simulation. Then the gait characteristics are analyzed by comparing two sets of actual data, and the performance of the weighted voting identification scheme is verified by 40 datasets of 10 subjects. PMID:25222034

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.

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.

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.

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 varieties of textile fibers by using Vis/NIR infrared spectroscopy technique].

PubMed

Wu, Gui-Fang; He, Yong

2010-02-01

The aim of the present paper was to provide new insight into Vis/NIR spectroscopic analysis of textile fibers. In order to achieve rapid identification of the varieties of fibers, the authors selected 5 kinds of fibers of cotton, flax, wool, silk and tencel to do a study with Vis/NIR spectroscopy. Firstly, the spectra of each kind of fiber were scanned by spectrometer, and principal component analysis (PCA) method was used to analyze the characteristics of the pattern of Vis/NIR spectra. Principal component scores scatter plot (PC1 x PC2 x PC3) of fiber indicated the classification effect of five varieties of fibers. The former 6 principal components (PCs) were selected according to the quantity and size of PCs. The PCA classification model was optimized by using the least-squares support vector machines (LS-SVM) method. The authors used the 6 PCs extracted by PCA as the inputs of LS-SVM, and PCA-LS-SVM model was built to achieve varieties validation as well as mathematical model building and optimization analysis. Two hundred samples (40 samples for each variety of fibers) of five varieties of fibers were used for calibration of PCA-LS-SVM model, and the other 50 samples (10 samples for each variety of fibers) were used for validation. The result of validation showed that Vis/NIR spectroscopy technique based on PCA-LS-SVM had a powerful classification capability. It provides a new method for identifying varieties of fibers rapidly and real time, so it has important significance for protecting the rights of consumers, ensuring the quality of textiles, and implementing rationalization production and transaction of textile materials and its production.

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.

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.

A Mixture Rasch Model-Based Computerized Adaptive Test for Latent Class Identification

ERIC Educational Resources Information Center

Jiao, Hong; Macready, George; Liu, Junhui; Cho, Youngmi

2012-01-01

This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

Nonenzymatic microorganism identification based on ribosomal RNA

NASA Astrophysics Data System (ADS)

Ives, Jeffrey T.; Pierini, Alicia M.; Stokes, Jeffrey A.; Wahlund, Thomas M.; Read, Betsy; Bechtel, James H.; Bronk, Burt V.

1999-11-01

Effective defense against biological warfare (BW) agents requires rapid, fieldable and accurate systems. For micro- organisms like bacteria and viruses, ribosomal RNA (rRNA) provides a valuable target with multiple advantages of species specificity and intrinsic target amplification. Vegetative and spore forms of bacteria contain approximately 104 copies of rRNA. Direct detection of rRNA copies can eliminate some of the interference and preparation difficulties involved in enzymatic amplification methods. In order to apply the advantages of rRNA to BW defense, we are developing a fieldable system based on 16S rRNA, physical disruption of the micro-organism, solid phase hybridization, and fluorescence detection. Our goals include species-specific identification, complete operation from raw sample to identification in 15 minutes or less, and compact, fieldable instrumentation. Initial work on this project has investigated the lysis and hybridization steps, the species-specificity of oligonucleotides probes, and the development of a novel electromagnetic method to physically disrupt the micro- organisms. Target bacteria have been Escherichia coli (E. coli) and Bacillus subtilis (B. subtilis). Continuing work includes further development of methods to rapidly disrupt the micro-organisms and release the rRNA, improved integration and processing, and extension to bacterial and mammalian viruses like MS2 and vesicular stomatitis virus.

A signal-detection-based diagnostic-feature-detection model of eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2014-04-01

The theoretical understanding of eyewitness identifications made from a police lineup has long been guided by the distinction between absolute and relative decision strategies. In addition, the accuracy of identifications associated with different eyewitness memory procedures has long been evaluated using measures like the diagnosticity ratio (the correct identification rate divided by the false identification rate). Framed in terms of signal-detection theory, both the absolute/relative distinction and the diagnosticity ratio are mainly relevant to response bias while remaining silent about the key issue of diagnostic accuracy, or discriminability (i.e., the ability to tell the difference between innocent and guilty suspects in a lineup). Here, we propose a signal-detection-based model of eyewitness identification, one that encourages the use of (and helps to conceptualize) receiver operating characteristic (ROC) analysis to measure discriminability. Recent ROC analyses indicate that the simultaneous presentation of faces in a lineup yields higher discriminability than the presentation of faces in isolation, and we propose a diagnostic feature-detection hypothesis to account for that result. According to this hypothesis, the simultaneous presentation of faces allows the eyewitness to appreciate that certain facial features (viz., those that are shared by everyone in the lineup) are non-diagnostic of guilt. To the extent that those non-diagnostic features are discounted in favor of potentially more diagnostic features, the ability to discriminate innocent from guilty suspects will be enhanced.

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.

Borehole Time Domain Reflectometry in Layered Sandstone: Impact of Measurement Technique on Vadose Zone Process Identification

NASA Astrophysics Data System (ADS)

West, J.; Truss, S. W.

2004-12-01

An investigation is reported into the hydraulic behaviour of the vadose zone of a layered sandstone aquifer using borehole-based Time Domain Reflectometry (TDR). TDR has been widely applied to shallow soils but has seen limited application at greater depth and in cemented lithologies due to the difficulty of installing conventional TDR probes in rock and from boreholes. Here, flat TDR probes that are simply in contact with, rather than inserted within the medium under investigation, have been developed and applied in a field study. Both a commercially available portable packer TDR system (TRIME-B3L Borehole Packer Probe) and specially designed TDR probes, permanently installed in boreholes on grouted-in packers were used to monitor seasonal fluctuations in moisture content in the vadose zone of a layered sandstone over one year under natural rainfall loading. The data show that the vadose zone contains seasonal perched water tables that form when downward percolating moisture reaches layers of fine grained sandstone and siltstone and causes local saturation. The formation of perched water tables is likely to lead to lateral flow bypassing the less permeable, finer layers. This contrasts with behaviour inferred from previous studies of the same aquifer that used borehole radar and resistivity, which suggested its vadose zone behaviour was characterized by uniform downwards migration of wetting fronts. To investigate the impact of measurement technique on observed response, the TDR data reported here were used to produce simulated zero offset profile (ZOP) borehole radar responses. This simulation confirmed the limited ability of ZOP borehole radar to detect key vadose zone processes, because the phenomenon of critical refraction minimizes the sensitivity of the results to high moisture content layers. The study illustrates that inappropriate technique selection results in hydrological process mis-identification, with serious consequences for the usefulness of data

DEM-based Approaches for the Identification of Flood Prone Areas

NASA Astrophysics Data System (ADS)

Samela, Caterina; Manfreda, Salvatore; Nardi, Fernando; Grimaldi, Salvatore; Roth, Giorgio; Sole, Aurelia

2013-04-01

The remarkable number of inundations that caused, in the last decades, thousands of deaths and huge economic losses, testifies the extreme vulnerability of many Countries to the flood hazard. As a matter of fact, human activities are often developed in the floodplains, creating conditions of extremely high risk. Terrain morphology plays an important role in understanding, modelling and analyzing the hydraulic behaviour of flood waves. Research during the last 10 years has shown that the delineation of flood prone areas can be carried out using fast methods that relay on basin geomorphologic features. In fact, the availability of new technologies to measure surface elevation (e.g., GPS, SAR, SAR interferometry, RADAR and LASER altimetry) has given a strong impulse to the development of Digital Elevation Models (DEMs) based approaches. The identification of the dominant topographic controls on the flood inundation process is a critical research question that we try to tackle with a comparative analysis of several techniques. We reviewed four different approaches for the morphological characterization of a river basin with the aim to provide a description of their performances and to identify their range of applicability. In particular, we explored the potential of the following tools. 1) The hydrogeomorphic method proposed by Nardi et al. (2006) which defines the flood prone areas according to the water level in the river network through the hydrogeomorphic theory. 2) The linear binary classifier proposed by Degiorgis et al. (2012) which allows distinguishing flood-prone areas using two features related to the location of the site under exam with respect to the nearest hazard source. The two features, proposed in the study, are the length of the path that hydrologically connects the location under exam to the nearest element of the drainage network and the difference in elevation between the cell under exam and the final point of the same path. 3) The method by

Projective Identification in Common Couple Dances.

ERIC Educational Resources Information Center

Middelberg, Carol V.

2001-01-01

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

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.

Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, X.; Liu, H.

2017-09-01

The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

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

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.

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.

Towards Open-World Person Re-Identification by One-Shot Group-Based Verification.

PubMed

Zheng, Wei-Shi; Gong, Shaogang; Xiang, Tao

2016-03-01

Solving the problem of matching people across non-overlapping multi-camera views, known as person re-identification (re-id), has received increasing interests in computer vision. In a real-world application scenario, a watch-list (gallery set) of a handful of known target people are provided with very few (in many cases only a single) image(s) (shots) per target. Existing re-id methods are largely unsuitable to address this open-world re-id challenge because they are designed for (1) a closed-world scenario where the gallery and probe sets are assumed to contain exactly the same people, (2) person-wise identification whereby the model attempts to verify exhaustively against each individual in the gallery set, and (3) learning a matching model using multi-shots. In this paper, a novel transfer local relative distance comparison (t-LRDC) model is formulated to address the open-world person re-identification problem by one-shot group-based verification. The model is designed to mine and transfer useful information from a labelled open-world non-target dataset. Extensive experiments demonstrate that the proposed approach outperforms both non-transfer learning and existing transfer learning based re-id methods.

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

Uncertainty analysis of wavelet-based feature extraction for isotope identification on NaI gamma-ray spectra

DOE PAGES

Stinnett, Jacob; Sullivan, Clair J.; Xiong, Hao

2017-03-02

Low-resolution isotope identifiers are widely deployed for nuclear security purposes, but these detectors currently demonstrate problems in making correct identifications in many typical usage scenarios. While there are many hardware alternatives and improvements that can be made, performance on existing low resolution isotope identifiers should be able to be improved by developing new identification algorithms. We have developed a wavelet-based peak extraction algorithm and an implementation of a Bayesian classifier for automated peak-based identification. The peak extraction algorithm has been extended to compute uncertainties in the peak area calculations. To build empirical joint probability distributions of the peak areas andmore » uncertainties, a large set of spectra were simulated in MCNP6 and processed with the wavelet-based feature extraction algorithm. Kernel density estimation was then used to create a new component of the likelihood function in the Bayesian classifier. Furthermore, identification performance is demonstrated on a variety of real low-resolution spectra, including Category I quantities of special nuclear material.« less

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.

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

Structural system identification based on variational mode decomposition

NASA Astrophysics Data System (ADS)

Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

2018-03-01

In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

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.

Contests versus Norms: Implications of Contest-Based and Norm-Based Intervention Techniques

PubMed Central

Bergquist, Magnus; Nilsson, Andreas; Hansla, André

2017-01-01

Interventions using either contests or norms can promote environmental behavioral change. Yet research on the implications of contest-based and norm-based interventions is lacking. Based on Goal-framing theory, we suggest that a contest-based intervention frames a gain goal promoting intensive but instrumental behavioral engagement. In contrast, the norm-based intervention was expected to frame a normative goal activating normative obligations for targeted and non-targeted behavior and motivation to engage in pro-environmental behaviors in the future. In two studies participants (n = 347) were randomly assigned to either a contest- or a norm-based intervention technique. Participants in the contest showed more intensive engagement in both studies. Participants in the norm-based intervention tended to report higher intentions for future energy conservation (Study 1) and higher personal norms for non-targeted pro-environmental behaviors (Study 2). These findings suggest that contest-based intervention technique frames a gain goal, while norm-based intervention frames a normative goal. PMID:29218026

Contests versus Norms: Implications of Contest-Based and Norm-Based Intervention Techniques.

PubMed

Bergquist, Magnus; Nilsson, Andreas; Hansla, André

2017-01-01

Interventions using either contests or norms can promote environmental behavioral change. Yet research on the implications of contest-based and norm-based interventions is lacking. Based on Goal-framing theory, we suggest that a contest-based intervention frames a gain goal promoting intensive but instrumental behavioral engagement. In contrast, the norm-based intervention was expected to frame a normative goal activating normative obligations for targeted and non-targeted behavior and motivation to engage in pro-environmental behaviors in the future. In two studies participants ( n = 347) were randomly assigned to either a contest- or a norm-based intervention technique. Participants in the contest showed more intensive engagement in both studies. Participants in the norm-based intervention tended to report higher intentions for future energy conservation (Study 1) and higher personal norms for non-targeted pro-environmental behaviors (Study 2). These findings suggest that contest-based intervention technique frames a gain goal, while norm-based intervention frames a normative goal.

Study on activity measurement of Nostoc flagelliforme cells based on color identification

NASA Astrophysics Data System (ADS)

Wang, Yizhong; Su, Jianyu; Liu, Tiegen; Kong, Fanzhi; Jia, Shiru

2008-12-01

In order to measure the activities of Nostoc flagelliforme cells, a new method based on color identification was proposed in this paper. N. flagelliforme cells were colored with fluoreseein diaeetate. Then, an image of colored N. flagelliforme cells was taken, and changed from RGB model to HIS model. Its histogram of hue H was calculated, which was used as the input of a designed BP network. The output of the BP network was the description of measured activity of N. flagelliforme cells. After training, the activity of N. flagelliforme cells was identified by the BP network according to the histogram of H of their colored image. Experiments were conducted with satisfied results to show the feasibility and usefulness of activity measurement of N. flagelliforme cells based on color identification.

Evaluation of speaker de-identification based on voice gender and age conversion

NASA Astrophysics Data System (ADS)

Přibil, Jiří; Přibilová, Anna; Matoušek, Jindřich

2018-03-01

Two basic tasks are covered in this paper. The first one consists in the design and practical testing of a new method for voice de-identification that changes the apparent age and/or gender of a speaker by multi-segmental frequency scale transformation combined with prosody modification. The second task is aimed at verification of applicability of a classifier based on Gaussian mixture models (GMM) to detect the original Czech and Slovak speakers after applied voice deidentification. The performed experiments confirm functionality of the developed gender and age conversion for all selected types of de-identification which can be objectively evaluated by the GMM-based open-set classifier. The original speaker detection accuracy was compared also for sentences uttered by German and English speakers showing language independence of the proposed method.

TipMT: Identification of PCR-based taxon-specific markers.

PubMed

Rodrigues-Luiz, Gabriela F; Cardoso, Mariana S; Valdivia, Hugo O; Ayala, Edward V; Gontijo, Célia M F; Rodrigues, Thiago de S; Fujiwara, Ricardo T; Lopes, Robson S; Bartholomeu, Daniella C

2017-02-11

Molecular genetic markers are one of the most informative and widely used genome features in clinical and environmental diagnostic studies. A polymerase chain reaction (PCR)-based molecular marker is very attractive because it is suitable to high throughput automation and confers high specificity. However, the design of taxon-specific primers may be difficult and time consuming due to the need to identify appropriate genomic regions for annealing primers and to evaluate primer specificity. Here, we report the development of a Tool for Identification of Primers for Multiple Taxa (TipMT), which is a web application to search and design primers for genotyping based on genomic data. The tool identifies and targets single sequence repeats (SSR) or orthologous/taxa-specific genes for genotyping using Multiplex PCR. This pipeline was applied to the genomes of four species of Leishmania (L. amazonensis, L. braziliensis, L. infantum and L. major) and validated by PCR using artificial genomic DNA mixtures of the Leishmania species as templates. This experimental validation demonstrates the reliability of TipMT because amplification profiles showed discrimination of genomic DNA samples from Leishmania species. The TipMT web tool allows for large-scale identification and design of taxon-specific primers and is freely available to the scientific community at http://200.131.37.155/tipMT/ .

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.

Identification of Diatraea spp. (Lepidoptera: Crambidae) based on cytochrome oxidase II.

PubMed

Barrera, Gloria Patricia; Villamizar, Laura Fernanda; Espinel, Carlos; Quintero, Edgar Mauricio; Belaich, Mariano Nicolás; Toloza, Deisy Liseth; Ghiringhelli, Pablo Daniel; Vargas, Germán

2017-01-01

Diatraea spp. (Lepidoptera: Crambidae) are a group of insects that are agriculture pests in many economically relevant crops such as sugarcane, sorghum, corn and rice. Recognized species for this genus respond differentially to natural enemies used in their biological control, emphasizing the importance of species in a regional approach. Currently, identification is based on the male genitalia. However, the availability of specimens collected from field and subjectivity based on the character recognition can seriously hamper species identification, and therefore result in inadequate pest management. To overcome this, individuals of Diatraea spp. preliminarily classified male genitalia and obtained from reared conditions and the field (both derived from natural populations occurring in Colombia) were analyzed using genitalic morphometry and molecular biology specifically using a fragment of the cytochrome oxidase subunit II (CO II) mitochondrial gene. Although morphometric analysis did not show any overriding results regarding genitalia morphology, the bioinformatics analyses of CO II sequences resulted in an adequate classification of the individuals within the recognized species. It also, revealed that the occurrence of clades associated with geographical distribution may be associated with cryptic species. The latter was also confirmed by a Single-Strand Conformation Polymorphism (SSCP) methodology evaluating the same fragment of CO II. This experimental approach allows properly recognizing each species and in consequence is proposed as an effective tool in Diatraea species identification.

Identification of Diatraea spp. (Lepidoptera: Crambidae) based on cytochrome oxidase II

PubMed Central

Villamizar, Laura Fernanda; Espinel, Carlos; Quintero, Edgar Mauricio; Belaich, Mariano Nicolás; Toloza, Deisy Liseth

2017-01-01

Diatraea spp. (Lepidoptera: Crambidae) are a group of insects that are agriculture pests in many economically relevant crops such as sugarcane, sorghum, corn and rice. Recognized species for this genus respond differentially to natural enemies used in their biological control, emphasizing the importance of species in a regional approach. Currently, identification is based on the male genitalia. However, the availability of specimens collected from field and subjectivity based on the character recognition can seriously hamper species identification, and therefore result in inadequate pest management. To overcome this, individuals of Diatraea spp. preliminarily classified male genitalia and obtained from reared conditions and the field (both derived from natural populations occurring in Colombia) were analyzed using genitalic morphometry and molecular biology specifically using a fragment of the cytochrome oxidase subunit II (CO II) mitochondrial gene. Although morphometric analysis did not show any overriding results regarding genitalia morphology, the bioinformatics analyses of CO II sequences resulted in an adequate classification of the individuals within the recognized species. It also, revealed that the occurrence of clades associated with geographical distribution may be associated with cryptic species. The latter was also confirmed by a Single-Strand Conformation Polymorphism (SSCP) methodology evaluating the same fragment of CO II. This experimental approach allows properly recognizing each species and in consequence is proposed as an effective tool in Diatraea species identification. PMID:28873431

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.

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

PubMed

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

2015-08-01

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

Application of an oligonucleotide microarray-based nano-amplification technique for the detection of fungal pathogens.

PubMed

Lu, Weiping; Gu, Dayong; Chen, Xingyun; Xiong, Renping; Liu, Ping; Yang, Nan; Zhou, Yuanguo

2010-10-01

The traditional techniques for diagnosis of invasive fungal infections in the clinical microbiology laboratory need improvement. These techniques are prone to delay results due to their time-consuming process, or result in misidentification of the fungus due to low sensitivity or low specificity. The aim of this study was to develop a method for the rapid detection and identification of fungal pathogens. The internal transcribed spacer two fragments of fungal ribosomal DNA were amplified using a polymerase chain reaction for all samples. Next, the products were hybridized with the probes immobilized on the surface of a microarray. These species-specific probes were designed to detect nine different clinical pathogenic fungi including Candida albicans, Candida tropocalis, Candida glabrata, Candida parapsilosis, Candida krusei, Candida lusitaniae, Candida guilliermondii, Candida keyfr, and Cryptococcus neoformans. The hybridizing signals were enhanced with gold nanoparticles and silver deposition, and detected using a flatbed scanner or visually. Fifty-nine strains of fungal pathogens, including standard and clinically isolated strains, were correctly identified by this method. The sensitivity of the assay for Candida albicans was 10 cells/mL. Ten cultures from clinical specimens and 12 clinical samples spiked with fungi were also identified correctly. This technique offers a reliable alternative to conventional methods for the detection and identification of fungal pathogens. It has higher efficiency, specificity and sensitivity compared with other methods commonly used in the clinical laboratory.

Recent Application of Solid Phase Based Techniques for Extraction and Preconcentration of Cyanotoxins in Environmental Matrices.

PubMed

Mashile, Geaneth Pertunia; Nomngongo, Philiswa N

2017-03-04

Cyanotoxins are toxic and are found in eutrophic, municipal, and residential water supplies. For this reason, their occurrence in drinking water systems has become a global concern. Therefore, monitoring, control, risk assessment, and prevention of these contaminants in the environmental bodies are important subjects associated with public health. Thus, rapid, sensitive, selective, simple, and accurate analytical methods for the identification and determination of cyanotoxins are required. In this paper, the sampling methodologies and applications of solid phase-based sample preparation methods for the determination of cyanotoxins in environmental matrices are reviewed. The sample preparation techniques mainly include solid phase micro-extraction (SPME), solid phase extraction (SPE), and solid phase adsorption toxin tracking technology (SPATT). In addition, advantages and disadvantages and future prospects of these methods have been discussed.

Feasibility of CRISPR-Cas9-Based In Vitro Drug Target Identification for Personalized Prostate Cancer Medicine

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-16-1-0502 TITLE: Feasibility of CRISPR -Cas9-Based In Vitro Drug Target Identification for Personalized Prostate Cancer Medicine...CONTRACT NUMBER Feasibility of CRISPR -Cas9-Based In Vitro Drug Target Identification for Personalized Prostate Cancer Medicine 5b. GRANT NUMBER...Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT This study tests the feasibility of using CRISPR -Cas9 to

Collaborative Processes in Species Identification Using an Internet-Based Taxonomic Resource

ERIC Educational Resources Information Center

Kontkanen, Jani; Kärkkäinen, Sirpa; Dillon, Patrick; Hartikainen-Ahia, Anu; Åhlberg, Mauri

2016-01-01

Visual databases are increasingly important resources through which individuals and groups can undertake species identification. This paper reports research on the collaborative processes undertaken by pre-service teacher students when working in small groups to identify birds using an Internet-based taxonomic resource. The student groups are…

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.

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.

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.

Confidence assignment for mass spectrometry based peptide identifications via the extreme value distribution.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2016-09-01

There is a growing trend for biomedical researchers to extract evidence and draw conclusions from mass spectrometry based proteomics experiments, the cornerstone of which is peptide identification. Inaccurate assignments of peptide identification confidence thus may have far-reaching and adverse consequences. Although some peptide identification methods report accurate statistics, they have been limited to certain types of scoring function. The extreme value statistics based method, while more general in the scoring functions it allows, demands accurate parameter estimates and requires, at least in its original design, excessive computational resources. Improving the parameter estimate accuracy and reducing the computational cost for this method has two advantages: it provides another feasible route to accurate significance assessment, and it could provide reliable statistics for scoring functions yet to be developed. We have formulated and implemented an efficient algorithm for calculating the extreme value statistics for peptide identification applicable to various scoring functions, bypassing the need for searching large random databases. The source code, implemented in C ++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit yyu@ncbi.nlm.nih.gov Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Identification of Poly(ethylene glycol) and Poly(ethylene glycol)-Based Detergents Using Peptide Search Engines.

PubMed

Ahmadi, Shiva; Winter, Dominic

2018-06-05

Poly(ethylene glycol) (PEG) is one of the most common polymer contaminations in mass spectrometry (MS) samples. At present, the detection of PEG and other polymers relies largely on manual inspection of raw data, which is laborious and frequently difficult due to sample complexity and retention characteristics of polymer species in reversed-phase chromatography. We developed a new strategy for the automated identification of PEG molecules from tandem mass spectrometry (MS/MS) data using protein identification algorithms in combination with a database containing "PEG-proteins". Through definition of variable modifications, we extend the approach for the identification of commonly used PEG-based detergents. We exemplify the identification of different types of polymers by static nanoelectrospray tandem mass spectrometry (nanoESI-MS/MS) analysis of pure detergent solutions and data analysis using Mascot. Analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) runs of a PEG-contaminated sample by Mascot identified 806 PEG spectra originating from four PEG species using a defined set of modifications covering PEG and common PEG-based detergents. Further characterization of the sample for unidentified PEG species using error-tolerant and mass-tolerant searches resulted in identification of 3409 and 3187 PEG-related MS/MS spectra, respectively. We further demonstrate the applicability of the strategy for Protein Pilot and MaxQuant.

Identification of the chemical components of Saussurea involucrata by high-resolution mass spectrometry and the mass spectral trees similarity filter technique.

PubMed

Jia, Zhixin; Wu, Caisheng; Jin, Hongtao; Zhang, Jinlan

2014-11-15

Saussurea involucrata is a rare traditional Chinese medicine (TCM) that displays anti-fatigue, anti-inflammatory and anti-tumor effects. In this paper, the different chemical components of Saussurea involucrata were characterized and identified over a wide dynamic range by high-performance liquid chromatography coupled with high-resolution hybrid mass spectrometry (HPLC/HRMS/MS(n)) and the mass spectral trees similarity filter (MTSF) technique. The aerial parts of Saussurea involucrata were extracted with 75% ethanol. The partial extract was separated on a chromatography column to concentrate the low-concentration compounds. Mass data were acquired using full-scan mass analysis (resolving power 50,000) with data-dependent incorporation of dynamic exclusion analysis. The identified compounds were used as templates to construct a database of mass spectral trees. Data for the unknown compounds were matched with those templates and matching candidate structures were obtained. The detected compounds were characterized based on matching to candidate structures by the MTSF technique and were further identified by their accurate mass weight, multiple-stage analysis and fragmentation patterns and through comparison with literature data. A total of 38 compounds were identified including 19 flavones, 11 phenylpropanoids and 8 sphingolipids. Among them, 7 flavonoids, 8 phenylpropanoids and 8 sphingolipids were identified for the first time in Saussurea involucrata. HPLC/HRMS/MS(n) combined with MTSF was successfully used to discover and identify the chemical compounds in Saussurea involucrata. The results indicated that this combined technique was extremely useful for the rapid detection and identification of the chemical components in TCMs. Copyright © 2014 John Wiley & Sons, Ltd.

Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric

NASA Astrophysics Data System (ADS)

Holobar, A.; Minetto, M. A.; Farina, D.

2014-02-01

Objective. A signal-based metric for assessment of accuracy of motor unit (MU) identification from high-density surface electromyograms (EMG) is introduced. This metric, so-called pulse-to-noise-ratio (PNR), is computationally efficient, does not require any additional experimental costs and can be applied to every MU that is identified by the previously developed convolution kernel compensation technique. Approach. The analytical derivation of the newly introduced metric is provided, along with its extensive experimental validation on both synthetic and experimental surface EMG signals with signal-to-noise ratios ranging from 0 to 20 dB and muscle contraction forces from 5% to 70% of the maximum voluntary contraction. Main results. In all the experimental and simulated signals, the newly introduced metric correlated significantly with both sensitivity and false alarm rate in identification of MU discharges. Practically all the MUs with PNR > 30 dB exhibited sensitivity >90% and false alarm rates <2%. Therefore, a threshold of 30 dB in PNR can be used as a simple method for selecting only reliably decomposed units. Significance. The newly introduced metric is considered a robust and reliable indicator of accuracy of MU identification. The study also shows that high-density surface EMG can be reliably decomposed at contraction forces as high as 70% of the maximum.

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

PubMed Central

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

2012-01-01

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

New Methodology for Known Metabolite Identification in Metabonomics/Metabolomics: Topological Metabolite Identification Carbon Efficiency (tMICE).

PubMed

Sanchon-Lopez, Beatriz; Everett, Jeremy R

2016-09-02

A new, simple-to-implement and quantitative approach to assessing the confidence in NMR-based identification of known metabolites is introduced. The approach is based on a topological analysis of metabolite identification information available from NMR spectroscopy studies and is a development of the metabolite identification carbon efficiency (MICE) method. New topological metabolite identification indices are introduced, analyzed, and proposed for general use, including topological metabolite identification carbon efficiency (tMICE). Because known metabolite identification is one of the key bottlenecks in either NMR-spectroscopy- or mass spectrometry-based metabonomics/metabolomics studies, and given the fact that there is no current consensus on how to assess metabolite identification confidence, it is hoped that these new approaches and the topological indices will find utility.

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

PubMed

Urwyler, S K; Glaubitz, J

2016-02-01

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

Electromechanical actuators affected by multiple failures: Prognostic method based on spectral analysis techniques

NASA Astrophysics Data System (ADS)

Belmonte, D.; Vedova, M. D. L. Dalla; Ferro, C.; Maggiore, P.

2017-06-01

The proposal of prognostic algorithms able to identify precursors of incipient failures of primary flight command electromechanical actuators (EMA) is beneficial for the anticipation of the incoming failure: an early and correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. An innovative prognostic model-based approach, able to recognize the EMA progressive degradations before his anomalous behaviors become critical, is proposed: the Fault Detection and Identification (FDI) of the considered incipient failures is performed analyzing proper system operational parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters will be correlated with the actual EMA health condition by means of failure maps created by a reference monitoring model-based algorithm. In this work, the proposed method has been tested in case of EMA affected by combined progressive failures: in particular, partial stator single phase turn to turn short-circuit and rotor static eccentricity are considered. In order to evaluate the prognostic method, a numerical test-bench has been conceived. Results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual malfunctioning, minimizing the risk of fake alarms or unannounced failures.

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.

Three dimensional indoor positioning based on visible light with Gaussian mixture sigma-point particle filter technique

NASA Astrophysics Data System (ADS)

Gu, Wenjun; Zhang, Weizhi; Wang, Jin; Amini Kashani, M. R.; Kavehrad, Mohsen

2015-01-01

Over the past decade, location based services (LBS) have found their wide applications in indoor environments, such as large shopping malls, hospitals, warehouses, airports, etc. Current technologies provide wide choices of available solutions, which include Radio-frequency identification (RFID), Ultra wideband (UWB), wireless local area network (WLAN) and Bluetooth. With the rapid development of light-emitting-diodes (LED) technology, visible light communications (VLC) also bring a practical approach to LBS. As visible light has a better immunity against multipath effect than radio waves, higher positioning accuracy is achieved. LEDs are utilized both for illumination and positioning purpose to realize relatively lower infrastructure cost. In this paper, an indoor positioning system using VLC is proposed, with LEDs as transmitters and photo diodes as receivers. The algorithm for estimation is based on received-signalstrength (RSS) information collected from photo diodes and trilateration technique. By appropriately making use of the characteristics of receiver movements and the property of trilateration, estimation on three-dimensional (3-D) coordinates is attained. Filtering technique is applied to enable tracking capability of the algorithm, and a higher accuracy is reached compare to raw estimates. Gaussian mixture Sigma-point particle filter (GM-SPPF) is proposed for this 3-D system, which introduces the notion of Gaussian Mixture Model (GMM). The number of particles in the filter is reduced by approximating the probability distribution with Gaussian components.