ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

PubMed Central

Zhang, Baixia; Li, Yanwen; Zhang, Yanling; Li, Zhiyong; Bi, Tian; He, Yusu; Song, Kuokui; Wang, Yun

2016-01-01

Identification of bioactive components is an important area of research in traditional Chinese medicine (TCM) formula. The reported identification methods only consider the interaction between the components and the target proteins, which is not sufficient to explain the influence of TCM on the gene expression. Here, we propose the Initial Transcription Process-based Identification (ITPI) method for the discovery of bioactive components that influence transcription factors (TFs). In this method, genome-wide chip detection technology was used to identify differentially expressed genes (DEGs). The TFs of DEGs were derived from GeneCards. The components influencing the TFs were derived from STITCH. The bioactive components in the formula were identified by evaluating the molecular similarity between the components in formula and the components that influence the TF of DEGs. Using the formula of Tian-Zhu-San (TZS) as an example, the reliability and limitation of ITPI were examined and 16 bioactive components that influence TFs were identified. PMID:27034696

A novel method for accurate needle-tip identification in trans-rectal ultrasound-based high-dose-rate prostate brachytherapy.

PubMed

Zheng, Dandan; Todor, Dorin A

2011-01-01

In real-time trans-rectal ultrasound (TRUS)-based high-dose-rate prostate brachytherapy, the accurate identification of needle-tip position is critical for treatment planning and delivery. Currently, needle-tip identification on ultrasound images can be subject to large uncertainty and errors because of ultrasound image quality and imaging artifacts. To address this problem, we developed a method based on physical measurements with simple and practical implementation to improve the accuracy and robustness of needle-tip identification. Our method uses measurements of the residual needle length and an off-line pre-established coordinate transformation factor, to calculate the needle-tip position on the TRUS images. The transformation factor was established through a one-time systematic set of measurements of the probe and template holder positions, applicable to all patients. To compare the accuracy and robustness of the proposed method and the conventional method (ultrasound detection), based on the gold-standard X-ray fluoroscopy, extensive measurements were conducted in water and gel phantoms. In water phantom, our method showed an average tip-detection accuracy of 0.7 mm compared with 1.6 mm of the conventional method. In gel phantom (more realistic and tissue-like), our method maintained its level of accuracy while the uncertainty of the conventional method was 3.4mm on average with maximum values of over 10mm because of imaging artifacts. A novel method based on simple physical measurements was developed to accurately detect the needle-tip position for TRUS-based high-dose-rate prostate brachytherapy. The method demonstrated much improved accuracy and robustness over the conventional method. Copyright © 2011 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Species Identification of Archaeological Skin Objects from Danish Bogs: Comparison between Mass Spectrometry-Based Peptide Sequencing and Microscopy-Based Methods

PubMed Central

Brandt, Luise Ørsted; Schmidt, Anne Lisbeth; Mannering, Ulla; Sarret, Mathilde; Kelstrup, Christian D.; Olsen, Jesper V.; Cappellini, Enrico

2014-01-01

Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC – AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029. PMID:25260035

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

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

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

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

PubMed

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

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

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.

Portraits of Benvenuto Cellini and Anthropological Methods of Their Identification

ERIC Educational Resources Information Center

Nasobin, Oleg

2016-01-01

Modern methods of biometric identification are increasingly applied in order to attribute works of art. They are based on developments in the 19th century anthropological methods. So, this article describes how the successional anthropological methods were applied for the identification of Benvenuto Cellini's portraits. Objective comparison of…

[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.

Personal Identification of Deceased Persons: An Overview of the Current Methods Based on Physical Appearance.

PubMed

Caplova, Zuzana; Obertova, Zuzana; Gibelli, Daniele M; De Angelis, Danilo; Mazzarelli, Debora; Sforza, Chiarella; Cattaneo, Cristina

2018-05-01

The use of the physical appearance of the deceased has become more important because the available antemortem information for comparisons may consist only of a physical description and photographs. Twenty-one articles dealing with the identification based on the physiognomic features of the human body were selected for review and were divided into four sections: (i) visual recognition, (ii) specific facial/body areas, (iii) biometrics, and (iv) dental superimposition. While opinions about the reliability of the visual recognition differ, the search showed that it has been used in mass disasters, even without testing its objectivity and reliability. Specific facial areas being explored for the identification of dead; however, their practical use is questioned, similarly to soft biometrics. The emerging dental superimposition seems to be the only standardized and successfully applied method for identification so far. More research is needed into a potential use of the individualizing features, considering that postmortem changes and technical difficulties may affect the identification. © 2017 American Academy of Forensic Sciences.

DNA methods for identification of Chinese medicinal materials

PubMed Central

Yip, Pui Ying; Chau, Chi Fai; Mak, Chun Yin; Kwan, Hoi Shan

2007-01-01

As adulterated and substituted Chinese medicinal materials are common in the market, therapeutic effectiveness of such materials cannot be guaranteed. Identification at species-, strain- and locality-levels, therefore, is required for quality assurance/control of Chinese medicine. This review provides an informative introduction to DNA methods for authentication of Chinese medicinal materials. Technical features and examples of the methods based on sequencing, hybridization and polymerase chain reaction (PCR) are described and their suitability for different identification objectives is discussed. PMID:17803808

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

PubMed

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

PubMed Central

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components. PMID:29692857

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.

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.

Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

PubMed

LaBudde, Robert A; Harnly, James M

2012-01-01

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

Exploratory methods for truck re-identification in a statewide network based on axle weight and axle spacing data to enhance freight metrics : phase II.

DOT National Transportation Integrated Search

2012-05-01

Vehicle re-identification methods can be used to anonymously match vehicles crossing two different locations based on vehicle attribute data. : This research builds upon a previous study and investigates different methods for solving the re-identific...

A subsystem identification method based on the path concept with coupling strength estimation

NASA Astrophysics Data System (ADS)

Magrans, Francesc Xavier; Poblet-Puig, Jordi; Rodríguez-Ferran, Antonio

2018-02-01

For complex geometries, the definition of the subsystems is not a straightforward task. We present here a subsystem identification method based on the direct transfer matrix, which represents the first-order paths. The key ingredient is a cluster analysis of the rows of the powers of the transfer matrix. These powers represent high-order paths in the system and are more affected than low-order paths by damping. Once subsystems are identified, the proposed approach also provides a quantification of the degree of coupling between subsystems. This information is relevant to decide whether a subsystem may be analysed in a computer model or measured in the laboratory independently of the rest or subsystems or not. The two features (subsystem identification and quantification of the degree of coupling) are illustrated by means of numerical examples: plates coupled by means of springs and rooms connected by means of a cavity.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

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.

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.

Minimum constitutive relation error based static identification of beams using force method

NASA Astrophysics Data System (ADS)

Guo, Jia; Takewaki, Izuru

2017-05-01

A new static identification approach based on the minimum constitutive relation error (CRE) principle for beam structures is introduced. The exact stiffness and the exact bending moment are shown to make the CRE minimal for given displacements to beam damages. A two-step substitution algorithm—a force-method step for the bending moment and a constitutive-relation step for the stiffness—is developed and its convergence is rigorously derived. Identifiability is further discussed and the stiffness in the undeformed region is found to be unidentifiable. An extra set of static measurements is complemented to remedy the drawback. Convergence and robustness are finally verified through numerical examples.

Search-based model identification of smart-structure damage

NASA Technical Reports Server (NTRS)

Glass, B. J.; Macalou, A.

1991-01-01

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

[Identification of special quality eggs with NIR spectroscopy technology based on symbol entropy feature extraction method].

PubMed

Zhao, Yong; Hong, Wen-Xue

2011-11-01

Fast, nondestructive and accurate identification of special quality eggs is an urgent problem. The present paper proposed a new feature extraction method based on symbol entropy to identify near infrared spectroscopy of special quality eggs. The authors selected normal eggs, free range eggs, selenium-enriched eggs and zinc-enriched eggs as research objects and measured the near-infrared diffuse reflectance spectra in the range of 12 000-4 000 cm(-1). Raw spectra were symbolically represented with aggregation approximation algorithm and symbolic entropy was extracted as feature vector. An error-correcting output codes multiclass support vector machine classifier was designed to identify the spectrum. Symbolic entropy feature is robust when parameter changed and the highest recognition rate reaches up to 100%. The results show that the identification method of special quality eggs using near-infrared is feasible and the symbol entropy can be used as a new feature extraction method of near-infrared spectra.

Method for identification of rigid domains and hinge residues in proteins based on exhaustive enumeration.

PubMed

Sim, Jaehyun; Sim, Jun; Park, Eunsung; Lee, Julian

2015-06-01

Many proteins undergo large-scale motions where relatively rigid domains move against each other. The identification of rigid domains, as well as the hinge residues important for their relative movements, is important for various applications including flexible docking simulations. In this work, we develop a method for protein rigid domain identification based on an exhaustive enumeration of maximal rigid domains, the rigid domains not fully contained within other domains. The computation is performed by mapping the problem to that of finding maximal cliques in a graph. A minimal set of rigid domains are then selected, which cover most of the protein with minimal overlap. In contrast to the results of existing methods that partition a protein into non-overlapping domains using approximate algorithms, the rigid domains obtained from exact enumeration naturally contain overlapping regions, which correspond to the hinges of the inter-domain bending motion. The performance of the algorithm is demonstrated on several proteins. © 2015 Wiley Periodicals, Inc.

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.

Identification Method of Mud Shale Fractures Base on Wavelet Transform

NASA Astrophysics Data System (ADS)

Xia, Weixu; Lai, Fuqiang; Luo, Han

2018-01-01

In recent years, inspired by seismic analysis technology, a new method for analysing mud shale fractures oil and gas reservoirs by logging properties has emerged. By extracting the high frequency attribute of the wavelet transform in the logging attribute, the formation information hidden in the logging signal is extracted, identified the fractures that are not recognized by conventional logging and in the identified fracture segment to show the “cycle jump”, “high value”, “spike” and other response effect is more obvious. Finally formed a complete wavelet denoising method and wavelet high frequency identification fracture method.

Damage identification method for continuous girder bridges based on spatially-distributed long-gauge strain sensing under moving loads

NASA Astrophysics Data System (ADS)

Wu, Bitao; Wu, Gang; Yang, Caiqian; He, Yi

2018-05-01

A novel damage identification method for concrete continuous girder bridges based on spatially-distributed long-gauge strain sensing is presented in this paper. First, the variation regularity of the long-gauge strain influence line of continuous girder bridges which changes with the location of vehicles on the bridge is studied. According to this variation regularity, a calculation method for the distribution regularity of the area of long-gauge strain history is investigated. Second, a numerical simulation of damage identification based on the distribution regularity of the area of long-gauge strain history is conducted, and the results indicate that this method is effective for identifying damage and is not affected by the speed, axle number and weight of vehicles. Finally, a real bridge test on a highway is conducted, and the experimental results also show that this method is very effective for identifying damage in continuous girder bridges, and the local element stiffness distribution regularity can be revealed at the same time. This identified information is useful for maintaining of continuous girder bridges on highways.

A lithology identification method for continental shale oil reservoir based on BP neural network

NASA Astrophysics Data System (ADS)

Han, Luo; Fuqiang, Lai; Zheng, Dong; Weixu, Xia

2018-06-01

The Dongying Depression and Jiyang Depression of the Bohai Bay Basin consist of continental sedimentary facies with a variable sedimentary environment and the shale layer system has a variety of lithologies and strong heterogeneity. It is difficult to accurately identify the lithologies with traditional lithology identification methods. The back propagation (BP) neural network was used to predict the lithology of continental shale oil reservoirs. Based on the rock slice identification, x-ray diffraction bulk rock mineral analysis, scanning electron microscope analysis, and the data of well logging and logging, the lithology was divided with carbonate, clay and felsic as end-member minerals. According to the core-electrical relationship, the frequency histogram was then used to calculate the logging response range of each lithology. The lithology-sensitive curves selected from 23 logging curves (GR, AC, CNL, DEN, etc) were chosen as the input variables. Finally, the BP neural network training model was established to predict the lithology. The lithology in the study area can be divided into four types: mudstone, lime mudstone, lime oil-mudstone, and lime argillaceous oil-shale. The logging responses of lithology were complicated and characterized by the low values of four indicators and medium values of two indicators. By comparing the number of hidden nodes and the number of training times, we found that the number of 15 hidden nodes and 1000 times of training yielded the best training results. The optimal neural network training model was established based on the above results. The lithology prediction results of BP neural network of well XX-1 showed that the accuracy rate was over 80%, indicating that the method was suitable for lithology identification of continental shale stratigraphy. The study provided the basis for the reservoir quality and oily evaluation of continental shale reservoirs and was of great significance to shale oil and gas exploration.

Noncontact blood species identification method based on spatially resolved near-infrared transmission spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Linna; Sun, Meixiu; Wang, Zhennan; Li, Hongxiao; Li, Yingxin; Li, Gang; Lin, Ling

2017-09-01

The inspection and identification of whole blood are crucially significant for import-export ports and inspection and quarantine departments. In our previous research, we proved Near-Infrared diffuse transmitted spectroscopy method was potential for noninvasively identifying three blood species, including macaque, human and mouse, with samples measured in the cuvettes. However, in open sampling cases, inspectors may be endangered by virulence factors in blood samples. In this paper, we explored the noncontact measurement for classification, with blood samples measured in the vacuum blood vessels. Spatially resolved near-infrared spectroscopy was used to improve the prediction accuracy. Results showed that the prediction accuracy of the model built with nine detection points was more than 90% in identification between all five species, including chicken, goat, macaque, pig and rat, far better than the performance of the model built with single-point spectra. The results fully supported the idea that spatially resolved near-infrared spectroscopy method can improve the prediction ability, and demonstrated the feasibility of this method for noncontact blood species identification in practical applications.

Novel inter-crystal scattering event identification method for PET detectors

NASA Astrophysics Data System (ADS)

Lee, Min Sun; Kang, Seung Kwan; Lee, Jae Sung

2018-06-01

Here, we propose a novel method to identify inter-crystal scattering (ICS) events from a PET detector that is even applicable to light-sharing designs. In the proposed method, the detector observation was considered as a linear problem and ICS events were identified by solving this problem. Two ICS identification methods were suggested for solving the linear problem, pseudoinverse matrix calculation and convex constrained optimization. The proposed method was evaluated based on simulation and experimental studies. For the simulation study, an 8  ×  8 photo sensor was coupled to 8  ×  8, 10  ×  10 and 12  ×  12 crystal arrays to simulate a one-to-one coupling and two light-sharing detectors, respectively. The identification rate, the rate that the identified ICS events correctly include the true first interaction position and the energy linearity were evaluated for the proposed ICS identification methods. For the experimental study, a digital silicon photomultiplier was coupled with 8  ×  8 and 10  ×  10 arrays of 3  ×  3  ×  20 mm3 LGSO crystals to construct the one-to-one coupling and light-sharing detectors, respectively. Intrinsic spatial resolutions were measured for two detector types. The proposed ICS identification methods were implemented, and intrinsic resolutions were compared with and without ICS recovery. As a result, the simulation study showed that the proposed convex optimization method yielded robust energy estimation and high ICS identification rates of 0.93 and 0.87 for the one-to-one and light-sharing detectors, respectively. The experimental study showed a resolution improvement after recovering the identified ICS events into the first interaction position. The average intrinsic spatial resolutions for the one-to-one and light-sharing detector were 1.95 and 2.25 mm in the FWHM without ICS recovery, respectively. These values improved to 1.72 and 1.83 mm after ICS

Do Toxicity Identification and Evaluation Laboratory-Based Methods Reflect Causes of Field Impairment?

EPA Science Inventory

Sediment Toxicity Identification and Evaluation (TIE) methods have been developed for both interstitial waters and whole sediments. These relatively simple laboratory methods are designed to identify specific toxicants or classes of toxicants in sediments; however, the question ...

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2015-10-21

The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the prior knowledge used to construct the feature vector for each instance (gene), the ways of selecting negative data (non-disease genes) where there is no investigational approach to find them and the classification methods used to make the final decision. In this work, a novel Sequence-based fusion method (SFM) is proposed to identify disease genes. In this regard, unlike existing methods, instead of using a noisy and incomplete prior-knowledge, the amino acid sequence of the proteins which is universal data has been carried out to present the genes (proteins) into four different feature vectors. To select more likely negative data from candidate genes, the intersection set of four negative sets which are generated using distance approach is considered. Then, Decision Tree (C4.5) has been applied as a fusion method to combine the results of four independent state-of the-art predictors based on support vector machine (SVM) algorithm, and to make the final decision. The experimental results of the proposed method have been evaluated by some standard measures. The results indicate the precision, recall and F-measure of 82.6%, 85.6% and 84, respectively. These results confirm the efficiency and validity of the proposed method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Method for genetic identification of unknown organisms

DOEpatents

Colston, Jr., Billy W.; Fitch, Joseph P.; Hindson, Benjamin J.; Carter, Chance J.; Beer, Neil Reginald

2016-08-23

A method of rapid, genome and proteome based identification of unknown pathogenic or non-pathogenic organisms in a complex sample. The entire sample is analyzed by creating millions of emulsion encapsulated microdroplets, each containing a single pathogenic or non-pathogenic organism sized particle and appropriate reagents for amplification. Following amplification, the amplified product is analyzed.

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.

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.

Individual-specific antibody identification methods

DOEpatents

Francoeur, Ann -Michele

1989-11-14

An identification method, applicable to the identification of animals or inanimate objects, is described. The method takes advantage of a hithertofore unknown set of individual-specific, or IS antibodies, that are part of the unique antibody repertoire present in animals, by reacting an effective amount of IS antibodies with a particular panel, or n-dimensional array (where n is typically one or two) consisting of an effective amount of many different antigens (typically greater than one thousand), to give antibody-antigen complexes. The profile or pattern formed by the antigen-antibody complexes, termed an antibody fingerprint, when revealed by an effective amount of an appropriate detector molecule, is uniquely representative of a particular individual. The method can similarly by used to distinguish genetically, or otherwise similar individuals, or their body parts containing IS antibodies. Identification of inanimate objects, particularly security documents, is similarly affected by associating with the documents, an effective amount of a particular individual's IS antibodies, or conversely, a particular panel of antigens, and forming antibody-antigen complexes with a particular panel of antigens, or a particular individual's IS antibodies, respectively. One embodiment of the instant identification method, termed the blocked fingerprint assay, has applications in the area of allergy testing, autoimmune diagnostics and therapeutics, and the detection of environmental antigens such as pathogens, chemicals, and toxins.

Critical Assessment of Small Molecule Identification 2016: automated methods.

PubMed

Schymanski, Emma L; Ruttkies, Christoph; Krauss, Martin; Brouard, Céline; Kind, Tobias; Dührkop, Kai; Allen, Felicity; Vaniya, Arpana; Verdegem, Dries; Böcker, Sebastian; Rousu, Juho; Shen, Huibin; Tsugawa, Hiroshi; Sajed, Tanvir; Fiehn, Oliver; Ghesquière, Bart; Neumann, Steffen

2017-03-27

The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest ( www.casmi-contest.org ) was held in 2016, with two new categories for automated methods. This article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluation of CASMI 2016 through to perspectives for future contests and small molecule annotation/identification. The Input Output Kernel Regression (CSI:IOKR) machine learning approach performed best in "Category 2: Best Automatic Structural Identification-In Silico Fragmentation Only", won by Team Brouard with 41% challenge wins. The winner of "Category 3: Best Automatic Structural Identification-Full Information" was Team Kind (MS-FINDER), with 76% challenge wins. The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges. This success rate rose to 70% Top 1 ranks in Category 3, with candidates in the Top 10 in over 80% of the challenges. The machine learning and chemistry-based approaches are shown to perform in complementary ways. The improvement in (semi-)automated fragmentation methods for small molecule identification has been substantial. The achieved high rates of correct candidates in the Top 1 and Top 10, despite large candidate numbers, open up great possibilities for high-throughput annotation of untargeted analysis for "known unknowns". As more high quality training data becomes available, the improvements in machine learning methods will likely continue, but the alternative approaches still provide valuable complementary information. Improved integration of experimental context will also improve identification success further for "real life" annotations. The true "unknown unknowns" remain to be evaluated in future CASMI contests. Graphical abstract .

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

PubMed Central

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

2014-01-01

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

Summary of tracking and identification methods

NASA Astrophysics Data System (ADS)

Blasch, Erik; Yang, Chun; Kadar, Ivan

2014-06-01

Over the last two decades, many solutions have arisen to combine target tracking estimation with classification methods. Target tracking includes developments from linear to non-linear and Gaussian to non-Gaussian processing. Pattern recognition includes detection, classification, recognition, and identification methods. Integrating tracking and pattern recognition has resulted in numerous approaches and this paper seeks to organize the various approaches. We discuss the terminology so as to have a common framework for various standards such as the NATO STANAG 4162 - Identification Data Combining Process. In a use case, we provide a comparative example highlighting that location information (as an example) with additional mission objectives from geographical, human, social, cultural, and behavioral modeling is needed to determine identification as classification alone does not allow determining identification or intent.

A multi-damages identification method for cantilever beam based on mode shape curvatures and Kriging surrogate model

NASA Astrophysics Data System (ADS)

Xie, Fengle; Jiang, Zhansi; Jiang, Hui

2018-05-01

This paper presents a multi-damages identification method for Cantilever Beam. First, the damage location is identified by using the mode shape curvatures. Second, samples of varying damage severities at the damage location and their corresponding natural frequencies are used to construct the initial Kriging surrogate model. Then a particle swarm optimization (PSO) algorithm is employed to identify the damage severities based on Kriging surrogate model. The simulation study of a double-damaged cantilever beam demonstrated that the proposed method is effective.

New approach for point pollution source identification in rivers based on the backward probability method.

PubMed

Wang, Jiabiao; Zhao, Jianshi; Lei, Xiaohui; Wang, Hao

2018-06-13

Pollution risk from the discharge of industrial waste or accidental spills during transportation poses a considerable threat to the security of rivers. The ability to quickly identify the pollution source is extremely important to enable emergency disposal of pollutants. This study proposes a new approach for point source identification of sudden water pollution in rivers, which aims to determine where (source location), when (release time) and how much pollutant (released mass) was introduced into the river. Based on the backward probability method (BPM) and the linear regression model (LR), the proposed LR-BPM converts the ill-posed problem of source identification into an optimization model, which is solved using a Differential Evolution Algorithm (DEA). The decoupled parameters of released mass are not dependent on prior information, which improves the identification efficiency. A hypothetical case study with a different number of pollution sources was conducted to test the proposed approach, and the largest relative errors for identified location, release time, and released mass in all tests were not greater than 10%. Uncertainty in the LR-BPM is mainly due to a problem with model equifinality, but averaging the results of repeated tests greatly reduces errors. Furthermore, increasing the gauging sections further improves identification results. A real-world case study examines the applicability of the LR-BPM in practice, where it is demonstrated to be more accurate and time-saving than two existing approaches, Bayesian-MCMC and basic DEA. Copyright © 2018 Elsevier Ltd. All rights reserved.

Blade resonance parameter identification based on tip-timing method without the once-per revolution sensor

NASA Astrophysics Data System (ADS)

Guo, Haotian; Duan, Fajie; Zhang, Jilong

2016-01-01

Blade tip-timing is the most effective method for blade vibration online measurement of turbomachinery. In this article a synchronous resonance vibration measurement method of blade based on tip-timing is presented. This method requires no once-per revolution sensor which makes it more generally applicable in the condition where this sensor is difficult to install, especially for the high-pressure rotors of dual-rotor engines. Only three casing mounted probes are required to identify the engine order, amplitude, natural frequency and the damping coefficient of the blade. A method is developed to identify the blade which a tip-timing data belongs to without once-per revolution sensor. Theoretical analyses of resonance parameter measurement are presented. Theoretic error of the method is investigated and corrected. Experiments are conducted and the results indicate that blade resonance parameter identification is achieved without once-per revolution sensor.

[A accurate identification method for Chinese materia medica--systematic identification of Chinese materia medica].

PubMed

Wang, Xue-Yong; Liao, Cai-Li; Liu, Si-Qi; Liu, Chun-Sheng; Shao, Ai-Juan; Huang, Lu-Qi

2013-05-01

This paper put forward a more accurate identification method for identification of Chinese materia medica (CMM), the systematic identification of Chinese materia medica (SICMM) , which might solve difficulties in CMM identification used the ordinary traditional ways. Concepts, mechanisms and methods of SICMM were systematically introduced and possibility was proved by experiments. The establishment of SICMM will solve problems in identification of Chinese materia medica not only in phenotypic characters like the mnorphous, microstructure, chemical constituents, but also further discovery evolution and classification of species, subspecies and population in medical plants. The establishment of SICMM will improve the development of identification of CMM and create a more extensive study space.

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

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

PubMed

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

2012-07-27

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

Identification of Pseudallescheria and Scedosporium species by three molecular methods.

PubMed

Lu, Qiaoyun; Gerrits van den Ende, A H G; Bakkers, J M J E; Sun, Jiufeng; Lackner, M; Najafzadeh, M J; Melchers, W J G; Li, Ruoyu; de Hoog, G S

2011-03-01

The major clinically relevant species in Scedosporium (teleomorph Pseudallescheria) are Pseudallescheria boydii, Scedosporium aurantiacum, Scedosporium apiospermum, and Scedosporium prolificans, while Pseudallescheria minutispora, Petriellopsis desertorum, and Scedosporium dehoogii are exceptional agents of disease. Three molecular methods targeting the partial β-tubulin gene were developed and evaluated to identify six closely related species of the S. apiospermum complex using quantitative real-time PCR (qPCR), PCR-based reverse line blot (PCR-RLB), and loop-mediated isothermal amplification (LAMP). qPCR was not specific enough for the identification of all species but had the highest sensitivity. The PCR-RLB assay was efficient for the identification of five species. LAMP distinguished all six species unambiguously. The analytical sensitivities of qPCR, PCR-RLB, and LAMP combined with MagNAPure, CTAB (cetyltrimethylammonium bromide), and FTA filter (Whatman) extraction were 50, 5 × 10(3), and 5 × 10(2) cells/μl, respectively. When LAMP was combined with a simplified DNA extraction method using an FTA filter, identification to the species level was achieved within 2 h, including DNA extraction. The FTA-LAMP assay is therefore recommended as a cost-effective, simple, and rapid method for the identification of Scedosporium species.

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.

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…

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.

A network-based method for the identification of putative genes related to infertility.

PubMed

Wang, ShaoPeng; Huang, GuoHua; Hu, Qinghua; Zou, Quan

2016-11-01

Infertility has become one of the major health problems worldwide, with its incidence having risen markedly in recent decades. There is an urgent need to investigate the pathological mechanisms behind infertility and to design effective treatments. However, this is made difficult by the fact that various biological factors have been identified to be related to infertility, including genetic factors. A network-based method was established to identify new genes potentially related to infertility. A network constructed using human protein-protein interactions based on previously validated infertility-related genes enabled the identification of some novel candidate genes. These genes were then filtered by a permutation test and their functional and structural associations with infertility-related genes. Our method identified 23 novel genes, which have strong functional and structural associations with previously validated infertility-related genes. Substantial evidence indicates that the identified genes are strongly related to dysfunction of the four main biological processes of fertility: reproductive development and physiology, gametogenesis, meiosis and recombination, and hormone regulation. The newly discovered genes may provide new directions for investigating infertility. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Rapid identification of ascomycetous yeasts from clinical specimens by a molecular method based on flow cytometry and comparison with identifications from phenotypic assays.

PubMed

Page, Brent T; Shields, Christine E; Merz, William G; Kurtzman, Cletus P

2006-09-01

This study was designed to compare the identification of ascomycetous yeasts recovered from clinical specimens by using phenotypic assays (PA) and a molecular flow cytometric (FC) method. Large-subunit rRNA domains 1 and 2 (D1/D2) gene sequence analysis was also performed and served as the reference for correct strain identification. A panel of 88 clinical isolates was tested that included representatives of nine commonly encountered species and six infrequently encountered species. The PA included germ tube production, fermentation of seven carbohydrates, morphology on corn meal agar, urease and phenoloxidase activities, and carbohydrate assimilation tests when needed. The FC method (Luminex) employed species-specific oligonucleotides attached to polystyrene beads, which were hybridized with D1/D2 amplicons from the unidentified isolates. The PA identified 81 of 88 strains correctly but misidentified 4 of Candida dubliniensis, 1 of C. bovina, 1 of C. palmioleophila, and 1 of C. bracarensis. The FC method correctly identified 79 of 88 strains and did not misidentify any isolate but did not identify nine isolates because oligonucleotide probes were not available in the current library. The FC assay takes approximately 5 h, whereas the PA takes from 2 h to 5 days for identification. In conclusion, PA did well with the commonly encountered species, was not accurate for uncommon species, and takes significantly longer than the FC method. These data strongly support the potential of FC technology for rapid and accurate identification of medically important yeasts. With the introduction of new antifungals, rapid, accurate identification of pathogenic yeasts is more important than ever for guiding antifungal chemotherapy.

Space-Based Identification of Archaeological Illegal Excavations and a New Automatic Method for Looting Feature Extraction in Desert Areas

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Masini, Nicola

2018-06-01

The identification and quantification of disturbance of archaeological sites has been generally approached by visual inspection of optical aerial or satellite pictures. In this paper, we briefly summarize the state of the art of the traditionally satellite-based approaches for looting identification and propose a new automatic method for archaeological looting feature extraction approach (ALFEA). It is based on three steps: the enhancement using spatial autocorrelation, unsupervised classification, and segmentation. ALFEA has been applied to Google Earth images of two test areas, selected in desert environs in Syria (Dura Europos), and in Peru (Cahuachi-Nasca). The reliability of ALFEA was assessed through field surveys in Peru and visual inspection for the Syrian case study. Results from the evaluation procedure showed satisfactory performance from both of the two analysed test cases with a rate of success higher than 90%.

Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture

DOEpatents

Steele, Kerry D [Kennewick, WA; Anderson, Gordon A [Benton City, WA; Gilbert, Ronald W [Morgan Hill, CA

2011-02-01

Communications device identification methods, communications methods, wireless communications readers, wireless communications systems, and articles of manufacture are described. In one aspect, a communications device identification method includes providing identification information regarding a group of wireless identification devices within a wireless communications range of a reader, using the provided identification information, selecting one of a plurality of different search procedures for identifying unidentified ones of the wireless identification devices within the wireless communications range, and identifying at least some of the unidentified ones of the wireless identification devices using the selected one of the search procedures.

Multiple independent identification decisions: a method of calibrating eyewitness identifications.

PubMed

Pryke, Sean; Lindsay, R C L; Dysart, Jennifer E; Dupuis, Paul

2004-02-01

Two experiments (N = 147 and N = 90) explored the use of multiple independent lineups to identify a target seen live. In Experiment 1, simultaneous face, body, and sequential voice lineups were used. In Experiment 2, sequential face, body, voice, and clothing lineups were used. Both studies demonstrated that multiple identifications (by the same witness) from independent lineups of different features are highly diagnostic of suspect guilt (G. L. Wells & R. C. L. Lindsay, 1980). The number of suspect and foil selections from multiple independent lineups provides a powerful method of calibrating the accuracy of eyewitness identification. Implications for use of current methods are discussed. ((c) 2004 APA, all rights reserved)

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

[Identification of Dens Draconis and Os Draconis by XRD method].

PubMed

Chen, Guang-Yun; Wu, Qi-Nan; Shen, Bei; Chen, Rong

2012-04-01

To establish an XRD method for evaluating the quality of Os Draconis and Dens Draconis and applying in judgement of the counterfeit. Dens Draconis, Os Draconis and the counterfeit of Os Draconis were analyzed by XRD. Their diffraction patterns were clustered analysis and evaluated their similarity degree. Established the analytical method of Dens Draconis and Os Draconis basing the features fingerprint information of the 10 common peaks by XRD pattern. Obtained the XRD pattern of the counterfeit of Os Draconis. The similarity degree of separate sources of Dens Draconis was high,while the similarity degree of separate sources of Os Draconis was significant different from each other. This method can be used for identification and evaluation of Os Draconis and Dens Draconis. It also can be used for identification the counterfeit of Os Draconis effectively.

Identification of active sources inside cavities using the equivalent source method-based free-field recovery technique

NASA Astrophysics Data System (ADS)

Bi, Chuan-Xing; Hu, Ding-Yu; Zhang, Yong-Bin; Jing, Wen-Qian

2015-06-01

In previous studies, an equivalent source method (ESM)-based technique for recovering the free sound field in a noisy environment has been successfully applied to exterior problems. In order to evaluate its performance when applied to a more general noisy environment, that technique is used to identify active sources inside cavities where the sound field is composed of the field radiated by active sources and that reflected by walls. A patch approach with two semi-closed surfaces covering the target active sources is presented to perform the measurements, and the field that would be radiated by these target active sources into free space is extracted from the mixed field by using the proposed technique, which will be further used as the input of nearfield acoustic holography for source identification. Simulation and experimental results validate the effectiveness of the proposed technique for source identification in cavities, and show the feasibility of performing the measurements with a double layer planar array.

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.

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.

An improved wavelet-Galerkin method for dynamic response reconstruction and parameter identification of shear-type frames

NASA Astrophysics Data System (ADS)

Bu, Haifeng; Wang, Dansheng; Zhou, Pin; Zhu, Hongping

2018-04-01

An improved wavelet-Galerkin (IWG) method based on the Daubechies wavelet is proposed for reconstructing the dynamic responses of shear structures. The proposed method flexibly manages wavelet resolution level according to excitation, thereby avoiding the weakness of the wavelet-Galerkin multiresolution analysis (WGMA) method in terms of resolution and the requirement of external excitation. IWG is implemented by this work in certain case studies, involving single- and n-degree-of-freedom frame structures subjected to a determined discrete excitation. Results demonstrate that IWG performs better than WGMA in terms of accuracy and computation efficiency. Furthermore, a new method for parameter identification based on IWG and an optimization algorithm are also developed for shear frame structures, and a simultaneous identification of structural parameters and excitation is implemented. Numerical results demonstrate that the proposed identification method is effective for shear frame structures.

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.

[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.

Spectrum-based method to generate good decoy libraries for spectral library searching in peptide identifications.

PubMed

Cheng, Chia-Ying; Tsai, Chia-Feng; Chen, Yu-Ju; Sung, Ting-Yi; Hsu, Wen-Lian

2013-05-03

As spectral library searching has received increasing attention for peptide identification, constructing good decoy spectra from the target spectra is the key to correctly estimating the false discovery rate in searching against the concatenated target-decoy spectral library. Several methods have been proposed to construct decoy spectral libraries. Most of them construct decoy peptide sequences and then generate theoretical spectra accordingly. In this paper, we propose a method, called precursor-swap, which directly constructs decoy spectral libraries directly at the "spectrum level" without generating decoy peptide sequences by swapping the precursors of two spectra selected according to a very simple rule. Our spectrum-based method does not require additional efforts to deal with ion types (e.g., a, b or c ions), fragment mechanism (e.g., CID, or ETD), or unannotated peaks, but preserves many spectral properties. The precursor-swap method is evaluated on different spectral libraries and the results of obtained decoy ratios show that it is comparable to other methods. Notably, it is efficient in time and memory usage for constructing decoy libraries. A software tool called Precursor-Swap-Decoy-Generation (PSDG) is publicly available for download at http://ms.iis.sinica.edu.tw/PSDG/.

A Review of System Identification Methods Applied to Aircraft

NASA Technical Reports Server (NTRS)

Klein, V.

1983-01-01

Airplane identification, equation error method, maximum likelihood method, parameter estimation in frequency domain, extended Kalman filter, aircraft equations of motion, aerodynamic model equations, criteria for the selection of a parsimonious model, and online aircraft identification are addressed.

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.

Methods of identification employing antibody profiles

DOEpatents

Francoeur, Ann-Michele

1993-12-14

An identification method, applicable to the identification of animals or inanimate objects, is described. The method takes advantage of the set of individual-specific antibodies that are part of the unique antibody repertoire present in animals, by reacting an effective amount of such antibodies with a particular panel, of n-dimensional array (where n is typically one or two) consisting of an effective amount of many different antigens (typically greater than one thousand), to give antibody-antigen complexes. The profile or pattern formed by the antigen-antibody complexes, termed an antibody fingerprint, when revealed by an effective amount of an appropriate detector molecule, is uniquely representative of a particular individual. The method can similarly be used to distinguish genetically, or otherwise similar individuals, or their body parts containing individual-specific antibodies.

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

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.

Chemocoding as an identification tool where morphological- and DNA-based methods fall short: Inga as a case study.

PubMed

Endara, María-José; Coley, Phyllis D; Wiggins, Natasha L; Forrister, Dale L; Younkin, Gordon C; Nicholls, James A; Pennington, R Toby; Dexter, Kyle G; Kidner, Catherine A; Stone, Graham N; Kursar, Thomas A

2018-04-01

The need for species identification and taxonomic discovery has led to the development of innovative technologies for large-scale plant identification. DNA barcoding has been useful, but fails to distinguish among many species in species-rich plant genera, particularly in tropical regions. Here, we show that chemical fingerprinting, or 'chemocoding', has great potential for plant identification in challenging tropical biomes. Using untargeted metabolomics in combination with multivariate analysis, we constructed species-level fingerprints, which we define as chemocoding. We evaluated the utility of chemocoding with species that were defined morphologically and subject to next-generation DNA sequencing in the diverse and recently radiated neotropical genus Inga (Leguminosae), both at single study sites and across broad geographic scales. Our results show that chemocoding is a robust method for distinguishing morphologically similar species at a single site and for identifying widespread species across continental-scale ranges. Given that species are the fundamental unit of analysis for conservation and biodiversity research, the development of accurate identification methods is essential. We suggest that chemocoding will be a valuable additional source of data for a quick identification of plants, especially for groups where other methods fall short. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

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.

Species Identification of Bovine, Ovine and Porcine Type 1 Collagen; Comparing Peptide Mass Fingerprinting and LC-Based Proteomics Methods.

PubMed

Buckley, Mike

2016-03-24

Collagen is one of the most ubiquitous proteins in the animal kingdom and the dominant protein in extracellular tissues such as bone, skin and other connective tissues in which it acts primarily as a supporting scaffold. It has been widely investigated scientifically, not only as a biomedical material for regenerative medicine, but also for its role as a food source for both humans and livestock. Due to the long-term stability of collagen, as well as its abundance in bone, it has been proposed as a source of biomarkers for species identification not only for heat- and pressure-rendered animal feed but also in ancient archaeological and palaeontological specimens, typically carried out by peptide mass fingerprinting (PMF) as well as in-depth liquid chromatography (LC)-based tandem mass spectrometric methods. Through the analysis of the three most common domesticates species, cow, sheep, and pig, this research investigates the advantages of each approach over the other, investigating sites of sequence variation with known functional properties of the collagen molecule. Results indicate that the previously identified species biomarkers through PMF analysis are not among the most variable type 1 collagen peptides present in these tissues, the latter of which can be detected by LC-based methods. However, it is clear that the highly repetitive sequence motif of collagen throughout the molecule, combined with the variability of the sites and relative abundance levels of hydroxylation, can result in high scoring false positive peptide matches using these LC-based methods. Additionally, the greater alpha 2(I) chain sequence variation, in comparison to the alpha 1(I) chain, did not appear to be specific to any particular functional properties, implying that intra-chain functional constraints on sequence variation are not as great as inter-chain constraints. However, although some of the most variable peptides were only observed in LC-based methods, until the range of

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

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.

Reference-based source separation method for identification of brain regions involved in a reference state from intracerebral EEG

PubMed Central

Samadi, Samareh; Amini, Ladan; Cosandier-Rimélé, Delphine; Soltanian-Zadeh, Hamid; Jutten, Christian

2013-01-01

In this paper, we present a fast method to extract the sources related to interictal epileptiform state. The method is based on general eigenvalue decomposition using two correlation matrices during: 1) periods including interictal epileptiform discharges (IED) as a reference activation model and 2) periods excluding IEDs or abnormal physiological signals as background activity. After extracting the most similar sources to the reference or IED state, IED regions are estimated by using multiobjective optimization. The method is evaluated using both realistic simulated data and actual intracerebral electroencephalography recordings of patients suffering from focal epilepsy. These patients are seizure-free after the resective surgery. Quantitative comparisons of the proposed IED regions with the visually inspected ictal onset zones by the epileptologist and another method of identification of IED regions reveal good performance. PMID:23428609

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

Experimental Methods for Protein Interaction Identification and Characterization

NASA Astrophysics Data System (ADS)

Uetz, Peter; Titz, Björn; Cagney, Gerard

There are dozens of methods for the detection of protein-protein interactions but they fall into a few broad categories. Fragment complementation assays such as the yeast two-hybrid (Y2H) system are based on split proteins that are functionally reconstituted by fusions of interacting proteins. Biophysical methods include structure determination and mass spectrometric (MS) identification of proteins in complexes. Biochemical methods include methods such as far western blotting and peptide arrays. Only the Y2H and protein complex purification combined with MS have been used on a larger scale. Due to the lack of data it is still difficult to compare these methods with respect to their efficiency and error rates. Current data does not favor any particular method and thus multiple experimental approaches are necessary to maximally cover the interactome of any target cell or organism.

Modified filter-aided sample preparation (FASP) method increases peptide and protein identifications for shotgun proteomics.

PubMed

Ni, Mao-Wei; Wang, Lu; Chen, Wei; Mou, Han-Zhou; Zhou, Jie; Zheng, Zhi-Guo

2017-01-30

Mass spectrometry (MS)-based protein identification depends mainly on protein extraction and digestion. Although sodium dodecyl sulfate (SDS) can preclude enzymatic digestion and interfere with MS analysis, it is still the most widely used surfactant in these steps. To overcome these disadvantages, a SDS-compatible proteomic technique for SDS removal prior to MS-based analyses was developed, namely filter-aided sample preparation (FASP). Herein, based on the effectiveness of sodium deoxycholate and a detergent removal spin column, we developed a modified FASP (mFASP) method and compared its overall performance, total number of peptides and proteins identified for shotgun proteomic experiments with that of the FASP method. Identification of 4570 ± 392 and 9139 ± 317 peptides and description of 862 ± 46 and 1377 ± 33 protein groups with two or more peptides from the ovarian cancer cell line A2780 was accomplished by FASP and mFASP methods, respectively. The mFASP method (21.2 ± 0.2%) had higher average peptide to protein coverage than FASP method (13.2 ± 0.5%). More hydrophobic peptides were identified by mFASP than by FASP, as indicated by the GRAVY score distribution. The reported method enables reliable and efficient identification of proteins and peptides in whole-cell extracts containing SDS. The new approach allows for higher throughput (the simultaneous identification of more proteins), a more comprehensive investigation of proteins, and potentially the discovery of new biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

[Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW)].

PubMed

Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui

2013-10-01

To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Method for star identification using neural networks

NASA Astrophysics Data System (ADS)

Lindsey, Clark S.; Lindblad, Thomas; Eide, Age J.

1997-04-01

Identification of star constellations with an onboard star tracker provides the highest precision of all attitude determination techniques for spacecraft. A method for identification of star constellations inspired by neural network (NNW) techniques is presented. It compares feature vectors derived from histograms of distances to multiple stars around the unknown star. The NNW method appears most robust with respect to position noise and would require a smaller database than conventional methods, especially for small fields of view. The neural network method is quite slow when performed on a sequential (serial) processor, but would provide very high speed if implemented in special hardware. Such hardware solutions could also yield lower low weight and low power consumption, both important features for small satellites.

Rapid identification and quantification of tumor cells using an electrocatalytic method based on gold nanoparticles.

PubMed

de la Escosura-Muñiz, Alfredo; Sánchez-Espinel, Christian; Díaz-Freitas, Belén; González-Fernández, Africa; Maltez-da Costa, Marisa; Merkoçi, Arben

2009-12-15

There is a high demand for simple, rapid, efficient, and user-friendly alternative methods for the detection of cells in general and, in particular, for the detection of cancer cells. A biosensor able to detect cells would be an all-in-one dream device for such applications. The successful integration of nanoparticles into cell detection assays could allow for the development of this novel class of cell sensors. Indeed, their application could well have a great future in diagnostics, as well as other fields. As an example of a novel biosensor, we report here an electrocatalytic device for the specific identification of tumor cells that quantifies gold nanoparticles (AuNPs) coupled with an electrotransducing platform/sensor. Proliferation and adherence of tumor cells are achieved on the electrotransducer/detector, which consists of a mass-produced screen-printed carbon electrode (SPCE). In situ identification/quantification of tumor cells is achieved with a detection limit of 4000 cells per 700 microL of suspension. This novel and selective cell-sensing device is based on the reaction of cell surface proteins with specific antibodies conjugated with AuNPs. Final detection requires only a couple of minutes, taking advantage of the catalytic properties of AuNPs on hydrogen evolution. The proposed detection method does not require the chemical agents used in most existing assays for the detection of AuNPs. It allows for the miniaturization of the system and is much cheaper than other expensive and sophisticated methods used for tumor cell detection. We envisage that this device could operate in a simple way as an immunosensor or DNA sensor. Moreover, it could be used, even by inexperienced staff, for the detection of protein molecules or DNA strands.

Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

PubMed

Nam, Seungyoon

2017-04-01

Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

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

NASA Astrophysics Data System (ADS)

Liao, Yabin; Wells, Valana

2011-10-01

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

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...

A simplified fractional order impedance model and parameter identification method for lithium-ion batteries

PubMed Central

Yang, Qingxia; Xu, Jun; Cao, Binggang; Li, Xiuqing

2017-01-01

Identification of internal parameters of lithium-ion batteries is a useful tool to evaluate battery performance, and requires an effective model and algorithm. Based on the least square genetic algorithm, a simplified fractional order impedance model for lithium-ion batteries and the corresponding parameter identification method were developed. The simplified model was derived from the analysis of the electrochemical impedance spectroscopy data and the transient response of lithium-ion batteries with different states of charge. In order to identify the parameters of the model, an equivalent tracking system was established, and the method of least square genetic algorithm was applied using the time-domain test data. Experiments and computer simulations were carried out to verify the effectiveness and accuracy of the proposed model and parameter identification method. Compared with a second-order resistance-capacitance (2-RC) model and recursive least squares method, small tracing voltage fluctuations were observed. The maximum battery voltage tracing error for the proposed model and parameter identification method is within 0.5%; this demonstrates the good performance of the model and the efficiency of the least square genetic algorithm to estimate the internal parameters of lithium-ion batteries. PMID:28212405

Chemoenzymatic method for glycomics: isolation, identification, and quantitation

PubMed Central

Yang, Shuang; Rubin, Abigail; Eshghi, Shadi Toghi; Zhang, Hui

2015-01-01

Over the past decade, considerable progress has been made with respect to the analytical methods for analysis of glycans from biological sources. Regardless of the specific methods that are used, glycan analysis includes isolation, identification, and quantitation. Derivatization is indispensable to increase their identification. Derivatization of glycans can be performed by permethylation or carbodiimide coupling / esterification. By introducing a fluorophore or chromophore at their reducing end, glycans can be separated by electrophoresis or chromatography. The fluorogenically labeled glycans can be quantitated using fluorescent detection. The recently developed approaches using solid-phase such as glycoprotein immobilization for glycan extraction and on-tissue glycan mass spectrometry imaging demonstrate advantages over methods performed in solution. Derivatization of sialic acids is favorably implemented on the solid support using carbodiimide coupling, and the released glycans can be further modified at the reducing end or permethylated for quantitative analysis. In this review, methods for glycan isolation, identification, and quantitation are discussed. PMID:26390280

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

System Identification Methods for Aircraft Flight Control Development and Validation

DOT National Transportation Integrated Search

1995-10-01

System-identification methods compose a mathematical model, or series of models, : from measurements of inputs and outputs of dynamic systems. This paper : discusses the use of frequency-domain system-identification methods for the : development and ...

Moving Force Identification: a Time Domain Method

NASA Astrophysics Data System (ADS)

Law, S. S.; Chan, T. H. T.; Zeng, Q. H.

1997-03-01

The solution for the vertical dynamic interaction forces between a moving vehicle and the bridge deck is analytically derived and experimentally verified. The deck is modelled as a simply supported beam with viscous damping, and the vehicle/bridge interaction force is modelled as one-point or two-point loads with fixed axle spacing, moving at constant speed. The method is based on modal superposition and is developed to identify the forces in the time domain. Both cases of one-point and two-point forces moving on a simply supported beam are simulated. Results of laboratory tests on the identification of the vehicle/bridge interaction forces are presented. Computation simulations and laboratory tests show that the method is effective, and acceptable results can be obtained by combining the use of bending moment and acceleration measurements.

Identification and compensation of the temperature influences in a miniature three-axial accelerometer based on the least squares method

NASA Astrophysics Data System (ADS)

Grigorie, Teodor Lucian; Corcau, Ileana Jenica; Tudosie, Alexandru Nicolae

2017-06-01

The paper presents a way to obtain an intelligent miniaturized three-axial accelerometric sensor, based on the on-line estimation and compensation of the sensor errors generated by the environmental temperature variation. Taking into account that this error's value is a strongly nonlinear complex function of the values of environmental temperature and of the acceleration exciting the sensor, its correction may not be done off-line and it requires the presence of an additional temperature sensor. The proposed identification methodology for the error model is based on the least square method which process off-line the numerical values obtained from the accelerometer experimental testing for different values of acceleration applied to its axes of sensitivity and for different values of operating temperature. A final analysis of the error level after the compensation highlights the best variant for the matrix in the error model. In the sections of the paper are shown the results of the experimental testing of the accelerometer on all the three sensitivity axes, the identification of the error models on each axis by using the least square method, and the validation of the obtained models with experimental values. For all of the three detection channels was obtained a reduction by almost two orders of magnitude of the acceleration absolute maximum error due to environmental temperature variation.

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.

Human Fecal Source Identification: Real-Time Quantitative PCR Method Standardization

EPA Science Inventory

Method standardization or the formal development of a protocol that establishes uniform performance benchmarks and practices is necessary for widespread adoption of a fecal source identification approach. Standardization of a human-associated fecal identification method has been...

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

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

Impact of identity theft on methods of identification.

PubMed

McLemore, Jerri; Hodges, Walker; Wyman, Amy

2011-06-01

Responsibility for confirming a decedent's identity commonly falls on the shoulders of the coroner or medical examiner. Misidentification of bodies results in emotional turmoil for the next-of-kin and can negatively impact the coroner's or medical examiner's career. To avoid such mishaps, the use of scientific methods to establish a positive identification is advocated. The use of scientific methods of identification may not be reliable in cases where the decedent had assumed the identity of another person. Case studies of erroneously identified bodies due to identity theft from the state medical examiner offices in Iowa and New Mexico are presented. This article discusses the scope and major concepts of identity theft and how identity theft prevents the guarantee of a positive identification.

Consistency of the Performance and Nonperformance Methods in Gifted Identification

ERIC Educational Resources Information Center

Acar, Selcuk; Sen, Sedat; Cayirdag, Nur

2016-01-01

Current approaches to gifted identification suggest collecting multiple sources of evidence. Some gifted identification guidelines allow for the interchangeable use of "performance" and "nonperformance" identification methods. This multiple criteria approach lacks a strong overlap between the assessment tools; however,…

Lenticular card: a new method for denture identification.

PubMed

Colvenkar, Shreya S

2010-01-01

The need for denture marking is important for forensic and social reasons in case patients need to be identified individually. Majority of the surface marking and inclusion techniques are expensive, time consuming, and do not permit the incorporation of large amounts of information. In this article, the method to include a lenticular identification card stood out from the currently available denture marking methods in various ways. The lenticular card stores the patient's information has two or more images that can be viewed by changing the angle of view. The maxillary denture was processed according to the manufacturer's instructions. The lenticular identification card was incorporated in the external posterior buccal surface of the maxillary denture using salt and pepper technique. For testing of durability, denture with the identifier was placed in water for up to 4 months. The proposed method is simple, cheap, and can store a large amount of information, thus allowing quick identification of the denture wearer. The labels showed no sign of fading or deterioration.

[Bacterial identification methods in the microbiology laboratory].

PubMed

Bou, Germán; Fernández-Olmos, Ana; García, Celia; Sáez-Nieto, Juan Antonio; Valdezate, Sylvia

2011-10-01

In order to identify the agent responsible of the infectious process and understanding the pathogenic/pathological implications, clinical course, and to implement an effective antimicrobial therapy, a mainstay in the practice of clinical microbiology is the allocation of species to a microbial isolation. In daily routine practice microbiology laboratory phenotypic techniques are applied to achieve this goal. However, they have some limitations that are seen more clearly for some kinds of microorganism. Molecular methods can circumvent some of these limitations, although its implementation is not universal. This is due to higher costs and the level of expertise required for thei implementation, so molecular methods are often centralized in reference laboratories and centers. Recently, proteomics-based methods made an important breakthrough in the field of diagnostic microbiology and will undoubtedly have a major impact on the future organization of the microbiology services. This paper is a short review of the most noteworthy aspects of the three bacterial identification methods described above used in microbiology laboratories. Copyright © 2011 Elsevier España, S.L. All rights reserved.

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

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

DOEpatents

Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

2013-01-08

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

Single classifier, OvO, OvA and RCC multiclass classification method in handheld based smartphone gait identification

NASA Astrophysics Data System (ADS)

Raziff, Abdul Rafiez Abdul; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

2017-10-01

Gait recognition is widely used in many applications. In the application of the gait identification especially in people, the number of classes (people) is many which may comprise to more than 20. Due to the large amount of classes, the usage of single classification mapping (direct classification) may not be suitable as most of the existing algorithms are mostly designed for the binary classification. Furthermore, having many classes in a dataset may result in the possibility of having a high degree of overlapped class boundary. This paper discusses the application of multiclass classifier mappings such as one-vs-all (OvA), one-vs-one (OvO) and random correction code (RCC) on handheld based smartphone gait signal for person identification. The results is then compared with a single J48 decision tree for benchmark. From the result, it can be said that using multiclass classification mapping method thus partially improved the overall accuracy especially on OvO and RCC with width factor more than 4. For OvA, the accuracy result is worse than a single J48 due to a high number of classes.

Perception-based road hazard identification with Internet support.

PubMed

Tarko, Andrew P; DeSalle, Brian R

2003-01-01

One of the most important tasks faced by highway agencies is identifying road hazards. Agencies use crash statistics to detect road intersections and segments where the frequency of crashes is excessive. With the crash-based method, a dangerous intersection or segment can be pointed out only after a sufficient number of crashes occur. A more proactive method is needed, and motorist complaints may be able to assist agencies in detecting road hazards before crashes occur. This paper investigates the quality of safety information reported by motorists and the effectiveness of hazard identification based on motorist reports, which were collected with an experimental Internet website. It demonstrates that the intersections pointed out by motorists tended to have more crashes than other intersections. The safety information collected through the website was comparable to 2-3 months of crash data. It was concluded that although the Internet-based method could not substitute for the traditional crash-based methods, its joint use with crash statistics might be useful in detecting new hazards where crash data had been collected for a short time.

Mathematical correlation of modal-parameter-identification methods via system-realization theory

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1987-01-01

A unified approach is introduced using system-realization theory to derive and correlate modal-parameter-identification methods for flexible structures. Several different time-domain methods are analyzed and treated. A basic mathematical foundation is presented which provides insight into the field of modal-parameter identification for comparison and evaluation. The relation among various existing methods is established and discussed. This report serves as a starting point to stimulate additional research toward the unification of the many possible approaches for modal-parameter identification.

Comparison of identification methods for oral asaccharolytic Eubacterium species.

PubMed

Wade, W G; Slayne, M A; Aldred, M J

1990-12-01

Thirty one strains of oral, asaccharolytic Eubacterium spp. and the type strains of E. brachy, E. nodatum and E. timidum were subjected to three identification techniques--protein-profile analysis, determination of metabolic end-products, and the API ATB32A identification kit. Five clusters were obtained from numerical analysis of protein profiles and excellent correlations were seen with the other two methods. Protein profiles alone allowed unequivocal identification.

Analysis of blind identification methods for estimation of kinetic parameters in dynamic medical imaging

NASA Astrophysics Data System (ADS)

Riabkov, Dmitri

Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well-modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. In this work it is shown that the blind identification problem has a unique solution for two-compartment model tissue response. For two-compartment model tissue responses in dynamic cardiac MRI imaging conditions with gadolinium-DTPA contrast agent, three blind identification algorithms are analyzed here to assess their utility: Eigenvector-based Algorithm for Multichannel Blind Deconvolution (EVAM), Cross Relations (CR), and Iterative Quadratic Maximum Likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that the IQML method gives more accurate estimates than the other two blind identification methods. A proof is presented here that three-compartment model blind identification is not unique in the case of only two regions. It is shown that it is likely unique for the case of more than two regions, but this has not been proved analytically. For the three-compartment model the tissue responses in dynamic FDG PET imaging conditions are analyzed with the blind identification algorithms EVAM and Separable variables Least Squares (SLS). A method of

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 statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics

PubMed Central

Stanley, Jeffrey R.; Adkins, Joshua N.; Slysz, Gordon W.; Monroe, Matthew E.; Purvine, Samuel O.; Karpievitch, Yuliya V.; Anderson, Gordon A.; Smith, Richard D.; Dabney, Alan R.

2011-01-01

Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, as this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referred to as Statistical Tools for AMT tag Confidence (STAC). STAC additionally provides a Uniqueness Probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download as both a command line and a Windows graphical application. PMID:21692516

Mathematical correlation of modal parameter identification methods via system realization theory

NASA Technical Reports Server (NTRS)

Juang, J. N.

1986-01-01

A unified approach is introduced using system realization theory to derive and correlate modal parameter identification methods for flexible structures. Several different time-domain and frequency-domain methods are analyzed and treated. A basic mathematical foundation is presented which provides insight into the field of modal parameter identification for comparison and evaluation. The relation among various existing methods is established and discussed. This report serves as a starting point to stimulate additional research towards the unification of the many possible approaches for modal parameter identification.

Patterns of Cognitive Strengths and Weaknesses: Identification Rates, Agreement, and Validity for Learning Disabilities Identification

PubMed Central

Miciak, Jeremy; Fletcher, Jack M.; Stuebing, Karla; Vaughn, Sharon; Tolar, Tammy D.

2014-01-01

Purpose Few empirical investigations have evaluated LD identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability and validity of two proposed PSW methods: the concordance/discordance method (C/DM) and cross battery assessment (XBA) method. Methods Cognitive assessment data for 139 adolescents demonstrating inadequate response to intervention was utilized to empirically classify participants as meeting or not meeting PSW LD identification criteria using the two approaches, permitting an analysis of: (1) LD identification rates; (2) agreement between methods; and (3) external validity. Results LD identification rates varied between the two methods depending upon the cut point for low achievement, with low agreement for LD identification decisions. Comparisons of groups that met and did not meet LD identification criteria on external academic variables were largely null, raising questions of external validity. Conclusions This study found low agreement and little evidence of validity for LD identification decisions based on PSW methods. An alternative may be to use multiple measures of academic achievement to guide intervention. PMID:24274155

HUMAN FECAL SOURCE IDENTIFICATION: REAL-TIME QUANTITATIVE PCR METHOD STANDARDIZATION - abstract

EPA Science Inventory

Method standardization or the formal development of a protocol that establishes uniform performance benchmarks and practices is necessary for widespread adoption of a fecal source identification approach. Standardization of a human-associated fecal identification method has been...

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.

Interfacial damage identification of steel and concrete composite beams based on piezoceramic wave method.

PubMed

Yan, Shi; Dai, Yong; Zhao, Putian; Liu, Weiling

2018-01-01

Steel-concrete composite structures are playing an increasingly important role in economic construction because of a series of advantages of great stiffness, good seismic performance, steel material saving, cost efficiency, convenient construction, etc. However, in service process, due to the long-term effects of environmental impacts and dynamic loading, interfaces of a composite structure might generate debonding cracks, relative slips or separations, and so on, lowering the composite effect of the composite structure. In this paper, the piezoceramics (PZT) are used as transducers to perform experiments on interface debonding slips and separations of composite beams, respectively, aimed at proposing an interface damage identification model and a relevant damage detection innovation method based on PZT wave technology. One part of various PZT patches was embedded in concrete as "smart aggregates," and another part of the PZT patches was pasted on the surface of the steel beam flange, forming a sensor array. A push-out test for four specimens was carried out and experimental results showed that, under the action of the external loading, the received signal amplitudes will increasingly decrease with increase of debonding slips along the interface. The proposed signal energy-based interface damage detection algorithm is highly efficient in surface state evaluations of composite beams.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

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.

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.

VIP Barcoding: composition vector-based software for rapid species identification based on DNA barcoding.

PubMed

Fan, Long; Hui, Jerome H L; Yu, Zu Guo; Chu, Ka Hou

2014-07-01

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/. © 2014 John Wiley & Sons Ltd.

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...

Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method

PubMed Central

Chen, Can; Li, Tienan; Sun, Jian; Chen, Feng

2016-01-01

Hotspot identification (HSID) is the first and key step of the expressway safety management process. This study presents a new HSID method using the quantitative risk assessment (QRA) technique. Crashes that are likely to happen for a specific site are treated as the risk. The aggregation of the crash occurrence probability for all exposure vehicles is estimated based on the empirical Bayesian method. As for the consequences of crashes, crashes may not only cause direct losses (e.g., occupant injuries and property damages) but also result in indirect losses. The indirect losses are expressed by the extra delays calculated using the deterministic queuing diagram method. The direct losses and indirect losses are uniformly monetized to be considered as the consequences of this risk. The potential costs of crashes, as a criterion to rank high-risk sites, can be explicitly expressed as the sum of the crash probability for all passing vehicles and the corresponding consequences of crashes. A case study on the urban expressways of Shanghai is presented. The results show that the new QRA method for HSID enables the identification of a set of high-risk sites that truly reveal the potential crash costs to society. PMID:28036009

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.

Automated retina identification based on multiscale elastic registration.

PubMed

Figueiredo, Isabel N; Moura, Susana; Neves, Júlio S; Pinto, Luís; Kumar, Sunil; Oliveira, Carlos M; Ramos, João D

2016-12-01

In this work we propose a novel method for identifying individuals based on retinal fundus image matching. The method is based on the image registration of retina blood vessels, since it is known that the retina vasculature of an individual is a signature, i.e., a distinctive pattern of the individual. The proposed image registration consists of a multiscale affine registration followed by a multiscale elastic registration. The major advantage of this particular two-step image registration procedure is that it is able to account for both rigid and non-rigid deformations either inherent to the retina tissues or as a result of the imaging process itself. Afterwards a decision identification measure, relying on a suitable normalized function, is defined to decide whether or not the pair of images belongs to the same individual. The method is tested on a data set of 21721 real pairs generated from a total of 946 retinal fundus images of 339 different individuals, consisting of patients followed in the context of different retinal diseases and also healthy patients. The evaluation of its performance reveals that it achieves a very low false rejection rate (FRR) at zero FAR (the false acceptance rate), equal to 0.084, as well as a low equal error rate (EER), equal to 0.053. Moreover, the tests performed by using only the multiscale affine registration, and discarding the multiscale elastic registration, clearly show the advantage of the proposed approach. The outcome of this study also indicates that the proposed method is reliable and competitive with other existing retinal identification methods, and forecasts its future appropriateness and applicability in real-life applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Object-based methods for individual tree identification and tree species classification from high-spatial resolution imagery

NASA Astrophysics Data System (ADS)

Wang, Le

2003-10-01

Modern forest management poses an increasing need for detailed knowledge of forest information at different spatial scales. At the forest level, the information for tree species assemblage is desired whereas at or below the stand level, individual tree related information is preferred. Remote Sensing provides an effective tool to extract the above information at multiple spatial scales in the continuous time domain. To date, the increasing volume and readily availability of high-spatial-resolution data have lead to a much wider application of remotely sensed products. Nevertheless, to make effective use of the improving spatial resolution, conventional pixel-based classification methods are far from satisfactory. Correspondingly, developing object-based methods becomes a central challenge for researchers in the field of Remote Sensing. This thesis focuses on the development of methods for accurate individual tree identification and tree species classification. We develop a method in which individual tree crown boundaries and treetop locations are derived under a unified framework. We apply a two-stage approach with edge detection followed by marker-controlled watershed segmentation. Treetops are modeled from radiometry and geometry aspects. Specifically, treetops are assumed to be represented by local radiation maxima and to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate overlapping trees and to produce a segmented image comprised of individual tree crowns. The image segmentation method developed achieves a promising result for a 256 x 256 CASI image. Then further effort is made to extend our methods to the multiscales which are constructed from a wavelet decomposition. A scale consistency and geometric consistency are designed to examine the gradients along the scale-space for the purpose of separating true crown boundary from unwanted

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.

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.

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.

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…

A new precipitation-based method of baseflow separation and event identification for small watersheds (<50 km2)

NASA Astrophysics Data System (ADS)

Koskelo, Antti I.; Fisher, Thomas R.; Utz, Ryan M.; Jordan, Thomas E.

2012-07-01

SummaryBaseflow separation methods are often impractical, require expensive materials and time-consuming methods, and/or are not designed for individual events in small watersheds. To provide a simple baseflow separation method for small watersheds, we describe a new precipitation-based technique known as the Sliding Average with Rain Record (SARR). The SARR uses rainfall data to justify each separation of the hydrograph. SARR has several advantages such as: it shows better consistency with the precipitation and discharge records, it is easier and more practical to implement, and it includes a method of event identification based on precipitation and quickflow response. SARR was derived from the United Kingdom Institute of Hydrology (UKIH) method with several key modifications to adapt it for small watersheds (<50 km2). We tested SARR on watersheds in the Choptank Basin on the Delmarva Peninsula (US Mid-Atlantic region) and compared the results with the UKIH method at the annual scale and the hydrochemical method at the individual event scale. Annually, SARR calculated a baseflow index that was ˜10% higher than the UKIH method due to the finer time step of SARR (1 d) compared to UKIH (5 d). At the watershed scale, hydric soils were an important driver of the annual baseflow index likely due to increased groundwater retention in hydric areas. At the event scale, SARR calculated less baseflow than the hydrochemical method, again because of the differences in time step (hourly for hydrochemical) and different definitions of baseflow. Both SARR and hydrochemical baseflow increased with event size, suggesting that baseflow contributions are more important during larger storms. To make SARR easy to implement, we have written a MatLab program to automate the calculations which requires only daily rainfall and daily flow data as inputs.

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.

A photometric mode identification method, including an improved non-adiabatic treatment of the atmosphere

NASA Astrophysics Data System (ADS)

Dupret, M.-A.; De Ridder, J.; De Cat, P.; Aerts, C.; Scuflaire, R.; Noels, A.; Thoul, A.

2003-02-01

We present an improved version of the method of photometric mode identification of Heynderickx et al. (\\cite{hey}). Our new version is based on the inclusion of precise non-adiabatic eigenfunctions determined in the outer stellar atmosphere according to the formalism recently proposed by Dupret et al. (\\cite{dup}). Our improved photometric mode identification technique is therefore no longer dependent on ad hoc parameters for the non-adiabatic effects. It contains the complete physical conditions of the outer atmosphere of the star, provided that rotation does not play a key role. We apply our method to the two slowly pulsating B stars HD 74560 and HD 138764 and to the beta Cephei star EN (16) Lac. Besides identifying the degree l of the pulsating stars, our method is also a tool for improving the knowledge of stellar interiors and atmospheres, by imposing constraints on parameters such as the metallicity and the mixing-length parameter alpha (a procedure we label non-adiabatic asteroseismology). The non-adiabatic eigenfunctions needed for the mode identification are available upon request from the authors.

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.

Moment Method and Pixel-by-Pixel Method: Complementary Mode Identification I. Testing FG Vir-like pulsation modes

NASA Astrophysics Data System (ADS)

Zima, W.; Kolenberg, K.; Briquet, M.; Breger, M.

2004-06-01

We have carried out a Hare-and-Hound test to determine the reliability of the Moment Method (Briquet & Aerts 2003) and the Pixel-by-Pixel Method (Mantegazza 2000) for the identification of pulsation modes in Delta Scuti stars. For this purpose we calculated synthetic line profiles, exhibiting six pulsation modes of low degree and with input parameters initially unknown to us. The aim was to test and increase the quality of the mode identification by applying both methods independently and by using a combined technique. Our results show that, whereas the azimuthal order m and its sign can be fixed by both methods, the degree l is not determined unambiguously. Both identification methods show a better reliability if multiple modes are fitted simultaneously. In particular, the inclination angle is better determined. We have to emphasize that the outcome of this test is only meaningful for stars having pulsational velocities below 0.2 vsini. This is the first part of a series of articles, in which we will test these spectroscopic identification methods.

A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-06-01

Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

IDENTIFICATION OF TOXICANTS IN WHOLE MARINE SEDIMENTS: METHODS AND RESULTS

EPA Science Inventory

Identification of stressors in aquatic systems is critical to sound assessment and management of our nation's waterways. Information from stressor identification can be useful in designing effective sediment remediation methods, assessing options for sediment disposal, allowing m...

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.

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.

The identification and repair of anomalous measurements in the measurement of big diameter based on rolling-wheel method

NASA Astrophysics Data System (ADS)

Chen, Haiou; Yu, Xiaofen

2011-05-01

Rolling-wheel method is an effective way of measuring big diameter. After amending the temperature error and pressure error, the uncertainty of measurement can not be φ =5um/m stably because of the influence of skid. The traditional method of identifying skid loses sight of the influences of the unstable motor speed, the appearance form error and the eccentric of installation of the big axis and rolling wheel and so on, so the method has its limitation. In this paper, a new method of multiple identification and repair is introduced, namely n diameters are measured and Chauvenet standard is used for identifying the anomalous measurements one by one, and then the average value of the remaining data is used for repairing identified anomalous measurements, and the next round identification and repair is carried out until the accuracy requirement of the measurement is satisfied. The result of experiments indicates that the method can identify anomalous measurements whose offsets caused by the skid are greater than 0.2φ , and the uncertainty of measurement has improved substantially.

Comparative evaluation of matrix-assisted laser desorption ionisation-time of flight mass spectrometry and conventional phenotypic-based methods for identification of clinically important yeasts in a UK-based medical microbiology laboratory.

PubMed

Fatania, Nita; Fraser, Mark; Savage, Mike; Hart, Jason; Abdolrasouli, Alireza

2015-12-01

Performance of matrix-assisted laser desorption ionisation-time of flight mass spectrometry (MALDI-TOF MS) was compared in a side-by side-analysis with conventional phenotypic methods currently in use in our laboratory for identification of yeasts in a routine diagnostic setting. A diverse collection of 200 clinically important yeasts (19 species, five genera) were identified by both methods using standard protocols. Discordant or unreliable identifications were resolved by sequencing of the internal transcribed spacer region of the rRNA gene. MALDI-TOF and conventional methods were in agreement for 182 isolates (91%) with correct identification to species level. Eighteen discordant results (9%) were due to rarely encountered species, hence the difficulty in their identification using traditional phenotypic methods. MALDI-TOF MS enabled rapid, reliable and accurate identification of clinically important yeasts in a routine diagnostic microbiology laboratory. Isolates with rare, unusual or low probability identifications should be confirmed using robust molecular methods. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Rapid screening of guar gum using portable Raman spectral identification methods.

PubMed

Srivastava, Hirsch K; Wolfgang, Steven; Rodriguez, Jason D

2016-01-25

Guar gum is a well-known inactive ingredient (excipient) used in a variety of oral pharmaceutical dosage forms as a thickener and stabilizer of suspensions and as a binder of powders. It is also widely used as a food ingredient in which case alternatives with similar properties, including chemically similar gums, are readily available. Recent supply shortages and price fluctuations have caused guar gum to come under increasing scrutiny for possible adulteration by substitution of cheaper alternatives. One way that the U.S. FDA is attempting to screen pharmaceutical ingredients at risk for adulteration or substitution is through field-deployable spectroscopic screening. Here we report a comprehensive approach to evaluate two field-deployable Raman methods--spectral correlation and principal component analysis--to differentiate guar gum from other gums. We report a comparison of the sensitivity of the spectroscopic screening methods with current compendial identification tests. The ability of the spectroscopic methods to perform unambiguous identification of guar gum compared to other gums makes them an enhanced surveillance alternative to the current compendial identification tests, which are largely subjective in nature. Our findings indicate that Raman spectral identification methods perform better than compendial identification methods and are able to distinguish guar gum from other gums with 100% accuracy for samples tested by spectral correlation and principal component analysis. Published by Elsevier B.V.

System Identification and POD Method Applied to Unsteady Aerodynamics

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Biometric identification based on feature fusion with PCA and SVM

NASA Astrophysics Data System (ADS)

Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

2018-04-01

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

Location identification of closed crack based on Duffing oscillator transient transition

NASA Astrophysics Data System (ADS)

Liu, Xiaofeng; Bo, Lin; Liu, Yaolu; Zhao, Youxuan; Zhang, Jun; Deng, Mingxi; Hu, Ning

2018-02-01

The existence of a closed micro-crack in plates can be detected by using the nonlinear harmonic characteristics of the Lamb wave. However, its location identification is difficult. By considering the transient nonlinear Lamb under the noise interference, we proposed a location identification method for the closed crack based on the quantitative measurement of Duffing oscillator transient transfer in the phase space. The sliding short-time window was used to create a window truncation of to-be-detected signal. And then, the periodic extension processing for transient nonlinear Lamb wave was performed to ensure that the Duffing oscillator has adequate response time to reach a steady state. The transient autocorrelation method was used to reduce the occurrence of missed harmonic detection due to the random variable phase of nonlinear Lamb wave. Moreover, to overcome the deficiency in the quantitative analysis of Duffing system state by phase trajectory diagram and eliminate the misjudgment caused by harmonic frequency component contained in broadband noise, logic operation method of oscillator state transition function based on circular zone partition was adopted to establish the mapping relation between the oscillator transition state and the nonlinear harmonic time domain information. Final state transition discriminant function of Duffing oscillator was used as basis for identifying the reflected and transmitted harmonics from the crack. Chirplet time-frequency analysis was conducted to identify the mode of generated harmonics and determine the propagation speed. Through these steps, accurate position identification of the closed crack was achieved.

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.

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

PubMed

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

2009-05-01

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

Luminescent Method for Porcelain Identification

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

A data recipient centered de-identification method to retain statistical attributes.

PubMed

Gal, Tamas S; Tucker, Thomas C; Gangopadhyay, Aryya; Chen, Zhiyuan

2014-08-01

Privacy has always been a great concern of patients and medical service providers. As a result of the recent advances in information technology and the government's push for the use of Electronic Health Record (EHR) systems, a large amount of medical data is collected and stored electronically. This data needs to be made available for analysis but at the same time patient privacy has to be protected through de-identification. Although biomedical researchers often describe their research plans when they request anonymized data, most existing anonymization methods do not use this information when de-identifying the data. As a result, the anonymized data may not be useful for the planned research project. This paper proposes a data recipient centered approach to tailor the de-identification method based on input from the recipient of the data. We demonstrate our approach through an anonymization project for biomedical researchers with specific goals to improve the utility of the anonymized data for statistical models used for their research project. The selected algorithm improves a privacy protection method called Condensation by Aggarwal et al. Our methods were tested and validated on real cancer surveillance data provided by the Kentucky Cancer Registry. Copyright © 2014 Elsevier Inc. All rights reserved.

Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation

NASA Astrophysics Data System (ADS)

Pentaris, Fragkiskos P.; Fouskitakis, George N.

2014-05-01

The problem of modal identification in civil structures is of crucial importance, and thus has been receiving increasing attention in recent years. Vibration-based methods are quite promising as they are capable of identifying the structure's global characteristics, they are relatively easy to implement and they tend to be time effective and less expensive than most alternatives [1]. This paper focuses on the off-line structural/modal identification of civil (concrete) structures subjected to low-level earthquake excitations, under which, they remain within their linear operating regime. Earthquakes and their details are recorded and provided by the seismological network of Crete [2], which 'monitors' the broad region of south Hellenic arc, an active seismic region which functions as a natural laboratory for earthquake engineering of this kind. A sufficient number of seismic events are analyzed in order to reveal the modal characteristics of the structures under study, that consist of the two concrete buildings of the School of Applied Sciences, Technological Education Institute of Crete, located in Chania, Crete, Hellas. Both buildings are equipped with high-sensitivity and accuracy seismographs - providing acceleration measurements - established at the basement (structure's foundation) presently considered as the ground's acceleration (excitation) and at all levels (ground floor, 1st floor, 2nd floor and terrace). Further details regarding the instrumentation setup and data acquisition may be found in [3]. The present study invokes stochastic, both non-parametric (frequency-based) and parametric methods for structural/modal identification (natural frequencies and/or damping ratios). Non-parametric methods include Welch-based spectrum and Frequency response Function (FrF) estimation, while parametric methods, include AutoRegressive (AR), AutoRegressive with eXogeneous input (ARX) and Autoregressive Moving-Average with eXogeneous input (ARMAX) models[4, 5

[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

Propensity Score-Based Methods versus MTE-Based Methods in Causal Inference: Identification, Estimation, and Application

ERIC Educational Resources Information Center

Zhou, Xiang; Xie, Yu

2016-01-01

Since the seminal introduction of the propensity score (PS) by Rosenbaum and Rubin, PS-based methods have been widely used for drawing causal inferences in the behavioral and social sciences. However, the PS approach depends on the ignorability assumption: there are no unobserved confounders once observed covariates are taken into account. For…

Parameter identification for structural dynamics based on interval analysis algorithm

NASA Astrophysics Data System (ADS)

Yang, Chen; Lu, Zixing; Yang, Zhenyu; Liang, Ke

2018-04-01

A parameter identification method using interval analysis algorithm for structural dynamics is presented in this paper. The proposed uncertain identification method is investigated by using central difference method and ARMA system. With the help of the fixed memory least square method and matrix inverse lemma, a set-membership identification technology is applied to obtain the best estimation of the identified parameters in a tight and accurate region. To overcome the lack of insufficient statistical description of the uncertain parameters, this paper treats uncertainties as non-probabilistic intervals. As long as we know the bounds of uncertainties, this algorithm can obtain not only the center estimations of parameters, but also the bounds of errors. To improve the efficiency of the proposed method, a time-saving algorithm is presented by recursive formula. At last, to verify the accuracy of the proposed method, two numerical examples are applied and evaluated by three identification criteria respectively.

Differential identification of mushrooms sclerotia by IR macro-fingerprint method

NASA Astrophysics Data System (ADS)

Choong, Yew Keong; Lan, Jin; Lee, Han Lim; Chen, Xiang-dong; Wang, Xiao-guang; Yang, Yu-ping

2016-01-01

Many macrofungus sclerotia are well-known medicinal herbs, health food and nutritional supplements. However, the prevalent adulterant commercial products are major hindrances to their incorporation into mainstream medical use in many countries. The mushroom sclerotia of Lignosus rhinocerotis, Poria cocos, Polyporus umbellatus, Pleurotus tuber-regium and Omphalia lapidescens are commonly used in traditional Chinese medicine. In this study, IR macro-fingerprint method was used in the identification of these sclerotia. The results showed that the spectrum of L. rhinocerotis (LR) was comparable with P. cocos with 94.4% correlation, except that the peak at 1543 cm-1 of LR appeared in lower intensity. The spectrum of P. umbellatus and P. tuber-regium was also correlated (91.5%), as both spectra could be clearly discriminated in that P. umbellatus spectrum has small base peaks located at the range of 1680-1500 cm-1. O. lapidescens was not comparable with all the other sclerotia as its spectrum was totally different. Its base peak was broad and derivated equally along the range. The first IR has revealed the dissimilarity among five mushrooms sclerotia. The second derivative and 2DIR further enhanced the identification in detail.

[The research and application of pretreatment method for matrix-assisted laser desorption ionization-time of flight mass spectrometry identification of filamentous fungi].

PubMed

Huang, Y F; Chang, Z; Bai, J; Zhu, M; Zhang, M X; Wang, M; Zhang, G; Li, X Y; Tong, Y G; Wang, J L; Lu, X X

2017-08-08

Objective: To establish and evaluate the feasibility of a pretreatment method for matrix-assisted laser desorption ionization-time of flight mass spectrometry identification of filamentous fungi developed by the laboratory. Methods: Three hundred and eighty strains of filamentous fungi from January 2014 to December 2016 were recovered and cultured on sabouraud dextrose agar (SDA) plate at 28 ℃ to mature state. Meanwhile, the fungi were cultured in liquid sabouraud medium with a vertical rotation method recommended by Bruker and a horizontal vibration method developed by the laboratory until adequate amount of colonies were observed. For the strains cultured with the three methods, protein was extracted with modified magnetic bead-based extraction method for mass spectrum identification. Results: For 380 fungi strains, it took 3-10 d to culture with SDA culture method, and the ratio of identification of the species and genus was 47% and 81%, respectively; it took 5-7 d to culture with vertical rotation method, and the ratio of identification of the species and genus was 76% and 94%, respectively; it took 1-2 d to culture with horizontal vibration method, and the ratio of identification of the species and genus was 96% and 99%, respectively. For the comparison between horizontal vibration method and SDA culture method comparison, the difference was statistically significant (χ(2)=39.026, P <0.01); for the comparison between horizontal vibration method and vertical rotation method recommended by Bruker, the difference was statistically significant(χ(2)=11.310, P <0.01). Conclusion: The horizontal vibration method and modified magnetic bead-based extraction method developed by the laboratory is superior to the method recommended by Bruker and SDA culture method in terms of the identification capacity for filamentous fungi, which can be applied in clinic.

Target-decoy Based False Discovery Rate Estimation for Large-scale Metabolite Identification.

PubMed

Wang, Xusheng; Jones, Drew R; Shaw, Timothy I; Cho, Ji-Hoon; Wang, Yuanyuan; Tan, Haiyan; Xie, Boer; Zhou, Suiping; Li, Yuxin; Peng, Junmin

2018-05-23

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. In this study, we report a novel method for estimating false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis, and was also evaluated with two other metabolomics tools, mzMatch and mzMine 2. The reliability of FDR calculation was examined by false datasets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled with the target-decoy strategy to process unlabeled and stable-isotope labeled metabolomic datasets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma

PubMed Central

Wang, Hanghang; Muehlbauer, Michael J.; O’Neal, Sara K.; Newgard, Christopher B.; Hauser, Elizabeth R.; Shah, Svati H.

2017-01-01

The field of metabolomics as applied to human disease and health is rapidly expanding. In recent efforts of metabolomics research, greater emphasis has been placed on quality control and method validation. In this study, we report an experience with quality control and a practical application of method validation. Specifically, we sought to identify and modify steps in gas chromatography-mass spectrometry (GC-MS)-based, non-targeted metabolomic profiling of human plasma that could influence metabolite identification and quantification. Our experimental design included two studies: (1) a limiting-dilution study, which investigated the effects of dilution on analyte identification and quantification; and (2) a concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We confirmed that contaminants, concentration, repeatability and intermediate precision are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized to provide recommendations for experimental design of GC-MS-based non-targeted profiling of human plasma. PMID:28841195

3D anisotropic modeling and identification for airborne EM systems based on the spectral-element method

NASA Astrophysics Data System (ADS)

Huang, Xin; Yin, Chang-Chun; Cao, Xiao-Yue; Liu, Yun-He; Zhang, Bo; Cai, Jing

2017-09-01

The airborne electromagnetic (AEM) method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element (SE) method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell's equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic

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

PubMed

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

2003-01-28

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

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.

Evaluation of the PCR method for identification of Bifidobacterium species.

PubMed

Youn, S Y; Seo, J M; Ji, G E

2008-01-01

Bifidobacterium species are known for their beneficial effects on health and their wide use as probiotics. Although various polymerase chain reaction (PCR) methods for the identification of Bifidobacterium species have been published, the reliability of these methods remains open to question. In this study, we evaluated 37 previously reported PCR primer sets designed to amplify 16S rDNA, 23S rDNA, intergenic spacer regions, or repetitive DNA sequences of various Bifidobacterium species. Ten of 37 experimental primer sets showed specificity for B. adolescentis, B. angulatum, B. pseudocatenulatum, B. breve, B. bifidum, B. longum, B. longum biovar infantis and B. dentium. The results suggest that published Bifidobacterium primer sets should be re-evaluated for both reproducibility and specificity for the identification of Bifidobacterium species using PCR. Improvement of existing PCR methods will be needed to facilitate identification of other Bifidobacterium strains, such as B. animalis, B. catenulatum, B. thermophilum and B. subtile.

A New Pulse Pileup Rejection Method Based on Position Shift Identification

NASA Astrophysics Data System (ADS)

Gu, Z.; Prout, D. L.; Taschereau, R.; Bai, B.; Chatziioannou, A. F.

2016-02-01

Pulse pileup events degrade the signal-to-noise ratio (SNR) of nuclear medicine data. When such events occur in multiplexed detectors, they cause spatial misposition, energy spectrum distortion and degraded timing resolution, which leads to image artifacts. Pulse pileup is pronounced in PETbox4, a bench top PET scanner dedicated to high sensitivity and high resolution imaging of mice. In that system, the combination of high absolute sensitivity, long scintillator decay time (BGO) and highly multiplexed electronics lead to a significant fraction of pulse pileup, reached at lower total activity than for comparable instruments. In this manuscript, a new pulse pileup rejection method named position shift rejection (PSR) is introduced. The performance of PSR is compared with a conventional leading edge rejection (LER) method and with no pileup rejection implemented (NoPR). A comprehensive digital pulse library was developed for objective evaluation and optimization of the PSR and LER, in which pulse waveforms were directly recorded from real measurements exactly representing the signals to be processed. Physical measurements including singles event acquisition, peak system sensitivity and NEMA NU-4 image quality phantom were also performed in the PETbox4 system to validate and compare the different pulse pile-up rejection methods. The evaluation of both physical measurements and model pulse trains demonstrated that the new PSR performs more accurate pileup event identification and avoids erroneous rejection of valid events. For the PETbox4 system, this improvement leads to a significant recovery of sensitivity at low count rates, amounting to about 1/4th of the expected true coincidence events, compared to the LER method. Furthermore, with the implementation of PSR, optimal image quality can be achieved near the peak noise equivalent count rate (NECR).

DNA-based identification of Brassica vegetable species for the juice industry.

PubMed

Etoh, Kazumi; Niijima, Noritaka; Yokoshita, Masahiko; Fukuoka, Shin-Ichi

2003-10-01

Since kale (Brassica oleracea var. acephala), a cruciferous vegetable with a high level of vitamins and functional compounds beneficial to health and wellness, has become widely used in the juice industry, a precise method for quality control of vegetable species is necessary. We describe here a DNA-based identification method to distinguish kale from cabbage (Brassica oleracea var. capitata), a closely related species, which can be inadvertently mixed with kale during the manufacturing process. Using genomic DNA from these vegetables and combinatory sets of nucleotide primers, we screened for random amplified polymorphic DNA (RAPD) fragments and found three cabbage-specific fragments. These RAPD fragments, with lengths of 1.4, 0.5, and 1.5 kb, were purified, subcloned, and sequenced. Based on sequence-tagged sites (STS), we designed sets of primers to detect cabbage-specific identification (CAI) DNA markers. Utilizing the CAI markers, we successfully distinguished more than 10 different local cabbage accessions from 20 kale accessions, and identified kale juices experimentally spiked with different amounts of cabbage.

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

PubMed

Yu, Dongchuan; Frasca, Mattia; Liu, Fang

2008-10-01

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

System identification methods for aircraft flight control development and validation

NASA Technical Reports Server (NTRS)

Tischler, Mark B.

1995-01-01

System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

Apparatus and method for identification and recognition of an item with ultrasonic patterns from item subsurface micro-features

DOEpatents

Perkins, Richard W.; Fuller, James L.; Doctor, Steven R.; Good, Morris S.; Heasler, Patrick G.; Skorpik, James R.; Hansen, Norman H.

1995-01-01

The present invention is a means and method for identification and recognition of an item by ultrasonic imaging of material microfeatures and/or macrofeatures within the bulk volume of a material. The invention is based upon ultrasonic interrogation and imaging of material microfeatures within the body of material by accepting only reflected ultrasonic energy from a preselected plane or volume within the material. An initial interrogation produces an identification reference. Subsequent new scans are statistically compared to the identification reference for making a match/non-match decision.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of

Computer method for identification of boiler transfer functions

NASA Technical Reports Server (NTRS)

Miles, J. H.

1972-01-01

Iterative computer aided procedure was developed which provides for identification of boiler transfer functions using frequency response data. Method uses frequency response data to obtain satisfactory transfer function for both high and low vapor exit quality data.

The best of both worlds: A combined approach for analyzing microalgal diversity via metabarcoding and morphology-based methods

PubMed Central

Kahlert, Maria; Fink, Patrick

2017-01-01

An increasing number of studies use next generation sequencing (NGS) to analyze complex communities, but is the method sensitive enough when it comes to identification and quantification of species? We compared NGS with morphology-based identification methods in an analysis of microalgal (periphyton) communities. We conducted a mesocosm experiment in which we allowed two benthic grazer species to feed upon benthic biofilms, which resulted in altered periphyton communities. Morphology-based identification and 454 (Roche) pyrosequencing of the V4 region in the small ribosomal unit (18S) rDNA gene were used to investigate the community change caused by grazing. Both the NGS-based data and the morphology-based method detected a marked shift in the biofilm composition, though the two methods varied strongly in their abilities to detect and quantify specific taxa, and neither method was able to detect all species in the biofilms. For quantitative analysis, we therefore recommend using both metabarcoding and microscopic identification when assessing the community composition of eukaryotic microorganisms. PMID:28234997

Fatigue crack identification method based on strain amplitude changing

NASA Astrophysics Data System (ADS)

Guo, Tiancai; Gao, Jun; Wang, Yonghong; Xu, Youliang

2017-09-01

Aiming at the difficulties in identifying the location and time of crack initiation in the castings of helicopter transmission system during fatigue tests, by introducing the classification diagnostic criteria of similar failure mode to find out the similarity of fatigue crack initiation among castings, an engineering method and quantitative criterion for detecting fatigue cracks based on strain amplitude changing is proposed. This method is applied on the fatigue test of a gearbox housing, whose results indicates: during the fatigue test, the system alarms when SC strain meter reaches the quantitative criterion. The afterwards check shows that a fatigue crack less than 5mm is found at the corresponding location of SC strain meter. The test result proves that the method can provide accurate test data for strength life analysis.

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.

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

PubMed

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

2014-01-01

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

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.

Differential identification of mushrooms sclerotia by IR macro-fingerprint method.

PubMed

Choong, Yew Keong; Lan, Jin; Lee, Han Lim; Chen, Xiang-Dong; Wang, Xiao-Guang; Yang, Yu-Ping

2016-01-05

Many macrofungus sclerotia are well-known medicinal herbs, health food and nutritional supplements. However, the prevalent adulterant commercial products are major hindrances to their incorporation into mainstream medical use in many countries. The mushroom sclerotia of Lignosus rhinocerotis, Poria cocos, Polyporus umbellatus, Pleurotus tuber-regium and Omphalia lapidescens are commonly used in traditional Chinese medicine. In this study, IR macro-fingerprint method was used in the identification of these sclerotia. The results showed that the spectrum of L. rhinocerotis (LR) was comparable with P. cocos with 94.4% correlation, except that the peak at 1543cm(-1) of LR appeared in lower intensity. The spectrum of P. umbellatus and P. tuber-regium was also correlated (91.5%), as both spectra could be clearly discriminated in that P. umbellatus spectrum has small base peaks located at the range of 1680-1500cm(-1). O. lapidescens was not comparable with all the other sclerotia as its spectrum was totally different. Its base peak was broad and derivated equally along the range. The first IR has revealed the dissimilarity among five mushrooms sclerotia. The second derivative and 2DIR further enhanced the identification in detail. Copyright © 2015 Elsevier B.V. All rights reserved.

Apparatus and method for identification and recognition of an item with ultrasonic patterns from item subsurface micro-features

DOEpatents

Perkins, R.W.; Fuller, J.L.; Doctor, S.R.; Good, M.S.; Heasler, P.G.; Skorpik, J.R.; Hansen, N.H.

1995-09-26

The present invention is a means and method for identification and recognition of an item by ultrasonic imaging of material microfeatures and/or macrofeatures within the bulk volume of a material. The invention is based upon ultrasonic interrogation and imaging of material microfeatures within the body of material by accepting only reflected ultrasonic energy from a preselected plane or volume within the material. An initial interrogation produces an identification reference. Subsequent new scans are statistically compared to the identification reference for making a match/non-match decision. 15 figs.

A novel GLM-based method for the Automatic IDentification of functional Events (AIDE) in fNIRS data recorded in naturalistic environments.

PubMed

Pinti, Paola; Merla, Arcangelo; Aichelburg, Clarisse; Lind, Frida; Power, Sarah; Swingler, Elizabeth; Hamilton, Antonia; Gilbert, Sam; Burgess, Paul W; Tachtsidis, Ilias

2017-07-15

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that "brain-first" rather than "behaviour-first" analysis is

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

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

Accuracy-enhanced constitutive parameter identification using virtual fields method and special stereo-digital image correlation

NASA Astrophysics Data System (ADS)

Zhang, Zhongya; Pan, Bing; Grédiac, Michel; Song, Weidong

2018-04-01

The virtual fields method (VFM) is generally used with two-dimensional digital image correlation (2D-DIC) or grid method (GM) for identifying constitutive parameters. However, when small out-of-plane translation/rotation occurs to the test specimen, 2D-DIC and GM are prone to yield inaccurate measurements, which further lessen the accuracy of the parameter identification using VFM. In this work, an easy-to-implement but effective "special" stereo-DIC (SS-DIC) method is proposed for accuracy-enhanced VFM identification. The SS-DIC can not only deliver accurate deformation measurement without being affected by unavoidable out-of-plane movement/rotation of a test specimen, but can also ensure evenly distributed calculation data in space, which leads to simple data processing. Based on the accurate kinematics fields with evenly distributed measured points determined by SS-DIC method, constitutive parameters can be identified by VFM with enhanced accuracy. Uniaxial tensile tests of a perforated aluminum plate and pure shear tests of a prismatic aluminum specimen verified the effectiveness and accuracy of the proposed method. Experimental results show that the constitutive parameters identified by VFM using SS-DIC are more accurate and stable than those identified by VFM using 2D-DIC. It is suggested that the proposed SS-DIC can be used as a standard measuring tool for mechanical identification using VFM.

Damage identification using inverse methods.

PubMed

Friswell, Michael I

2007-02-15

This paper gives an overview of the use of inverse methods in damage detection and location, using measured vibration data. Inverse problems require the use of a model and the identification of uncertain parameters of this model. Damage is often local in nature and although the effect of the loss of stiffness may require only a small number of parameters, the lack of knowledge of the location means that a large number of candidate parameters must be included. This paper discusses a number of problems that exist with this approach to health monitoring, including modelling error, environmental effects, damage localization and regularization.

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.

CULTURE-INDEPENDENT MOLECULAR METHODS FOR FECAL SOURCE IDENTIFICATION

EPA Science Inventory

Fecal contamination is widespread in the waterways of the United States. Both to correct the problem, and to estimate public health risk, it is necessary to identify the source of the contamination. Several culture-independent molecular methods for fecal source identification hav...

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications.

PubMed

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation.

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation. PMID:26958441

Testing efficacy of distance and tree-based methods for DNA barcoding of grasses (Poaceae tribe Poeae) in Australia

PubMed Central

Walsh, Neville G.; Cantrill, David J.; Holmes, Gareth D.; Murphy, Daniel J.

2017-01-01

In Australia, Poaceae tribe Poeae are represented by 19 genera and 99 species, including economically and environmentally important native and introduced pasture grasses [e.g. Poa (Tussock-grasses) and Lolium (Ryegrasses)]. We used this tribe, which are well characterised in regards to morphological diversity and evolutionary relationships, to test the efficacy of DNA barcoding methods. A reference library was generated that included 93.9% of species in Australia (408 individuals, x¯ = 3.7 individuals per species). Molecular data were generated for official plant barcoding markers (rbcL, matK) and the nuclear ribosomal internal transcribed spacer (ITS) region. We investigated accuracy of specimen identifications using distance- (nearest neighbour, best-close match, and threshold identification) and tree-based (maximum likelihood, Bayesian inference) methods and applied species discovery methods (automatic barcode gap discovery, Poisson tree processes) based on molecular data to assess congruence with recognised species. Across all methods, success rate for specimen identification of genera was high (87.5–99.5%) and of species was low (25.6–44.6%). Distance- and tree-based methods were equally ineffective in providing accurate identifications for specimens to species rank (26.1–44.6% and 25.6–31.3%, respectively). The ITS marker achieved the highest success rate for specimen identification at both generic and species ranks across the majority of methods. For distance-based analyses the best-close match method provided the greatest accuracy for identification of individuals with a high percentage of “correct” (97.6%) and a low percentage of “incorrect” (0.3%) generic identifications, based on the ITS marker. For tribe Poeae, and likely for other grass lineages, sequence data in the standard DNA barcode markers are not variable enough for accurate identification of specimens to species rank. For recently diverged grass species similar challenges are

Testing efficacy of distance and tree-based methods for DNA barcoding of grasses (Poaceae tribe Poeae) in Australia.

PubMed

Birch, Joanne L; Walsh, Neville G; Cantrill, David J; Holmes, Gareth D; Murphy, Daniel J

2017-01-01

In Australia, Poaceae tribe Poeae are represented by 19 genera and 99 species, including economically and environmentally important native and introduced pasture grasses [e.g. Poa (Tussock-grasses) and Lolium (Ryegrasses)]. We used this tribe, which are well characterised in regards to morphological diversity and evolutionary relationships, to test the efficacy of DNA barcoding methods. A reference library was generated that included 93.9% of species in Australia (408 individuals, [Formula: see text] = 3.7 individuals per species). Molecular data were generated for official plant barcoding markers (rbcL, matK) and the nuclear ribosomal internal transcribed spacer (ITS) region. We investigated accuracy of specimen identifications using distance- (nearest neighbour, best-close match, and threshold identification) and tree-based (maximum likelihood, Bayesian inference) methods and applied species discovery methods (automatic barcode gap discovery, Poisson tree processes) based on molecular data to assess congruence with recognised species. Across all methods, success rate for specimen identification of genera was high (87.5-99.5%) and of species was low (25.6-44.6%). Distance- and tree-based methods were equally ineffective in providing accurate identifications for specimens to species rank (26.1-44.6% and 25.6-31.3%, respectively). The ITS marker achieved the highest success rate for specimen identification at both generic and species ranks across the majority of methods. For distance-based analyses the best-close match method provided the greatest accuracy for identification of individuals with a high percentage of "correct" (97.6%) and a low percentage of "incorrect" (0.3%) generic identifications, based on the ITS marker. For tribe Poeae, and likely for other grass lineages, sequence data in the standard DNA barcode markers are not variable enough for accurate identification of specimens to species rank. For recently diverged grass species similar challenges are

Perceptron ensemble of graph-based positive-unlabeled learning for disease gene identification.

PubMed

Jowkar, Gholam-Hossein; Mansoori, Eghbal G

2016-10-01

Identification of disease genes, using computational methods, is an important issue in biomedical and bioinformatics research. According to observations that diseases with the same or similar phenotype have the same biological characteristics, researchers have tried to identify genes by using machine learning tools. In recent attempts, some semi-supervised learning methods, called positive-unlabeled learning, is used for disease gene identification. In this paper, we present a Perceptron ensemble of graph-based positive-unlabeled learning (PEGPUL) on three types of biological attributes: gene ontologies, protein domains and protein-protein interaction networks. In our method, a reliable set of positive and negative genes are extracted using co-training schema. Then, the similarity graph of genes is built using metric learning by concentrating on multi-rank-walk method to perform inference from labeled genes. At last, a Perceptron ensemble is learned from three weighted classifiers: multilevel support vector machine, k-nearest neighbor and decision tree. The main contributions of this paper are: (i) incorporating the statistical properties of gene data through choosing proper metrics, (ii) statistical evaluation of biological features, and (iii) noise robustness characteristic of PEGPUL via using multilevel schema. In order to assess PEGPUL, we have applied it on 12950 disease genes with 949 positive genes from six class of diseases and 12001 unlabeled genes. Compared with some popular disease gene identification methods, the experimental results show that PEGPUL has reasonable performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Study on Parameter Identification of Assembly Robot based on Screw Theory

NASA Astrophysics Data System (ADS)

Yun, Shi; Xiaodong, Zhang

2017-11-01

The kinematic model of assembly robot is one of the most important factors affecting repetitive precision. In order to improve the accuracy of model positioning, this paper first establishes the exponential product model of ER16-1600 assembly robot on the basis of screw theory, and then based on iterative least squares method, using ER16-1600 model robot parameter identification. By comparing the experiment before and after the calibration, it is proved that the method has obvious improvement on the positioning accuracy of the assembly robot.

Data pieces-based parameter identification for lithium-ion battery

NASA Astrophysics Data System (ADS)

Gao, Wei; Zou, Yuan; Sun, Fengchun; Hu, Xiaosong; Yu, Yang; Feng, Sen

2016-10-01

Battery characteristics vary with temperature and aging, it is necessary to identify battery parameters periodically for electric vehicles to ensure reliable State-of-Charge (SoC) estimation, battery equalization and safe operation. Aiming for on-board applications, this paper proposes a data pieces-based parameter identification (DPPI) method to identify comprehensive battery parameters including capacity, OCV (open circuit voltage)-Ah relationship and impedance-Ah relationship simultaneously only based on battery operation data. First a vehicle field test was conducted and battery operation data was recorded, then the DPPI method is elaborated based on vehicle test data, parameters of all 97 cells of the battery package are identified and compared. To evaluate the adaptability of the proposed DPPI method, it is used to identify battery parameters of different aging levels and different temperatures based on battery aging experiment data. Then a concept of ;OCV-Ah aging database; is proposed, based on which battery capacity can be identified even though the battery was never fully charged or discharged. Finally, to further examine the effectiveness of the identified battery parameters, they are used to perform SoC estimation for the test vehicle with adaptive extended Kalman filter (AEKF). The result shows good accuracy and reliability.

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.

Frontal sinus recognition for human identification

NASA Astrophysics Data System (ADS)

Falguera, Juan Rogelio; Falguera, Fernanda Pereira Sartori; Marana, Aparecido Nilceu

2008-03-01

Many methods based on biometrics such as fingerprint, face, iris, and retina have been proposed for person identification. However, for deceased individuals, such biometric measurements are not available. In such cases, parts of the human skeleton can be used for identification, such as dental records, thorax, vertebrae, shoulder, and frontal sinus. It has been established in prior investigations that the radiographic pattern of frontal sinus is highly variable and unique for every individual. This has stimulated the proposition of measurements of the frontal sinus pattern, obtained from x-ray films, for skeletal identification. This paper presents a frontal sinus recognition method for human identification based on Image Foresting Transform and shape context. Experimental results (ERR = 5,82%) have shown the effectiveness of the proposed method.

An odor identification approach based on event-related pupil dilation and gaze focus.

PubMed

Aguillon-Hernandez, Nadia; Naudin, Marine; Roché, Laëtitia; Bonnet-Brilhault, Frédérique; Belzung, Catherine; Martineau, Joëlle; Atanasova, Boriana

2015-06-01

Olfactory disorders constitute a potential marker of many diseases and are considered valuable clues to the diagnosis and evaluation of progression for many disorders. The most commonly used test for the evaluation of impairments of olfactory identification requires the active participation of the subject, who must select the correct name of the perceived odor from a list. An alternative method is required because speech may be impaired or not yet learned in many patients. As odor identification is known to be facilitated by searching for visual clues, we aimed to develop an objective, vision-based approach for the evaluation of odor identification. We used an eye tracking method to quantify pupillary and ocular responses during the simultaneous presentation of olfactory and visual stimuli, in 39 healthy participants aged from 19 to 77years. Odor presentation triggered an increase in pupil dilation and gaze focus on the picture corresponding to the odor presented. These results suggest that odorant stimuli increase recruitment of the sympathetic system (as demonstrated by the reactivity of the pupil) and draw attention to the visual clue. These results validate the objectivity of this method. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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.

[Combine fats products: methodic opportunities of it identification].

PubMed

Viktorova, E V; Kulakova, S N; Mikhaĭlov, N A

2006-01-01

At present time very topical problem is falsification of milk fat. The number of methods was considered to detection of milk fat authention and possibilities his difference from combined fat products. The analysis of modern approaches to valuation of milk fat authention has showed that the main method for detection of fat nature is gas chromatography analysis. The computer method of express identification of fat products is proposed for quick getting of information about accessory of examine fat to nature milk or combined fat product.

[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.

Neural methods based on modified reputation rules for detection and identification of intrusion attacks in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2010-04-01

Determining methods to secure the process of data fusion against attacks by compromised nodes in wireless sensor networks (WSNs) and to quantify the uncertainty that may exist in the aggregation results is a critical issue in mitigating the effects of intrusion attacks. Published research has introduced the concept of the trustworthiness (reputation) of a single sensor node. Reputation is evaluated using an information-theoretic concept, the Kullback- Leibler (KL) distance. Reputation is added to the set of security features. In data aggregation, an opinion, a metric of the degree of belief, is generated to represent the uncertainty in the aggregation result. As aggregate information is disseminated along routes to the sink node(s), its corresponding opinion is propagated and regulated by Josang's belief model. By applying subjective logic on the opinion to manage trust propagation, the uncertainty inherent in aggregation results can be quantified for use in decision making. The concepts of reputation and opinion are modified to allow their application to a class of dynamic WSNs. Using reputation as a factor in determining interim aggregate information is equivalent to implementation of a reputation-based security filter at each processing stage of data fusion, thereby improving the intrusion detection and identification results based on unsupervised techniques. In particular, the reputation-based version of the probabilistic neural network (PNN) learns the signature of normal network traffic with the random probability weights normally used in the PNN replaced by the trust-based quantified reputations of sensor data or subsequent aggregation results generated by the sequential implementation of a version of Josang's belief model. A two-stage, intrusion detection and identification algorithm is implemented to overcome the problems of large sensor data loads and resource restrictions in WSNs. Performance of the twostage algorithm is assessed in simulations of WSN

matK-QR classifier: a patterns based approach for plant species identification.

PubMed

More, Ravi Prabhakar; Mane, Rupali Chandrashekhar; Purohit, Hemant J

2016-01-01

DNA barcoding is widely used and most efficient approach that facilitates rapid and accurate identification of plant species based on the short standardized segment of the genome. The nucleotide sequences of maturaseK ( matK ) and ribulose-1, 5-bisphosphate carboxylase ( rbcL ) marker loci are commonly used in plant species identification. Here, we present a new and highly efficient approach for identifying a unique set of discriminating nucleotide patterns to generate a signature (i.e. regular expression) for plant species identification. In order to generate molecular signatures, we used matK and rbcL loci datasets, which encompass 125 plant species in 52 genera reported by the CBOL plant working group. Initially, we performed Multiple Sequence Alignment (MSA) of all species followed by Position Specific Scoring Matrix (PSSM) for both loci to achieve a percentage of discrimination among species. Further, we detected Discriminating Patterns (DP) at genus and species level using PSSM for the matK dataset. Combining DP and consecutive pattern distances, we generated molecular signatures for each species. Finally, we performed a comparative assessment of these signatures with the existing methods including BLASTn, Support Vector Machines (SVM), Jrip-RIPPER, J48 (C4.5 algorithm), and the Naïve Bayes (NB) methods against NCBI-GenBank matK dataset. Due to the higher discrimination success obtained with the matK as compared to the rbcL , we selected matK gene for signature generation. We generated signatures for 60 species based on identified discriminating patterns at genus and species level. Our comparative assessment results suggest that a total of 46 out of 60 species could be correctly identified using generated signatures, followed by BLASTn (34 species), SVM (18 species), C4.5 (7 species), NB (4 species) and RIPPER (3 species) methods As a final outcome of this study, we converted signatures into QR codes and developed a software matK -QR Classifier (http

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Study on Urban Heat Island Intensity Level Identification Based on an Improved Restricted Boltzmann Machine.

PubMed

Zhang, Yang; Jiang, Ping; Zhang, Hongyan; Cheng, Peng

2018-01-23

Thermal infrared remote sensing has become one of the main technology methods used for urban heat island research. When applying urban land surface temperature inversion of the thermal infrared band, problems with intensity level division arise because the method is subjective. However, this method is one of the few that performs heat island intensity level identification. This paper will build an intensity level identifier for an urban heat island, by using weak supervision and thought-based learning in an improved, restricted Boltzmann machine (RBM) model. The identifier automatically initializes the annotation and optimizes the model parameters sequentially until the target identifier is completed. The algorithm needs very little information about the weak labeling of the target training sample and generates an urban heat island intensity spatial distribution map. This study can provide reliable decision-making support for urban ecological planning and effective protection of urban ecological security. The experimental results showed the following: (1) The heat island effect in Wuhan is existent and intense. Heat island areas are widely distributed. The largest heat island area is in Wuhan, followed by the sub-green island. The total area encompassed by heat island and strong island levels accounts for 54.16% of the land in Wuhan. (2) Partially based on improved RBM identification, this method meets the research demands of determining the spatial distribution characteristics of the internal heat island effect; its identification accuracy is superior to that of comparable methods.

Study on Urban Heat Island Intensity Level Identification Based on an Improved Restricted Boltzmann Machine

PubMed Central

Jiang, Ping; Zhang, Hongyan; Cheng, Peng

2018-01-01

Thermal infrared remote sensing has become one of the main technology methods used for urban heat island research. When applying urban land surface temperature inversion of the thermal infrared band, problems with intensity level division arise because the method is subjective. However, this method is one of the few that performs heat island intensity level identification. This paper will build an intensity level identifier for an urban heat island, by using weak supervision and thought-based learning in an improved, restricted Boltzmann machine (RBM) model. The identifier automatically initializes the annotation and optimizes the model parameters sequentially until the target identifier is completed. The algorithm needs very little information about the weak labeling of the target training sample and generates an urban heat island intensity spatial distribution map. This study can provide reliable decision-making support for urban ecological planning and effective protection of urban ecological security. The experimental results showed the following: (1) The heat island effect in Wuhan is existent and intense. Heat island areas are widely distributed. The largest heat island area is in Wuhan, followed by the sub-green island. The total area encompassed by heat island and strong island levels accounts for 54.16% of the land in Wuhan. (2) Partially based on improved RBM identification, this method meets the research demands of determining the spatial distribution characteristics of the internal heat island effect; its identification accuracy is superior to that of comparable methods. PMID:29360786

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.

A New Paradigm for Known Metabolite Identification in Metabonomics/Metabolomics: Metabolite Identification Efficiency

PubMed Central

Everett, Jeremy R.

2015-01-01

A new paradigm is proposed for assessing confidence in the identification of known metabolites in metabonomics studies using NMR spectroscopy approaches. This new paradigm is based upon the analysis of the amount of metabolite identification information retrieved from NMR spectra relative to the molecular size of the metabolite. Several new indices are proposed including: metabolite identification efficiency (MIE) and metabolite identification carbon efficiency (MICE), both of which can be easily calculated. These indices, together with some guidelines, can be used to provide a better indication of known metabolite identification confidence in metabonomics studies than existing methods. Since known metabolite identification in untargeted metabonomics studies is one of the key bottlenecks facing the science currently, it is hoped that these concepts based on molecular spectroscopic informatics, will find utility in the field. PMID:25750701

A new paradigm for known metabolite identification in metabonomics/metabolomics: metabolite identification efficiency.

PubMed

Everett, Jeremy R

2015-01-01

A new paradigm is proposed for assessing confidence in the identification of known metabolites in metabonomics studies using NMR spectroscopy approaches. This new paradigm is based upon the analysis of the amount of metabolite identification information retrieved from NMR spectra relative to the molecular size of the metabolite. Several new indices are proposed including: metabolite identification efficiency (MIE) and metabolite identification carbon efficiency (MICE), both of which can be easily calculated. These indices, together with some guidelines, can be used to provide a better indication of known metabolite identification confidence in metabonomics studies than existing methods. Since known metabolite identification in untargeted metabonomics studies is one of the key bottlenecks facing the science currently, it is hoped that these concepts based on molecular spectroscopic informatics, will find utility in the field.

Real-Time Parameter Estimation Method Applied to a MIMO Process and its Comparison with an Offline Identification Method

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

Kaplanoglu, Erkan; Safak, Koray K.; Varol, H. Selcuk

2009-01-12

An experiment based method is proposed for parameter estimation of a class of linear multivariable systems. The method was applied to a pressure-level control process. Experimental time domain input/output data was utilized in a gray-box modeling approach. Prior knowledge of the form of the system transfer function matrix elements is assumed to be known. Continuous-time system transfer function matrix parameters were estimated in real-time by the least-squares method. Simulation results of experimentally determined system transfer function matrix compare very well with the experimental results. For comparison and as an alternative to the proposed real-time estimation method, we also implemented anmore » offline identification method using artificial neural networks and obtained fairly good results. The proposed methods can be implemented conveniently on a desktop PC equipped with a data acquisition board for parameter estimation of moderately complex linear multivariable systems.« less

Full-Field Strain Measurement On Titanium Welds And Local Elasto-Plastic Identification With The Virtual Fields Method

NASA Astrophysics Data System (ADS)

Tattoli, F.; Pierron, F.; Rotinat, R.; Casavola, C.; Pappalettere, C.

2011-01-01

One of the main problems in welding is the microstructural transformation within the area affected by the thermal history. The resulting heterogeneous microstructure within the weld nugget and the heat affected zones is often associated with changes in local material properties. The present work deals with the identification of material parameters governing the elasto—plastic behaviour of the fused and heat affected zones as well as the base material for titanium hybrid welded joints (Ti6Al4V alloy). The material parameters are identified from heterogeneous strain fields with the Virtual Fields Method. This method is based on a relevant use of the principle of virtual work and it has been shown to be useful and much less time consuming than classical finite element model updating approaches applied to similar problems. The paper will present results and discuss the problem of selection of the weld zones for the identification.

Stochastic system identification in structural dynamics

USGS Publications Warehouse

Safak, Erdal

1988-01-01

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

From the patient to the clinical mycology laboratory: how can we optimise microscopy and culture methods for mould identification?

PubMed

Vyzantiadis, Timoleon-Achilleas A; Johnson, Elizabeth M; Kibbler, Christopher C

2012-06-01

The identification of fungi relies mainly on morphological criteria. However, there is a need for robust and definitive phenotypic identification procedures in order to evaluate continuously evolving molecular methods. For the future, there is an emerging consensus that a combined (phenotypic and molecular) approach is more powerful for fungal identification, especially for moulds. Most of the procedures used for phenotypic identification are based on experience rather than comparative studies of effectiveness or performance and there is a need for standardisation among mycology laboratories. This review summarises and evaluates the evidence for the major existing phenotypic identification procedures for the predominant causes of opportunistic mould infection. We have concentrated mainly on Aspergillus, Fusarium and mucoraceous mould species, as these are the most important clinically and the ones for which there are the most molecular taxonomic data.

Identification and Severity Determination of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data Acquired Using a Black-Paper-Based Measuring Method.

PubMed

Wang, Hui; Qin, Feng; Ruan, Liu; Wang, Rui; Liu, Qi; Ma, Zhanhong; Li, Xiaolong; Cheng, Pei; Wang, Haiguang

2016-01-01

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies.

Identification and Severity Determination of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data Acquired Using a Black-Paper-Based Measuring Method

PubMed Central

Ruan, Liu; Wang, Rui; Liu, Qi; Ma, Zhanhong; Li, Xiaolong; Cheng, Pei; Wang, Haiguang

2016-01-01

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies. PMID:27128464

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.

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.

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

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

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

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

Comparison of outlier identification methods in hospital surgical quality improvement programs.

PubMed

Bilimoria, Karl Y; Cohen, Mark E; Merkow, Ryan P; Wang, Xue; Bentrem, David J; Ingraham, Angela M; Richards, Karen; Hall, Bruce L; Ko, Clifford Y

2010-10-01

Surgeons and hospitals are being increasingly assessed by third parties regarding surgical quality and outcomes, and much of this information is reported publicly. Our objective was to compare various methods used to classify hospitals as outliers in established surgical quality assessment programs by applying each approach to a single data set. Using American College of Surgeons National Surgical Quality Improvement Program data (7/2008-6/2009), hospital risk-adjusted 30-day morbidity and mortality were assessed for general surgery at 231 hospitals (cases = 217,630) and for colorectal surgery at 109 hospitals (cases = 17,251). The number of outliers (poor performers) identified using different methods and criteria were compared. The overall morbidity was 10.3% for general surgery and 25.3% for colorectal surgery. The mortality was 1.6% for general surgery and 4.0% for colorectal surgery. Programs used different methods (logistic regression, hierarchical modeling, partitioning) and criteria (P < 0.01, P < 0.05, P < 0.10) to identify outliers. Depending on outlier identification methods and criteria employed, when each approach was applied to this single dataset, the number of outliers ranged from 7 to 57 hospitals for general surgery morbidity, 1 to 57 hospitals for general surgery mortality, 4 to 27 hospitals for colorectal morbidity, and 0 to 27 hospitals for colorectal mortality. There was considerable variation in the number of outliers identified using different detection approaches. Quality programs seem to be utilizing outlier identification methods contrary to what might be expected, thus they should justify their methodology based on the intent of the program (i.e., quality improvement vs. reimbursement). Surgeons and hospitals should be aware of variability in methods used to assess their performance as these outlier designations will likely have referral and reimbursement consequences.

Testing contamination source identification methods for water distribution networks

DOE PAGES

Seth, Arpan; Klise, Katherine A.; Siirola, John D.; ...

2016-04-01

In the event of contamination in a water distribution network (WDN), source identification (SI) methods that analyze sensor data can be used to identify the source location(s). Knowledge of the source location and characteristics are important to inform contamination control and cleanup operations. Various SI strategies that have been developed by researchers differ in their underlying assumptions and solution techniques. The following manuscript presents a systematic procedure for testing and evaluating SI methods. The performance of these SI methods is affected by various factors including the size of WDN model, measurement error, modeling error, time and number of contaminant injections,more » and time and number of measurements. This paper includes test cases that vary these factors and evaluates three SI methods on the basis of accuracy and specificity. The tests are used to review and compare these different SI methods, highlighting their strengths in handling various identification scenarios. These SI methods and a testing framework that includes the test cases and analysis tools presented in this paper have been integrated into EPA’s Water Security Toolkit (WST), a suite of software tools to help researchers and others in the water industry evaluate and plan various response strategies in case of a contamination incident. Lastly, a set of recommendations are made for users to consider when working with different categories of SI methods.« less

Species identification in meat products: A new screening method based on high resolution melting analysis of cyt b gene.

PubMed

Lopez-Oceja, A; Nuñez, C; Baeta, M; Gamarra, D; de Pancorbo, M M

2017-12-15

Meat adulteration by substitution with lower value products and/or mislabeling involves economic, health, quality and socio-religious issues. Therefore, identification and traceability of meat species has become an important subject to detect possible fraudulent practices. In the present study the development of a high resolution melt (HRM) screening method for the identification of eight common meat species is reported. Samples from Bos taurus, Ovis aries, Sus scrofa domestica, Equus caballus, Oryctolagus cuniculus, Gallus gallus domesticus, Meleagris gallopavo and Coturnix coturnix were analyzed through the amplification of a 148 bp fragment from the cyt b gene with a universal primer pair in HRM analyses. Melting profiles from each species, as well as from several DNA mixtures of these species and blind samples, allowed a successful species differentiation. The results demonstrated that the HRM method here proposed is a fast, reliable, and low-cost screening technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

NASA Astrophysics Data System (ADS)

An, Lu; Guo, Baolong

2018-03-01

Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).

BP network identification technology of infrared polarization based on fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Zeng, Haifang; Gu, Guohua; He, Weiji; Chen, Qian; Yang, Wei

2011-08-01

Infrared detection system is frequently employed on surveillance operations and reconnaissance mission to detect particular targets of interest in both civilian and military communities. By incorporating the polarization of light as supplementary information, the target discrimination performance could be enhanced. So this paper proposed an infrared target identification method which is based on fuzzy theory and neural network with polarization properties of targets. The paper utilizes polarization degree and light intensity to advance the unsupervised KFCM (kernel fuzzy C-Means) clustering method. And establish different material pol1arization properties database. In the built network, the system can feedback output corresponding material types of probability distribution toward any input polarized degree such as 10° 15°, 20°, 25°, 30°. KFCM, which has stronger robustness and accuracy than FCM, introduces kernel idea and gives the noise points and invalid value different but intuitively reasonable weights. Because of differences in characterization of material properties, there will be some conflicts in classification results. And D - S evidence theory was used in the combination of the polarization and intensity information. Related results show KFCM clustering precision and operation rate are higher than that of the FCM clustering method. The artificial neural network method realizes material identification, which reasonable solved the problems of complexity in environmental information of infrared polarization, and improperness of background knowledge and inference rule. This method of polarization identification is fast in speed, good in self-adaption and high in resolution.

Exploring Dual Identification among Muslim-American Emerging Adults: A Mixed Methods Study

ERIC Educational Resources Information Center

Sirin, Selcuk R.; Bikmen, Nida; Mir, Madeeha; Fine, Michelle; Zaal, Mayida; Katsiaficas, Dalal

2008-01-01

This mixed methods study explored dual identification among Muslim-American emerging adults of immigrant origin. A closer look was taken at the relationship between American and Muslim identifications and how this relationship was influenced by experiences of discrimination, acculturative and religious practices, and whether it varied by gender.…

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

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

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

Comparison of methods for the identification of microorganisms isolated from blood cultures.

PubMed

Monteiro, Aydir Cecília Marinho; Fortaleza, Carlos Magno Castelo Branco; Ferreira, Adriano Martison; Cavalcante, Ricardo de Souza; Mondelli, Alessandro Lia; Bagagli, Eduardo; da Cunha, Maria de Lourdes Ribeiro de Souza

2016-08-05

Bloodstream infections are responsible for thousands of deaths each year. The rapid identification of the microorganisms causing these infections permits correct therapeutic management that will improve the prognosis of the patient. In an attempt to reduce the time spent on this step, microorganism identification devices have been developed, including the VITEK(®) 2 system, which is currently used in routine clinical microbiology laboratories. This study evaluated the accuracy of the VITEK(®) 2 system in the identification of 400 microorganisms isolated from blood cultures and compared the results to those obtained with conventional phenotypic and genotypic methods. In parallel to the phenotypic identification methods, the DNA of these microorganisms was extracted directly from the blood culture bottles for genotypic identification by the polymerase chain reaction (PCR) and DNA sequencing. The automated VITEK(®) 2 system correctly identified 94.7 % (379/400) of the isolates. The YST and GN cards resulted in 100 % correct identifications of yeasts (15/15) and Gram-negative bacilli (165/165), respectively. The GP card correctly identified 92.6 % (199/215) of Gram-positive cocci, while the ANC card was unable to correctly identify any Gram-positive bacilli (0/5). The performance of the VITEK(®) 2 system was considered acceptable and statistical analysis showed that the system is a suitable option for routine clinical microbiology laboratories to identify different microorganisms.

Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions

PubMed Central

Chiou, Shin-Yan

2013-01-01

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

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

PubMed

Chiou, Shin-Yan

2013-01-01

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

Probability of identification (POI): a statistical model for the validation of qualitative botanical identification methods

USDA-ARS?s Scientific Manuscript database

A qualitative botanical identification method (BIM) is an analytical procedure which returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) mate...

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.

Testing isotopic labeling with [¹³C₆]glucose as a method of advanced glycation sites identification.

PubMed

Kielmas, Martyna; Kijewska, Monika; Stefanowicz, Piotr; Szewczuk, Zbigniew

2012-12-01

The Maillard reaction occurring between reducing sugars and reactive amino groups of biomolecules leads to the formation of a heterogeneous mixture of compounds: early, intermediate, and advanced glycation end products (AGEs). These compounds could be markers of certain diseases and of the premature aging process. Detection of Amadori products can be performed by various methods, including MS/MS techniques and affinity chromatography on immobilized boronic acid. However, the diversity of the structures of AGEs makes detection of these compounds more difficult. The aim of this study was to test a new method of AGE identification based on isotope (13)C labeling. The model protein (hen egg lysozyme) was modified with an equimolar mixture of [(12)C(6)]glucose and [(13)C(6)]glucose and then subjected to reduction of the disulfide bridges followed by tryptic hydrolysis. The digest obtained was analyzed by LC-MS. The glycation products were identified on the basis of characteristic isotopic patterns resulting from the use of isotopically labeled glucose. This method allowed identification of 38 early Maillard reaction products and five different structures of the end glycation products. This isotopic labeling technique combined with LC-MS is a sensitive method for identification of advanced glycation end products even if their chemical structure is unknown. Copyright © 2012 Elsevier Inc. All rights reserved.

A comparison of microscopic and spectroscopic identification methods for analysis of microplastics in environmental samples.

PubMed

Song, Young Kyoung; Hong, Sang Hee; Jang, Mi; Han, Gi Myung; Rani, Manviri; Lee, Jongmyoung; Shim, Won Joon

2015-04-15

The analysis of microplastics in various environmental samples requires the identification of microplastics from natural materials. The identification technique lacks a standardized protocol. Herein, stereomicroscope and Fourier transform infrared spectroscope (FT-IR) identification methods for microplastics (<1mm) were compared using the same samples from the sea surface microlayer (SML) and beach sand. Fragmented microplastics were significantly (p<0.05) underestimated and fiber was significantly overestimated using the stereomicroscope both in the SML and beach samples. The total abundance by FT-IR was higher than by microscope both in the SML and beach samples, but they were not significantly (p>0.05) different. Depending on the number of samples and the microplastic size range of interest, the appropriate identification method should be determined; selecting a suitable identification method for microplastics is crucial for evaluating microplastic pollution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Finger-vein and fingerprint recognition based on a feature-level fusion method

NASA Astrophysics Data System (ADS)

Yang, Jinfeng; Hong, Bofeng

2013-07-01

Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.

Equivalent orthotropic elastic moduli identification method for laminated electrical steel sheets

NASA Astrophysics Data System (ADS)

Saito, Akira; Nishikawa, Yasunari; Yamasaki, Shintaro; Fujita, Kikuo; Kawamoto, Atsushi; Kuroishi, Masakatsu; Nakai, Hideo

2016-05-01

In this paper, a combined numerical-experimental methodology for the identification of elastic moduli of orthotropic media is presented. Special attention is given to the laminated electrical steel sheets, which are modeled as orthotropic media with nine independent engineering elastic moduli. The elastic moduli are determined specifically for use with finite element vibration analyses. We propose a three-step methodology based on a conventional nonlinear least squares fit between measured and computed natural frequencies. The methodology consists of: (1) successive augmentations of the objective function by increasing the number of modes, (2) initial condition updates, and (3) appropriate selection of the natural frequencies based on their sensitivities on the elastic moduli. Using the results of numerical experiments, it is shown that the proposed method achieves more accurate converged solution than a conventional approach. Finally, the proposed method is applied to measured natural frequencies and mode shapes of the laminated electrical steel sheets. It is shown that the method can successfully identify the orthotropic elastic moduli that can reproduce the measured natural frequencies and frequency response functions by using finite element analyses with a reasonable accuracy.

Application of DNA-based methods in forensic entomology.

PubMed

Wells, Jeffrey D; Stevens, Jamie R

2008-01-01

A forensic entomological investigation can benefit from a variety of widely practiced molecular genotyping methods. The most commonly used is DNA-based specimen identification. Other applications include the identification of insect gut contents and the characterization of the population genetic structure of a forensically important insect species. The proper application of these procedures demands that the analyst be technically expert. However, one must also be aware of the extensive list of standards and expectations that many legal systems have developed for forensic DNA analysis. We summarize the DNA techniques that are currently used in, or have been proposed for, forensic entomology and review established genetic analyses from other scientific fields that address questions similar to those in forensic entomology. We describe how accepted standards for forensic DNA practice and method validation are likely to apply to insect evidence used in a death or other forensic entomological investigation.

19 CFR 191.14 - Identification of merchandise or articles by accounting method.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Identification of merchandise or articles by accounting method. 191.14 Section 191.14 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK General Provisions § 191.14 Identification of merchandise or articles by...

19 CFR 191.14 - Identification of merchandise or articles by accounting method.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 2 2014-04-01 2014-04-01 false Identification of merchandise or articles by accounting method. 191.14 Section 191.14 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK General Provisions § 191.14 Identification of merchandise or articles by...

19 CFR 191.14 - Identification of merchandise or articles by accounting method.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 2 2013-04-01 2013-04-01 false Identification of merchandise or articles by accounting method. 191.14 Section 191.14 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK General Provisions § 191.14 Identification of merchandise or articles by...

19 CFR 191.14 - Identification of merchandise or articles by accounting method.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Identification of merchandise or articles by accounting method. 191.14 Section 191.14 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK General Provisions § 191.14 Identification of merchandise or articles by...

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.

Codestream-Based Identification of JPEG 2000 Images with Different Coding Parameters

NASA Astrophysics Data System (ADS)

Watanabe, Osamu; Fukuhara, Takahiro; Kiya, Hitoshi

A method of identifying JPEG 2000 images with different coding parameters, such as code-block sizes, quantization-step sizes, and resolution levels, is presented. It does not produce false-negative matches regardless of different coding parameters (compression rate, code-block size, and discrete wavelet transform (DWT) resolutions levels) or quantization step sizes. This feature is not provided by conventional methods. Moreover, the proposed approach is fast because it uses the number of zero-bit-planes that can be extracted from the JPEG 2000 codestream by only parsing the header information without embedded block coding with optimized truncation (EBCOT) decoding. The experimental results revealed the effectiveness of image identification based on the new method.

[Identification of Candida dubliniensis strains using heat tolerance tests, morphological characteristics and molecular methods].

PubMed

Arikan, Sevtap; Darka, Ozge; Hasçelik, Gülşen; Günalp, Ayfer

2003-01-01

Described in 1995, Candida dubliniensis is a novel Candida species closely related to Candida albicans due primarily to its ability to produce germ tube and chlamydospores. Given these phenotypic similarities between the two species, C. dubliniensis cannot be readily distinguished from Candida albicans by routine laboratory work-up. We explored the frequency of isolation of C. dubliniensis among 213 strains previously defined as C. albicans based on their ability to produce germ tube. The test isolates were initially examined for their morphological features on cornmeal tween 80 agar, inability to grow at 45 degrees C, and the biochemical assimilation profile (ID 32C system, bioMerieux, France). Among all, 2 (0.9%) of the isolates were identified as C. dubliniensis based on the production of numerous chlamydospores in chains on cornmeal tween 80 agar and the lack of growth at 45 degrees C. The assimilation profile of these isolates was found to be in accordance with this identification. In an effort to confirm the identification, polymerase chain reaction (PCR) studies were carried out by using the C. dubliniensis specific primer set, DUBF and DUBR. Both of the isolates yielded C. dubliniensis-specific 288 base pair amplification products, confirming the previous identification obtained with the initial screening tests. The isolates were found to be susceptible to fluconazole and itraconazole, and generated amphotericin B minimal inhibitory concentrations of 0.5-1 microgram/ml by NCCLS M27-A2 microdilution method. These data suggest that the isolation rate of C. dubliniensis among our clinical isolates is low. The morphological features on cornmeal tween 80 agar and the lack of ability to grow at 45 degrees C appear as reliable, cheap, and practical screening tests in initial identification of C. dubliniensis among germ tube-producing Candida strains.

Identification of the heart wall and chamber based on temporal change of ultrasonic scatterer distribution

NASA Astrophysics Data System (ADS)

Takahashi, Kohei; Taki, Hirofumi; Kanai, Hiroshi

2017-07-01

In most current methods for evaluating the cardiac function by ultrasound, the heart wall area is identified manually by an examiner. To eliminate examiner dependence and to improve usability, an automatic heart wall identification method is desirable. Identification based on only echogenicity often fails because of low echogenicity of some areas of the heart wall. In the present study, to determine more essential features, we focused on the relative temporal change of ultrasonic scatterer distribution and proposed three features for identification of the heart wall and the chamber: cross-correlation of RF signals, that of envelopes, and spatial dispersion of movement vectors in small regions. In an in vivo experiment, using echogenicity and the three features, we identified the heart wall and the chamber in the left ventricular long-axis view, resulting in criteria of separability J of 1.69, 1.40, and 3.02 using these features compared with the result of 0.979 using echogenicity.

Eye movement identification based on accumulated time feature

NASA Astrophysics Data System (ADS)

Guo, Baobao; Wu, Qiang; Sun, Jiande; Yan, Hua

2017-06-01

Eye movement is a new kind of feature for biometrical recognition, it has many advantages compared with other features such as fingerprint, face, and iris. It is not only a sort of static characteristics, but also a combination of brain activity and muscle behavior, which makes it effective to prevent spoofing attack. In addition, eye movements can be incorporated with faces, iris and other features recorded from the face region into multimode systems. In this paper, we do an exploring study on eye movement identification based on the eye movement datasets provided by Komogortsev et al. in 2011 with different classification methods. The time of saccade and fixation are extracted from the eye movement data as the eye movement features. Furthermore, the performance analysis was conducted on different classification methods such as the BP, RBF, ELMAN and SVM in order to provide a reference to the future research in this field.

Behavior identification based on geotagged photo data set.

PubMed

Liu, Guo-qi; Zhang, Yi-jia; Fu, Ying-mao; Liu, Ying

2014-01-01

The popularity of mobile devices has produced a set of image data with geographic information, time information, and text description information, which is called geotagged photo data set. The division of this kind of data by its behavior and the location not only can identify the user's important location and daily behavior, but also helps users to sort the huge image data. This paper proposes a method to build an index based on multiple classification result, which can divide the data set multiple times and distribute labels to the data to build index according to the estimated probability of classification results in order to accomplish the identification of users' important location and daily behaviors. This paper collects 1400 discrete sets of data as experimental data to verify the method proposed in this paper. The result of the experiment shows that the index and actual tagging results have a high inosculation.

ROKU: a novel method for identification of tissue-specific genes.

PubMed

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-06-12

One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

ROKU: a novel method for identification of tissue-specific genes

PubMed Central

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-01-01

Background One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. Results We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. Conclusion ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes. PMID:16764735

An unusual method of forensic human identification: use of selfie photographs.

PubMed

Miranda, Geraldo Elias; Freitas, Sílvia Guzella de; Maia, Luiza Valéria de Abreu; Melani, Rodolfo Francisco Haltenhoff

2016-06-01

As with other methods of identification, in forensic odontology, antemortem data are compared with postmortem findings. In the absence of dental documentation, photographs of the smile play an important role in this comparison. As yet, there are no reports of the use of the selfie photograph for identification purposes. Owing to advancements in technology, electronic devices, and social networks, this type of photograph has become increasingly common. This paper describes a case in which selfie photographs were used to identify a carbonized body, by using the smile line and image superimposition. This low-cost, rapid, and easy to analyze technique provides highly reliable results. Nevertheless, there are disadvantages, such as the limited number of teeth that are visible in a photograph, low image quality, possibility of morphological changes in the teeth after the antemortem image was taken, and difficulty of making comparisons depending on the orientation of the photo. In forensic odontology, new methods of identification must be sought to accompany technological evolution, particularly when no traditional methods of comparison, such as clinical record charts or radiographs, are available. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Water Quality Assessment for Deep-water Channel area of Guangzhou Port based on the Comprehensive Water Quality Identification Index Method

NASA Astrophysics Data System (ADS)

Chen, Yi

2018-03-01

The comprehensive water quality identification index method is able to assess the general water quality situation comprehensively and represent the water quality classification; water environment functional zone achieves pollution level and standard objectively and systematically. This paper selects 3 representative zones along deep-water channel of Guangzhou port and applies comprehensive water quality identification index method to calculate sea water quality monitoring data for different selected zones from year 2006 to 2014, in order to investigate the temporal variation of water quality along deep-water channel of Guangzhou port. The comprehensive water quality level from north to south presents an increased trend, and the water quality of the three zones in 2014 is much better than in 2006. This paper puts forward environmental protection measurements and suggestions for Pearl River Estuary, provides data support and theoretical basis for studied sea area pollution prevention and control.

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.

The Development of DNA Based Methods for the Reliable and Efficient Identification of Nicotiana tabacum in Tobacco and Its Derived Products

PubMed Central

Fan, Wei; Li, Rong; Li, Sifan; Ping, Wenli; Li, Shujun; Naumova, Alexandra; Peelen, Tamara; Yuan, Zheng; Zhang, Dabing

2016-01-01

Reliable methods are needed to detect the presence of tobacco components in tobacco products to effectively control smuggling and classify tariff and excise in tobacco industry to control illegal tobacco trade. In this study, two sensitive and specific DNA based methods, one quantitative real-time PCR (qPCR) assay and the other loop-mediated isothermal amplification (LAMP) assay, were developed for the reliable and efficient detection of the presence of tobacco (Nicotiana tabacum) in various tobacco samples and commodities. Both assays targeted the same sequence of the uridine 5′-monophosphate synthase (UMPS), and their specificities and sensitivities were determined with various plant materials. Both qPCR and LAMP methods were reliable and accurate in the rapid detection of tobacco components in various practical samples, including customs samples, reconstituted tobacco samples, and locally purchased cigarettes, showing high potential for their application in tobacco identification, particularly in the special cases where the morphology or chemical compositions of tobacco have been disrupted. Therefore, combining both methods would facilitate not only the detection of tobacco smuggling control, but also the detection of tariff classification and of excise. PMID:27635142

SLD Identification: A Survey of Methods Used by School Psychologists

ERIC Educational Resources Information Center

Watson, Michael D., Jr.; Simon, Joan B.; Nunnley, Lenora

2016-01-01

IDEA 2004 opened the door for states, and in some cases districts, to choose among three different methods for identifying children with Specific Learning Disabilities (SLDs). This study provides an in-depth look at SLD identification practices in a state that allows school psychologists to use any of the three methods. Eighty-four school…

Kalman and particle filtering methods for full vehicle and tyre identification

NASA Astrophysics Data System (ADS)

Bogdanski, Karol; Best, Matthew C.

2018-05-01

This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators.

PIPI: PTM-Invariant Peptide Identification Using Coding Method.

PubMed

Yu, Fengchao; Li, Ning; Yu, Weichuan

2016-12-02

In computational proteomics, the identification of peptides with an unlimited number of post-translational modification (PTM) types is a challenging task. The computational cost associated with database search increases exponentially with respect to the number of modified amino acids and linearly with respect to the number of potential PTM types at each amino acid. The problem becomes intractable very quickly if we want to enumerate all possible PTM patterns. To address this issue, one group of methods named restricted tools (including Mascot, Comet, and MS-GF+) only allow a small number of PTM types in database search process. Alternatively, the other group of methods named unrestricted tools (including MS-Alignment, ProteinProspector, and MODa) avoids enumerating PTM patterns with an alignment-based approach to localizing and characterizing modified amino acids. However, because of the large search space and PTM localization issue, the sensitivity of these unrestricted tools is low. This paper proposes a novel method named PIPI to achieve PTM-invariant peptide identification. PIPI belongs to the category of unrestricted tools. It first codes peptide sequences into Boolean vectors and codes experimental spectra into real-valued vectors. For each coded spectrum, it then searches the coded sequence database to find the top scored peptide sequences as candidates. After that, PIPI uses dynamic programming to localize and characterize modified amino acids in each candidate. We used simulation experiments and real data experiments to evaluate the performance in comparison with restricted tools (i.e., Mascot, Comet, and MS-GF+) and unrestricted tools (i.e., Mascot with error tolerant search, MS-Alignment, ProteinProspector, and MODa). Comparison with restricted tools shows that PIPI has a close sensitivity and running speed. Comparison with unrestricted tools shows that PIPI has the highest sensitivity except for Mascot with error tolerant search and Protein

The evidence of the rugoscopy effectiveness as a human identification method in patients submitted to rapid palatal expansion.

PubMed

Barbieri, Ana A; Scoralick, Raquel A; Naressi, Suely C M; Moraes, Mari E L; Daruge, Eduardo; Daruge, Eduardo

2013-01-01

The objective of this study was to demonstrate the effectiveness of rugoscopy as a human identification method, even when the patient is submitted to rapid palatal expansion, which in theory would introduce doubt. With this intent, the Rugoscopic Identity was obtained for each subject using the classification formula proposed by Santos based on the intra-oral casts made before and after treatment from patients who were subjected to palatal expansion. The casts were labeled with the patients' initials and randomly arranged for studying. The palatine rugae kept the same patterns in every case studied. The technical error of the intra-evaluator measurement provided a confidence interval of 95%, making rugoscopy a reliable identification method for patients who were submitted to rapid palatal expansion, because even in the presence of intra-oral changes owing to the use of palatal expanders, the palatine rugae retained the biological and technical requirements for the human identification process. © 2012 American Academy of Forensic Sciences.

Comparison among four proposed direct blood culture microbial identification methods using MALDI-TOF MS.

PubMed

Bazzi, Ali M; Rabaan, Ali A; El Edaily, Zeyad; John, Susan; Fawarah, Mahmoud M; Al-Tawfiq, Jaffar A

Matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry facilitates rapid and accurate identification of pathogens, which is critical for sepsis patients. In this study, we assessed the accuracy in identification of both Gram-negative and Gram-positive bacteria, except for Streptococcus viridans, using four rapid blood culture methods with Vitek MALDI-TOF-MS. We compared our proposed lysis centrifugation followed by washing and 30% acetic acid treatment method (method 2) with two other lysis centrifugation methods (washing and 30% formic acid treatment (method 1); 100% ethanol treatment (method 3)), and picking colonies from 90 to 180min subculture plates (method 4). Methods 1 and 2 identified all organisms down to species level with 100% accuracy, except for Streptococcus viridans, Streptococcus pyogenes, Enterobacter cloacae and Proteus vulgaris. The latter two were identified to genus level with 100% accuracy. Each method exhibited excellent accuracy and precision in terms of identification to genus level with certain limitations. Copyright © 2016 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Applications of graph theory in protein structure identification

PubMed Central

2011-01-01

There is a growing interest in the identification of proteins on the proteome wide scale. Among different kinds of protein structure identification methods, graph-theoretic methods are very sharp ones. Due to their lower costs, higher effectiveness and many other advantages, they have drawn more and more researchers’ attention nowadays. Specifically, graph-theoretic methods have been widely used in homology identification, side-chain cluster identification, peptide sequencing and so on. This paper reviews several methods in solving protein structure identification problems using graph theory. We mainly introduce classical methods and mathematical models including homology modeling based on clique finding, identification of side-chain clusters in protein structures upon graph spectrum, and de novo peptide sequencing via tandem mass spectrometry using the spectrum graph model. In addition, concluding remarks and future priorities of each method are given. PMID:22165974

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

NASA Astrophysics Data System (ADS)

Zhao, Lei; Xu, Hengying; Bai, Chenglin

2018-03-01

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

Improved symbol rate identification method for on-off keying and advanced modulation format signals based on asynchronous delayed sampling

NASA Astrophysics Data System (ADS)

Cui, Sheng; Jin, Shang; Xia, Wenjuan; Ke, Changjian; Liu, Deming

2015-11-01

Symbol rate identification (SRI) based on asynchronous delayed sampling is accurate, cost-effective and robust to impairments. For on-off keying (OOK) signals the symbol rate can be derived from the periodicity of the second-order autocorrelation function (ACF2) of the delay tap samples. But it is found that when applied this method to advanced modulation format signals with auxiliary amplitude modulation (AAM), incorrect results may be produced because AAM has significant impact on ACF2 periodicity, which makes the symbol period harder or even unable to be correctly identified. In this paper it is demonstrated that for these signals the first order autocorrelation function (ACF1) has stronger periodicity and can be used to replace ACF2 to produce more accurate and robust results. Utilizing the characteristics of the ACFs, an improved SRI method is proposed to accommodate both OOK and advanced modulation formant signals in a transparent manner. Furthermore it is proposed that by minimizing the peak to average ratio (PAPR) of the delay tap samples with an additional tunable dispersion compensator (TDC) the limited dispersion tolerance can be expanded to desired values.

Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

PubMed Central

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6–7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and

Examining the effectiveness of discriminant function analysis and cluster analysis in species identification of male field crickets based on their calling songs.

PubMed

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and

[Progress in the spectral library based protein identification strategy].

PubMed

Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

2018-04-25

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

Identification of Burkholderia spp. in the Clinical Microbiology Laboratory: Comparison of Conventional and Molecular Methods

PubMed Central

van Pelt, Cindy; Verduin, Cees M.; Goessens, Wil H. F.; Vos, Margreet C.; Tümmler, Burkhard; Segonds, Christine; Reubsaet, Frans; Verbrugh, Henri; van Belkum, Alex

1999-01-01

Cystic fibrosis (CF) predisposes patients to bacterial colonization and infection of the lower airways. Several species belonging to the genus Burkholderia are potential CF-related pathogens, but microbiological identification may be complicated. This situation is not in the least due to the poorly defined taxonomic status of these bacteria, and further validation of the available diagnostic assays is required. A total of 114 geographically diverse bacterial isolates, previously identified in reference laboratories as Burkholderia cepacia (n = 51), B. gladioli (n = 14), Ralstonia pickettii (n = 6), B. multivorans (n = 2), Stenotrophomonas maltophilia (n = 3), and Pseudomonas aeruginosa (n = 11), were collected from environmental, clinical, and reference sources. In addition, 27 clinical isolates putatively identified as Burkholderia spp. were recovered from the sputum of Dutch CF patients. All isolates were used to evaluate the accuracy of two selective growth media, four systems for biochemical identification (API 20NE, Vitek GNI, Vitek NFC, and MicroScan), and three different PCR-based assays. The PCR assays amplify different parts of the ribosomal DNA operon, either alone or in combination with cleavage by various restriction enzymes (PCR-restriction fragment length polymorphism [RFLP] analysis). The best system for the biochemical identification of B. cepacia appeared to be the API 20NE test. None of the biochemical assays successfully grouped the B. gladioli strains. The PCR-RFLP method appeared to be the optimal method for accurate nucleic acid-mediated identification of the different Burkholderia spp. With this method, B. gladioli was also reliably classified in a separate group. For the laboratory diagnosis of B. cepacia, we recommend parallel cultures on blood agar medium and selective agar plates. Further identification of colonies with a Burkholderia phenotype should be performed with the API 20NE test. For final confirmation of species identities, PCR

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

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.

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

PubMed

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

2016-01-01

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

An improved EMD method for modal identification and a combined static-dynamic method for damage detection

NASA Astrophysics Data System (ADS)

Yang, Jinping; Li, Peizhen; Yang, Youfa; Xu, Dian

2018-04-01

Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

Frequency Response Function Based Damage Identification for Aerospace Structures

NASA Astrophysics Data System (ADS)

Oliver, Joseph Acton

Structural health monitoring technologies continue to be pursued for aerospace structures in the interests of increased safety and, when combined with health prognosis, efficiency in life-cycle management. The current dissertation develops and validates damage identification technology as a critical component for structural health monitoring of aerospace structures and, in particular, composite unmanned aerial vehicles. The primary innovation is a statistical least-squares damage identification algorithm based in concepts of parameter estimation and model update. The algorithm uses frequency response function based residual force vectors derived from distributed vibration measurements to update a structural finite element model through statistically weighted least-squares minimization producing location and quantification of the damage, estimation uncertainty, and an updated model. Advantages compared to other approaches include robust applicability to systems which are heavily damped, large, and noisy, with a relatively low number of distributed measurement points compared to the number of analytical degrees-of-freedom of an associated analytical structural model (e.g., modal finite element model). Motivation, research objectives, and a dissertation summary are discussed in Chapter 1 followed by a literature review in Chapter 2. Chapter 3 gives background theory and the damage identification algorithm derivation followed by a study of fundamental algorithm behavior on a two degree-of-freedom mass-spring system with generalized damping. Chapter 4 investigates the impact of noise then successfully proves the algorithm against competing methods using an analytical eight degree-of-freedom mass-spring system with non-proportional structural damping. Chapter 5 extends use of the algorithm to finite element models, including solutions for numerical issues, approaches for modeling damping approximately in reduced coordinates, and analytical validation using a composite

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Comparison of SVM RBF-NN and DT for crop and weed identification based on spectral measurement over corn fields

USDA-ARS?s Scientific Manuscript database

It is important to find an appropriate pattern-recognition method for in-field plant identification based on spectral measurement in order to classify the crop and weeds accurately. In this study, the method of Support Vector Machine (SVM) was evaluated and compared with two other methods, Decision ...

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

NASA Astrophysics Data System (ADS)

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

2009-06-01

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

Adventitious sounds identification and extraction using temporal-spectral dominance-based features.

PubMed

Jin, Feng; Krishnan, Sridhar Sri; Sattar, Farook

2011-11-01

Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds (ASs). Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused on the analysis of the evolution of symptom-related signal components in joint time-frequency (TF) plane. This paper proposes a new signal identification and extraction method for various ASs based on instantaneous frequency (IF) analysis. The presented TF decomposition method produces a noise-resistant high definition TF representation of RS signals as compared to the conventional linear TF analysis methods, yet preserving the low computational complexity as compared to those quadratic TF analysis methods. The discarded phase information in conventional spectrogram has been adopted for the estimation of IF and group delay, and a temporal-spectral dominance spectrogram has subsequently been constructed by investigating the TF spreads of the computed time-corrected IF components. The proposed dominance measure enables the extraction of signal components correspond to ASs from noisy RS signal at high noise level. A new set of TF features has also been proposed to quantify the shapes of the obtained TF contours, and therefore strongly, enhances the identification of multicomponents signals such as polyphonic wheezes. An overall accuracy of 92.4±2.9% for the classification of real RS recordings shows the promising performance of the presented method.

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).

Identification of eggs from different production systems based on hyperspectra and CS-SVM.

PubMed

Sun, J; Cong, S L; Mao, H P; Zhou, X; Wu, X H; Zhang, X D

2017-06-01

1. To identify the origin of table eggs more accurately, a method based on hyperspectral imaging technology was studied. 2. The hyperspectral data of 200 samples of intensive and extensive eggs were collected. Standard normalised variables combined with a Savitzky-Golay were used to eliminate noise, then stepwise regression (SWR) was used for feature selection. Grid search algorithm (GS), genetic search algorithm (GA), particle swarm optimisation algorithm (PSO) and cuckoo search algorithm (CS) were applied by support vector machine (SVM) methods to establish an SVM identification model with the optimal parameters. The full spectrum data and the data after feature selection were the input of the model, while egg category was the output. 3. The SWR-CS-SVM model performed better than the other models, including SWR-GS-SVM, SWR-GA-SVM, SWR-PSO-SVM and others based on full spectral data. The training and test classification accuracy of the SWR-CS-SVM model were respectively 99.3% and 96%. 4. SWR-CS-SVM proved effective for identifying egg varieties and could also be useful for the non-destructive identification of other types of egg.

Robust wafer identification recognition based on asterisk-shape filter and high-low score comparison method.

PubMed

Hsu, Wei-Chih; Yu, Tsan-Ying; Chen, Kuan-Liang

2009-12-10

Wafer identifications (wafer ID) can be used to identify wafers from each other so that wafer processing can be traced easily. Wafer ID recognition is one of the problems of optical character recognition. The process to recognize wafer IDs is similar to that used in recognizing car license-plate characters. However, due to some unique characteristics, such as the irregular space between two characters and the unsuccessive strokes of wafer ID, it will not get a good result to recognize wafer ID by directly utilizing the approaches used in car license-plate character recognition. Wafer ID scratches are engraved by a laser scribe almost along the following four fixed directions: horizontal, vertical, plus 45 degrees , and minus 45 degrees orientations. The closer to the center line of a wafer ID scratch, the higher the gray level will be. These and other characteristics increase the difficulty to recognize the wafer ID. In this paper a wafer ID recognition scheme based on an asterisk-shape filter and a high-low score comparison method is proposed to cope with the serious influence of uneven luminance and make recognition more efficiently. Our proposed approach consists of some processing stages. Especially in the final recognition stage, a template-matching method combined with stroke analysis is used as a recognizing scheme. This is because wafer IDs are composed of Semiconductor Equipment and Materials International (SEMI) standard Arabic numbers and English alphabets, and thus the template ID images are easy to obtain. Furthermore, compared with the approach that requires prior training, such as a support vector machine, which often needs a large amount of training image samples, no prior training is required for our approach. The testing results show that our proposed scheme can efficiently and correctly segment out and recognize the wafer ID with high performance.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Superpixel segmentation and pigment identification of colored relics based on visible spectral image.

PubMed

Li, Junfeng; Wan, Xiaoxia

2018-01-15

To enrich the contents of digital archive and to guide the copy and restoration of colored relics, non-invasive methods for extraction of painting boundary and identification of pigment composition are proposed in this study based on the visible spectral images of colored relics. Superpixel concept is applied for the first time to the field of oversegmentation of visible spectral images and implemented on the visible spectral images of colored relics to extract their painting boundary. Since different pigments are characterized by their own spectrum and the same kind of pigment has the similar geometric profile in spectrum, an automatic identification method is established by comparing the proximity between the geometric profiles of the unknown spectrum from each superpixel and the pre-known spectrum from a deliberately prepared database. The methods are validated using the visible spectral images of the ancient wall paintings in Mogao Grottoes. By the way, the visible spectral images are captured by a multispectral imaging system consisting of two broadband filters and a RGB camera with high spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Model Predictive Control Based on System Re-Identification (MPC-SRI) to Control Bio-H2 Production from Biomass

NASA Astrophysics Data System (ADS)

Wahid, A.; Taqwallah, H. M. H.

2018-03-01

Compressors and a steam reformer are the important units in biohydrogen from biomass plant. The compressors are useful for achieving high-pressure operating conditions while the steam reformer is the main process to produce H2 gas. To control them, in this research used a model predictive control (MPC) expected to have better controller performance than conventional controllers. Because of the explicit model empowerment in MPC, obtaining a better model is the main objective before employing MPC. The common way to get the empirical model is through the identification system, so that obtained a first-order plus dead-time (FOPDT) model. This study has already improved that way since used the system re-identification (SRI) based on closed loop mode. Based on this method the results of the compressor pressure control and temperature control of steam reformer were that MPC based on system re-identification (MPC-SRI) has better performance than MPC without system re-identification (MPCWSRI) and the proportional-integral (PI) controller, by % improvement of 73% against MPCWSRI and 75% against the PI controller.

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

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2000-12-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2001-01-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

A multiplex PCR-based method for the detection and early identification of wood rotting fungi in standing trees.

PubMed

Guglielmo, F; Bergemann, S E; Gonthier, P; Nicolotti, G; Garbelotto, M

2007-11-01

The goal of this research was the development of a PCR-based assay to identify important decay fungi from wood of hardwood tree species in northern temperate regions. Eleven taxon-specific primers were designed for PCR amplification of either nuclear or mitochondrial ribosomal DNA regions of Armillaria spp., Ganoderma spp., Hericium spp., Hypoxylon thouarsianum var. thouarsianum, Inonotus/Phellinus-group, Laetiporus spp., Perenniporia fraxinea, Pleurotus spp., Schizophyllum spp., Stereum spp. and Trametes spp. Multiplex PCR reactions were developed and optimized to detect fungal DNA and identify each taxon with a sensitivity of at least 1 pg of target DNA in the template. This assay correctly identified the agents of decay in 82% of tested wood samples. The development and optimization of multiplex PCRs allowed for reliable identification of wood rotting fungi directly from wood. Early detection of wood decay fungi is crucial for assessment of tree stability in urban landscapes. Furthermore, this method may prove useful for prediction of the severity and the evolution of decay in standing trees.

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.

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.

Currently used methods for identification and characterization of hemichannels.

PubMed

Schalper, Kurt A; Palacios-Prado, Nicolás; Orellana, Juan A; Sáez, Juan C

2008-05-01

Connexins and pannexins are vertebrate transmembrane proteins that form hexameric conduits termed hemichannels. Functional hemichannels allow the diffusional transport of ions and small molecules across the plasma membrane and serve as paracrine and autocrine communication pathways. During the last decade, interest in the hemichannel field increased substantially. Today, there is evidence for the existence of connexin hemichannels in vertebrate cells and bulk of information supports their function in diverse physiological and pathological responses. Controversy regarding the molecular identity of the hemichannel type mediating many responses arose recently with the identification of pannexin-based hemichannels. Here, the authors describe the most frequently used methods for studying hemichannels in living mammalian cells and focus on those with which they have more experience. Although the available in vitro evidence is substantial, further studies and possibly new experimental approaches are required to understand the role and properties of connexin and pannexin hemichannels in vivo.

In Situ Identification of Pigment Composition and Particle Size on Wall Paintings Using Visible Spectroscopy as a Noninvasive Measurement Method.

PubMed

Li, Junfeng; Wan, Xiaoxia; Bu, Yajing; Li, Chan; Liang, Jinxing; Liu, Qiang

2016-11-01

Noninvasive examination methods of chemical composition and particle size are presented here based on visible spectroscopy to achieve the identification and recording of mineral pigments used on ancient wall paintings. The normalized spectral curve, slope and curvature extracted from visible spectral reflectance are combined with adjustable weighting coefficients to construct the identification feature space, and Euclid distances between spectral reflectance from wall paintings and a reference database are calculated in the feature space as the discriminant criterion to identify the chemical composition of mineral pigments. A parametric relationship between the integral quantity of spectral reflectance and logarithm of mean particle size is established using a quadratic polynomial to accomplish the noninvasive prediction of mineral pigment particle size used on ancient wall paintings. The feasibility of the proposed methods is validated by the in situ nondestructive identification of the wall paintings in the Mogao Grottoes at Dunhuang. Chinese painting styles and historical evolution are then analyzed according to the identification results of 16 different grottoes constructed from the Sixteen Kingdoms to the Yuan Dynasty. © The Author(s) 2016.

New support vector machine-based method for microRNA target prediction.

PubMed

Li, L; Gao, Q; Mao, X; Cao, Y

2014-06-09

MicroRNA (miRNA) plays important roles in cell differentiation, proliferation, growth, mobility, and apoptosis. An accurate list of precise target genes is necessary in order to fully understand the importance of miRNAs in animal development and disease. Several computational methods have been proposed for miRNA target-gene identification. However, these methods still have limitations with respect to their sensitivity and accuracy. Thus, we developed a new miRNA target-prediction method based on the support vector machine (SVM) model. The model supplies information of two binding sites (primary and secondary) for a radial basis function kernel as a similarity measure for SVM features. The information is categorized based on structural, thermodynamic, and sequence conservation. Using high-confidence datasets selected from public miRNA target databases, we obtained a human miRNA target SVM classifier model with high performance and provided an efficient tool for human miRNA target gene identification. Experiments have shown that our method is a reliable tool for miRNA target-gene prediction, and a successful application of an SVM classifier. Compared with other methods, the method proposed here improves the sensitivity and accuracy of miRNA prediction. Its performance can be further improved by providing more training examples.

PepPat, a pattern-based oligopeptide homology search method and the identification of a novel tachykinin-like peptide.

PubMed

Jiang, Ying; Gao, Ge; Fang, Gang; Gustafson, Eric L; Laverty, Maureen; Yin, Yanbin; Zhang, Yong; Luo, Jingchu; Greene, Jonathan R; Bayne, Marvin L; Hedrick, Joseph A; Murgolo, Nicholas J

2003-05-01

PepPat, a hybrid method that combines pattern matching with similarity scoring, is described. We also report PepPat's application in the identification of a novel tachykinin-like peptide. PepPat takes as input a query peptide and a user-specified regular expression pattern within the peptide. It first performs a database pattern match and then ranks candidates on the basis of their similarity to the query peptide. PepPat calculates similarity over the pattern spanning region, enhancing PepPat's sensitivity for short query peptides. PepPat can also search for a user-specified number of occurrences of a repeated pattern within the target sequence. We illustrate PepPat's application in short peptide ligand mining. As a validation example, we report the identification of a novel tachykinin-like peptide, C14TKL-1, and show it is an NK1 (neuokinin receptor 1) agonist whose message is widely expressed in human periphery. PepPat is offered online at: http://peppat.cbi.pku.edu.cn.

General Anisotropy Identification of Paperboard with Virtual Fields Method

Treesearch

J.M. Considine; F. Pierron; K.T. Turner; D.W. Vahey

2014-01-01

This work extends previous efforts in plate bending of Virtual Fields Method (VFM) parameter identification to include a general 2-D anisotropicmaterial. Such an extension was needed for instances in which material principal directions are unknown or when specimen orientation is not aligned with material principal directions. A new fixture with a multiaxial force...

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

NASA Technical Reports Server (NTRS)

1997-01-01

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

Dynamic biometric identification from multiple views using the GLBP-TOP method.

PubMed

Wang, Yu; Shen, Xuanjing; Chen, Haipeng; Zhai, Yujie

2014-01-01

To realize effective and rapid dynamic biometric identification with low computational complexity, a video-based facial texture program that extracts local binary patterns from three orthogonal planes in the frequency domain of the Gabor transform (GLBP-TOP) was proposed. Firstly, each normalized face was transformed by Gabor wavelet to get the enhanced Gabor magnitude map, and then the LBP-TOP operator was applied to the maps to extract video texture. Finally, weighted Chi square statistics based on the Fisher Criterion were used to realize the identification. The proposed algorithm was proved effective through the biometric experiments using the Honda/UCSD database, and was robust against changes of illumination and expressions.

A reference estimator based on composite sensor pattern noise for source device identification

NASA Astrophysics Data System (ADS)

Li, Ruizhe; Li, Chang-Tsun; Guan, Yu

2014-02-01

It has been proved that Sensor Pattern Noise (SPN) can serve as an imaging device fingerprint for source camera identification. Reference SPN estimation is a very important procedure within the framework of this application. Most previous works built reference SPN by averaging the SPNs extracted from 50 images of blue sky. However, this method can be problematic. Firstly, in practice we may face the problem of source camera identification in the absence of the imaging cameras and reference SPNs, which means only natural images with scene details are available for reference SPN estimation rather than blue sky images. It is challenging because the reference SPN can be severely contaminated by image content. Secondly, the number of available reference images sometimes is too few for existing methods to estimate a reliable reference SPN. In fact, existing methods lack consideration of the number of available reference images as they were designed for the datasets with abundant images to estimate the reference SPN. In order to deal with the aforementioned problem, in this work, a novel reference estimator is proposed. Experimental results show that our proposed method achieves better performance than the methods based on the averaged reference SPN, especially when few reference images used.

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

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Distribution of different yeasts isolates among trauma patients and comparison of accuracy in identification of yeasts by automated method versus conventional methods for better use in low resource countries.

PubMed

Rajkumari, N; Mathur, P; Xess, I; Misra, M C

2014-01-01

As most trauma patients require long-term hospital stay and long-term antibiotic therapy, the risk of fungal infections in such patients is steadily increasing. Early diagnosis and rapid treatment is life saving in such critically ill trauma patients. To see the distribution of various species of Candida among trauma patients and compare the accuracy, rapid identification and cost effectiveness between VITEK 2, CHROMagar and conventional methods. Retrospective laboratory-based surveillance study performed over a period of 52 months (January 2009 to April 2013) at a level I trauma centre in New Delhi, India. All microbiological samples positive for Candida were processed for microbial identification using standard methods. Identification of Candida was done using chromogenic medium and by automated VITEK 2 Compact system and later confirmed using the conventional method. Time to identification in both was noted and accuracy compared with conventional method. Performed using the SPSS software for Windows (SPSS Inc. Chicago, IL, version 15.0). P values calculated using χ2 test for categorical variables. A P<0.05 was considered significant. Out of 445 yeasts isolates, Candida tropicalis (217, 49%) was the species that was maximally isolated. VITEK 2 was able to correctly identify 354 (79.5%) isolates but could not identify 48 (10.7%) isolates and wrongly identified or showed low discrimination in 43 (9.6%) isolates but CHROM agar correctly identified 381 (85.6%) isolates with 64 (14.4%) misidentification. Highest rate of misidentification was seen in C. tropicalis and C. glabrata (13, 27.1% each) by VITEK 2 and among C. albicans (9, 14%) by CHROMagar. Though CHROMagar gives identification at a lower cost compared with VITEK 2 and are more accurate, which is useful in low resource countries, its main drawback is the long duration taken for complete identification.

Identification of Anisotropic Criteria for Stratified Soil Based on Triaxial Tests Results

NASA Astrophysics Data System (ADS)

Tankiewicz, Matylda; Kawa, Marek

2017-09-01

The paper presents the identification methodology of anisotropic criteria based on triaxial test results. The considered material is varved clay - a sedimentary soil occurring in central Poland which is characterized by the so-called "layered microstructure". The strength examination outcomes were identified by standard triaxial tests. The results include the estimated peak strength obtained for a wide range of orientations and confining pressures. Two models were chosen as potentially adequate for the description of the tested material, namely Pariseau and its conjunction with the Jaeger weakness plane. Material constants were obtained by fitting the model to the experimental results. The identification procedure is based on the least squares method. The optimal values of parameters are searched for between specified bounds by sequentially decreasing the distance between points and reducing the length of the searched range. For both considered models the optimal parameters have been obtained. The comparison of theoretical and experimental results as well as the assessment of the suitability of selected criteria for the specified range of confining pressures are presented.

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

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

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1987-10-07

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1990-10-09

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, James H.; Keller, Richard A.; Martin, John C.; Moyzis, Robert K.; Ratliff, Robert L.; Shera, E. Brooks; Stewart, Carleton C.

1990-01-01

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed.

Personal identification by eyes.

PubMed

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

2011-09-01

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

Multiscale global identification of porous structures

NASA Astrophysics Data System (ADS)

Hatłas, Marcin; Beluch, Witold

2018-01-01

The paper is devoted to the evolutionary identification of the material constants of porous structures based on measurements conducted on a macro scale. Numerical homogenization with the RVE concept is used to determine the equivalent properties of a macroscopically homogeneous material. Finite element method software is applied to solve the boundary-value problem in both scales. Global optimization methods in form of evolutionary algorithm are employed to solve the identification task. Modal analysis is performed to collect the data necessary for the identification. A numerical example presenting the effectiveness of proposed attitude is attached.

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2010-01-01

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

[Study on TLC identification and UPLC determination method of atractylenolide in Atractylodes macrocephala].

PubMed

Zhao, Yu-Jiao; Xu, Wen-Hui; Shen, Xiao-Li; Tian, Jun-Sheng; Qin, Xue-Mei

2017-02-01

This research is to establish TLC and UPLC methods for simultaneous determination of 3 atractylenolides in Atractylodes macrocephala. Silica gel GF254 plate was used for identification of A. macrocephala, and UPLC-PDA gradient elution method was used to simultaneously determine atractylenolide Ⅰ, Ⅱ and Ⅲ. The Waters BEH C₁₈ column（2.1 mm×100 mm,1.7 μm）with acetonitrile-water as mobile phase and the wavelength of UV detector of 235 nm were performed. The quality control study showed that the characteristic for identification by TLC was distinct and highly specific. The method of content determination was in accordance with the regulations. The quantitative evaluation of atractylenolide Ⅰ,Ⅱ and Ⅲ was in good linear range（r>0.999 9）, and the average recovery was 93.48%（RSD 1.4%）,94.97%（RSD 1.6%）,92.71%（RSD 1.2%）,respectively. TLC identification was in good specificity and repeatability, and the UPLC-PDA method for the simultaneous determination of 3 atractylenolides was simple and reliable for the quality control of A.macrocephala. Copyright© by the Chinese Pharmaceutical Association.

Molecular identification of coliform bacteria isolated from drinking water reservoirs with traditional methods and the Colilert-18 system.

PubMed

Kämpfer, Peter; Nienhüser, Anita; Packroff, Gabriele; Wernicke, Frank; Mehling, Arnd; Nixdorf, Katja; Fiedler, Stefanie; Kolauch, Claudia; Esser, Michael

2008-07-01

The accuracy of a traditional method (lactose utilization with acid and gas production) for the detection of coliform bacteria and E. coli was tested in comparison with method ISO 9308-1 (based on acid formation from lactose) and the Colilert-18 system (detection of beta-galactosidase). A total of 345 isolates were identified after isolation from water samples using API 20E strips. The Colilert-18 led to the highest number of positive findings (95% of the isolates were assigned to coliforms), whereas the ISO-9308-1 method resulted only in 29% coliform findings. With the traditional method only 15% were rated positive. Most of the isolates were identified by the API 20E system as Enterobacter spp. (species of the Enterobacter cloacae complex), Serratia spp., Citrobacter spp.and Klebsiella spp.; but species identification remained vague in several cases. A more detailed identification of 126 pure cultures by using 16S rRNA gene sequence analysis and analysis of the hsp60 gene resulted in the identification of Enterobacter nimipressuralis, E. amnigenus, E. asburiae, E. hormaechei, and Serratia fonticola as predominat coliforms. These species are beta-galactosidase positive, but show acid formation from lactose often after a prolonged incubation time. They are often not of fecal origin and may interfere with the ability to accurately detect coliforms of fecal origin.

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

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

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

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

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

NASA Astrophysics Data System (ADS)

Mao, Dachao; Yang, Wenlong; Du, Zhijiang

2017-06-01

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

Streptococcus iniae, a Human and Animal Pathogen: Specific Identification by the Chaperonin 60 Gene Identification Method

PubMed Central

Goh, Swee Han; Driedger, David; Gillett, Sandra; Low, Donald E.; Hemmingsen, Sean M.; Amos, Mayben; Chan, David; Lovgren, Marguerite; Willey, Barbara M.; Shaw, Carol; Smith, John A.

1998-01-01

It was recently reported that Streptococcus iniae, a bacterial pathogen of aquatic animals, can cause serious disease in humans. Using the chaperonin 60 (Cpn60) gene identification method with reverse checkerboard hybridization and chemiluminescent detection, we identified correctly each of 12 S. iniae samples among 34 aerobic gram-positive isolates from animal and clinical human sources. PMID:9650992

Development of a rapid diagnostic method for identification of Staphylococcus aureus and antimicrobial resistance in positive blood culture bottles using a PCR-DNA-chromatography method.

PubMed

Ohshiro, Takeya; Miyagi, Chihiro; Tamaki, Yoshikazu; Mizuno, Takuya; Ezaki, Takayuki

2016-06-01

Blood culturing and the rapid reporting of results are essential for infectious disease clinics to obtain bacterial information that can affect patient prognosis. When gram-positive coccoid cells are observed in blood culture bottles, it is important to determine whether the strain is Staphylococcus aureus and whether the strain has resistance genes, such as mecA and blaZ, for proper antibiotic selection. Previous work led to the development of a PCR method that is useful for rapid identification of bacterial species and antimicrobial susceptibility. However, that method has not yet been adopted in community hospitals due to the high cost and methodological complexity. We report here the development of a quick PCR and DNA-chromatography test, based on single-tag hybridization chromatography, that permits detection of S. aureus and the mecA and blaZ genes; results can be obtained within 1 h for positive blood culture bottles. We evaluated this method using 42 clinical isolates. Detection of S. aureus and the resistance genes by the PCR-DNA-chromatography method was compared with that obtained via the conventional identification method and actual antimicrobial susceptibility testing. Our method had a sensitivity of 97.0% and a specificity of 100% for the identification of the bacterial species. For the detection of the mecA gene of S. aureus, the sensitivity was 100% and the specificity was 95.2%. For the detection of the blaZ gene of S. aureus, the sensitivity was 100% and the specificity was 88.9%. The speed and simplicity of this PCR-DNA-chromatography method suggest that our method will facilitate rapid diagnoses. Copyright © 2016 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Research on Damage Identification of Bridge Based on Digital Image Measurement

NASA Astrophysics Data System (ADS)

Liang, Yingjing; Huan, Shi; Tao, Weijun

2017-12-01

In recent years, the number of the damage bridge due to excessive deformation gradually increased, which caused significant property damage and casualties. Hence health monitoring and the damage detection of the bridge structure based on the deflection measurement are particularly important. The current conventional deflection measurement methods, such as total station, connected pipe, GPS, etc., have many shortcomings as low efficiency, heavy workload, low degree of automation, operating frequency and working time constrained. GPS has a low accuracy in the vertical displacement measurement and cannot meet the dynamic measured requirements of the current bridge engineering. This paper presents a bridge health monitoring and damage detection technology based on digital image measurement method in which the measurement accuracy is sub-millimeter level and can achieve the 24-hour automatic non-destructive monitoring for the deflection. It can be concluded from this paper that it is feasible to use digital image measurement method for identification of the damage in the bridge structure, because it has been validated by the theoretical analysis, the laboratory model and the application of the real bridge.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Utility of a novel error-stepping method to improve gradient-based parameter identification by increasing the smoothness of the local objective surface: a case-study of pulmonary mechanics.

PubMed

Docherty, Paul D; Schranz, Christoph; Chase, J Geoffrey; Chiew, Yeong Shiong; Möller, Knut

2014-05-01

Accurate model parameter identification relies on accurate forward model simulations to guide convergence. However, some forward simulation methodologies lack the precision required to properly define the local objective surface and can cause failed parameter identification. The role of objective surface smoothness in identification of a pulmonary mechanics model was assessed using forward simulation from a novel error-stepping method and a proprietary Runge-Kutta method. The objective surfaces were compared via the identified parameter discrepancy generated in a Monte Carlo simulation and the local smoothness of the objective surfaces they generate. The error-stepping method generated significantly smoother error surfaces in each of the cases tested (p<0.0001) and more accurate model parameter estimates than the Runge-Kutta method in three of the four cases tested (p<0.0001) despite a 75% reduction in computational cost. Of note, parameter discrepancy in most cases was limited to a particular oblique plane, indicating a non-intuitive multi-parameter trade-off was occurring. The error-stepping method consistently improved or equalled the outcomes of the Runge-Kutta time-integration method for forward simulations of the pulmonary mechanics model. This study indicates that accurate parameter identification relies on accurate definition of the local objective function, and that parameter trade-off can occur on oblique planes resulting prematurely halted parameter convergence. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The use of a calculus-based cyclone identification method for generating storm statistics

NASA Astrophysics Data System (ADS)

Benestad, R. E.; Chen, D.

2006-08-01

Maps of 12 hr sea-level pressure (SLP) from the former National Meteotrological Center (NMC) and 24 hr SLP maps from the European Centre for Medium-range Weather Forecasts (ECMWF) 40 yr re-analysis (ERA40) were used to identify extratropical cyclones in the North Atlantic region. A calculus-based cyclone identification (CCI) method is introduced and evaluated, where a multiple regression against a truncated series of sinusoids was used to obtain a Fourier approximation of the north-south and east-west SLP profiles, providing a basis for analytical expressions of the derivatives. Local SLP minima were found from the zero-crossing points of the first-order derivatives for the SLP gradients where the second-order derivatives were greater than zero. Evaluation of cyclone counts indicates a good correspondence with storm track maps and independent monthly large-scale SLP anomalies. The results derived from ERA40 also revealed that the central storm pressure sometimes could be extremely deep in the re-analysis product, and it is not clear whether such outliers are truly representative of the actual events. The position and the depth of the cyclones were subjects for a study of long-term trends in cyclone number for various regions around the North Atlantic. Noting that the re-analyses may contain time-dependent biases due to changes in the observing practises, a tentative positive linear trend, statistically significant at the 10% level, was found in the number of intense storms over the Nordic countries over the period 1955-1994 in both the NMC and the ERA40 data. However, there was no significant trend in the western parts of the North Atlantic where trend analysis derived from NMC and ERA40 yielded different results. The choice of data set had a stronger influence on the results than choices such as the number of harmonics to include or spatial resolution of interpolation.

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

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.

Bearing faults identification and resonant band demodulation based on wavelet de-noising methods and envelope analysis

NASA Astrophysics Data System (ADS)

Abdelrhman, Ahmed M.; Sei Kien, Yong; Salman Leong, M.; Meng Hee, Lim; Al-Obaidi, Salah M. Ali

2017-07-01

The vibration signals produced by rotating machinery contain useful information for condition monitoring and fault diagnosis. Fault severities assessment is a challenging task. Wavelet Transform (WT) as a multivariate analysis tool is able to compromise between the time and frequency information in the signals and served as a de-noising method. The CWT scaling function gives different resolutions to the discretely signals such as very fine resolution at lower scale but coarser resolution at a higher scale. However, the computational cost increased as it needs to produce different signal resolutions. DWT has better low computation cost as the dilation function allowed the signals to be decomposed through a tree of low and high pass filters and no further analysing the high-frequency components. In this paper, a method for bearing faults identification is presented by combing Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) with envelope analysis for bearing fault diagnosis. The experimental data was sampled by Case Western Reserve University. The analysis result showed that the proposed method is effective in bearing faults detection, identify the exact fault’s location and severity assessment especially for the inner race and outer race faults.

Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network.

PubMed

Jiang, Xue; Zhang, Han; Quan, Xiongwen

2016-01-01

Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets.

Patterns of Cognitive Strengths and Weaknesses: Identification Rates, Agreement, and Validity for Learning Disabilities Identification

ERIC Educational Resources Information Center

Miciak, Jeremy; Fletcher, Jack M.; Stuebing, Karla K.; Vaughn, Sharon; Tolar, Tammy D.

2014-01-01

Few empirical investigations have evaluated learning disabilities (LD) identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability and validity of two proposed PSW methods: the concordance/discordance method (C/DM) and cross battery assessment (XBA) method. Cognitive assessment…

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.

[Comparison of different methods for the identification of Candida species isolated from clinical specimens].

PubMed

Cetinkaya, Zafer; Altindiş, Mustafa; Aktepe, Orhan Cem; Karabiçak, Nilgün

2003-10-01

The aim of this study was to compare the different methods for the identification of Candida strains isolated from clinical specimens. The methods of germ tube examination, chlamydospore examination formed on the rice Tween-80 (RT-80) agar and evaluation of colony morphologies on the two chromogenic agars (CHROMagar Candida, Albicans ID), were compared with a reference API 20C AUX (bioMerieux, France) automated system based on the carbohydrate assimilation, for the identification of a total 255 Candida isolates. Of them, 173 (67.8%) were identified as C. albicans, 37 (14.5%) were C. glabrata, 23 (9%) were C. krusei, 9 (3.5%) were C. tropicalis, 9 (3.5%) were C. kefyr, 2 (0.8%) were C. guillermondii and 2 (0.8%) were C. parapsilosis, by API 20C AUX system. In the view of these results, 146 (84.4%) of C. albicans strains were identified by germ tube examination, 161 (93.1%) of C. albicans strains and 208 (81.5%) of total strains were identified by chlamydospore examination. 169 (97.7%) of C. albicans strains and 231 (90.6%) of total strains were identified by CHROMagar Candida method, and 168 (97.1%) of C. albicans strains were identified by Albicans ID method, correctly. In the CHROMagar Candida medium, 169 C. albicans isolates have produced bright green colored colonies, whereas 33 (89.2%) isolates which produced dark pink/purple colored colonies were identified as C. glabrata, 7 (77.8%) isolates which produced metalical blue colored colonies were identified as C. tropicalis and 22 (95.6%) isolates which produced pale pink colored colonies were identified as C. krusei. In the Albicans ID medium, four of the 172 isolates which were evaluated as C. albicans initially by producing blue colored colonies, have been identified as C. tropicalis by API 20C AUX system. The sensitivities and specificities of germ tube examination, RT-80, CHROMagar Candida and Albicans ID methods were found as follows, respectively; 84.4% and 100%, 93.1% and 100%, 97.7% and 100%, 99.4% and 95

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.

Fast Fourier-based deconvolution for three-dimensional acoustic source identification with solid spherical arrays

NASA Astrophysics Data System (ADS)

Yang, Yang; Chu, Zhigang; Shen, Linbang; Ping, Guoli; Xu, Zhongming

2018-07-01

Being capable of demystifying the acoustic source identification result fast, Fourier-based deconvolution has been studied and applied widely for the delay and sum (DAS) beamforming with two-dimensional (2D) planar arrays. It is, however so far, still blank in the context of spherical harmonics beamforming (SHB) with three-dimensional (3D) solid spherical arrays. This paper is motivated to settle this problem. Firstly, for the purpose of determining the effective identification region, the premise of deconvolution, a shift-invariant point spread function (PSF), is analyzed with simulations. To make the premise be satisfied approximately, the opening angle in elevation dimension of the surface of interest should be small, while no restriction is imposed to the azimuth dimension. Then, two kinds of deconvolution theories are built for SHB using the zero and the periodic boundary conditions respectively. Both simulations and experiments demonstrate that the periodic boundary condition is superior to the zero one, and fits the 3D acoustic source identification with solid spherical arrays better. Finally, four periodic boundary condition based deconvolution methods are formulated, and their performance is disclosed both with simulations and experimentally. All the four methods offer enhanced spatial resolution and reduced sidelobe contaminations over SHB. The recovered source strength approximates to the exact one multiplied with a coefficient that is the square of the focus distance divided by the distance from the source to the array center, while the recovered pressure contribution is scarcely affected by the focus distance, always approximating to the exact one.

Rapid label-free identification of Klebsiella pneumoniae antibiotic resistant strains by the drop-coating deposition surface-enhanced Raman scattering method

NASA Astrophysics Data System (ADS)

Cheong, Youjin; Kim, Young Jin; Kang, Heeyoon; Choi, Samjin; Lee, Hee Joo

2017-08-01

Although many methodologies have been developed to identify unknown bacteria, bacterial identification in clinical microbiology remains a complex and time-consuming procedure. To address this problem, we developed a label-free method for rapidly identifying clinically relevant multilocus sequencing typing-verified quinolone-resistant Klebsiella pneumoniae strains. We also applied the method to identify three strains from colony samples, ATCC70063 (control), ST11 and ST15; these are the prevalent quinolone-resistant K. pneumoniae strains in East Asia. The colonies were identified using a drop-coating deposition surface-enhanced Raman scattering (DCD-SERS) procedure coupled with a multivariate statistical method. Our workflow exhibited an enhancement factor of 11.3 × 106 to Raman intensities, high reproducibility (relative standard deviation of 7.4%), and a sensitive limit of detection (100 pM rhodamine 6G), with a correlation coefficient of 0.98. All quinolone-resistant K. pneumoniae strains showed similar spectral Raman shifts (high correlations) regardless of bacterial type, as well as different Raman vibrational modes compared to Escherichia coli strains. Our proposed DCD-SERS procedure coupled with the multivariate statistics-based identification method achieved excellent performance in discriminating similar microbes from one another and also in subtyping of K. pneumoniae strains. Therefore, our label-free DCD-SERS procedure coupled with the computational decision supporting method is a potentially useful method for the rapid identification of clinically relevant K. pneumoniae strains.

A multiplex PCR method for the identification of commercially important salmon and trout species (Oncorhynchus and Salmo) in North America.

PubMed

Rasmussen Hellberg, Rosalee S; Morrissey, Michael T; Hanner, Robert H

2010-09-01

The purpose of this study was to develop a species-specific multiplex polymerase chain reaction (PCR) method that allows for the detection of salmon species substitution on the commercial market. Species-specific primers and TaqMan® probes were developed based on a comprehensive collection of mitochondrial 5' cytochrome c oxidase subunit I (COI) deoxyribonucleic acid (DNA) "barcode" sequences. Primers and probes were combined into multiplex assays and tested for specificity against 112 reference samples representing 25 species. Sensitivity and linearity tests were conducted using 10-fold serial dilutions of target DNA (single-species samples) and DNA admixtures containing the target species at levels of 10%, 1.0%, and 0.1% mixed with a secondary species. The specificity tests showed positive signals for the target DNA in both real-time and conventional PCR systems. Nonspecific amplification in both systems was minimal; however, false positives were detected at low levels (1.2% to 8.3%) in conventional PCR. Detection levels were similar for admixtures and single-species samples based on a 30 PCR cycle cut-off, with limits of 0.25 to 2.5 ng (1% to 10%) in conventional PCR and 0.05 to 5.0 ng (0.1% to 10%) in real-time PCR. A small-scale test with food samples showed promising results, with species identification possible even in heavily processed food items. Overall, this study presents a rapid, specific, and sensitive method for salmon species identification that can be applied to mixed-species and heavily processed samples in either conventional or real-time PCR formats. This study provides a newly developed method for salmon and trout species identification that will assist both industry and regulatory agencies in the detection and prevention of species substitution. This multiplex PCR method allows for rapid, high-throughput species identification even in heavily processed and mixed-species samples. An inter-laboratory study is currently being carried out to

Comparison of a rapid micromedia method to cystine trypticase agar (CTA) and fluorescent methods for the identification of pathogenic Neisseria.

PubMed

Brake, S R; Marsik, F J; Rein, M R

1982-01-01

A four-hour micromedia method which detects enzymes formed by bacteria for the degradion of carbohydrates was compared to the utilization of carbohydrates was compared to the utilization of carbohydrates in cystine tyrpticase agar (CTA) for the identification of Neisseria gonorrhoeae and Neisseria meningitidis. This rapid micromedia method (RMM) correlated 100% with the utilization of carbohydrates in CTA. Identification of N. gonorrhoeae by RMM was compared to the identification achieved by a commercially available coagglutination method and a fluorescent antibody (FA) technique. Of 144 isolates identified as N. gonorrhoeae by RMM, 122 (84.7%) were identified by coagglutination and 141 (97.9%) were identified by FA as N. gonorrhoeae. Five (13%) of 40 isolates identified as N. meningitidis by RMM were identified as N. gonorrhoeae by coagglutination while eleven (28%) were identified as N. gonorrhoeae by the FA technique. One (14%) and four (57%) of seven isolates identified as Neisseria species were identified as N. gonorrhoeae by coagglutination and the FA technique respectively. The rapid micromedia method was found to be a quick, sensitive, specific and economic way of identifying N. gonorrhoeae and N. meningitidis.

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

PubMed

da Silva, Núbia Rosa; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

2015-01-01

The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

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.

Identification of Cronobacter species by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with an optimized analysis method.

PubMed

Wang, Qi; Zhao, Xiao-Juan; Wang, Zi-Wei; Liu, Li; Wei, Yong-Xin; Han, Xiao; Zeng, Jing; Liao, Wan-Jin

2017-08-01

Rapid and precise identification of Cronobacter species is important for foodborne pathogen detection, however, commercial biochemical methods can only identify Cronobacter strains to genus level in most cases. To evaluate the power of mass spectrometry based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF MS) for Cronobacter species identification, 51 Cronobacter strains (eight reference and 43 wild strains) were identified by both MALDI-TOF MS and 16S rRNA gene sequencing. Biotyper RTC provided by Bruker identified all eight reference and 43 wild strains as Cronobacter species, which demonstrated the power of MALDI-TOF MS to identify Cronobacter strains to genus level. However, using the Bruker's database (6903 main spectra products) and Biotyper software, the MALDI-TOF MS analysis could not identify the investigated strains to species level. When MALDI-TOF MS analysis was performed using the combined in-house Cronobacter database and Bruker's database, bin setting, and unweighted pair group method with arithmetic mean (UPGMA) clustering, all the 51 strains were clearly identified into six Cronobacter species and the identification accuracy increased from 60% to 100%. We demonstrated that MALDI-TOF MS was reliable and easy-to-use for Cronobacter species identification and highlighted the importance of establishing a reliable database and improving the current data analysis methods by integrating the bin setting and UPGMA clustering. Copyright © 2017. Published by Elsevier B.V.

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.

Improved method for rapid and accurate isolation and identification of Streptococcus mutans and Streptococcus sobrinus from human plaque samples.

PubMed

Villhauer, Alissa L; Lynch, David J; Drake, David R

2017-08-01

Mutans streptococci (MS), specifically Streptococcus mutans (SM) and Streptococcus sobrinus (SS), are bacterial species frequently targeted for investigation due to their role in the etiology of dental caries. Differentiation of S. mutans and S. sobrinus is an essential part of exploring the role of these organisms in disease progression and the impact of the presence of either/both on a subject's caries experience. Of vital importance to the study of these organisms is an identification protocol that allows us to distinguish between the two species in an easy, accurate, and timely manner. While conducting a 5-year birth cohort study in a Northern Plains American Indian tribe, the need for a more rapid procedure for isolating and identifying high volumes of MS was recognized. We report here on the development of an accurate and rapid method for MS identification. Accuracy, ease of use, and material and time requirements for morphological differentiation on selective agar, biochemical tests, and various combinations of PCR primers were compared. The final protocol included preliminary identification based on colony morphology followed by PCR confirmation of species identification using primers targeting regions of the glucosyltransferase (gtf) genes of SM and SS. This method of isolation and identification was found to be highly accurate, more rapid than the previous methodology used, and easily learned. It resulted in more efficient use of both time and material resources. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

PubMed

Cui, Peng; Zhong, Tingyan; Wang, Zhuo; Wang, Tao; Zhao, Hongyu; Liu, Chenglin; Lu, Hui

2018-06-01

Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological

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.

Atlas-based identification of targets for functional radiosurgery

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

Stancanello, Joseph; Romanelli, Pantaleo; Modugno, Nicola

2006-06-15

Functional disorders of the brain, such as Parkinson's disease, dystonia, epilepsy, and neuropathic pain, may exhibit poor response to medical therapy. In such cases, surgical intervention may become necessary. Modern surgical approaches to such disorders include radio-frequency lesioning and deep brain stimulation (DBS). The subthalamic nucleus (STN) is one of the most useful stereotactic targets available: STN DBS is known to induce substantial improvement in patients with end-stage Parkinson's disease. Other targets include the Globus Pallidus pars interna (GPi) for dystonia and Parkinson's disease, and the centromedian nucleus of the thalamus (CMN) for neuropathic pain. Radiosurgery is an attractive noninvasivemore » alternative to treat some functional brain disorders. The main technical limitation to radiosurgery is that the target can be selected only on the basis of magnetic resonance anatomy without electrophysiological confirmation. The aim of this work is to provide a method for the correct atlas-based identification of the target to be used in functional neurosurgery treatment planning. The coordinates of STN, CMN, and GPi were identified in the Talairach and Tournoux atlas and transformed to the corresponding regions of the Montreal Neurological Institute (MNI) electronic atlas. Binary masks describing the target nuclei were created. The MNI electronic atlas was deformed onto the patient magnetic resonance imaging-T1 scan by applying an affine transformation followed by a local nonrigid registration. The first transformation was based on normalized cross correlation and the second on optimization of a two-part objective function consisting of similarity criteria and weighted regularization. The obtained deformation field was then applied to the target masks. The minimum distance between the surface of an implanted electrode and the surface of the deformed mask was calculated. The validation of the method consisted of comparing the electrode

Mass spectrometry-based protein identification with accurate statistical significance assignment.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2015-03-01

Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging. We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested. 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. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

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.

Simple Sample Preparation Method for Direct Microbial Identification and Susceptibility Testing From Positive Blood Cultures.

PubMed

Pan, Hong-Wei; Li, Wei; Li, Rong-Guo; Li, Yong; Zhang, Yi; Sun, En-Hua

2018-01-01

Rapid identification and determination of the antibiotic susceptibility profiles of the infectious agents in patients with bloodstream infections are critical steps in choosing an effective targeted antibiotic for treatment. However, there has been minimal effort focused on developing combined methods for the simultaneous direct identification and antibiotic susceptibility determination of bacteria in positive blood cultures. In this study, we constructed a lysis-centrifugation-wash procedure to prepare a bacterial pellet from positive blood cultures, which can be used directly for identification by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) and antibiotic susceptibility testing by the Vitek 2 system. The method was evaluated using a total of 129 clinical bacteria-positive blood cultures. The whole sample preparation process could be completed in <15 min. The correct rate of direct MALDI-TOF MS identification was 96.49% for gram-negative bacteria and 97.22% for gram-positive bacteria. Vitek 2 antimicrobial susceptibility testing of gram-negative bacteria showed an agreement rate of antimicrobial categories of 96.89% with a minor error, major error, and very major error rate of 2.63, 0.24, and 0.24%, respectively. Category agreement of antimicrobials against gram-positive bacteria was 92.81%, with a minor error, major error, and very major error rate of 4.51, 1.22, and 1.46%, respectively. These results indicated that our direct antibiotic susceptibility analysis method worked well compared to the conventional culture-dependent laboratory method. Overall, this fast, easy, and accurate method can facilitate the direct identification and antibiotic susceptibility testing of bacteria in positive blood cultures.

Simulation of LD Identification Accuracy Using a Pattern of Processing Strengths and Weaknesses Method with Multiple Measures

ERIC Educational Resources Information Center

Miciak, Jeremy; Taylor, W. Pat; Stuebing, Karla K.; Fletcher, Jack M.

2018-01-01

We investigated the classification accuracy of learning disability (LD) identification methods premised on the identification of an intraindividual pattern of processing strengths and weaknesses (PSW) method using multiple indicators for all latent constructs. Known LD status was derived from latent scores; values at the observed level identified…

Scene-based method for spatial misregistration detection in hyperspectral imagery.

PubMed

Dell'Endice, Francesco; Nieke, Jens; Schläpfer, Daniel; Itten, Klaus I

2007-05-20

Hyperspectral imaging (HSI) sensors suffer from spatial misregistration, an artifact that prevents the accurate acquisition of the spectra. Physical considerations let us assume that the influence of the spatial misregistration on the acquired data depends both on the wavelength and on the across-track position. A scene-based method, based on edge detection, is therefore proposed. Such a procedure measures the variation on the spatial location of an edge between its various monochromatic projections, giving an estimation for spatial misregistration, and also allowing identification of misalignments. The method has been applied to several hyperspectral sensors, either prism, or grating-based designs. The results confirm the dependence assumptions on lambda and theta, spectral wavelength and across-track pixel, respectively. Suggestions are also given to correct for spatial misregistration.

The efficacy of obtaining genetic-based identifications from putative wolverine snow tracks

Treesearch

Todd J. Ulizio; John R. Squires; Daniel H. Pletscher; Michael K. Schwartz; James J. Claar; Leonard F. Ruggiero

2006-01-01

Snow-track surveys to detect rare carnivores require unequivocal species identification because of management and political ramifications associated with the presence of such species. Collecting noninvasive genetic samples from putative wolverine (Gulo gulo) snow tracks is an effective method for providing definitive species identification for use in presence-...

Grid-based Molecular Footprint Comparison Method for Docking and De Novo Design: Application to HIVgp41

PubMed Central

Mukherjee, Sudipto; Rizzo, Robert C.

2014-01-01

Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multi-grid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method will be made available in the program DOCK6. PMID:23436713

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).

A single-laboratory validated method for the generation of DNA barcodes for the identification of fish for regulatory compliance.

PubMed

Handy, Sara M; Deeds, Jonathan R; Ivanova, Natalia V; Hebert, Paul D N; Hanner, Robert H; Ormos, Andrea; Weigt, Lee A; Moore, Michelle M; Yancy, Haile F

2011-01-01

The U.S. Food and Drug Administration is responsible for ensuring that the nation's food supply is safe and accurately labeled. This task is particularly challenging in the case of seafood where a large variety of species are marketed, most of this commodity is imported, and processed product is difficult to identify using traditional morphological methods. Reliable species identification is critical for both foodborne illness investigations and for prevention of deceptive practices, such as those where species are intentionally mislabeled to circumvent import restrictions or for resale as species of higher value. New methods that allow accurate and rapid species identifications are needed, but any new methods to be used for regulatory compliance must be both standardized and adequately validated. "DNA barcoding" is a process by which species discriminations are achieved through the use of short, standardized gene fragments. For animals, a fragment (655 base pairs starting near the 5' end) of the cytochrome c oxidase subunit 1 mitochondrial gene has been shown to provide reliable species level discrimination in most cases. We provide here a protocol with single-laboratory validation for the generation of DNA barcodes suitable for the identification of seafood products, specifically fish, in a manner that is suitable for FDA regulatory use.

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 .

Adaptive Modal Identification for Flutter Suppression Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

2016-01-01

In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

Fluid identification based on P-wave anisotropy dispersion gradient inversion for fractured reservoirs

NASA Astrophysics Data System (ADS)

Zhang, J. W.; Huang, H. D.; Zhu, B. H.; Liao, W.

2017-10-01

Fluid identification in fractured reservoirs is a challenging issue and has drawn increasing attentions. As aligned fractures in subsurface formations can induce anisotropy, we must choose parameters independent with azimuths to characterize fractures and fluid effects such as anisotropy parameters for fractured reservoirs. Anisotropy is often frequency dependent due to wave-induced fluid flow between pores and fractures. This property is conducive for identifying fluid type using azimuthal seismic data in fractured reservoirs. Through the numerical simulation based on Chapman model, we choose the P-wave anisotropy parameter dispersion gradient (PADG) as the new fluid factor. PADG is dependent both on average fracture radius and fluid type but independent on azimuths. When the aligned fractures in the reservoir are meter-scaled, gas-bearing layer could be accurately identified using PADG attribute. The reflection coefficient formula for horizontal transverse isotropy media by Rüger is reformulated and simplified according to frequency and the target function for inverting PADG based on frequency-dependent amplitude versus azimuth is derived. A spectral decomposition method combining Orthogonal Matching Pursuit and Wigner-Ville distribution is used to prepare the frequency-division data. Through application to synthetic data and real seismic data, the results suggest that the method is useful for gas identification in reservoirs with meter-scaled fractures using high-qualified seismic data.

A novel method for simultaneous Enterococcus species identification/typing and van genotyping by high resolution melt analysis.

PubMed

Gurtler, Volker; Grando, Danilla; Mayall, Barrie C; Wang, Jenny; Ghaly-Derias, Shahbano

2012-09-01

In order to develop a typing and identification method for van gene containing Enterococcus faecium, two multiplex PCR reactions were developed for use in HRM-PCR (High Resolution Melt-PCR): (i) vanA, vanB, vanC, vanC23 to detect van genes from different Enterococcus species; (ii) ISR (intergenic spacer region between the 16S and 23S rRNA genes) to detect all Enterococcus species and obtain species and isolate specific HRM curves. To test and validate the method three groups of isolates were tested: (i) 1672 Enterococcus species isolates from January 2009 to December 2009; (ii) 71 isolates previously identified and typed by PFGE (pulsed-field gel electrophoresis) and MLST (multi-locus sequence typing); and (iii) 18 of the isolates from (i) for which ISR sequencing was done. As well as successfully identifying 2 common genotypes by HRM from the Austin Hospital clinical isolates, this study analysed the sequences of all the vanB genes deposited in GenBank and developed a numerical classification scheme for the standardised naming of these vanB genotypes. The identification of Enterococcus faecalis from E. faecium was reliable and stable using ISR PCR. The typing of E. faecium by ISR PCR: (i) detected two variable peaks corresponding to different copy numbers of insertion sequences I and II corresponding to peak I and II respectively; (ii) produced 7 melt profiles for E. faecium with variable copy numbers of sequences I and II; (iii) demonstrated stability and instability of peak heights with equal frequency within the patient sample (36.4±4.5 days and 38.6±5.8 days respectively for 192 patients); (iv) detected ISR-HRM types with as much discrimination as PFGE and more than MLST; and (v) detected ISR-HRM types that differentiated some isolates that were identical by PFGE and MLST. In conjunction with the rapid and accurate van genotyping method described here, this ISR-HRM typing and identification method can be used as a stable identification and typing method with

Vibro-Acoustic Modulation Based Damage Identification in a Composite Skin-Stiffener Structure

NASA Technical Reports Server (NTRS)

Ooijevaar, T. H.; Loendersloot, R.; Rogge, M. D.; Akkerman, R.; Tinga, T.

2014-01-01

The vibro-acoustic modulation method is applied to a composite skin-stiffener structure to investigate the possibilities to utilize this method for damage identification in terms of detection, localisation and damage quantification. The research comprises a theoretical part and an experimental part. An impact load is applied to the skin-stiffener structure, resulting in a delamination underneath the stiffener. The structure is interrogated with a low frequency pump excitation and a high frequency carrier excitation. The analysis of the response in a frequency band around the carrier frequency is employed to assess the damage identification capabilities and to gain a better understanding of the modulations occurring and the underlying physical phenomena. Though vibro-acoustic is shown to be a sensitive method for damage identification, the complexity of the damage, combined with a high modal density, complicate the understanding of the relation between the physical phenomena and the modulations occurring. more research is recommended to reveal the physics behind the observations.

Volumetric error modeling, identification and compensation based on screw theory for a large multi-axis propeller-measuring machine

NASA Astrophysics Data System (ADS)

Zhong, Xuemin; Liu, Hongqi; Mao, Xinyong; Li, Bin; He, Songping; Peng, Fangyu

2018-05-01

Large multi-axis propeller-measuring machines have two types of geometric error, position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs), which both have significant effects on the volumetric error of the measuring tool relative to the worktable. This paper focuses on modeling, identifying and compensating for the volumetric error of the measuring machine. A volumetric error model in the base coordinate system is established based on screw theory considering all the geometric errors. In order to fully identify all the geometric error parameters, a new method for systematic measurement and identification is proposed. All the PIGEs of adjacent axes and the six PDGEs of the linear axes are identified with a laser tracker using the proposed model. Finally, a volumetric error compensation strategy is presented and an inverse kinematic solution for compensation is proposed. The final measuring and compensation experiments have further verified the efficiency and effectiveness of the measuring and identification method, indicating that the method can be used in volumetric error compensation for large machine tools.

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

High resolution melt curve analysis based on methylation status for human semen identification.

PubMed

Fachet, Caitlyn; Quarino, Lawrence; Karnas, K Joy

2017-03-01

A high resolution melt curve assay to differentiate semen from blood, saliva, urine, and vaginal fluid based on methylation status at the Dapper Isoform 1 (DACT1) gene was developed. Stains made from blood, saliva, urine, semen, and vaginal fluid were obtained from volunteers and DNA was isolated using either organic extraction (saliva, urine, and vaginal fluid) or Chelex ® 100 extraction (blood and semen). Extracts were then subjected to bisulfite modification in order to convert unmethylated cytosines to uracil, consequently creating sequences whose amplicons have melt curves that vary depending on their initial methylation status. When primers designed to amplify the promoter region of the DACT1 gene were used, DNA from semen samples was distinguishable from other fluids by a having a statistically significant lower melting temperature. The assay was found to be sperm-significant since semen from a vasectomized man produced a melting temperature similar to the non-semen body fluids. Blood and semen stains stored up to 5 months and tested at various intervals showed little variation in melt temperature indicating the methylation status was stable during the course of the study. The assay is a more viable method for forensic science practice than most molecular-based methods for body fluid stain identification since it is time efficient and utilizes instrumentation common to forensic biology laboratories. In addition, the assay is advantageous over traditional presumptive chemical methods for body fluid identification since results are confirmatory and the assay offers the possibility of multiplexing which may test for multiple body fluids simultaneously.

A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra

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

Kou, Qiang; Wu, Si; Tolić, Nikola

Motivation: Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a “bird’s eye view” of intact proteoforms. The combinatorial explosion of various alterations on a protein may result inmore » billions of possible proteoforms, making proteoform identification a challenging computational problem. Results: We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry data sets showed that TopMG outperformed existing methods in identifying complex proteoforms.« less

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.

Ultra-fast DNA-based multiplex convection PCR method for meat species identification with possible on-site applications.

PubMed

Song, Kyung-Young; Hwang, Hyun Jin; Kim, Jeong Hee

2017-08-15

The aim of this study was to develop an ultra-fast molecular detection method for meat identification using convection Palm polymerase chain reaction (PCR). The mitochondrial cytochrome b (Cyt b) gene was used as a target gene. Amplicon size was designed to be different for beef, lamb, and pork. When these primer sets were used, each species-specific set specifically detected the target meat species in singleplex and multiplex modes in a 24min PCR run. The detection limit was 1pg of DNA for each meat species. The convection PCR method could detect as low as 1% of meat adulteration. The stability of the assay was confirmed using thermal processed meats. We also showed that direct PCR can be successfully performed with mixed meats and food samples. These results suggest that the developed assay may be useful in the authentication of meats and meat products in laboratory and rapid on-site applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

An identification method for damping ratio in rotor systems

NASA Astrophysics Data System (ADS)

Wang, Weimin; Li, Qihang; Gao, Jinji; Yao, Jianfei; Allaire, Paul

2016-02-01

Centrifugal compressor testing with magnetic bearing excitations is the last step to assure the compressor rotordynamic stability in the designed operating conditions. To meet the challenges of stability evaluation, a new method combining the rational polynomials method (RPM) with the weighted instrumental variables (WIV) estimator to fit the directional frequency response function (dFRF) is presented. Numerical simulation results show that the method suggested in this paper can identify the damping ratio of the first forward and backward modes with high accuracy, even in a severe noise environment. Experimental tests were conducted to study the effect of different bearing configurations on the stability of rotor. Furthermore, two example centrifugal compressors (a nine-stage straight-through and a six-stage back-to-back) were employed to verify the feasibility of identification method in industrial configurations as well.

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

NASA Astrophysics Data System (ADS)

Zhong, Chongquan; Lin, Yaoyao

2017-11-01

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

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

PubMed

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

2017-05-01

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

DNA identification of human remains in Disaster Victim Identification (DVI): An efficient sampling method for muscle, bone, bone marrow and teeth.

PubMed

de Boer, Hans H; Maat, George J R; Kadarmo, D Aji; Widodo, Putut T; Kloosterman, Ate D; Kal, Arnoud J

2018-06-04

In disaster victim identification (DVI), DNA profiling is considered to be one of the most reliable and efficient means to identify bodies or separated body parts. This requires a post mortem DNA sample, and an ante mortem DNA sample of the presumed victim or their biological relative(s). Usually the collection of an adequate ante mortem sample is technically simple, but the acquisition of a good quality post mortem sample under unfavourable DVI circumstances is complicated due to the variable degree of preservation of the human remains and the high risk of DNA (cross) contamination. This paper provides the community with an efficient method to collect post-mortem DNA samples from muscle, bone, bone marrow and teeth, with a minimal risk of contamination. Our method has been applied in a recent, challenging DVI operation (i.e. the identification of the 298 victims of the MH17 airplane crash in 2014). 98,2% of the collected PM samples provided the DVI team with highly informative DNA genotyping results without the risk of contamination and consequent mistyping the victim's DNA. Moreover, the method is easy, cheap and quick. This paper provides the DVI community with a step-wise instructions with recommendations for the type of tissue to be sampled and the site of excision (preferably the upper leg). Although initially designed for DVI purposes, the method is also suited for the identification of individual victims. Copyright © 2018 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Wei, Xiaojun; Živanović, Stana

2018-05-01

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

A rapid, one step molecular identification of Trichoderma citrinoviride and Trichoderma reesei.

PubMed

Saroj, Dina B; Dengeti, Shrinivas N; Aher, Supriya; Gupta, Anil K