Maximum likelihood estimation of label imperfections and its use in the identification of mislabeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of estimating label imperfections and the use of the estimation in identifying mislabeled patterns is presented. Expressions for the maximum likelihood estimates of classification errors and a priori probabilities are derived from the classification of a set of labeled patterns. Expressions also are given for the asymptotic variances of probability of correct classification and proportions. Simple models are developed for imperfections in the labels and for classification errors and are used in the formulation of a maximum likelihood estimation scheme. Schemes are presented for the identification of mislabeled patterns in terms of threshold on the discriminant functions for both two-class and multiclass cases. Expressions are derived for the probability that the imperfect label identification scheme will result in a wrong decision and are used in computing thresholds. The results of practical applications of these techniques in the processing of remotely sensed multispectral data are presented.

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

NASA Astrophysics Data System (ADS)

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

1990-09-01

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

Automated Coronal Loop Identification Using Digital Image Processing Techniques

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

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

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

PubMed

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

2017-09-04

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

Techniques for generation of control and guidance signals derived from optical fields, part 2

NASA Technical Reports Server (NTRS)

Hemami, H.; Mcghee, R. B.; Gardner, S. R.

1971-01-01

The development is reported of a high resolution technique for the detection and identification of landmarks from spacecraft optical fields. By making use of nonlinear regression analysis, a method is presented whereby a sequence of synthetic images produced by a digital computer can be automatically adjusted to provide a least squares approximation to a real image. The convergence of the method is demonstrated by means of a computer simulation for both elliptical and rectangular patterns. Statistical simulation studies with elliptical and rectangular patterns show that the computational techniques developed are able to at least match human pattern recognition capabilities, even in the presence of large amounts of noise. Unlike most pattern recognition techniques, this ability is unaffected by arbitrary pattern rotation, translation, and scale change. Further development of the basic approach may eventually allow a spacecraft or robot vehicle to be provided with an ability to very accurately determine its spatial relationship to arbitrary known objects within its optical field of view.

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

PubMed

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

2017-11-01

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

Seasonal and species-specific patterns in abundance of freshwater mussel glochidia in stream drift

Treesearch

Jacob J. Culp; Wendell R. Haag; D. Albrey Arrington; Thomas B. Kennedy

2011-01-01

Abstract. We examined seasonal patterns of abundance of mussel larvae (glochidia) in stream drift in a diverse, large-stream mussel assemblage in the Sipsey River, Alabama, across 1 y. We used recently developed techniques for glochidial identification combined with information about mussel fecundity and benthic assemblages to evaluate how well observed glochidial...

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

PubMed Central

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

2012-01-01

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

MALDI-TOF MS Profiling-Advances in Species Identification of Pests, Parasites, and Vectors.

PubMed

Murugaiyan, Jayaseelan; Roesler, Uwe

2017-01-01

Invertebrate pests and parasites of humans, animals, and plants continue to cause serious diseases and remain as a high treat to agricultural productivity and storage. The rapid and accurate species identification of the pests and parasites are needed for understanding epidemiology, monitoring outbreaks, and designing control measures. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as a rapid, cost effective, and high throughput technique of microbial species identification in modern diagnostic laboratories. The development of soft ionization techniques and the release of commercial pattern matching software platforms has resulted in the exponential growth of applications in higher organisms including parasitology. The present review discusses the proof-of-principle experiments and various methods of MALDI MS profiling in rapid species identification of both laboratory and field isolates of pests, parasites and vectors.

MALDI-TOF MS Profiling-Advances in Species Identification of Pests, Parasites, and Vectors

PubMed Central

Murugaiyan, Jayaseelan; Roesler, Uwe

2017-01-01

Invertebrate pests and parasites of humans, animals, and plants continue to cause serious diseases and remain as a high treat to agricultural productivity and storage. The rapid and accurate species identification of the pests and parasites are needed for understanding epidemiology, monitoring outbreaks, and designing control measures. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as a rapid, cost effective, and high throughput technique of microbial species identification in modern diagnostic laboratories. The development of soft ionization techniques and the release of commercial pattern matching software platforms has resulted in the exponential growth of applications in higher organisms including parasitology. The present review discusses the proof-of-principle experiments and various methods of MALDI MS profiling in rapid species identification of both laboratory and field isolates of pests, parasites and vectors. PMID:28555175

Stitch overlap via coloring technique enables maskless via

NASA Astrophysics Data System (ADS)

Civay, D.; Laffosse, E.

2017-03-01

Lithographic patterning limits can be a cost-barrier that delays advancement to new nodes. This paper introduces a cost-saving design method that enables a maskless via. Multi-patterning or coloring of a design is a technique that is used at advanced nodes to aid in patterning. Coloring allows designers to designate different patterns on one level to be printed with different masks. Stitch overlap via (SOV) is a coloring technique introduced herein. SOV utilizes via-aware coloring and a unique process flow to print a maskless via. Identification of qualifying design structures is achieved through a custom program. The program inputs the design level of the multipatterned layer and the via levels above and below to determine the coloring decomposition. Vias are a particularly challenging layer to print due to the dimensions required for these pillars. SOV is a methodology for identifying qualifying multi-patterned layouts and replacing them with a new design that enables a maskless via layer.

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

PubMed

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

2018-04-25

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

Structural Pattern Recognition Techniques for Data Retrieval in Massive Fusion Databases

NASA Astrophysics Data System (ADS)

Vega, J.; Murari, A.; Rattá, G. A.; Castro, P.; Pereira, A.; Portas, A.

2008-03-01

Diagnostics of present day reactor class fusion experiments, like the Joint European Torus (JET), generate thousands of signals (time series and video images) in each discharge. There is a direct correspondence between the physical phenomena taking place in the plasma and the set of structural shapes (patterns) that they form in the signals: bumps, unexpected amplitude changes, abrupt peaks, periodic components, high intensity zones or specific edge contours. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behavior, i.e. discharges with "similar" patterns. Pattern recognition techniques are efficient tools to search for similar structural forms within the database in a fast an intelligent way. To this end, classification systems must be developed to be used as indexation methods to directly fetch the more similar patterns.

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

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

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

Routine use of PCR-restriction fragment length polymorphism analysis for identification of mycobacteria growing in liquid media.

PubMed Central

Taylor, T B; Patterson, C; Hale, Y; Safranek, W W

1997-01-01

A PCR-restriction fragment length polymorphism (PCR-RFLP) procedure capable of rapidly identifying 28 species of clinically encountered mycobacteria was evaluated for use in the routine identification of acid-fast isolates growing in BACTEC 12B and 13A liquid media. PCR-RFLP identified 100 of 103 acid-fast isolates recovered from 610 patient specimens submitted for culture during the study. The three isolates unidentifiable by PCR-RFLP produced restriction patterns not included in the PCR-RFLP algorithm and could therefore not be assigned to a species. These isolates were characterized by their morphologic and biochemical characteristics. Two of the isolates were identified as M. terrae complex and M. gordonae. The third isolate could not be definitively identified and could only be characterized as a Mycobacterium sp. most closely resembling M. chelonae. PCR-RFLP identifications agreed with the conventional identifications for 96 of the 100 isolates identified by PCR-RFLP. Subsequent identification of the four discordant isolates by gas chromatography analysis supported the PCR-RFLP identification of each isolate. Amplification products were also obtained from isolates of Streptococcus albus and Rhodococcus equi recovered from patient specimens; however, the restriction patterns of these nonmycobacterial species did not resemble the patterns of any mycobacterial species included in the PCR-RFLP algorithm. PCR-RFLP seems to be a reliable procedure for the routine identification of mycobacteria and has the potential for providing identifications of mycobacterial isolates which are more accurate than conventional identification techniques based on morphologic and biochemical characteristics. PMID:8968884

Using of methods of speckle optics for Chlamydia trachomatis typing

NASA Astrophysics Data System (ADS)

Ulyanov, Sergey S.; Zaytsev, Sergey S.; Ulianova, Onega V.; Saltykov, Yury V.; Feodorova, Valentina A.

2017-03-01

Specific method of transformation of nucleotide of gene into speckle pattern is suggested. Reference speckle pattern of omp1 gene of typical wild strains of Chlamydia trachomatis of genovars D, E, F, G, J and K and Chlamydia psittaci as well is generated. Perspectives of proposed technique in the gene identification and detection of natural genetic mutations as single nucleotide polymorphism (SNP) are demonstrated.

Plan View Pattern Control for Steel Plates through Constrained Locally Weighted Regression

NASA Astrophysics Data System (ADS)

Shigemori, Hiroyasu; Nambu, Koji; Nagao, Ryo; Araki, Tadashi; Mizushima, Narihito; Kano, Manabu; Hasebe, Shinji

A technique for performing parameter identification in a locally weighted regression model using foresight information on the physical properties of the object of interest as constraints was proposed. This method was applied to plan view pattern control of steel plates, and a reduction of shape nonconformity (crop) at the plate head end was confirmed by computer simulation based on real operation data.

Gene Identification Algorithms Using Exploratory Statistical Analysis of Periodicity

NASA Astrophysics Data System (ADS)

Mukherjee, Shashi Bajaj; Sen, Pradip Kumar

2010-10-01

Studying periodic pattern is expected as a standard line of attack for recognizing DNA sequence in identification of gene and similar problems. But peculiarly very little significant work is done in this direction. This paper studies statistical properties of DNA sequences of complete genome using a new technique. A DNA sequence is converted to a numeric sequence using various types of mappings and standard Fourier technique is applied to study the periodicity. Distinct statistical behaviour of periodicity parameters is found in coding and non-coding sequences, which can be used to distinguish between these parts. Here DNA sequences of Drosophila melanogaster were analyzed with significant accuracy.

Fingerprint pattern restoration by digital image processing techniques.

PubMed

Wen, Che-Yen; Yu, Chiu-Chung

2003-09-01

Fingerprint evidence plays an important role in solving criminal problems. However, defective (lacking information needed for completeness) or contaminated (undesirable information included) fingerprint patterns make identifying and recognizing processes difficult. Unfortunately. this is the usual case. In the recognizing process (enhancement of patterns, or elimination of "false alarms" so that a fingerprint pattern can be searched in the Automated Fingerprint Identification System (AFIS)), chemical and physical techniques have been proposed to improve pattern legibility. In the identifying process, a fingerprint examiner can enhance contaminated (but not defective) fingerprint patterns under guidelines provided by the Scientific Working Group on Friction Ridge Analysis, Study and Technology (SWGFAST), the Scientific Working Group on Imaging Technology (SWGIT), and an AFIS working group within the National Institute of Justice. Recently, the image processing techniques have been successfully applied in forensic science. For example, we have applied image enhancement methods to improve the legibility of digital images such as fingerprints and vehicle plate numbers. In this paper, we propose a novel digital image restoration technique based on the AM (amplitude modulation)-FM (frequency modulation) reaction-diffusion method to restore defective or contaminated fingerprint patterns. This method shows its potential application to fingerprint pattern enhancement in the recognizing process (but not for the identifying process). Synthetic and real images are used to show the capability of the proposed method. The results of enhancing fingerprint patterns by the manual process and our method are evaluated and compared.

Physical vs. photolithographic patterning of plasma polymers: an investigation by ToF-SSIMS and multivariate analysis

PubMed Central

Mishra, Gautam; Easton, Christopher D.; McArthur, Sally L.

2009-01-01

Physical and photolithographic techniques are commonly used to create chemical patterns for a range of technologies including cell culture studies, bioarrays and other biomedical applications. In this paper, we describe the fabrication of chemical micropatterns from commonly used plasma polymers. Atomic force microcopy (AFM) imaging, Time-of-Flight Static Secondary Ion Mass Spectrometry (ToF-SSIMS) imaging and multivariate analysis have been employed to visualize the chemical boundaries created by these patterning techniques and assess the spatial and chemical resolution of the patterns. ToF-SSIMS analysis demonstrated that well defined chemical and spatial boundaries were obtained from photolithographic patterning, while the resolution of physical patterning via a transmission electron microscopy (TEM) grid varied depending on the properties of the plasma system including the substrate material. In general, physical masking allowed diffusion of the plasma species below the mask and bleeding of the surface chemistries. Multivariate analysis techniques including Principal Component Analysis (PCA) and Region of Interest (ROI) assessment were used to investigate the ToF-SSIMS images of a range of different plasma polymer patterns. In the most challenging case, where two strongly reacting polymers, allylamine and acrylic acid were deposited, PCA confirmed the fabrication of micropatterns with defined spatial resolution. ROI analysis allowed for the identification of an interface between the two plasma polymers for patterns fabricated using the photolithographic technique which has been previously overlooked. This study clearly demonstrated the versatility of photolithographic patterning for the production of multichemistry plasma polymer arrays and highlighted the need for complimentary characterization and analytical techniques during the fabrication plasma polymer micropatterns. PMID:19950941

AIRWAY IDENTIFICATION WITHIN PLANAR GAMMA CAMERA IMAGES USING COMPUTER MODELS OF LUNG MORPHOLOGY

EPA Science Inventory

The quantification of inhaled aerosols could be improved if a more comprehensive assessment of their spatial distribution patterns among lung airways were obtained. A common technique for quantifying particle deposition in human lungs is with planar gamma scintigraphy. However, t...

3-D QSARS FOR RANKING AND PRIORITIZATION OF LARGE CHEMICAL DATASETS: AN EDC CASE STUDY

EPA Science Inventory

The COmmon REactivity Pattern (COREPA) approach is a three-dimensional structure activity (3-D QSAR) technique that permits identification and quantification of specific global and local steroelectronic characteristics associated with a chemical's biological activity. It goes bey...

Optical rangefinding applications using communications modulation technique

NASA Astrophysics Data System (ADS)

Caplan, William D.; Morcom, Christopher John

2010-10-01

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

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

PubMed

Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

2015-11-04

European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

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

PubMed

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

2010-01-01

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Observing Consistency in Online Communication Patterns for User Re-Identification.

PubMed

Adeyemi, Ikuesan Richard; Razak, Shukor Abd; Salleh, Mazleena; Venter, Hein S

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Gas-liquid two-phase flow pattern identification by ultrasonic echoes reflected from the inner wall of a pipe

NASA Astrophysics Data System (ADS)

Liang, Fachun; Zheng, Hongfeng; Yu, Hao; Sun, Yuan

2016-03-01

A novel ultrasonic pulse echo method is proposed for flow pattern identification in a horizontal pipe with gas-liquid two-phase flow. A trace of echoes reflected from the pipe’s internal wall rather than the gas-liquid interface is used for flow pattern identification. Experiments were conducted in a horizontal air-water two-phase flow loop. Two ultrasonic transducers with central frequency of 5 MHz were mounted at the top and bottom of the pipe respectively. The experimental results show that the ultrasonic reflection coefficient of the wall-gas interface is much larger than that of the wall-liquid interface due to the large difference in the acoustic impedance of gas and liquid. The stratified flow, annular flow and slug flow can be successfully recognized using the attenuation ratio of the echoes. Compared with the conventional ultrasonic echo measurement method, echoes reflected from the inner surface of a pipe wall are independent of gas-liquid interface fluctuation, sound speed, and gas and liquid superficial velocities, which makes the method presented a promising technique in field practice.

Unravelling associations between unassigned mass spectrometry peaks with frequent itemset mining techniques.

PubMed

Vu, Trung Nghia; Mrzic, Aida; Valkenborg, Dirk; Maes, Evelyne; Lemière, Filip; Goethals, Bart; Laukens, Kris

2014-01-01

Mass spectrometry-based proteomics experiments generate spectra that are rich in information. Often only a fraction of this information is used for peptide/protein identification, whereas a significant proportion of the peaks in a spectrum remain unexplained. In this paper we explore how a specific class of data mining techniques termed "frequent itemset mining" can be employed to discover patterns in the unassigned data, and how such patterns can help us interpret the origin of the unexpected/unexplained peaks. First a model is proposed that describes the origin of the observed peaks in a mass spectrum. For this purpose we use the classical correlative database search algorithm. Peaks that support a positive identification of the spectrum are termed explained peaks. Next, frequent itemset mining techniques are introduced to infer which unexplained peaks are associated in a spectrum. The method is validated on two types of experimental proteomic data. First, peptide mass fingerprint data is analyzed to explain the unassigned peaks in a full scan mass spectrum. Interestingly, a large numbers of experimental spectra reveals several highly frequent unexplained masses, and pattern mining on these frequent masses demonstrates that subsets of these peaks frequently co-occur. Further evaluation shows that several of these co-occurring peaks indeed have a known common origin, and other patterns are promising hypothesis generators for further analysis. Second, the proposed methodology is validated on tandem mass spectrometral data using a public spectral library, where associations within the mass differences of unassigned peaks and peptide modifications are explored. The investigation of the found patterns illustrates that meaningful patterns can be discovered that can be explained by features of the employed technology and found modifications. This simple approach offers opportunities to monitor accumulating unexplained mass spectrometry data for emerging new patterns, with possible applications for the development of mass exclusion lists, for the refinement of quality control strategies and for a further interpretation of unexplained spectral peaks in mass spectrometry and tandem mass spectrometry.

Influence of condition of growth of bacterial colonies on fractal dimension of bacterial speckle patterns

NASA Astrophysics Data System (ADS)

Ulyanov, Alexander S.; Lyapina, Anna M.; Ulianova, Onega V.; Feodorova, Valentina A.

2010-10-01

New field of application of fractal dimensions is proposed. A technique, based on the calculation of fractal dimension, was used for express-diagnostics and identification of bacteria of the vaccine strain Yersinia pestis EV line NIIEG. Purpose of this study was the experimental investigation of properties of speckle patterns, formed under laser illumination of a single colony of the strain that was grown on different agars.

Influence of condition of growth of bacterial colonies on fractal dimension of bacterial speckle patterns

NASA Astrophysics Data System (ADS)

Ulyanov, Alexander S.; Lyapina, Anna M.; Ulianova, Onega V.; Feodorova, Valentina A.

2011-03-01

New field of application of fractal dimensions is proposed. A technique, based on the calculation of fractal dimension, was used for express-diagnostics and identification of bacteria of the vaccine strain Yersinia pestis EV line NIIEG. Purpose of this study was the experimental investigation of properties of speckle patterns, formed under laser illumination of a single colony of the strain that was grown on different agars.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms. Copyright © 2018 John Wiley & Sons, Ltd.

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...

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Spectral identification of sperm whales from Littoral Acoustic Demonstration Center passive acoustic recordings

NASA Astrophysics Data System (ADS)

Sidorovskaia, Natalia A.; Richard, Blake; Ioup, George E.; Ioup, Juliette W.

2005-09-01

The Littoral Acoustic Demonstration Center (LADC) made a series of passive broadband acoustic recordings in the Gulf of Mexico and Ligurian Sea to study noise and marine mammal phonations. The collected data contain a large amount of various types of sperm whale phonations, such as isolated clicks and communication codas. It was previously reported that the spectrograms of the extracted clicks and codas contain well-defined null patterns that seem to be unique for individuals. The null pattern is formed due to individual features of the sound production organs of an animal. These observations motivated the present studies of adapting human speech identification techniques for deep-diving marine mammal phonations. A three-state trained hidden Markov model (HMM) was used with the phonation spectra of sperm whales. The HHM-algorithm gave 75% accuracy in identifying individuals when it had been initially tested for the acoustic data set correlated with visual observations of sperm whales. A comparison of the identification accuracy based on null-pattern similarity analysis and the HMM-algorithm is presented. The results can establish the foundation for developing an acoustic identification database for sperm whales and possibly other deep-diving marine mammals that would be difficult to observe visually. [Research supported by ONR.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

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

PubMed

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

2015-03-01

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

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

NASA Technical Reports Server (NTRS)

Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor); Guan, Chun (Inventor)

2010-01-01

A technique, associated system and program code, for retrieving depth information about at least one surface of an object, such as an anatomical feature. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the anatomical feature; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

NASA Technical Reports Server (NTRS)

Guan, Chun (Inventor); Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor)

2008-01-01

A technique, associated system and program code, for retrieving depth information about at least one surface of an object. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the object; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

Proposal and evaluation of FASDIM, a Fast And Simple De-Identification Method for unstructured free-text clinical records.

PubMed

Chazard, Emmanuel; Mouret, Capucine; Ficheur, Grégoire; Schaffar, Aurélien; Beuscart, Jean-Baptiste; Beuscart, Régis

2014-04-01

Medical free-text records enable to get rich information about the patients, but often need to be de-identified by removing the Protected Health Information (PHI), each time the identification of the patient is not mandatory. Pattern matching techniques require pre-defined dictionaries, and machine learning techniques require an extensive training set. Methods exist in French, but either bring weak results or are not freely available. The objective is to define and evaluate FASDIM, a Fast And Simple De-Identification Method for French medical free-text records. FASDIM consists in removing all the words that are not present in the authorized word list, and in removing all the numbers except those that match a list of protection patterns. The corresponding lists are incremented in the course of the iterations of the method. For the evaluation, the workload is estimated in the course of records de-identification. The efficiency of the de-identification is assessed by independent medical experts on 508 discharge letters that are randomly selected and de-identified by FASDIM. Finally, the letters are encoded after and before de-identification according to 3 terminologies (ATC, ICD10, CCAM) and the codes are compared. The construction of the list of authorized words is progressive: 12h for the first 7000 letters, 16 additional hours for 20,000 additional letters. The Recall (proportion of removed Protected Health Information, PHI) is 98.1%, the Precision (proportion of PHI within the removed token) is 79.6% and the F-measure (harmonic mean) is 87.9%. In average 30.6 terminology codes are encoded per letter, and 99.02% of those codes are preserved despite the de-identification. FASDIM gets good results in French and is freely available. It is easy to implement and does not require any predefined dictionary. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Proteomic patterns for classification of ovarian cancer and CTCL serum samples utilizing peak pairs indicative of post-translational modifications.

PubMed

Liu, Chenwei; Shea, Nancy; Rucker, Sally; Harvey, Linda; Russo, Paul; Saul, Richard; Lopez, Mary F; Mikulskis, Alvydas; Kuzdzal, Scott; Golenko, Eva; Fishman, David; Vonderheid, Eric; Booher, Susan; Cowen, Edward W; Hwang, Sam T; Whiteley, Gordon R

2007-11-01

Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are regulated through PTM of proteins. These modifications are also detectable with high confidence using high-resolution MS. We generated data using a prOTOF mass spectrometer on two sets of patient samples: ovarian cancer and cutaneous t-cell lymphoma (CTCL) with matched normal samples for each disease. Using the knowledge of mass shifts caused by common modifications, we built models using peak pairs and compared this to a conventional technique using individual peaks. The results for each disease showed that a small number of peak pairs gave classification equal to or better than the conventional technique that used multiple individual peaks. This simple peak picking technique could be used to guide identification of important peak pairs involved in the disease process.

Evaluation of the veracity of one work by the artist Di Cavalcanti through non-destructive techniques: XRF, imaging and brush stroke analysis

NASA Astrophysics Data System (ADS)

Kajiya, E. A. M.; Campos, P. H. O. V.; Rizzutto, M. A.; Appoloni, C. R.; Lopes, F.

2014-02-01

This paper presents systematic studies and analysis that contributed to the identification of the forgery of a work by the artist Emiliano Augusto Cavalcanti de Albuquerque e Melo, known as Di Cavalcanti. The use of several areas of expertise such as brush stroke analysis ("pinacologia"), applied physics, and art history resulted in an accurate diagnosis for ascertaining the authenticity of the work entitled "Violeiro" (1950). For this work we used non-destructive methods such as techniques of infrared, ultraviolet, visible and tangential light imaging combined with chemical analysis of the pigments by portable X-Ray Fluorescence (XRF) and graphic gesture analysis. Each applied method of analysis produced specific information that made possible the identification of materials and techniques employed and we concluded that this work is not consistent with patterns characteristic of the artist Di Cavalcanti.

Detection of Anomalies in Hydrometric Data Using Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Lauzon, N.; Lence, B. J.

2002-12-01

This work focuses on the detection of anomalies in hydrometric data sequences, such as 1) outliers, which are individual data having statistical properties that differ from those of the overall population; 2) shifts, which are sudden changes over time in the statistical properties of the historical records of data; and 3) trends, which are systematic changes over time in the statistical properties. For the purpose of the design and management of water resources systems, it is important to be aware of these anomalies in hydrometric data, for they can induce a bias in the estimation of water quantity and quality parameters. These anomalies may be viewed as specific patterns affecting the data, and therefore pattern recognition techniques can be used for identifying them. However, the number of possible patterns is very large for each type of anomaly and consequently large computing capacities are required to account for all possibilities using the standard statistical techniques, such as cluster analysis. Artificial intelligence techniques, such as the Kohonen neural network and fuzzy c-means, are clustering techniques commonly used for pattern recognition in several areas of engineering and have recently begun to be used for the analysis of natural systems. They require much less computing capacity than the standard statistical techniques, and therefore are well suited for the identification of outliers, shifts and trends in hydrometric data. This work constitutes a preliminary study, using synthetic data representing hydrometric data that can be found in Canada. The analysis of the results obtained shows that the Kohonen neural network and fuzzy c-means are reasonably successful in identifying anomalies. This work also addresses the problem of uncertainties inherent to the calibration procedures that fit the clusters to the possible patterns for both the Kohonen neural network and fuzzy c-means. Indeed, for the same database, different sets of clusters can be established with these calibration procedures. A simple method for analyzing uncertainties associated with the Kohonen neural network and fuzzy c-means is developed here. The method combines the results from several sets of clusters, either from the Kohonen neural network or fuzzy c-means, so as to provide an overall diagnosis as to the identification of outliers, shifts and trends. The results indicate an improvement in the performance for identifying anomalies when the method of combining cluster sets is used, compared with when only one cluster set is used.

Iris indexing based on local intensity order pattern

NASA Astrophysics Data System (ADS)

Emerich, Simina; Malutan, Raul; Crisan, Septimiu; Lefkovits, Laszlo

2017-03-01

In recent years, iris biometric systems have increased in popularity and have been proven that are capable of handling large-scale databases. The main advantage of these systems is accuracy and reliability. A proper iris patterns classification is expected to reduce the matching time in huge databases. This paper presents an iris indexing technique based on Local Intensity Order Pattern. The performance of the present approach is evaluated on UPOL database and is compared with other recent systems designed for iris indexing. The results illustrate the potential of the proposed method for large scale iris identification.

FT-IR spectroscopic, thermal analysis of human urinary stones and their characterization

NASA Astrophysics Data System (ADS)

Selvaraju, R.; Raja, A.; Thiruppathi, G.

2015-02-01

In the present study, FT-IR, XRD, TGA-DTA spectral methods have been used to investigate the chemical compositions of urinary calculi. Multi-components of urinary calculi such as calcium oxalate, hydroxyl apatite, struvite and uric acid have been studied. The chemical compounds are identified by FT-IR spectroscopic technique. The mineral identification was confirmed by powder X-ray diffraction patterns as compared with JCPDS reported values. Thermal analysis techniques are considered the best techniques for the characterization and detection of endothermic and exothermic behaviors of the urinary stones. The percentages of each hydrate (COM and COD) are present together, in the presences of MAPH or UA. Finally, the present study suggests that the Urolithiasis is significant health problem in children, and is very common in some parts of the world, especially in India. So that present study is so useful and helpful to the scientific community for identification of latest human health problems and their remedies using spectroscopic techniques.

Optical processing for landmark identification

NASA Technical Reports Server (NTRS)

Casasent, D.; Luu, T. K.

1981-01-01

A study of optical pattern recognition techniques, available components and airborne optical systems for use in landmark identification was conducted. A data base of imagery exhibiting multisensor, seasonal, snow and fog cover, exposure, and other differences was assembled. These were successfully processed in a scaling optical correlator using weighted matched spatial filter synthesis. Distinctive data classes were defined and a description of the data (with considerable input information and content information) emerged from this study. It has considerable merit with regard to the preprocessing needed and the image difference categories advanced. A optical pattern recognition airborne applications was developed, assembled and demontrated. It employed a laser diode light source and holographic optical elements in a new lensless matched spatial filter architecture with greatly reduced size and weight, as well as component positioning toleranced.

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

PubMed

Cao, Gang; Zhao, Yao; Ni, Rongrong

2012-03-10

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

Atmospheric solids analysis probe mass spectrometry for the rapid identification of pollens and semi-quantification of flavonoid fingerprints.

PubMed

Xiao, Xiaoyin; Miller, Lance L; Parchert, Kylea J; Hayes, Dulce; Hochrein, James M

2016-07-15

From allergies to plant reproduction, pollens have important impacts on the health of human and plant populations, yet identification of pollen grains remains difficult and time-consuming. Low-volatility flavonoids generated from pollens cannot be easily characterized and quantified with current analytical techniques. Here we present the novel use of atmospheric solids analysis probe mass spectrometry (ASAP-MS) for the characterization of flavonoids in pollens. Flavonoid patterns were generated for pollens collected from different plant types (trees and bushes) in addition to bee pollens from distinct geographic regions. Standard flavonoids (kaempferol and rhamnazin) and those produced from pollens were compared and assessed with ASAP-MS using low-energy collision MS/MS. Results for a semi-quantitative method for assessing the amount of a flavonoid in pollens are also presented. Flavonoid patterns for pollen samples were distinct with variability in the number and relative abundance of flavonoids in each sample. Pollens contained 2-5 flavonoids, and all but Kochia scoparia contained kaempferol or kaempferol isomers. We establish this method as a reliable and applicable technique for analyzing low-volatility compounds with minimal sample preparation. Standard curves were generated using 0.2-5 μg of kaempferol; from these experiments, it was estimated that there is approximately 2 mg of kaempferol present in 1 g of P. nigra italica pollen. Pollens can be characterized with a simple flavonoid pattern rather than analyzing the whole product pattern or the products-temperature profiles. ASAP-MS is a rapid analytical technique that can be used to distinguish between plant pollens and between bee pollens originating from different regions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. PMID:27918593

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

Treesearch

R.E. Kennedy; W.B. Cohen

2003-01-01

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

Whale Identification

NASA Technical Reports Server (NTRS)

1991-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

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

Analysis of DNA Cytosine Methylation Patterns Using Methylation-Sensitive Amplification Polymorphism (MSAP).

PubMed

Guevara, María Ángeles; de María, Nuria; Sáez-Laguna, Enrique; Vélez, María Dolores; Cervera, María Teresa; Cabezas, José Antonio

2017-01-01

Different molecular techniques have been developed to study either the global level of methylated cytosines or methylation at specific gene sequences. One of them is the methylation-sensitive amplified polymorphism technique (MSAP) which is a modification of amplified fragment length polymorphism (AFLP). It has been used to study methylation of anonymous CCGG sequences in different fungi, plants, and animal species. The main variation of this technique resides on the use of isoschizomers with different methylation sensitivity (such as HpaII and MspI) as a frequent-cutter restriction enzyme. For each sample, MSAP analysis is performed using both EcoRI/HpaII- and EcoRI/MspI-digested samples. A comparative analysis between EcoRI/HpaII and EcoRI/MspI fragment patterns allows the identification of two types of polymorphisms: (1) methylation-insensitive polymorphisms that show common EcoRI/HpaII and EcoRI/MspI patterns but are detected as polymorphic amplified fragments among samples and (2) methylation-sensitive polymorphisms which are associated with the amplified fragments that differ in their presence or absence or in their intensity between EcoRI/HpaII and EcoRI/MspI patterns. This chapter describes a detailed protocol of this technique and discusses the modifications that can be applied to adjust the technology to different species of interest.

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

The application of artificial intelligence for the identification of the maceral groups and mineral components of coal

NASA Astrophysics Data System (ADS)

Mlynarczuk, Mariusz; Skiba, Marta

2017-06-01

The correct and consistent identification of the petrographic properties of coal is an important issue for researchers in the fields of mining and geology. As part of the study described in this paper, investigations concerning the application of artificial intelligence methods for the identification of the aforementioned characteristics were carried out. The methods in question were used to identify the maceral groups of coal, i.e. vitrinite, inertinite, and liptinite. Additionally, an attempt was made to identify some non-organic minerals. The analyses were performed using pattern recognition techniques (NN, kNN), as well as artificial neural network techniques (a multilayer perceptron - MLP). The classification process was carried out using microscopy images of polished sections of coals. A multidimensional feature space was defined, which made it possible to classify the discussed structures automatically, based on the methods of pattern recognition and algorithms of the artificial neural networks. Also, from the study we assessed the impact of the parameters for which the applied methods proved effective upon the final outcome of the classification procedure. The result of the analyses was a high percentage (over 97%) of correct classifications of maceral groups and mineral components. The paper discusses also an attempt to analyze particular macerals of the inertinite group. It was demonstrated that using artificial neural networks to this end makes it possible to classify the macerals properly in over 91% of cases. Thus, it was proved that artificial intelligence methods can be successfully applied for the identification of selected petrographic features of coal.

INDIRECT COMPUTED TOMOGRAPHIC LYMPHOGRAPHY FOR ILIOSACRAL LYMPHATIC MAPPING IN A COHORT OF DOGS WITH ANAL SAC GLAND ADENOCARCINOMA: TECHNIQUE DESCRIPTION.

PubMed

Majeski, Stephanie A; Steffey, Michele A; Fuller, Mark; Hunt, Geraldine B; Mayhew, Philipp D; Pollard, Rachel E

2017-05-01

Sentinel lymph node mapping can help to direct surgical oncologic staging and metastatic disease detection in patients with complex lymphatic pathways. We hypothesized that indirect computed tomographic lymphography (ICTL) with a water-soluble iodinated contrast agent would successfully map lymphatic pathways of the iliosacral lymphatic center in dogs with anal sac gland carcinoma, providing a potential preoperative method for iliosacral sentinel lymph node identification in dogs. Thirteen adult dogs diagnosed with anal sac gland carcinoma were enrolled in this prospective, pilot study, and ICTL was performed via peritumoral contrast injection with serial caudal abdominal computed tomography scans for iliosacral sentinel lymph node identification. Technical and descriptive details for ICTL were recorded, including patient positioning, total contrast injection volume, timing of contrast visualization, and sentinel lymph nodes and lymphatic pathways identified. Indirect CT lymphography identified lymphatic pathways and sentinel lymph nodes in 12/13 cases (92%). Identified sentinel lymph nodes were ipsilateral to the anal sac gland carcinoma in 8/12 and contralateral to the anal sac gland carcinoma in 4/12 cases. Sacral, internal iliac, and medial iliac lymph nodes were identified as sentinel lymph nodes, and patterns were widely variable. Patient positioning and timing of imaging may impact successful sentinel lymph node identification. Positioning in supported sternal recumbency is recommended. Results indicate that ICTL may be a feasible technique for sentinel lymph node identification in dogs with anal sac gland carcinoma and offer preliminary data to drive further investigation of iliosacral lymphatic metastatic patterns using ICTL and sentinel lymph node biopsy. © 2017 American College of Veterinary Radiology.

Evaluation of the Technical Adequacy of Three Methods for Identifying Specific Learning Disabilities Based on Cognitive Discrepancies

ERIC Educational Resources Information Center

Stuebing, Karla K.; Fletcher, Jack M.; Branum-Martin, Lee; Francis, David J.

2012-01-01

This study used simulation techniques to evaluate the technical adequacy of three methods for the identification of specific learning disabilities via patterns of strengths and weaknesses in cognitive processing. Latent and observed data were generated and the decision-making process of each method was applied to assess concordance in…

A Mixture Rasch Model with a Covariate: A Simulation Study via Bayesian Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Dai, Yunyun

2013-01-01

Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…

A novel histological technique for distinguishing between epithelial cells in forensic casework.

PubMed

French, Claire E V; Jensen, Cynthia G; Vintiner, Susan K; Elliot, Douglas A; McGlashan, Susan R

2008-06-10

There are a number of forensic cases in which the identification of the epithelial cell type from which DNA originated would provide important probative evidence. This study aimed to develop a technique using histological staining of fixed cells to distinguish between skin, buccal and vaginal epithelium. First, 11 different stains were screened on formalin-fixed, wax-embedded cells from five women. Samples were analysed qualitatively by examining staining patterns (colour) and morphology (absence or presence of nuclei). Three of the staining methods--Dane's, Csaba's and Ayoub-Shklar--were successful in distinguishing skin epithelial cells from buccal and vaginal. Second, cells were smeared directly onto slides, fixed with one of five fixatives and stained with one of the three stains mentioned above. Methanol fixation, coupled with the Dane's staining method, specific to keratin, was the only technique that distinguished between all three cell types. Skin cells stained magenta, red and orange and lacked nuclei; buccal cells stained predominantly orange-pink with red nuclei; while vaginal cells stained bright orange with orange nuclei and a blue extracellular hue. This staining pattern in vaginal cells was consistent in samples collected from 50 women aged between 18 and 67. Identification of cell type from unlabelled micrographs by 10 trained observers showed a mean success rate of 95%. The results of this study demonstrate that histological staining may provide forensic scientists with a technique for distinguishing between skin, buccal and vaginal epithelial cells and thus would enable more conclusive analyses when investigating sexual assault cases.

Automating the generation of lexical patterns for processing free text in clinical documents.

PubMed

Meng, Frank; Morioka, Craig

2015-09-01

Many tasks in natural language processing utilize lexical pattern-matching techniques, including information extraction (IE), negation identification, and syntactic parsing. However, it is generally difficult to derive patterns that achieve acceptable levels of recall while also remaining highly precise. We present a multiple sequence alignment (MSA)-based technique that automatically generates patterns, thereby leveraging language usage to determine the context of words that influence a given target. MSAs capture the commonalities among word sequences and are able to reveal areas of linguistic stability and variation. In this way, MSAs provide a systemic approach to generating lexical patterns that are generalizable, which will both increase recall levels and maintain high levels of precision. The MSA-generated patterns exhibited consistent F1-, F.5-, and F2- scores compared to two baseline techniques for IE across four different tasks. Both baseline techniques performed well for some tasks and less well for others, but MSA was found to consistently perform at a high level for all four tasks. The performance of MSA on the four extraction tasks indicates the method's versatility. The results show that the MSA-based patterns are able to handle the extraction of individual data elements as well as relations between two concepts without the need for large amounts of manual intervention. We presented an MSA-based framework for generating lexical patterns that showed consistently high levels of both performance and recall over four different extraction tasks when compared to baseline methods. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Contrast-enhanced ultrasound in diagnosis and characterization of focal hepatic lesions.

PubMed

Molins, Inés Gómez; Font, Juan Manuel Fernández; Alvaro, Juan Carrero; Navarro, Jose Luís Lledó; Gil, Marta Fernández; Rodríguez, Conrado M Fernández

2010-12-28

The extensive use of imaging techniques in differential diagnosis of abdominal conditions and screening of hepatocellular carcinoma in patients with chronic hepatic diseases, has led to an important increase in identification of focal liver lesions. The development of contrast-enhanced ultrasound (CEUS) opens a new window in the diagnosis and follow-up of these lesions. This technique offers obvious advantages over the computed tomography and magnetic resonance, without a decrease in its sensitivity and specificity. The new second generation contrast agents, due to their intravascular distribution, allow a continuous evaluation of the enhancement pattern, which is crucial in characterization of liver lesions. The dual blood supply in the liver shows three different phases, namely arterial, portal and late phases. The enhancement during portal and late phases can give important information about the lesion's behavior. Each liver lesion has a different enhancement pattern that makes possible an accurate approach to their diagnosis. The role of emerging techniques as a contrast-enhanced three-dimensional US is also discussed. In this article, the advantages, indications and technique employed during CEUS and the different enhancement patterns of most benign and malignant focal liver lesions are discussed.

Contrast-enhanced ultrasound in diagnosis and characterization of focal hepatic lesions

PubMed Central

Molins, Inés Gómez; Font, Juan Manuel Fernández; Álvaro, Juan Carrero; Navarro, Jose Luís Lledó; Gil, Marta Fernández; Rodríguez, Conrado M Fernández

2010-01-01

The extensive use of imaging techniques in differential diagnosis of abdominal conditions and screening of hepatocellular carcinoma in patients with chronic hepatic diseases, has led to an important increase in identification of focal liver lesions. The development of contrast-enhanced ultrasound (CEUS) opens a new window in the diagnosis and follow-up of these lesions. This technique offers obvious advantages over the computed tomography and magnetic resonance, without a decrease in its sensitivity and specificity. The new second generation contrast agents, due to their intravascular distribution, allow a continuous evaluation of the enhancement pattern, which is crucial in characterization of liver lesions. The dual blood supply in the liver shows three different phases, namely arterial, portal and late phases. The enhancement during portal and late phases can give important information about the lesion’s behavior. Each liver lesion has a different enhancement pattern that makes possible an accurate approach to their diagnosis. The role of emerging techniques as a contrast-enhanced three-dimensional US is also discussed. In this article, the advantages, indications and technique employed during CEUS and the different enhancement patterns of most benign and malignant focal liver lesions are discussed. PMID:21225000

Creation of hybrid optoelectronic systems for document identification

NASA Astrophysics Data System (ADS)

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

2001-06-01

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

Dealing with Liars: Misbehavior Identification via Rényi-Ulam Games

NASA Astrophysics Data System (ADS)

Kozma, William; Lazos, Loukas

We address the problem of identifying misbehaving nodes that refuse to forward packets in wireless multi-hop networks. We map the process of locating the misbehaving nodes to the classic Rényi-Ulam game of 20 questions. Compared to previous methods, our mapping allows the evaluation of node behavior on a per-packet basis, without the need for energy-expensive overhearing techniques or intensive acknowledgment schemes. Furthermore, it copes with colluding adversaries that coordinate their behavioral patterns to avoid identification and frame honest nodes. We show via simulations that our algorithms reduce the communication overhead for identifying misbehaving nodes by at least one order of magnitude compared to other methods, while increasing the identification delay logarithmically with the path size.

Identification of Group G Streptococcal Isolates from Companion Animals in Japan and Their Antimicrobial Resistance Patterns.

PubMed

Tsuyuki, Yuzo; Kurita, Goro; Murata, Yoshiteru; Goto, Mieko; Takahashi, Takashi

2017-07-24

In this study, we conducted a species-level identification of group G streptococcal (GGS) isolates from companion animals in Japan and analyzed antimicrobial resistance (AMR) patterns. Strains were isolated from sterile and non-sterile specimens collected from 72 animals with clinical signs or symptoms in April-May, 2015. We identified the strain by 16S rRNA sequencing, mass spectrometry (MS), and an automated method based on their biochemical properties. Antimicrobial susceptibility was determined using the broth microdilution method and E-test. AMR determinants (erm(A), erm(B), mef(A), tet(M), tet(O), tet(K), tet(L), and tet(S)) in corresponding resistant isolates were amplified by PCR. The 16S rRNA sequencing identified the GGS species as Streptococcus canis (n = 68), Streptococcus dysgalactiae subsp. equisimilis (n = 3), and S. dysgalactiae subsp. dysgalactiae (n = 1). However, there were discrepancies between the sequencing data and both the MS and automated identification data. MS and the automated biochemical technique identified 18 and 37 of the 68 sequencing-identified S. canis strains, respectively. The AMR rates were 20.8% for tetracycline and 5.6% for clarithromycin, with minimum inhibitory concentrations (MIC) 50 -MIC 90 of 2-64 and ≤ 0.12-0.25μg/mL, respectively. AMR genotyping showed single or combined genotypes: erm(B) or tet(M)-tet(O)-tet(S). Our findings show the unique characteristics of GGS isolates from companion animals in Japan in terms of species-level identification and AMR patterns.

A primer to frequent itemset mining for bioinformatics

PubMed Central

Naulaerts, Stefan; Meysman, Pieter; Bittremieux, Wout; Vu, Trung Nghia; Vanden Berghe, Wim; Goethals, Bart

2015-01-01

Over the past two decades, pattern mining techniques have become an integral part of many bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining techniques designed to identify elements that frequently co-occur. An archetypical example is the identification of products that often end up together in the same shopping basket in supermarket transactions. A number of algorithms have been developed to address variations of this computationally non-trivial problem. Frequent itemset mining techniques are able to efficiently capture the characteristics of (complex) data and succinctly summarize it. Owing to these and other interesting properties, these techniques have proven their value in biological data analysis. Nevertheless, information about the bioinformatics applications of these techniques remains scattered. In this primer, we introduce frequent itemset mining and their derived association rules for life scientists. We give an overview of various algorithms, and illustrate how they can be used in several real-life bioinformatics application domains. We end with a discussion of the future potential and open challenges for frequent itemset mining in the life sciences. PMID:24162173

The role of chemometrics in single and sequential extraction assays: a review. Part II. Cluster analysis, multiple linear regression, mixture resolution, experimental design and other techniques.

PubMed

Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo

2011-03-04

Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.

Can dead man tooth do tell tales? Tooth prints in forensic identification.

PubMed

Christopher, Vineetha; Murthy, Sarvani; Ashwinirani, S R; Prasad, Kulkarni; Girish, Suragimath; Vinit, Shashikanth Patil

2017-01-01

We know that teeth trouble us a lot when we are alive, but they last longer for thousands of years even after we are dead. Teeth being the strongest and resistant structure are the most significant tool in forensic investigations. Patterns of enamel rod end on the tooth surface are known as tooth prints. This study is aimed to know whether these tooth prints can become a forensic tool in personal identification such as finger prints. A study has been targeted toward the same. In the present in-vivo study, acetate peel technique has been used to obtain the replica of enamel rod end patterns. Tooth prints of upper first premolars were recorded from 80 individuals after acid etching using cellulose acetate strips. Then, digital images of the tooth prints obtained at two different intervals were subjected to biometric conversion using Verifinger standard software development kit version 6.5 software followed by the use of Automated Fingerprint Identification System (AFIS) software for comparison of the tooth prints. Similarly, each individual's finger prints were also recorded and were subjected to the same software. Further, recordings of AFIS scores obtained from images were statistically analyzed using Cronbach's test. We observed that comparing two tooth prints taken from an individual at two intervals exhibited similarity in many cases, with wavy pattern tooth print being the predominant type. However, the same prints showed dissimilarity when compared with other individuals. We also found that most of the individuals with whorl pattern finger print showed wavy pattern tooth print and few loop type fingerprints showed linear pattern of tooth prints. Further more experiments on both tooth prints and finger prints are required in establishing an individual's identity.

Can dead man tooth do tell tales? Tooth prints in forensic identification

PubMed Central

Christopher, Vineetha; Murthy, Sarvani; Ashwinirani, S. R.; Prasad, Kulkarni; Girish, Suragimath; Vinit, Shashikanth Patil

2017-01-01

Background: We know that teeth trouble us a lot when we are alive, but they last longer for thousands of years even after we are dead. Teeth being the strongest and resistant structure are the most significant tool in forensic investigations. Patterns of enamel rod end on the tooth surface are known as tooth prints. Aim: This study is aimed to know whether these tooth prints can become a forensic tool in personal identification such as finger prints. A study has been targeted toward the same. Settings and Design: In the present in-vivo study, acetate peel technique has been used to obtain the replica of enamel rod end patterns. Materials and Methods: Tooth prints of upper first premolars were recorded from 80 individuals after acid etching using cellulose acetate strips. Then, digital images of the tooth prints obtained at two different intervals were subjected to biometric conversion using Verifinger standard software development kit version 6.5 software followed by the use of Automated Fingerprint Identification System (AFIS) software for comparison of the tooth prints. Similarly, each individual's finger prints were also recorded and were subjected to the same software. Statistical Analysis: Further, recordings of AFIS scores obtained from images were statistically analyzed using Cronbach's test. Results: We observed that comparing two tooth prints taken from an individual at two intervals exhibited similarity in many cases, with wavy pattern tooth print being the predominant type. However, the same prints showed dissimilarity when compared with other individuals. We also found that most of the individuals with whorl pattern finger print showed wavy pattern tooth print and few loop type fingerprints showed linear pattern of tooth prints. Conclusions: Further more experiments on both tooth prints and finger prints are required in establishing an individual's identity. PMID:28584483

An analysis of pilot error-related aircraft accidents

NASA Technical Reports Server (NTRS)

Kowalsky, N. B.; Masters, R. L.; Stone, R. B.; Babcock, G. L.; Rypka, E. W.

1974-01-01

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

Manta Matcher: automated photographic identification of manta rays using keypoint features.

PubMed

Town, Christopher; Marshall, Andrea; Sethasathien, Nutthaporn

2013-07-01

For species which bear unique markings, such as natural spot patterning, field work has become increasingly more reliant on visual identification to recognize and catalog particular specimens or to monitor individuals within populations. While many species of interest exhibit characteristic markings that in principle allow individuals to be identified from photographs, scientists are often faced with the task of matching observations against databases of hundreds or thousands of images. We present a novel technique for automated identification of manta rays (Manta alfredi and Manta birostris) by means of a pattern-matching algorithm applied to images of their ventral surface area. Automated visual identification has recently been developed for several species. However, such methods are typically limited to animals that can be photographed above water, or whose markings exhibit high contrast and appear in regular constellations. While manta rays bear natural patterning across their ventral surface, these patterns vary greatly in their size, shape, contrast, and spatial distribution. Our method is the first to have proven successful at achieving high matching accuracies on a large corpus of manta ray images taken under challenging underwater conditions. Our method is based on automated extraction and matching of keypoint features using the Scale-Invariant Feature Transform (SIFT) algorithm. In order to cope with the considerable variation in quality of underwater photographs, we also incorporate preprocessing and image enhancement steps. Furthermore, we use a novel pattern-matching approach that results in better accuracy than the standard SIFT approach and other alternative methods. We present quantitative evaluation results on a data set of 720 images of manta rays taken under widely different conditions. We describe a novel automated pattern representation and matching method that can be used to identify individual manta rays from photographs. The method has been incorporated into a website (mantamatcher.org) which will serve as a global resource for ecological and conservation research. It will allow researchers to manage and track sightings data to establish important life-history parameters as well as determine other ecological data such as abundance, range, movement patterns, and structure of manta ray populations across the world.

Manta Matcher: automated photographic identification of manta rays using keypoint features

PubMed Central

Town, Christopher; Marshall, Andrea; Sethasathien, Nutthaporn

2013-01-01

For species which bear unique markings, such as natural spot patterning, field work has become increasingly more reliant on visual identification to recognize and catalog particular specimens or to monitor individuals within populations. While many species of interest exhibit characteristic markings that in principle allow individuals to be identified from photographs, scientists are often faced with the task of matching observations against databases of hundreds or thousands of images. We present a novel technique for automated identification of manta rays (Manta alfredi and Manta birostris) by means of a pattern-matching algorithm applied to images of their ventral surface area. Automated visual identification has recently been developed for several species. However, such methods are typically limited to animals that can be photographed above water, or whose markings exhibit high contrast and appear in regular constellations. While manta rays bear natural patterning across their ventral surface, these patterns vary greatly in their size, shape, contrast, and spatial distribution. Our method is the first to have proven successful at achieving high matching accuracies on a large corpus of manta ray images taken under challenging underwater conditions. Our method is based on automated extraction and matching of keypoint features using the Scale-Invariant Feature Transform (SIFT) algorithm. In order to cope with the considerable variation in quality of underwater photographs, we also incorporate preprocessing and image enhancement steps. Furthermore, we use a novel pattern-matching approach that results in better accuracy than the standard SIFT approach and other alternative methods. We present quantitative evaluation results on a data set of 720 images of manta rays taken under widely different conditions. We describe a novel automated pattern representation and matching method that can be used to identify individual manta rays from photographs. The method has been incorporated into a website (mantamatcher.org) which will serve as a global resource for ecological and conservation research. It will allow researchers to manage and track sightings data to establish important life-history parameters as well as determine other ecological data such as abundance, range, movement patterns, and structure of manta ray populations across the world. PMID:23919138

Root System Water Consumption Pattern Identification on Time Series Data

PubMed Central

Figueroa, Manuel; Pope, Christopher

2017-01-01

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers’ detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system’s 0.348 precision. PMID:28621739

Root System Water Consumption Pattern Identification on Time Series Data.

PubMed

Figueroa, Manuel; Pope, Christopher

2017-06-16

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers' detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system's 0.348 precision.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

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

Identification of individual foothill yellow-legged frogs (Rana boylii) using chin pattern photographs: a non-invasive and effective method for small population studies

Treesearch

K.R. Marlow; K.D. Wiseman; Clara Wheeler; J.E.  Drennan; R.E.  Jackman

2016-01-01

The ability to identify individual animals is a valuable tool in the study of amphibian population dynamics, movement ecology, social behavior, and habitat use. Numerous methods of marking amphibians have been employed including the use of passive integrated transponder (PIT) tags, radio-transmitters, elastomers, branding, and mutilation techniques such as toe...

Detection and identification of illicit drugs using terahertz imaging

NASA Astrophysics Data System (ADS)

Lu, Meihong; Shen, Jingling; Li, Ning; Zhang, Yan; Zhang, Cunlin; Liang, Laishun; Xu, Xiaoyu

2006-11-01

We demonstrated an advanced terahertz imaging technique for detection and identification of illicit drugs by introducing the component spatial pattern analysis. As an explanation, the characteristic fingerprint spectra and refractive index of ketamine were first measured with terahertz time-domain spectroscopy both in the air and nitrogen. The results obtained in the ambient air indicated that some absorption peaks are not obvious or probably not dependable. It is necessary and important to present a more practical technique for the detection. The spatial distributions of several illicit drugs [3,4-methylenedioxymethamphetamine, methylenedioxyamphetamine, heroin, acetylcodeine, morphine, and ketamine], widely consumed in the world, were obtained from terahertz images using absorption spectra previously measured in the range from 0.2to2.6THz in the ambient air. The different kinds of pure illicit drugs hidden in mail envelopes were inspected and identified. It could be an effective method in the field of safety inspection.

Observation and discrimination of the mode patterns in a micron-sized hollow optical fiber and its synthetic measurements: far-field micro-imaging technique

NASA Astrophysics Data System (ADS)

Yin, Jianping; Kim, Kihwan; Shim, Wooshik; Zhu, Yifu; Jhe, Wonho

1998-08-01

We report a far-field micro-imaging technique that is used for the observation and discrimination of the mode patterns in a micron-sized hollow optical fiber as well as for the synthetic measurement of the fiber. By using an M-20X microscope objective lens, we obtained images, magnified by a factor of about 460, from the mode patterns at an output end facet of the hollow fiber with relative measurement accuracy better than 3%. This method can be used for clear identification of the mode patterns in the hollow fiber and detailed study of the relationship between the excitation conditions and the excited modes in the hollow fiber. Moreover, it is useful for the measurement of the geometrical sizes of the hollow fiber end and for testing the coupling efficiencies of the core and cladding modes in their mixed mode pattern. In addition, this method can be also used in the generation of a dark hollow laser beam with 10-micrometers dark-spot size and the measurement of the focused- spot size of a Gaussian laser beam with about 1-micrometers diameter.

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Isoschizomers and amplified fragment length polymorphism for the detection of specific cytosine methylation changes.

PubMed

Ruiz-García, Leonor; Cabezas, Jose Antonio; de María, Nuria; Cervera, María-Teresa

2010-01-01

Different molecular techniques have been developed to study either the global level of methylated cytosines or methylation at specific gene sequences. One of them is a modification of the Amplified Fragment Length Polymorphism (AFLP) technique that has been used to study methylation of anonymous CCGG sequences in different fungi, plant and animal species. The main variation of this technique is based on the use of isoschizomers with different methylation sensitivity (such as HpaII and MspI) as a frequent cutter restriction enzyme. For each sample, AFLP analysis is performed using both EcoRI/HpaII and EcoRI/MspI digested samples. Comparative analysis between EcoRI/HpaII and EcoRI/MspI fragment patterns allows the identification of two types of polymorphisms: (1) "Methylation-insensitive polymorphisms" that show common EcoRI/HpaII and EcoRI/MspI patterns but are detected as polymorphic amplified fragments among samples; and (2) "Methylation-sensitive polymorphisms" that are associated with amplified fragments differing in their presence or absence or in their intensity between EcoRI/HpaII and EcoRI/MspI patterns. This chapter describes a detailed protocol of this technique and discusses modifications that can be applied to adjust the technology to different species of interest.

Beyond the ridge pattern: multi-informative analysis of latent fingermarks by MALDI mass spectrometry.

PubMed

Francese, S; Bradshaw, R; Ferguson, L S; Wolstenholme, R; Clench, M R; Bleay, S

2013-08-07

After over a century, fingerprints are still one of the most powerful means of biometric identification. The conventional forensic workflow for suspect identification consists of (i) recovering latent marks from crime scenes using the appropriate enhancement technique and (ii) obtaining an image of the mark to compare either against known suspect prints and/or to search in a Fingerprint Database. The suspect is identified through matching the ridge pattern and local characteristics of the ridge pattern (minutiae). However successful, there are a number of scenarios in which this process may fail; they include the recovery of partial, distorted or smudged marks, poor quality of the image resulting from inadequacy of the enhancement technique applied, extensive scarring/abrasion of the fingertips or absence of suspect's fingerprint records in the database. In all of these instances it would be very desirable to have a technology able to provide additional information from a fingermark exploiting its endogenous and exogenous chemical content. This opportunity could potentially provide new investigative leads, especially when the fingermark comparison and match process fails. We have demonstrated that Matrix Assisted Laser Desorption Ionisation Mass Spectrometry and Mass Spectrometry Imaging (MALDI MSI) can provide multiple images of the same fingermark in one analysis simultaneous with additional intelligence. Here, a review on the pioneering use and development of MALDI MSI for the analysis of latent fingermarks is presented along with the latest achievements on the forensic intelligence retrievable.

Classifying and modelling spiral structures in hydrodynamic simulations of astrophysical discs

NASA Astrophysics Data System (ADS)

Forgan, D. H.; Ramón-Fox, F. G.; Bonnell, I. A.

2018-05-01

We demonstrate numerical techniques for automatic identification of individual spiral arms in hydrodynamic simulations of astrophysical discs. Building on our earlier work, which used tensor classification to identify regions that were `spiral-like', we can now obtain fits to spirals for individual arm elements. We show this process can even detect spirals in relatively flocculent spiral patterns, but the resulting fits to logarithmic `grand-design' spirals are less robust. Our methods not only permit the estimation of pitch angles, but also direct measurements of the spiral arm width and pattern speed. In principle, our techniques will allow the tracking of material as it passes through an arm. Our demonstration uses smoothed particle hydrodynamics simulations, but we stress that the method is suitable for any finite-element hydrodynamics system. We anticipate our techniques will be essential to studies of star formation in disc galaxies, and attempts to find the origin of recently observed spiral structure in protostellar discs.

Application of holography to flow visualization within rotating compressor blade row. [to determine three dimensional shock patterns

NASA Technical Reports Server (NTRS)

Wuerker, R. F.; Kobayashi, R. J.; Heflinger, L. O.; Ware, T. C.

1974-01-01

Two holographic interblade row flow visualization systems were designed to determine the three-dimensional shock patterns and velocity distributions within the rotating blade row of a transonic fan rotor, utilizing the techniques of pulsed laser transmission holography. Both single- and double-exposure bright field holograms and dark field scattered-light holograms were successfully recorded. Two plastic windows were installed in the rotor tip casing and outer casing forward of the rotor to view the rotor blade passage. The viewing angle allowed detailed investigation of the leading edge shocks and shocks in the midspan damper area; limited details of the trailing edge shocks also were visible. A technique was devised for interpreting the reconstructed holograms by constructing three dimensional models that allowed identification of the major shock systems. The models compared favorably with theoretical predictions and results of the overall and blade element data. Most of the holograms were made using the rapid double-pulse technique.

Development of automated optical verification technologies for control systems

NASA Astrophysics Data System (ADS)

Volegov, Peter L.; Podgornov, Vladimir A.

1999-08-01

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

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues.

PubMed

Mangeot-Peter, Lauralie; Legay, Sylvain; Hausman, Jean-Francois; Esposito, Sergio; Guerriero, Gea

2016-09-15

Gene expression profiling via quantitative real-time PCR is a robust technique widely used in the life sciences to compare gene expression patterns in, e.g., different tissues, growth conditions, or after specific treatments. In the field of plant science, real-time PCR is the gold standard to study the dynamics of gene expression and is used to validate the results generated with high throughput techniques, e.g., RNA-Seq. An accurate relative quantification of gene expression relies on the identification of appropriate reference genes, that need to be determined for each experimental set-up used and plant tissue studied. Here, we identify suitable reference genes for expression profiling in stems of textile hemp (Cannabis sativa L.), whose tissues (isolated bast fibres and core) are characterized by remarkable differences in cell wall composition. We additionally validate the reference genes by analysing the expression of putative candidates involved in the non-oxidative phase of the pentose phosphate pathway and in the first step of the shikimate pathway. The goal is to describe the possible regulation pattern of some genes involved in the provision of the precursors needed for lignin biosynthesis in the different hemp stem tissues. The results here shown are useful to design future studies focused on gene expression analyses in hemp.

Evaluation of fingerprint deformation using optical coherence tomography

NASA Astrophysics Data System (ADS)

Gutierrez da Costa, Henrique S.; Maxey, Jessica R.; Silva, Luciano; Ellerbee, Audrey K.

2014-02-01

Biometric identification systems have important applications to privacy and security. The most widely used of these, print identification, is based on imaging patterns present in the fingers, hands and feet that are formed by the ridges, valleys and pores of the skin. Most modern print sensors acquire images of the finger when pressed against a sensor surface. Unfortunately, this pressure may result in deformations, characterized by changes in the sizes and relative distances of the print patterns, and such changes have been shown to negatively affect the performance of fingerprint identification algorithms. Optical coherence tomography (OCT) is a novel imaging technique that is capable of imaging the subsurface of biological tissue. Hence, OCT may be used to obtain images of subdermal skin structures from which one can extract an internal fingerprint. The internal fingerprint is very similar in structure to the commonly used external fingerprint and is of increasing interest in investigations of identify fraud. We proposed and tested metrics based on measurements calculated from external and internal fingerprints to evaluate the amount of deformation of the skin. Such metrics were used to test hypotheses about the differences of deformation between the internal and external images, variations with the type of finger and location inside the fingerprint.

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

DOEpatents

Zheng, Yufeng

2014-12-23

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

Directed nucleation assembly of DNA tile complexes for barcode-patterned lattices

NASA Astrophysics Data System (ADS)

Yan, Hao; Labean, Thomas H.; Feng, Liping; Reif, John H.

2003-07-01

The programmed self-assembly of patterned aperiodic molecular structures is a major challenge in nanotechnology and has numerous potential applications for nanofabrication of complex structures and useful devices. Here we report the construction of an aperiodic patterned DNA lattice (barcode lattice) by a self-assembly process of directed nucleation of DNA tiles around a scaffold DNA strand. The input DNA scaffold strand, constructed by ligation of shorter synthetic oligonucleotides, provides layers of the DNA lattice with barcode patterning information represented by the presence or absence of DNA hairpin loops protruding out of the lattice plane. Self-assembly of multiple DNA tiles around the scaffold strand was shown to result in a patterned lattice containing barcode information of 01101. We have also demonstrated the reprogramming of the system to another patterning. An inverted barcode pattern of 10010 was achieved by modifying the scaffold strands and one of the strands composing each tile. A ribbon lattice, consisting of repetitions of the barcode pattern with expected periodicity, was also constructed by the addition of sticky ends. The patterning of both classes of lattices was clearly observable via atomic force microscopy. These results represent a step toward implementation of a visual readout system capable of converting information encoded on a 1D DNA strand into a 2D form readable by advanced microscopic techniques. A functioning visual output method would not only increase the readout speed of DNA-based computers, but may also find use in other sequence identification techniques such as mutation or allele mapping.

Directed nucleation assembly of DNA tile complexes for barcode-patterned lattices.

PubMed

Yan, Hao; LaBean, Thomas H; Feng, Liping; Reif, John H

2003-07-08

The programmed self-assembly of patterned aperiodic molecular structures is a major challenge in nanotechnology and has numerous potential applications for nanofabrication of complex structures and useful devices. Here we report the construction of an aperiodic patterned DNA lattice (barcode lattice) by a self-assembly process of directed nucleation of DNA tiles around a scaffold DNA strand. The input DNA scaffold strand, constructed by ligation of shorter synthetic oligonucleotides, provides layers of the DNA lattice with barcode patterning information represented by the presence or absence of DNA hairpin loops protruding out of the lattice plane. Self-assembly of multiple DNA tiles around the scaffold strand was shown to result in a patterned lattice containing barcode information of 01101. We have also demonstrated the reprogramming of the system to another patterning. An inverted barcode pattern of 10010 was achieved by modifying the scaffold strands and one of the strands composing each tile. A ribbon lattice, consisting of repetitions of the barcode pattern with expected periodicity, was also constructed by the addition of sticky ends. The patterning of both classes of lattices was clearly observable via atomic force microscopy. These results represent a step toward implementation of a visual readout system capable of converting information encoded on a 1D DNA strand into a 2D form readable by advanced microscopic techniques. A functioning visual output method would not only increase the readout speed of DNA-based computers, but may also find use in other sequence identification techniques such as mutation or allele mapping.

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

NASA Astrophysics Data System (ADS)

Lwin, A.; Khaing, M. M.

2012-07-01

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

Identification of Malicious Web Pages by Inductive Learning

NASA Astrophysics Data System (ADS)

Liu, Peishun; Wang, Xuefang

Malicious web pages are an increasing threat to current computer systems in recent years. Traditional anti-virus techniques focus typically on detection of the static signatures of Malware and are ineffective against these new threats because they cannot deal with zero-day attacks. In this paper, a novel classification method for detecting malicious web pages is presented. This method is generalization and specialization of attack pattern based on inductive learning, which can be used for updating and expanding knowledge database. The attack pattern is established from an example and generalized by inductive learning, which can be used to detect unknown attacks whose behavior is similar to the example.

Biomarker patterns in present-day vegetation: consistency and variation - A study on plaggen soils

NASA Astrophysics Data System (ADS)

Kirkels, Frédérique; Jansen, Boris; Kalbitz, Karsten

2013-04-01

Biomarker patterns in present-day vegetation are commonly used as proxies to reconstruct paleo-vegetation composition, land use history and to elucidate carbon cycling. Plaggen soils are formed by diverse vegetational inputs during century-long plaggen (i.e. sod) application associated with plaggen-agriculture on poor soils in north-western Europe. This resulted in remarkably stable organic matter. Plant source identification by biomarkers could provide insight in yet unknown stabilization mechanisms and the fate of organic matter upon ongoing land use change. The current rationale behind biomarker-based source identification is that patterns observed in present-day vegetation are generally representative with little random variation. However, our knowledge on variability and consistency of biomarker patterns is yet scarce. Therefore, to assess the applicability of biomarkers for source identification in plaggen soils, we analyzed published n-alkane and n-alcohol patterns of species and their various parts which contribute(d) input to plaggen soils. We considered shrubs, trees and grass species and evaluated rescaled patterns (i.e. relative abundances in chain-length range C17-36), odd-over-even predominance (OEP) and predominant n-alkanes. In addition, we explicitly looked into potential sources of systematic variation, e.g. spatial variation (climate, site conditions), temporal variation (seasonality, ontogeny) and laboratory methodology (extraction technique: washing/shaking, Soxhlet/ASE, saponification). We found meaningful clustering of n-alkanes C27, C29, C31 and C33, allowing for clear distinction of input by shrubs, trees and grasses to plaggen soils. Combination of these homologues with complete n-alkane patterns (C17-36) and OEP enabled further differentiation, while n-alcohols patterns were less distinct. Current limitation is the lack of extended and diverse quantitative records on biomarker patterns, especially for n-alcohols, non-leaf and belowground tissues, which hindered full statistical analysis. On species level we also recognized outliers and spreading. Systematic variation was indicated among tree species according to spatial conditions and by ontogeny. Yet, observed effects were ambiguous for other variation sources. This study highlights clear opportunities for application of biomarker patterns for source identification and elucidation of stabilization processes in (plaggen) soils. At the same time, application is challenged by systematic variation. Further research is key to quantify controls, magnitude and potential correction factors for such systematic variation. This would validate the use of n-alkane and n-alcohol patterns across broad spatial and temporal scales or identify boundaries wherein their consistency is ensured. Likely, these challenges apply to vegetation in a broad perspective, transcending plaggen vegetation, as assessment and application of present-day vegetation patterns is emerging.

UPLC/Q-TOFMS/MS as a powerful technique for rapid identification of polymethoxylated flavones in Fructus aurantii.

PubMed

Zhou, Da-Yong; Zhang, Xiu-Li; Xu, Qing; Xue, Xing-Ya; Zhang, Fei-Fang; Liang, Xin-Miao

2009-08-15

Polymethoxylated flavones (PMFs), as potential cancer chemopreventive agents, are widely distributed in Citrus genus. In this study, a selected ion monitoring-tandem mass (SIM-MS/MS) method for the rapid identification of PMFs in Fructus aurantii (F. aurantii) with ultra-performance liquid chromatography (UPLC) coupled to quadrupole, hybrid orthogonal acceleration time-of-flight tandem mass spectrometer (Q-TOFMS/MS) was proposed. The MS data for candidates, containing accurate mass and isotopic patterns for both precursors and their fragment ions, were acquired selectively. Based on the MS data, the mass spectrometric fingerprint (MSFP) for candidates, consisting of chemical formula and dissociation pattern, was determined. Comparing the MSFPs of the observed compounds with the diagnostic MSFP of the species, 44 PMFs were tentatively identified. The method was validated by tangeretin and sinensetin, two representative compounds of PMFs, and was considered to be suitable for the rapid screening of PMFs in crude and partially purified samples.

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

PubMed

Malin, Bradley; Sweeney, Latanya

2004-06-01

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

Use of reciprocal lattice layer spacing in electron backscatter diffraction pattern analysis

PubMed

Michael; Eades

2000-03-01

In the scanning electron microscope using electron backscattered diffraction, it is possible to measure the spacing of the layers in the reciprocal lattice. These values are of great use in confirming the identification of phases. The technique derives the layer spacing from the higher-order Laue zone rings which appear in patterns from many materials. The method adapts results from convergent-beam electron diffraction in the transmission electron microscope. For many materials the measured layer spacing compares well with the calculated layer spacing. A noted exception is for higher atomic number materials. In these cases an extrapolation procedure is described that requires layer spacing measurements at a range of accelerating voltages. This procedure is shown to improve the accuracy of the technique significantly. The application of layer spacing measurements in EBSD is shown to be of use for the analysis of two polytypes of SiC.

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

Logical Framework of Forensic Identification: Ability to Resist Fabricated DNA.

PubMed

Wang, Zheng; Zhou, Di; Zhang, Suhua; Bian, Yingnan; Hu, Zhen; Zhu, Ruxin; Lu, Daru; Li, Chengtao

2015-12-01

Over the past 30 years, DNA analysis has revolutionized forensic science and has become the most useful single tool in the multifaceted fight against crime. Today, DNA profiling with sets of highly polymorphic autosomal short tandem repeat markers is widely employed and accepted in the courts due to its high discriminating power and reliability. However, an artificial bloodstain purposefully created using molecular biology techniques succeeded in tricking a leading forensic DNA laboratory. The disturbing possibility that a forensic DNA profile can be faked shocked the general public and the mass media, and generated serious discussion about the credibility of DNA evidence. Herein, we present two exemplary assays based on tissue-specific methylation patterns and cell-specific mRNA expression, respectively. These two assays can be integrated into the DNA analysis pipelines without consumption of additional samples. We show that the two assays can not only distinguish between artificial and genuine samples, but also provide information on tissue origin. The two assays were tested on natural and artificial bloodstains (generated by polymerase chain reaction and whole genome amplification technique) and the results illustrated that the logical framework of forensic identification is still useful for forensic identification with the high credibility.

Genetic fingerprinting proves cross-correlated automatic photo-identification of individuals as highly efficient in large capture–mark–recapture studies

PubMed Central

Drechsler, Axel; Helling, Tobias; Steinfartz, Sebastian

2015-01-01

Capture–mark–recapture (CMR) approaches are the backbone of many studies in population ecology to gain insight on the life cycle, migration, habitat use, and demography of target species. The reliable and repeatable recognition of an individual throughout its lifetime is the basic requirement of a CMR study. Although invasive techniques are available to mark individuals permanently, noninvasive methods for individual recognition mainly rest on photographic identification of external body markings, which are unique at the individual level. The re-identification of an individual based on comparing shape patterns of photographs by eye is commonly used. Automated processes for photographic re-identification have been recently established, but their performance in large datasets (i.e., > 1000 individuals) has rarely been tested thoroughly. Here, we evaluated the performance of the program AMPHIDENT, an automatic algorithm to identify individuals on the basis of ventral spot patterns in the great crested newt (Triturus cristatus) versus the genotypic fingerprint of individuals based on highly polymorphic microsatellite loci using GENECAP. Between 2008 and 2010, we captured, sampled and photographed adult newts and calculated for 1648 samples/photographs recapture rates for both approaches. Recapture rates differed slightly with 8.34% for GENECAP and 9.83% for AMPHIDENT. With an estimated rate of 2% false rejections (FRR) and 0.00% false acceptances (FAR), AMPHIDENT proved to be a highly reliable algorithm for CMR studies of large datasets. We conclude that the application of automatic recognition software of individual photographs can be a rather powerful and reliable tool in noninvasive CMR studies for a large number of individuals. Because the cross-correlation of standardized shape patterns is generally applicable to any pattern that provides enough information, this algorithm is capable of becoming a single application with broad use in CMR studies for many species. PMID:25628871

In vivo drug metabolite identification in preclinical ADME studies by means of UPLC/TWIMS/high resolution-QTOF MS(E) and control comparison: cost and benefit of vehicle-dosed control samples.

PubMed

Fiebig, Lukas; Laux, Ralf; Binder, Rudolf; Ebner, Thomas

2016-10-01

1. Liquid chromatography (LC)-high resolution mass spectrometry (HRMS) techniques proved to be well suited for the identification of predicted and unexpected drug metabolites in complex biological matrices. 2. To efficiently discriminate between drug-related and endogenous matrix compounds, however, sophisticated postacquisition data mining tools, such as control comparison techniques are needed. For preclinical absorption, distribution, metabolism and excretion (ADME) studies that usually lack a placebo-dosed control group, the question arises how high-quality control data can be yielded using only a minimum number of control animals. 3. In the present study, the combination of LC-traveling wave ion mobility separation (TWIMS)-HRMS(E) and multivariate data analysis was used to study the polymer patterns of the frequently used formulation constituents polyethylene glycol 400 and polysorbate 80 in rat plasma and urine after oral and intravenous administration, respectively. 4. Complex peak patterns of both constituents were identified underlining the general importance of a vehicle-dosed control group in ADME studies for control comparison. Furthermore, the detailed analysis of administration route, blood sampling time and gender influences on both vehicle peak pattern as well as endogenous matrix background revealed that high-quality control data is obtained when (i) control animals receive an intravenous dose of the vehicle, (ii) the blood sampling time point is the same for analyte and control sample and (iii) analyte and control samples of the same gender are compared.

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.

Interpretation of biological and mechanical variations between the Lowry versus Bradford method for protein quantification.

PubMed

Lu, Tzong-Shi; Yiao, Szu-Yu; Lim, Kenneth; Jensen, Roderick V; Hsiao, Li-Li

2010-07-01

The identification of differences in protein expression resulting from methodical variations is an essential component to the interpretation of true, biologically significant results. We used the Lowry and Bradford methods- two most commonly used methods for protein quantification, to assess whether differential protein expressions are a result of true biological or methodical variations. MATERIAL #ENTITYSTARTX00026; Differential protein expression patterns was assessed by western blot following protein quantification by the Lowry and Bradford methods. We have observed significant variations in protein concentrations following assessment with the Lowry versus Bradford methods, using identical samples. Greater variations in protein concentration readings were observed over time and in samples with higher concentrations, with the Bradford method. Identical samples quantified using both methods yielded significantly different expression patterns on Western blot. We show for the first time that methodical variations observed in these protein assay techniques, can potentially translate into differential protein expression patterns, that can be falsely taken to be biologically significant. Our study therefore highlights the pivotal need to carefully consider methodical approaches to protein quantification in techniques that report quantitative differences.

The search for a hippocampal engram.

PubMed

Mayford, Mark

2014-01-05

Understanding the molecular and cellular changes that underlie memory, the engram, requires the identification, isolation and manipulation of the neurons involved. This presents a major difficulty for complex forms of memory, for example hippocampus-dependent declarative memory, where the participating neurons are likely to be sparse, anatomically distributed and unique to each individual brain and learning event. In this paper, I discuss several new approaches to this problem. In vivo calcium imaging techniques provide a means of assessing the activity patterns of large numbers of neurons over long periods of time with precise anatomical identification. This provides important insight into how the brain represents complex information and how this is altered with learning. The development of techniques for the genetic modification of neural ensembles based on their natural, sensory-evoked, activity along with optogenetics allows direct tests of the coding function of these ensembles. These approaches provide a new methodological framework in which to examine the mechanisms of complex forms of learning at the level of the neurons involved in a specific memory.

The search for a hippocampal engram

PubMed Central

Mayford, Mark

2014-01-01

Understanding the molecular and cellular changes that underlie memory, the engram, requires the identification, isolation and manipulation of the neurons involved. This presents a major difficulty for complex forms of memory, for example hippocampus-dependent declarative memory, where the participating neurons are likely to be sparse, anatomically distributed and unique to each individual brain and learning event. In this paper, I discuss several new approaches to this problem. In vivo calcium imaging techniques provide a means of assessing the activity patterns of large numbers of neurons over long periods of time with precise anatomical identification. This provides important insight into how the brain represents complex information and how this is altered with learning. The development of techniques for the genetic modification of neural ensembles based on their natural, sensory-evoked, activity along with optogenetics allows direct tests of the coding function of these ensembles. These approaches provide a new methodological framework in which to examine the mechanisms of complex forms of learning at the level of the neurons involved in a specific memory. PMID:24298162

Doppler Feature Based Classification of Wind Profiler Data

NASA Astrophysics Data System (ADS)

Sinha, Swati; Chandrasekhar Sarma, T. V.; Lourde. R, Mary

2017-01-01

Wind Profilers (WP) are coherent pulsed Doppler radars in UHF and VHF bands. They are used for vertical profiling of wind velocity and direction. This information is very useful for weather modeling, study of climatic patterns and weather prediction. Observations at different height and different wind velocities are possible by changing the operating parameters of WP. A set of Doppler power spectra is the standard form of WP data. Wind velocity, direction and wind velocity turbulence at different heights can be derived from it. Modern wind profilers operate for long duration and generate approximately 4 megabytes of data per hour. The radar data stream contains Doppler power spectra from different radar configurations with echoes from different atmospheric targets. In order to facilitate systematic study, this data needs to be segregated according the type of target. A reliable automated target classification technique is required to do this job. Classical techniques of radar target identification use pattern matching and minimization of mean squared error, Euclidean distance etc. These techniques are not effective for the classification of WP echoes, as these targets do not have well-defined signature in Doppler power spectra. This paper presents an effective target classification technique based on range-Doppler features.

Advanced neuroimaging techniques for the term newborn with encephalopathy.

PubMed

Chau, Vann; Poskitt, Kenneth John; Miller, Steven Paul

2009-03-01

Neonatal encephalopathy is associated with a high risk of morbidity and mortality in the neonatal period and of long-term neurodevelopmental disability in survivors. Advanced magnetic resonance techniques now play a major role in the clinical care of newborns with encephalopathy and in research addressing this important condition. From conventional magnetic resonance imaging, typical patterns of injury have been defined in neonatal encephalopathy. When applied in contemporary cohorts of newborns with encephalopathy, the patterns of brain injury on magnetic resonance imaging distinguish risk factors, clinical presentation, and risk of abnormal outcome. Advanced magnetic resonance techniques such as magnetic resonance spectroscopy, diffusion-weighted imaging, and diffusion tensor imaging provide novel perspectives on neonatal brain metabolism, microstructure, and connectivity. With the application of these imaging tools, it is increasingly apparent that brain injury commonly occurs at or near the time of birth and evolves over the first weeks of life. These observations have complemented findings from trials of emerging strategies of brain protection, such as hypothermia. Application of these advanced magnetic resonance techniques may enable the earliest possible identification of newborns at risk of neurodevelopmental impairment, thereby ensuring appropriate follow-up with rehabilitation and psychoeducational resources.

Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

DTIC Science & Technology

2015-12-31

AFRL-RQ-WP-TP-2016-0079 FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING NEURAL NETWORKS (POSTPRINT) Abdeel J...Journal Article Postprint 01 October 2013 – 22 June 2015 4. TITLE AND SUBTITLE FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING...networks were used to automatically identify two-phase flow patterns for refrigerant R-134a flowing in a horizontal tube. In laboratory experiments

Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

PubMed

Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

2018-04-20

Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

Combined point and distributed techniques for multidimensional estimation of spatial groundwater-stream water exchange in a heterogeneous sand bed-stream.

NASA Astrophysics Data System (ADS)

Gaona Garcia, J.; Lewandowski, J.; Bellin, A.

2017-12-01

Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.

Palatal rugae pattern: An aid for sex identification

PubMed Central

Gadicherla, Prahlad; Saini, Divya; Bhaskar, Milana

2017-01-01

Background: Palatal rugoscopy, or palatoscopy, is the process by which human identification can be obtained by inspecting the transverse palatal rugae inside the mouth. Aim: The aim of the study is to investigate the potential of using palatal rugae as an aid for sex identification in Bengaluru population. Materials and Methods: One hundred plaster casts equally distributed between males and females belonging to age range of 4–16 years were examined for different rugae patterns. Thomas and Kotze classification was adopted for identification of these rugae patterns. Statistical Analysis: The data obtained were subjected to discriminant function analysis to determine the applicability of palatal rugae pattern as an aid for sex identification. Results: Difference in unification patterns among males and females was found to be statistically significant. No significant difference was found between males and females in terms of number of rugae. Overall, wavy and curvy were the most predominant type of rugae seen. Discriminant function analysis enabled sex identification with an accuracy of 80%. Conclusion: This preliminary study undertaken showed the existence of a distinct pattern of distribution of palatal rugae between males and females of Bengaluru population. This study opens scope for further research with a larger sample size to establish palatal rugae as a valuable tool for sex identification for forensic purposes. PMID:28584485

Directed nucleation assembly of DNA tile complexes for barcode-patterned lattices

PubMed Central

Yan, Hao; LaBean, Thomas H.; Feng, Liping; Reif, John H.

2003-01-01

The programmed self-assembly of patterned aperiodic molecular structures is a major challenge in nanotechnology and has numerous potential applications for nanofabrication of complex structures and useful devices. Here we report the construction of an aperiodic patterned DNA lattice (barcode lattice) by a self-assembly process of directed nucleation of DNA tiles around a scaffold DNA strand. The input DNA scaffold strand, constructed by ligation of shorter synthetic oligonucleotides, provides layers of the DNA lattice with barcode patterning information represented by the presence or absence of DNA hairpin loops protruding out of the lattice plane. Self-assembly of multiple DNA tiles around the scaffold strand was shown to result in a patterned lattice containing barcode information of 01101. We have also demonstrated the reprogramming of the system to another patterning. An inverted barcode pattern of 10010 was achieved by modifying the scaffold strands and one of the strands composing each tile. A ribbon lattice, consisting of repetitions of the barcode pattern with expected periodicity, was also constructed by the addition of sticky ends. The patterning of both classes of lattices was clearly observable via atomic force microscopy. These results represent a step toward implementation of a visual readout system capable of converting information encoded on a 1D DNA strand into a 2D form readable by advanced microscopic techniques. A functioning visual output method would not only increase the readout speed of DNA-based computers, but may also find use in other sequence identification techniques such as mutation or allele mapping. PMID:12821776

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

Collective behaviour across animal species.

PubMed

DeLellis, Pietro; Polverino, Giovanni; Ustuner, Gozde; Abaid, Nicole; Macrì, Simone; Bollt, Erik M; Porfiri, Maurizio

2014-01-16

We posit a new geometric perspective to define, detect, and classify inherent patterns of collective behaviour across a variety of animal species. We show that machine learning techniques, and specifically the isometric mapping algorithm, allow the identification and interpretation of different types of collective behaviour in five social animal species. These results offer a first glimpse at the transformative potential of machine learning for ethology, similar to its impact on robotics, where it enabled robots to recognize objects and navigate the environment.

Identification and Antimicrobial Susceptibility Testing of Anaerobic Bacteria: Rubik’s Cube of Clinical Microbiology?

PubMed Central

Gajdács, Márió; Spengler, Gabriella; Urbán, Edit

2017-01-01

Anaerobic bacteria have pivotal roles in the microbiota of humans and they are significant infectious agents involved in many pathological processes, both in immunocompetent and immunocompromised individuals. Their isolation, cultivation and correct identification differs significantly from the workup of aerobic species, although the use of new technologies (e.g., matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, whole genome sequencing) changed anaerobic diagnostics dramatically. In the past, antimicrobial susceptibility of these microorganisms showed predictable patterns and empirical therapy could be safely administered but recently a steady and clear increase in the resistance for several important drugs (β-lactams, clindamycin) has been observed worldwide. For this reason, antimicrobial susceptibility testing of anaerobic isolates for surveillance purposes or otherwise is of paramount importance but the availability of these testing methods is usually limited. In this present review, our aim was to give an overview of the methods currently available for the identification (using phenotypic characteristics, biochemical testing, gas-liquid chromatography, MALDI-TOF MS and WGS) and antimicrobial susceptibility testing (agar dilution, broth microdilution, disk diffusion, gradient tests, automated systems, phenotypic and molecular resistance detection techniques) of anaerobes, when should these methods be used and what are the recent developments in resistance patterns of anaerobic bacteria. PMID:29112122

Identification and Antimicrobial Susceptibility Testing of Anaerobic Bacteria: Rubik's Cube of Clinical Microbiology?

PubMed

Gajdács, Márió; Spengler, Gabriella; Urbán, Edit

2017-11-07

Anaerobic bacteria have pivotal roles in the microbiota of humans and they are significant infectious agents involved in many pathological processes, both in immunocompetent and immunocompromised individuals. Their isolation, cultivation and correct identification differs significantly from the workup of aerobic species, although the use of new technologies (e.g., matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, whole genome sequencing) changed anaerobic diagnostics dramatically. In the past, antimicrobial susceptibility of these microorganisms showed predictable patterns and empirical therapy could be safely administered but recently a steady and clear increase in the resistance for several important drugs (β-lactams, clindamycin) has been observed worldwide. For this reason, antimicrobial susceptibility testing of anaerobic isolates for surveillance purposes or otherwise is of paramount importance but the availability of these testing methods is usually limited. In this present review, our aim was to give an overview of the methods currently available for the identification (using phenotypic characteristics, biochemical testing, gas-liquid chromatography, MALDI-TOF MS and WGS) and antimicrobial susceptibility testing (agar dilution, broth microdilution, disk diffusion, gradient tests, automated systems, phenotypic and molecular resistance detection techniques) of anaerobes, when should these methods be used and what are the recent developments in resistance patterns of anaerobic bacteria.

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

NASA Astrophysics Data System (ADS)

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

2006-10-01

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

Identification and classification of failure modes in laminated composites by using a multivariate statistical analysis of wavelet coefficients

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2017-11-01

Acoustic Emission (AE) is a suitable method to monitor the health of composite structures in real-time. However, AE-based failure mode identification and classification are still complex to apply due to the fact that AE waves are generally released simultaneously from all AE-emitting damage sources. Hence, the use of advanced signal processing techniques in combination with pattern recognition approaches is required. In this paper, AE signals generated from laminated carbon fiber reinforced polymer (CFRP) subjected to indentation test are examined and analyzed. A new pattern recognition approach involving a number of processing steps able to be implemented in real-time is developed. Unlike common classification approaches, here only CWT coefficients are extracted as relevant features. Firstly, Continuous Wavelet Transform (CWT) is applied to the AE signals. Furthermore, dimensionality reduction process using Principal Component Analysis (PCA) is carried out on the coefficient matrices. The PCA-based feature distribution is analyzed using Kernel Density Estimation (KDE) allowing the determination of a specific pattern for each fault-specific AE signal. Moreover, waveform and frequency content of AE signals are in depth examined and compared with fundamental assumptions reported in this field. A correlation between the identified patterns and failure modes is achieved. The introduced method improves the damage classification and can be used as a non-destructive evaluation tool.

Classification of crystal structure using a convolutional neural network

PubMed Central

Park, Woon Bae; Chung, Jiyong; Sohn, Keemin; Pyo, Myoungho

2017-01-01

A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture. The CNN interprets features that humans cannot recognize in a powder XRD pattern. As a result, accuracy levels of 81.14, 83.83 and 94.99% were achieved for the space-group, extinction-group and crystal-system classifications, respectively. The well trained CNN was then used for symmetry identification of unknown novel inorganic compounds. PMID:28875035

Classification of crystal structure using a convolutional neural network.

PubMed

Park, Woon Bae; Chung, Jiyong; Jung, Jaeyoung; Sohn, Keemin; Singh, Satendra Pal; Pyo, Myoungho; Shin, Namsoo; Sohn, Kee-Sun

2017-07-01

A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture. The CNN interprets features that humans cannot recognize in a powder XRD pattern. As a result, accuracy levels of 81.14, 83.83 and 94.99% were achieved for the space-group, extinction-group and crystal-system classifications, respectively. The well trained CNN was then used for symmetry identification of unknown novel inorganic compounds.

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

PubMed

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

2017-09-01

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

Application of gray level mapping in computed tomographic colonography: a pilot study to compare with traditional surface rendering method for identification and differentiation of endoluminal lesions

PubMed Central

Chen, Lih-Shyang; Hsu, Ta-Wen; Chang, Shu-Han; Lin, Chih-Wen; Chen, Yu-Ruei; Hsieh, Chin-Chiang; Han, Shu-Chen; Chang, Ku-Yaw; Hou, Chun-Ju

2017-01-01

Objective: In traditional surface rendering (SR) computed tomographic endoscopy, only the shape of endoluminal lesion is depicted without gray-level information unless the volume rendering technique is used. However, volume rendering technique is relatively slow and complex in terms of computation time and parameter setting. We use computed tomographic colonography (CTC) images as examples and report a new visualization technique by three-dimensional gray level mapping (GM) to better identify and differentiate endoluminal lesions. Methods: There are 33 various endoluminal cases from 30 patients evaluated in this clinical study. These cases were segmented using gray-level threshold. The marching cube algorithm was used to detect isosurfaces in volumetric data sets. GM is applied using the surface gray level of CTC. Radiologists conducted the clinical evaluation of the SR and GM images. The Wilcoxon signed-rank test was used for data analysis. Results: Clinical evaluation confirms GM is significantly superior to SR in terms of gray-level pattern and spatial shape presentation of endoluminal cases (p < 0.01) and improves the confidence of identification and clinical classification of endoluminal lesions significantly (p < 0.01). The specificity and diagnostic accuracy of GM is significantly better than those of SR in diagnostic performance evaluation (p < 0.01). Conclusion: GM can reduce confusion in three-dimensional CTC and well correlate CTC with sectional images by the location as well as gray-level value. Hence, GM increases identification and differentiation of endoluminal lesions, and facilitates diagnostic process. Advances in knowledge: GM significantly improves the traditional SR method by providing reliable gray-level information for the surface points and is helpful in identification and differentiation of endoluminal lesions according to their shape and density. PMID:27925483

A comparison of algorithms for inference and learning in probabilistic graphical models.

PubMed

Frey, Brendan J; Jojic, Nebojsa

2005-09-01

Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.

Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography.

PubMed

Buzalewicz, Igor; Kujawińska, Małgorzata; Krauze, Wojciech; Podbielska, Halina

2016-01-01

The use of light diffraction for the microbiological diagnosis of bacterial colonies was a significant breakthrough with widespread implications for the food industry and clinical practice. We previously confirmed that optical sensors for bacterial colony light diffraction can be used for bacterial identification. This paper is focused on the novel perspectives of this method based on digital in-line holography (DIH), which is able to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the bacterial colony in any chosen observation plane behind the object from single digital hologram. Analysis of the amplitude and phase patterns inside a colony revealed its unique optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, on a computational level, it is possible to select the desired scattered/diffracted pattern within the entire observation volume that exhibits the largest amount of unique, differentiating bacterial features. These properties distinguish this method from the already proposed sensing techniques based on light diffraction/scattering of bacterial colonies. The reconstructed diffraction patterns have a similar spatial distribution as the recorded Fresnel patterns, previously applied for bacterial identification with over 98% accuracy, but they are characterized by both intensity and phase distributions. Our results using digital holography provide new optical discriminators of bacterial species revealed in one single step in form of new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, as well as diffraction patterns from all observation space, which exhibit species-dependent features. To the best of our knowledge, this is the first report on bacterial colony analysis via digital holography and our study represents an innovative approach to the subject.

Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography

PubMed Central

Buzalewicz, Igor; Kujawińska, Małgorzata; Krauze, Wojciech; Podbielska, Halina

2016-01-01

The use of light diffraction for the microbiological diagnosis of bacterial colonies was a significant breakthrough with widespread implications for the food industry and clinical practice. We previously confirmed that optical sensors for bacterial colony light diffraction can be used for bacterial identification. This paper is focused on the novel perspectives of this method based on digital in-line holography (DIH), which is able to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the bacterial colony in any chosen observation plane behind the object from single digital hologram. Analysis of the amplitude and phase patterns inside a colony revealed its unique optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, on a computational level, it is possible to select the desired scattered/diffracted pattern within the entire observation volume that exhibits the largest amount of unique, differentiating bacterial features. These properties distinguish this method from the already proposed sensing techniques based on light diffraction/scattering of bacterial colonies. The reconstructed diffraction patterns have a similar spatial distribution as the recorded Fresnel patterns, previously applied for bacterial identification with over 98% accuracy, but they are characterized by both intensity and phase distributions. Our results using digital holography provide new optical discriminators of bacterial species revealed in one single step in form of new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, as well as diffraction patterns from all observation space, which exhibit species-dependent features. To the best of our knowledge, this is the first report on bacterial colony analysis via digital holography and our study represents an innovative approach to the subject. PMID:26943121

Optimization of illuminating system to detect optical properties inside a finger

NASA Astrophysics Data System (ADS)

Sano, Emiko; Shikai, Masahiro; Shiratsuki, Akihide; Maeda, Takuji; Matsushita, Masahito; Sasakawa, Koichi

2007-01-01

Biometrics performs personal authentication using individual bodily features including fingerprints, faces, etc. These technologies have been studied and developed for many years. In particular, fingerprint authentication has evolved over many years, and fingerprinting is currently one of world's most established biometric authentication techniques. Not long ago this technique was only used for personal identification in criminal investigations and high-security facilities. In recent years, however, various biometric authentication techniques have appeared in everyday applications. Even though providing great convenience, they have also produced a number of technical issues concerning operation. Generally, fingerprint authentication is comprised of a number of component technologies: (1) sensing technology for detecting the fingerprint pattern; (2) image processing technology for converting the captured pattern into feature data that can be used for verification; (3) verification technology for comparing the feature data with a reference and determining whether it matches. Current fingerprint authentication issues, revealed in research results, originate with fingerprint sensing technology. Sensing methods for detecting a person's fingerprint pattern for image processing are particularly important because they impact overall fingerprint authentication performance. The following are the current problems concerning sensing methods that occur in some cases: Some fingers whose fingerprints used to be difficult to detect by conventional sensors. Fingerprint patterns are easily affected by the finger's surface condition, such noise as discontinuities and thin spots can appear in fingerprint patterns obtained from wrinkled finger, sweaty finger, and so on. To address these problems, we proposed a novel fingerprint sensor based on new scientific knowledge. A characteristic of this new method is that obtained fingerprint patterns are not easily affected by the finger's surface condition because it detects the fingerprint pattern inside the finger using transmitted light. We examined optimization of illumination system of this novel fingerprint sensor to detect contrasty fingerprint pattern from wide area and to improve image processing at (2).

Interpretation of geographic patterns in simulated orbital television imagery of earth resources

NASA Technical Reports Server (NTRS)

Latham, J. P.; Cross, C. I.; Kuyper, W. H.; Witmer, R. E.

1972-01-01

In order to better determine the effects of the television imagery characteristics upon the interpretation of geographic patterns obtainable from orbital television sensors, and in order to better evaluate the influences of alternative sensor system parameters such as changes in orbital altitudes or scan line rates, a team of three professional interpreters independently mapped thematically the selected geographic phenomena that they could detect in orbital television imagery produced on a fourteen inch monitor and recorded photographically for analysis. Three thematic maps were compiled by each interpreter. The maps were: (1) transportation patterns; (2) other land use; and (3) physical regions. The results from the three interpreters are compared, agreements noted, and differences analyzed for cause such as disagreement on identification of phenomenon, visual acuity, differences in interpretation techniques, and differing professional backgrounds.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Comments on the use of network structures to analyse commercial companies’ evolution and their impact on economic behaviour

NASA Astrophysics Data System (ADS)

Costea, Carmen

2006-10-01

Network analysis studies the development of the social structure of relationships around a group or an institutional body, and how it affects beliefs and behaviours. Causal constraints require a special and deeper attention to the social structure. The purpose of this paper is to give a new approach to the idea that this reality should be primarily conceived and investigated from the perspective of the properties of relations between and within units, instead of the properties of these units themselves. The relationship may refer to the exchange of products, labour, information and money. By mapping these relationships, network analysis can help to uncover the emergent and informal communication patterns of commercial companies that may be compared to the formal communication structures. These emergent patterns can be used to explain institutional and individuals’ behaviours. Network analysis techniques focus on the communication structure of an organization that can be subdivided and handled with different approaches. Structural features that can be analysed through the use of network analysis techniques are, for example, the (formal and informal) communication patterns in an organization or the identification of specific groups within an organization. Special attention may be given to specific aspects of communication patterns.

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

NASA Astrophysics Data System (ADS)

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

2000-03-01

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

Causal gene identification using combinatorial V-structure search.

PubMed

Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng

2013-07-01

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

The use of ERTS imagery in reservoir management and operation

NASA Technical Reports Server (NTRS)

Cooper, S. (Principal Investigator)

1973-01-01

There are no author-identified significant results in this report. Preliminary analysis of ERTS-1 imagery suggests that the configuration and areal coverage of surface waters, as well as other hydrologically related terrain features, may be obtained from ERTS-1 imagery to an extent that would be useful. Computer-oriented pattern recognition techniques are being developed to help automate the identification and analysis of hydrologic features. Considerable man-machine interaction is required while training the computer for these tasks.

Collective behaviour across animal species

PubMed Central

DeLellis, Pietro; Polverino, Giovanni; Ustuner, Gozde; Abaid, Nicole; Macrì, Simone; Bollt, Erik M.; Porfiri, Maurizio

2014-01-01

We posit a new geometric perspective to define, detect, and classify inherent patterns of collective behaviour across a variety of animal species. We show that machine learning techniques, and specifically the isometric mapping algorithm, allow the identification and interpretation of different types of collective behaviour in five social animal species. These results offer a first glimpse at the transformative potential of machine learning for ethology, similar to its impact on robotics, where it enabled robots to recognize objects and navigate the environment. PMID:24430561

Music-Elicited Emotion Identification Using Optical Flow Analysis of Human Face

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Smirnova, Z. N.

2015-05-01

Human emotion identification from image sequences is highly demanded nowadays. The range of possible applications can vary from an automatic smile shutter function of consumer grade digital cameras to Biofied Building technologies, which enables communication between building space and residents. The highly perceptual nature of human emotions leads to the complexity of their classification and identification. The main question arises from the subjective quality of emotional classification of events that elicit human emotions. A variety of methods for formal classification of emotions were developed in musical psychology. This work is focused on identification of human emotions evoked by musical pieces using human face tracking and optical flow analysis. Facial feature tracking algorithm used for facial feature speed and position estimation is presented. Facial features were extracted from each image sequence using human face tracking with local binary patterns (LBP) features. Accurate relative speeds of facial features were estimated using optical flow analysis. Obtained relative positions and speeds were used as the output facial emotion vector. The algorithm was tested using original software and recorded image sequences. The proposed technique proves to give a robust identification of human emotions elicited by musical pieces. The estimated models could be used for human emotion identification from image sequences in such fields as emotion based musical background or mood dependent radio.

Gender determination: Role of lip prints, finger prints and mandibular canine index

PubMed Central

KRISHNAN, RESHMA POOTHAKULATH; THANGAVELU, RADHIKA; RATHNAVELU, VIDHYA; NARASIMHAN, MALATHI

2016-01-01

Personal identification has a pivotal role in forensic investigations. Gender determination is an essential step in personal identification. Despite the advent of advanced techniques such as DNA fingerprinting, methods such as lip print and fingerprint analysis and mandibular canine index calculations are routinely used in gender determination, as they are simple and cost-effective. The present study investigated the hypothesis that lip print analysis is an effective tool in gender determination compared with fingerprint analysis and the mandibular canine index. The predominant patterns of lip prints and fingerprints were analyzed in males and females, and the efficacy of the mandibular canine index in gender determination was evaluated. The study group comprised 50 students, 25 males and 25 females who were 18–25 years of age. Lip prints and fingerprints were obtained and classified according to Tsuchihashi's classification and Kücken and Newell's classification, respectively. Mandibular impressions were made and the mandibular canine index was calculated. Type I and Type I' lip prints were predominant in females, and Type IV lip prints were predominant in males. The analysis of fingerprints revealed that the loop fingerprint pattern was predominant in both males and females. The mandibular canine index was not found to be significant in gender identification. The predominant patterns of lip prints were distinct for males and females; conversely, fingerprints were demonstrated to be similar in both genders. Therefore, lip prints hold an increased potential for gender determination, as compared with fingerprints, and the mandibular canine index is not a reliable indicator of gender. PMID:27284316

A novel method for flow pattern identification in unstable operational conditions using gamma ray and radial basis function.

PubMed

Roshani, G H; Nazemi, E; Roshani, M M

2017-05-01

Changes of fluid properties (especially density) strongly affect the performance of radiation-based multiphase flow meter and could cause error in recognizing the flow pattern and determining void fraction. In this work, we proposed a methodology based on combination of multi-beam gamma ray attenuation and dual modality densitometry techniques using RBF neural network in order to recognize the flow regime and determine the void fraction in gas-liquid two phase flows independent of the liquid phase changes. The proposed system is consisted of one 137 Cs source, two transmission detectors and one scattering detector. The registered counts in two transmission detectors were used as the inputs of one primary Radial Basis Function (RBF) neural network for recognizing the flow regime independent of liquid phase density. Then, after flow regime identification, three RBF neural networks were utilized for determining the void fraction independent of liquid phase density. Registered count in scattering detector and first transmission detector were used as the inputs of these three RBF neural networks. Using this simple methodology, all the flow patterns were correctly recognized and the void fraction was predicted independent of liquid phase density with mean relative error (MRE) of less than 3.28%. Copyright © 2017 Elsevier Ltd. All rights reserved.

Event identification by acoustic signature recognition

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

Dress, W.B.; Kercel, S.W.

1995-07-01

Many events of interest to the security commnnity produce acoustic emissions that are, in principle, identifiable as to cause. Some obvious examples are gunshots, breaking glass, takeoffs and landings of small aircraft, vehicular engine noises, footsteps (high frequencies when on gravel, very low frequencies. when on soil), and voices (whispers to shouts). We are investigating wavelet-based methods to extract unique features of such events for classification and identification. We also discuss methods of classification and pattern recognition specifically tailored for acoustic signatures obtained by wavelet analysis. The paper is divided into three parts: completed work, work in progress, and futuremore » applications. The completed phase has led to the successful recognition of aircraft types on landing and takeoff. Both small aircraft (twin-engine turboprop) and large (commercial airliners) were included in the study. The project considered the design of a small, field-deployable, inexpensive device. The techniques developed during the aircraft identification phase were then adapted to a multispectral electromagnetic interference monitoring device now deployed in a nuclear power plant. This is a general-purpose wavelet analysis engine, spanning 14 octaves, and can be adapted for other specific tasks. Work in progress is focused on applying the methods previously developed to speaker identification. Some of the problems to be overcome include recognition of sounds as voice patterns and as distinct from possible background noises (e.g., music), as well as identification of the speaker from a short-duration voice sample. A generalization of the completed work and the work in progress is a device capable of classifying any number of acoustic events-particularly quasi-stationary events such as engine noises and voices and singular events such as gunshots and breaking glass. We will show examples of both kinds of events and discuss their recognition likelihood.« less

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Integrative two-dimensional correlation spectroscopy (i2DCOS) for the intuitive identification of adulterated herbal materials

NASA Astrophysics Data System (ADS)

Chen, Jianbo; Wang, Yue; Rong, Lixin; Wang, Jingjuan

2018-07-01

IR, Raman and other separation-free and label-free spectroscopic techniques have been the promising methods for the rapid and low-cost quality control of complex mixtures such as food and herb. However, as the overlapped signals from different ingredients usually make it difficult to extract useful information, chemometrics tools are often needed to find out spectral features of interest. With designed perturbations, two-dimensional correlation spectroscopy (2DCOS) is a powerful technique to resolve the overlapped spectral bands and enhance the apparent spectral resolution. In this research, the integrative two-dimensional correlation spectroscopy (i2DCOS) is defined for the first time overcome some disadvantages of synchronous and asynchronous correlation spectra for identification. The integrative 2D correlation spectra weight the asynchronous cross peaks by the corresponding synchronous cross peaks, which combines the signal-to-noise ratio advantage of synchronous correlation spectra and the spectral resolution advantage of asynchronous correlation spectra. The feasibility of the integrative 2D correlation spectra for the quality control of complex mixtures is examined by the identification of adulterated Fritillariae Bulbus powders. Compared with model-based pattern recognition and multivariate calibration methods, i2DCOS can provide intuitive identification results but not require the number of samples. The results show the potential of i2DCOS in the intuitive quality control of herbs and other complex mixtures, especially when the number of samples is not large.

Robust pattern decoding in shape-coded structured light

NASA Astrophysics Data System (ADS)

Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai

2017-09-01

Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.

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

PubMed

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

2013-01-01

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

Array magnetics modal analysis for the DIII-D tokamak based on localized time-series modelling

DOE PAGES

Olofsson, K. Erik J.; Hanson, Jeremy M.; Shiraki, Daisuke; ...

2014-07-14

Here, time-series analysis of magnetics data in tokamaks is typically done using block-based fast Fourier transform methods. This work presents the development and deployment of a new set of algorithms for magnetic probe array analysis. The method is based on an estimation technique known as stochastic subspace identification (SSI). Compared with the standard coherence approach or the direct singular value decomposition approach, the new technique exhibits several beneficial properties. For example, the SSI method does not require that frequencies are orthogonal with respect to the timeframe used in the analysis. Frequencies are obtained directly as parameters of localized time-series models.more » The parameters are extracted by solving small-scale eigenvalue problems. Applications include maximum-likelihood regularized eigenmode pattern estimation, detection of neoclassical tearing modes, including locked mode precursors, and automatic clustering of modes, and magnetics-pattern characterization of sawtooth pre- and postcursors, edge harmonic oscillations and fishbones.« less

Functional assessment of the fundus autofluorescence pattern in Best vitelliform macular dystrophy.

PubMed

Parodi, Maurizio Battaglia; Iacono, Pierluigi; Del Turco, Claudia; Triolo, Giacinto; Bandello, Francesco

2016-07-01

To identify the fundus autofluorescence (FAF) patterns in Best vitelliform macular dystrophy (VMD). Patients affected by VMD in vitelliform, pseudohypopyon, and vitelliruptive stages underwent a complete ophthalmological examination, including best-corrected visual acuity (BCVA), short-wavelength FAF (SW-FAF), near-infrared FAF (NIR-FAF) and microperimetry. the identification of the correlation between SW-FAF and NIR-FAF patterns of the foveal region with BCVA, and central retinal sensitivity in eyes affected by VMD. The secondary outcomes included the definition of the frequency of foveal patterns on SW-FAF and NIR-FAF. Thirty-seven of 64 (58 %), 8 of 64 (12.5 %) and 19 of 64 (29.5 %) eyes showed vitelliform, pseudohypopyon, and vitelliruptive stages respectively. Three main FAF patterns were identified on both techniques: hyper-autofluorescent pattern, hypo-autofluorescent pattern, and patchy pattern. BCVA was significantly different in eyes with hypo-autofluorescent and patchy patterns with respect to eyes showing a hyper-autofluorescent pattern. Similar differences were registered in the FS according to SW-FAF classification. However, the FS differed in each subgroup in the NIR-FAF analysis. Subgroup analyses were performed on the patchy pattern, combining FAF and fundus abnormalities. Considering both FAF techniques, the BCVA differed between the vitelliform and pseudohypopyon stages, and between the vitelliform and vitelliruptive stages. In the NIR-FAF classification, there was a significant statistical difference in the FS between each subgroup; in the SW-FAF, there was a significant difference between the vitelliform and pseudohypopyon stages and the vitelliform and vitelliruptive stages. Three main FAF patterns can be identified in VMD. The patchy pattern is the most frequent, accounting for 70 % of eyes on SW-FAF and 80 % of eyes on NIR-FAF. A tighter correlation links the classification of NIR-FAF patterns and FS. Longitudinal investigations are warranted to evaluate the course of FAF patterns and their role in disease monitoring.

Processing ultrasonic inspection data from multiple scan patterns for turbine rotor weld build-up evaluations

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

Guan, Xuefei; Zhou, S. Kevin; Rasselkorde, El Mahjoub

The study presents a data processing methodology for weld build-up using multiple scan patterns. To achieve an overall high probability of detection for flaws with different orientations, an inspection procedure with three different scan patterns is proposed. The three scan patterns are radial-tangential longitude wave pattern, axial-radial longitude wave pattern, and tangential shear wave pattern. Scientific fusion of the inspection data is implemented using volume reconstruction techniques. The idea is to perform spatial domain forward data mapping for all sampling points. A conservative scheme is employed to handle the case that multiple sampling points are mapped to one grid location.more » The scheme assigns the maximum value for the grid location to retain the largest equivalent reflector size for the location. The methodology is demonstrated and validated using a realistic ring of weld build-up. Tungsten balls and bars are embedded to the weld build-up during manufacturing process to represent natural flaws. Flat bottomed holes and side drilled holes are installed as artificial flaws. Automatic flaw identification and extraction are demonstrated. Results indicate the inspection procedure with multiple scan patterns can identify all the artificial and natural flaws.« less

Processing ultrasonic inspection data from multiple scan patterns for turbine rotor weld build-up evaluations

NASA Astrophysics Data System (ADS)

Guan, Xuefei; Rasselkorde, El Mahjoub; Abbasi, Waheed; Zhou, S. Kevin

2015-03-01

The study presents a data processing methodology for weld build-up using multiple scan patterns. To achieve an overall high probability of detection for flaws with different orientations, an inspection procedure with three different scan patterns is proposed. The three scan patterns are radial-tangential longitude wave pattern, axial-radial longitude wave pattern, and tangential shear wave pattern. Scientific fusion of the inspection data is implemented using volume reconstruction techniques. The idea is to perform spatial domain forward data mapping for all sampling points. A conservative scheme is employed to handle the case that multiple sampling points are mapped to one grid location. The scheme assigns the maximum value for the grid location to retain the largest equivalent reflector size for the location. The methodology is demonstrated and validated using a realistic ring of weld build-up. Tungsten balls and bars are embedded to the weld build-up during manufacturing process to represent natural flaws. Flat bottomed holes and side drilled holes are installed as artificial flaws. Automatic flaw identification and extraction are demonstrated. Results indicate the inspection procedure with multiple scan patterns can identify all the artificial and natural flaws.

Dental Evidence in Forensic Identification - An Overview, Methodology and Present Status.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Garg, Arun K

2015-01-01

Forensic odontology is primarily concerned with the use of teeth and oral structures for identification in a legal context. Various forensic odontology techniques help in the identification of the human remains in incidents such as terrorists' attacks, airplane, train and road accidents, fires, mass murders, and natural disasters such as tsunamis, earth quakes and floods, etc. (Disaster Victim Identification-DVI). Dental structures are the hardest and well protected structures in the body. These structures resist decomposition and high temperatures and are among the last ones to disintegrate after death. The principal basis of the dental identification lies in the fact that no two oral cavities are alike and the teeth are unique to an individual. The dental evidence of the deceased recovered from the scene of crime/occurrence is compared with the ante-mortem records for identification. Dental features such as tooth morphology, variations in shape and size, restorations, pathologies, missing tooth, wear patterns, crowding of the teeth, colour and position of the tooth, rotations and other peculiar dental anomalies give every individual a unique identity. In absence of ante-mortem dental records for comparison, the teeth can help in the determination of age, sex, race/ethnicity, habits, occupations, etc. which can give further clues regarding the identity of the individuals. This piece of writing gives an overview of dental evidence, its use in forensic identification and its limitations.

Dental Evidence in Forensic Identification – An Overview, Methodology and Present Status

PubMed Central

Krishan, Kewal; Kanchan, Tanuj; Garg, Arun K

2015-01-01

Forensic odontology is primarily concerned with the use of teeth and oral structures for identification in a legal context. Various forensic odontology techniques help in the identification of the human remains in incidents such as terrorists’ attacks, airplane, train and road accidents, fires, mass murders, and natural disasters such as tsunamis, earth quakes and floods, etc. (Disaster Victim Identification-DVI). Dental structures are the hardest and well protected structures in the body. These structures resist decomposition and high temperatures and are among the last ones to disintegrate after death. The principal basis of the dental identification lies in the fact that no two oral cavities are alike and the teeth are unique to an individual. The dental evidence of the deceased recovered from the scene of crime/occurrence is compared with the ante-mortem records for identification. Dental features such as tooth morphology, variations in shape and size, restorations, pathologies, missing tooth, wear patterns, crowding of the teeth, colour and position of the tooth, rotations and other peculiar dental anomalies give every individual a unique identity. In absence of ante-mortem dental records for comparison, the teeth can help in the determination of age, sex, race/ethnicity, habits, occupations, etc. which can give further clues regarding the identity of the individuals. This piece of writing gives an overview of dental evidence, its use in forensic identification and its limitations. PMID:26312096

Unconstrained and contactless hand geometry biometrics.

PubMed

de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; Del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

2011-01-01

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

Unconstrained and Contactless Hand Geometry Biometrics

PubMed Central

de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

2011-01-01

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM) and k-Nearest Neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices. PMID:22346634

Identification of a Group's Physiological Synchronization with Earth's Magnetic Field.

PubMed

Timofejeva, Inga; McCraty, Rollin; Atkinson, Mike; Joffe, Roza; Vainoras, Alfonsas; Alabdulgader, Abdullah A; Ragulskis, Minvydas

2017-09-01

A new analysis technique for the evaluation of the degree of synchronization between the physiological state of a group of people and changes in the Earth's magnetic field based on their cardiac inter-beat intervals was developed and validated. The new analysis method was then used to identify clusters of similar synchronization patterns in a group of 20 individuals over a two-week period. The algorithm for the identification of slow wave dynamics for every person was constructed in order to determine meaningful interrelationships between the participants and the local magnetic field data. The results support the hypothesis that the slow wave rhythms in heart rate variability can synchronize with changes in local magnetic field data, and that the degree of synchronization is affected by the quality of interpersonal relationships.

Identification of medically relevant Nocardia species with an abbreviated battery of tests.

PubMed

Kiska, Deanna L; Hicks, Karen; Pettit, David J

2002-04-01

Identification of Nocardia to the species level is useful for predicting antimicrobial susceptibility patterns and defining the pathogenicity and geographic distribution of these organisms. We sought to develop an identification method which was accurate, timely, and employed tests which would be readily available in most clinical laboratories. We evaluated the API 20C AUX yeast identification system as well as several biochemical tests and Kirby-Bauer susceptibility patterns for the identification of 75 isolates encompassing the 8 medically relevant Nocardia species. There were few biochemical reactions that were sufficiently unique for species identification; of note, N. nova were positive for arylsulfatase, N. farcinica were positive for opacification of Middlebrook 7H11 agar, and N. brasiliensis and N. pseudobrasiliensis were the only species capable of liquefying gelatin. API 20C sugar assimilation patterns were unique for N. transvalensis, N. asteroides IV, and N. brevicatena. There was overlap among the assimilation patterns for the other species. Species-specific patterns of susceptibility to gentamicin, tobramycin, amikacin, and erythromycin were obtained for N. nova, N. farcinica, and N. brevicatena, while there was overlap among the susceptibility patterns for the other isolates. No single method could identify all Nocardia isolates to the species level; therefore, a combination of methods was necessary. An algorithm utilizing antibiotic susceptibility patterns, citrate utilization, acetamide utilization, and assimilation of inositol and adonitol accurately identified all isolates. The algorithm was expanded to include infrequent drug susceptibility patterns which have been reported in the literature but which were not seen in this study.

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

PubMed

Joukal, Marek; Frišhons, Jan

2015-07-01

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

Mass Spectrometry as a Powerful Analytical Technique for the Structural Characterization of Synthesized and Natural Products

NASA Astrophysics Data System (ADS)

Es-Safi, Nour-Eddine; Essassi, El Mokhtar; Massoui, Mohamed; Banoub, Joseph

Mass spectrometry is an important tool for the identification and structural elucidation of natural and synthesized compounds. Its high sensitivity and the possibility of coupling liquid chromatography with mass spectrometry detection make it a technique of choice for the investigation of complex mixtures like raw natural extracts. The mass spectrometer is a universal detector that can achieve very high sensitivity and provide information on the molecular mass. More detailed information can be subsequently obtained by resorting to collision-induced dissociation tandem mass spectrometry (CID-MS/MS). In this review, the application of mass spectrometric techniques for the identification of natural and synthetic compounds is presented. The gas-phase fragmentation patterns of a series of four natural flavonoid glycosides, three synthesized benzodiazepines and two synthesized quinoxalinone derivatives were investigated using electrospray ionization mass spectrometry (ESI-MS) and tandem mass spectrometry techniques. Exact accurate masses were measured using a modorate resolution quadrupole orthogonal time-of-flight QqTOF-MS/MS hybrid mass spectrometer instrument. Confirmation of the molecular masses and the chemical structures of the studied compounds were achieved by exploring the gas-phase breakdown routes of the ionized molecules. This was rationalized by conducting low-energy collision CID-MS/MS analyses (product ion- and precursor ion scans) using a conventional quadrupole hexapole-quadrupole (QhQ) tandem mass spectrometer.

Standoff detection: classification of biological aerosols using laser induced fluorescence (LIF) technique

NASA Astrophysics Data System (ADS)

Hausmann, Anita; Duschek, Frank; Fischbach, Thomas; Pargmann, Carsten; Aleksejev, Valeri; Poryvkina, Larisa; Sobolev, Innokenti; Babichenko, Sergey; Handke, Jürgen

2014-05-01

The challenges of detecting hazardous biological materials are manifold: Such material has to be discriminated from other substances in various natural surroundings. The detection sensitivity should be extremely high. As living material may reproduce itself, already one single bacterium may represent a high risk. Of course, identification should be quite fast with a low false alarm rate. Up to now, there is no single technique to solve this problem. Point sensors may collect material and identify it, but the problems of fast identification and especially of appropriate positioning of local collectors are sophisticated. On the other hand, laser based standoff detection may instantaneously provide the information of some accidental spillage of material by detecting the generated thin cloud. LIF technique may classify but hardly identify the substance. A solution can be the use of LIF technique in a first step to collect primary data and - if necessary- followed by utilizing these data for an optimized positioning of point sensors. We perform studies on an open air laser test range at distances between 20 and 135 m applying LIF technique to detect and classify aerosols. In order to employ LIF capability, we use a laser source emitting two wavelengths alternatively, 280 and 355 nm, respectively. Moreover, the time dependence of fluorescence spectra is recorded by a gated intensified CCD camera. Signal processing is performed by dedicated software for spectral pattern recognition. The direct comparison of all results leads to a basic classification of the various compounds.

Identification of volatile markers for indoor fungal growth and chemotaxonomic classification of Aspergillus species.

PubMed

Polizzi, Viviana; Adams, An; Malysheva, Svetlana V; De Saeger, Sarah; Van Peteghem, Carlos; Moretti, Antonio; Picco, Anna Maria; De Kimpe, Norbert

2012-09-01

Microbial volatile organic compounds (MVOCs) were collected in water-damaged buildings to evaluate their use as possible indicators of indoor fungal growth. Fungal species isolated from contaminated buildings were screened for MVOC production on malt extract agar by means of headspace solid-phase microextraction followed by gas chromatography-mass spectrometry (GC-MS) analysis. Some sesquiterpenes, specifically derived from fungal growth, were detected in the sampled environments and the corresponding fungal producers were identified. Statistical analysis of the detected MVOC profiles allowed the identification of species-specific MVOCs or MVOC patterns for Aspergillus versicolor group, Aspergillus ustus, and Eurotium amstelodami. In addition, Chaetomium spp. and Epicoccum spp. were clearly differentiated by their volatile production from a group of 76 fungal strains belonging to different genera. These results are useful in the chemotaxonomic discrimination of fungal species, in aid to the classical morphological and molecular identification techniques. Copyright © 2012 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

2010-01-01

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

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

PubMed

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

2010-08-02

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

Wafer hot spot identification through advanced photomask characterization techniques

NASA Astrophysics Data System (ADS)

Choi, Yohan; Green, Michael; McMurran, Jeff; Ham, Young; Lin, Howard; Lan, Andy; Yang, Richer; Lung, Mike

2016-10-01

As device manufacturers progress through advanced technology nodes, limitations in standard 1-dimensional (1D) mask Critical Dimension (CD) metrics are becoming apparent. Historically, 1D metrics such as Mean to Target (MTT) and CD Uniformity (CDU) have been adequate for end users to evaluate and predict the mask impact on the wafer process. However, the wafer lithographer's process margin is shrinking at advanced nodes to a point that the classical mask CD metrics are no longer adequate to gauge the mask contribution to wafer process error. For example, wafer CDU error at advanced nodes is impacted by mask factors such as 3-dimensional (3D) effects and mask pattern fidelity on subresolution assist features (SRAFs) used in Optical Proximity Correction (OPC) models of ever-increasing complexity. These items are not quantifiable with the 1D metrology techniques of today. Likewise, the mask maker needs advanced characterization methods in order to optimize the mask process to meet the wafer lithographer's needs. These advanced characterization metrics are what is needed to harmonize mask and wafer processes for enhanced wafer hot spot analysis. In this paper, we study advanced mask pattern characterization techniques and their correlation with modeled wafer performance.

C-MOS bulk metal design handbook. [LSI standard cell (circuits)

NASA Technical Reports Server (NTRS)

Edge, T. M.

1977-01-01

The LSI standard cell array technique was used in the fabrication of more than 20 CMOS custom arrays. This technique consists of a series of computer programs and design automation techniques referred to as the Computer Aided Design And Test (CADAT) system that automatically translate a partitioned logic diagram into a set of instructions for driving an automatic plotter which generates precision mask artwork for complex LSI arrays of CMOS standard cells. The standard cell concept for producing LSI arrays begins with the design, layout, and validation of a group of custom circuits called standard cells. Once validated, these cells are given identification or pattern numbers and are permanently stored. To use one of these cells in a logic design, the user calls for the desired cell by pattern number. The Place, Route in Two Dimension (PR2D) computer program is then used to automatically generate the metalization and/or tunnels to interconnect the standard cells into the required function. Data sheets that describe the function, artwork, and performance of each of the standard cells, the general procedure for implementation of logic in CMOS standard cells, and additional detailed design information are presented.

Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications.

PubMed

Singh, Anushikha; Dutta, Malay Kishore; Sharma, Dilip Kumar

2016-10-01

Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information. Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image. The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging. Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra

NASA Astrophysics Data System (ADS)

Unglert, K.; Radić, V.; Jellinek, A. M.

2016-06-01

Variations in the spectral content of volcano seismicity related to changes in volcanic activity are commonly identified manually in spectrograms. However, long time series of monitoring data at volcano observatories require tools to facilitate automated and rapid processing. Techniques such as self-organizing maps (SOM) and principal component analysis (PCA) can help to quickly and automatically identify important patterns related to impending eruptions. For the first time, we evaluate the performance of SOM and PCA on synthetic volcano seismic spectra constructed from observations during two well-studied eruptions at Klauea Volcano, Hawai'i, that include features observed in many volcanic settings. In particular, our objective is to test which of the techniques can best retrieve a set of three spectral patterns that we used to compose a synthetic spectrogram. We find that, without a priori knowledge of the given set of patterns, neither SOM nor PCA can directly recover the spectra. We thus test hierarchical clustering, a commonly used method, to investigate whether clustering in the space of the principal components and on the SOM, respectively, can retrieve the known patterns. Our clustering method applied to the SOM fails to detect the correct number and shape of the known input spectra. In contrast, clustering of the data reconstructed by the first three PCA modes reproduces these patterns and their occurrence in time more consistently. This result suggests that PCA in combination with hierarchical clustering is a powerful practical tool for automated identification of characteristic patterns in volcano seismic spectra. Our results indicate that, in contrast to PCA, common clustering algorithms may not be ideal to group patterns on the SOM and that it is crucial to evaluate the performance of these tools on a control dataset prior to their application to real data.

Interventions that involve parents to improve children's weight-related nutrition intake and activity patterns - what nutrition and activity targets and behaviour change techniques are associated with intervention effectiveness?

PubMed

Golley, R K; Hendrie, G A; Slater, A; Corsini, N

2011-02-01

Parent involvement is an important component of obesity prevention interventions. However, the best way to support parents remains unclear. This review identifies interventions targeting parents to improve children's weight status, dietary and/or activity patterns, examines whether intervention content and behaviour change techniques employed are associated with effectiveness. Seventeen studies, in English, 1998-2008, were included. Studies were evaluated by two reviewers for study quality, nutrition/activity content and behaviour change techniques using a validated quality assessment tool and behaviour change technique taxonomy. Study findings favoured intervention effectiveness in 11 of 17 studies. Interventions that were considered effective had similar features: better study quality, parents responsible for participation and implementation, greater parental involvement and inclusion of prompt barrier identification, restructure the home environment, prompt self-monitoring, prompt specific goal setting behaviour change techniques. Energy intake/density and food choices were more likely to be targeted in effective interventions. The number of lifestyle behaviours targeted did not appear to be associated with effectiveness. Intervention effectiveness was favoured when behaviour change techniques spanned the spectrum of behaviour change process. The review provides guidance for researchers to make informed decisions on how best to utilize resources in interventions to support and engage parents, and highlights a need for improvement in intervention content reporting practices. © 2010 The Authors. obesity reviews © 2010 International Association for the Study of Obesity.

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…

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

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…

Connecting Self-Esteem and Achievement: Diversity in Academic Identification and Dis-Identification Patterns among Black College Students

ERIC Educational Resources Information Center

Hope, Elan C.; Chavous, Tabbye M.; Jagers, Robert J.; Sellers, Robert M.

2013-01-01

Using a person-oriented approach, we explored patterns of self-esteem and achievement among 324 Black college students across the freshman college year and identified four academic identification profiles. Multivariate analyses revealed profile differences in academic and psychological outcomes at beginning and end of freshman year (academic…

High Resolution Ultrasonic Method for 3D Fingerprint Representation in Biometrics

NASA Astrophysics Data System (ADS)

Maev, R. Gr.; Bakulin, E. Y.; Maeva, E. Y.; Severin, F. M.

Biometrics is an important field which studies different possible ways of personal identification. Among a number of existing biometric techniques fingerprint recognition stands alone - because very large database of fingerprints has already been acquired. Also, fingerprints are an important evidence that can be collected at a crime scene. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. Ultrasonic method of fingerprint imaging was originally introduced over a decade as the mapping of the reflection coefficient at the interface between the finger and a covering plate and has shown very good reliability and free from imperfections of previous two methods. This work introduces a newer development of the ultrasonic fingerprint imaging, focusing on the imaging of the internal structures of fingerprints (including sweat pores) with raw acoustic resolution of about 500 dpi (0.05 mm) using a scanning acoustic microscope to obtain images and acoustic data in the form of 3D data array. C-scans from different depths inside the fingerprint area of fingers of several volunteers were obtained and showed good contrast of ridges-and-valleys patterns and practically exact correspondence to the standard ink-and-paper prints of the same areas. Important feature reveled on the acoustic images was the clear appearance of the sweat pores, which could provide additional means of identification.

Surface-enhanced Raman scattering (SERS) study of anthocyanidins

NASA Astrophysics Data System (ADS)

Zaffino, Chiara; Russo, Bianca; Bruni, Silvia

2015-10-01

Anthocyanins are an important class of natural compounds responsible for the red, purple and blue colors in a large number of flowers, fruits and cereal grains. They are polyhydroxy- and polymethoxy-derivatives of 2-phenylbenzopyrylium (flavylium) salts, which are present in nature as glycosylated molecules. The aim of the present study is to assess the identification of anthocyanidins, i.e. anthocyanins without the glycosidic moiety, by means of surface-enhanced Raman spectroscopy (SERS), a very chemically-specific technique which is moreover sensitive to subtle changes in molecular structures. These features can lead to elect SERS, among the spectroscopic tools currently at disposal of scientists, as a technique of choice for the identification of anthocyanidins, since: (1) anthocyanidins structurally present the same benzopyrylium moiety and differentiate only for the substitution pattern on their phenyl ring, (2) different species are present in aqueous solution depending on the pH. It will be demonstrated that, while resonance Raman spectra of anthocyanidins are very similar to one another, SER spectra show greater differences, leading to a further step in the identification of such important compounds in diluted solutions by means of vibrational spectroscopy. Moreover, the dependence on the pH of the six most common anthocyanidins, i.e. cyanidin, delphinidin, pelargonidin, peonidin, malvidin and petunidin, is studied. To the best of the authors' knowledge, a complete SERS study of such important molecules is reported in the present work for the first time.

Comparative analysis of lip with thumbprints: An identification tool in personal authentication.

PubMed

Naik, Rashmi; Ahmed Mujib, B R; Telagi, Neethu; Hallur, Jaydeva

2017-01-01

Identification of person living or dead using diverse characteristics is the basis in forensic science. The uniqueness of lip and fingerprints and further, association between them can be useful in establishing facts in legal issues. The present study was carried out to determine the distribution of different lip print patterns among subjects having different thumbprint patterns and to determine the correlation between lip print patterns and thumbprint patterns. The study sample comprised 100 students randomly selected from Bapuji Dental College Hospital, Davangere, Karnataka, 50 males and 50 females aged between 18 and 20 years. Red colored lipstick was applied on the lips by a lipstick applicator brush. Lip and thumb impressions were made on No. 1 Whatman filter paper and visualized using magnifying lens. Three main types of fingerprints (loop, whorl and arch) were identified; Tsuchihashi Y classification of lip print patterns was followed in the study. Chi-square test was used to see the association between lip and thumbprints. The correlation between lip and left thumb print patterns for gender identification was statistically significant. In both males and females, Type II lip pattern associated with loop finger pattern were most significant and in males, Type III lip pattern with whorl type of finger pattern showed statistical significance. We conclude that the correlation found between lip print and thumbprint can be utilized in the field of forensic science for gender identification.

Effective use of ERTS multisensor data in the Northern Great Plains

NASA Technical Reports Server (NTRS)

Myers, V. I.; Westin, F. C.; Horton, M. L.; Lewis, J. K. (Principal Investigator)

1974-01-01

The author has identified the following significant results. ERTS imagery was used as a tool in the identification and refinement of soil association areas; to classify land use patterns between crop and fallow fields; to identify corn, soybeans, and oats; and to identify broad generalized range ecosystems. Various data handling techniques were developed and applied to accomplish these tasks. A map outlining soil associations and relative land values was completed on a base mosaic of ERTS imagery and is included as an appendix to the report.

Correlative microscopy of a carbide-free bainitic steel.

PubMed

Hofer, Christina; Bliznuk, Vitaliy; Verdiere, An; Petrov, Roumen; Winkelhofer, Florian; Clemens, Helmut; Primig, Sophie

2016-02-01

In this work a carbide-free bainitic steel was examined by a novel correlative microscopy approach using transmission Kikuchi diffraction (TKD) and transmission electron microscopy (TEM). The individual microstructural constituents could be identified by TKD based on their different crystal structure for bainitic ferrite and retained austenite and by image quality for the martensite-austenite (M-A) constituent. Subsequently, the same area was investigated in the TEM and a good match of these two techniques regarding the identification of the area position and crystal orientation could be proven. Additionally, the M-A constituent was examined in the TEM for the first time after preceded unambiguous identification using a correlative microscopy approach. The selected area diffraction pattern showed satellites around the main reflexes which might indicate a structural modulation. Copyright © 2015 Elsevier Ltd. All rights reserved.

THz-wave parametric source and its imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-08-01

Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

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

PubMed

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

2013-01-01

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

qPMS9: An Efficient Algorithm for Quorum Planted Motif Search

NASA Astrophysics Data System (ADS)

Nicolae, Marius; Rajasekaran, Sanguthevar

2015-01-01

Discovering patterns in biological sequences is a crucial problem. For example, the identification of patterns in DNA sequences has resulted in the determination of open reading frames, identification of gene promoter elements, intron/exon splicing sites, and SH RNAs, location of RNA degradation signals, identification of alternative splicing sites, etc. In protein sequences, patterns have led to domain identification, location of protease cleavage sites, identification of signal peptides, protein interactions, determination of protein degradation elements, identification of protein trafficking elements, discovery of short functional motifs, etc. In this paper we focus on the identification of an important class of patterns, namely, motifs. We study the (l, d) motif search problem or Planted Motif Search (PMS). PMS receives as input n strings and two integers l and d. It returns all sequences M of length l that occur in each input string, where each occurrence differs from M in at most d positions. Another formulation is quorum PMS (qPMS), where the motif appears in at least q% of the strings. We introduce qPMS9, a parallel exact qPMS algorithm that offers significant runtime improvements on DNA and protein datasets. qPMS9 solves the challenging DNA (l, d)-instances (28, 12) and (30, 13). The source code is available at https://code.google.com/p/qpms9/.

Identification of abnormal accident patterns at intersections

DOT National Transportation Integrated Search

1999-08-01

This report presents the findings and recommendations based on the Identification of Abnormal Accident Patterns at Intersections. This project used a statistically valid sampling method to determine whether a specific intersection has an abnormally h...

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique.

PubMed

Ardila-Rey, Jorge Alfredo; Montaña, Johny; de Castro, Bruno Albuquerque; Schurch, Roger; Covolan Ulson, José Alfredo; Muhammad-Sukki, Firdaus; Bani, Nurul Aini

2018-03-29

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

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

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

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

CpG PatternFinder: a Windows-based utility program for easy and rapid identification of the CpG methylation status of DNA.

PubMed

Xu, Yi-Hua; Manoharan, Herbert T; Pitot, Henry C

2007-09-01

The bisulfite genomic sequencing technique is one of the most widely used techniques to study sequence-specific DNA methylation because of its unambiguous ability to reveal DNA methylation status to the order of a single nucleotide. One characteristic feature of the bisulfite genomic sequencing technique is that a number of sample sequence files will be produced from a single DNA sample. The PCR products of bisulfite-treated DNA samples cannot be sequenced directly because they are heterogeneous in nature; therefore they should be cloned into suitable plasmids and then sequenced. This procedure generates an enormous number of sample DNA sequence files as well as adding extra bases belonging to the plasmids to the sequence, which will cause problems in the final sequence comparison. Finding the methylation status for each CpG in each sample sequence is not an easy job. As a result CpG PatternFinder was developed for this purpose. The main functions of the CpG PatternFinder are: (i) to analyze the reference sequence to obtain CpG and non-CpG-C residue position information. (ii) To tailor sample sequence files (delete insertions and mark deletions from the sample sequence files) based on a configuration of ClustalW multiple alignment. (iii) To align sample sequence files with a reference file to obtain bisulfite conversion efficiency and CpG methylation status. And, (iv) to produce graphics, highlighted aligned sequence text and a summary report which can be easily exported to Microsoft Office suite. CpG PatternFinder is designed to operate cooperatively with BioEdit, a freeware on the internet. It can handle up to 100 files of sample DNA sequences simultaneously, and the total CpG pattern analysis process can be finished in minutes. CpG PatternFinder is an ideal software tool for DNA methylation studies to determine the differential methylation pattern in a large number of individuals in a population. Previously we developed the CpG Analyzer program; CpG PatternFinder is our further effort to create software tools for DNA methylation studies.

Longitudinal strain bull's eye plot patterns in patients with cardiomyopathy and concentric left ventricular hypertrophy.

PubMed

Liu, Dan; Hu, Kai; Nordbeck, Peter; Ertl, Georg; Störk, Stefan; Weidemann, Frank

2016-05-10

Despite substantial advances in the imaging techniques and pathophysiological understanding over the last decades, identification of the underlying causes of left ventricular hypertrophy by means of echocardiographic examination remains a challenge in current clinical practice. The longitudinal strain bull's eye plot derived from 2D speckle tracking imaging offers an intuitive visual overview of the global and regional left ventricular myocardial function in a single diagram. The bull's eye mapping is clinically feasible and the plot patterns could provide clues to the etiology of cardiomyopathies. The present review summarizes the longitudinal strain, bull's eye plot features in patients with various cardiomyopathies and concentric left ventricular hypertrophy and the bull's eye plot features might serve as one of the cardiac workup steps on evaluating patients with left ventricular hypertrophy.

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

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

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

Statistical discrimination of footwear: a method for the comparison of accidentals on shoe outsoles inspired by facial recognition techniques.

PubMed

Petraco, Nicholas D K; Gambino, Carol; Kubic, Thomas A; Olivio, Dayhana; Petraco, Nicholas

2010-01-01

In the field of forensic footwear examination, it is a widely held belief that patterns of accidental marks found on footwear and footwear impressions possess a high degree of "uniqueness." This belief, however, has not been thoroughly studied in a numerical way using controlled experiments. As a result, this form of valuable physical evidence has been the subject of admissibility challenges. In this study, we apply statistical techniques used in facial pattern recognition, to a minimal set of information gleaned from accidental patterns. That is, in order to maximize the amount of potential similarity between patterns, we only use the coordinate locations of accidental marks (on the top portion of a footwear impression) to characterize the entire pattern. This allows us to numerically gauge how similar two patterns are to one another in a worst-case scenario, i.e., in the absence of a tremendous amount of information normally available to the footwear examiner such as accidental mark size and shape. The patterns were recorded from the top portion of the shoe soles (i.e., not the heel) of five shoe pairs. All shoes were the same make and model and all were worn by the same person for a period of 30 days. We found that in 20-30 dimensional principal component (PC) space (99.5% variance retained), patterns from the same shoe, even at different points in time, tended to cluster closer to each other than patterns from different shoes. Correct shoe identification rates using maximum likelihood linear classification analysis and the hold-one-out procedure ranged from 81% to 100%. Although low in variance, three-dimensional PC plots were made and generally corroborated the findings in the much higher dimensional PC-space. This study is intended to be a starting point for future research to build statistical models on the formation and evolution of accidental patterns.

Zonal Acoustic Velocimetry in 30-cm, 60-cm, and 3-m Laboratory Models of the Outer Core

NASA Astrophysics Data System (ADS)

Rojas, R.; Doan, M. N.; Adams, M. M.; Mautino, A. R.; Stone, D.; Lekic, V.; Lathrop, D. P.

2016-12-01

A knowledge of zonal flows and shear is key in understanding magnetic field dynamics in the Earth and laboratory experiments with Earth-like geometries. Traditional techniques for measuring fluid flow using visualization and particle tracking are not well-suited to liquid metal flows. This has led us to develop a flow measurement technique based on acoustic mode velocimetry adapted from helioseismology. As a first step prior to measurements in the liquid sodium experiments, we implement this technique in our 60-cm diameter spherical Couette experiment in air. To account for a more realistic experimental geometry, including deviations from spherical symmetry, we compute predicted frequencies of acoustic normal modes using the finite element method. The higher accuracy of the predicted frequencies allows the identification of over a dozen acoustic modes, and mode identification is further aided by the use of multiple microphones and by analyzing spectra together with those obtained at a variety of nearby Rossby numbers. Differences between the predicted and observed mode frequencies are caused by differences in flow patterns present in the experiment. We compare acoustic mode frequency splittings with theoretical predictions for stationary fluid and solid body flow condition with excellent agreement. We also use this technique to estimate the zonal shear in those experiments across a range of Rossby numbers. Finally, we report on initial attempts to use this in liquid sodium in the 3-meter diameter experiment and parallel experiments performed in water in the 30-cm diameter experiment.

Application of HPLC and ESI-MS techniques in the analysis of phenolic acids and flavonoids from green leafy vegetables (GLVs).

PubMed

Kumar, B Ramesh

2017-12-01

Diets containing high proportions of fruits and vegetables reduce the risk of onset of chronic diseases. The role of herbal medicines in improving human health is gaining popularity over the years, which also increases the need for safety and efficiency of these products. Green leafy vegetables (GLVs) are the richest source of phenolic compounds with excellent antioxidant properties. Increased consumption of diets containing phenolic compounds may give positive and better results to human health and significantly improves the immune system. Highly selective, susceptible and versatile analytical techniques are necessary for extraction, identification, and quantification of phenolic compounds from plant extracts, which helps to utilize their important biological properties. Recent advances in the pre-treatment procedures, separation techniques and spectrometry methods are used for qualitative and quantitative analysis of phenolic compounds. The online coupling of liquid chromatography with mass spectrometry (LC-MS) has become a useful tool in the metabolic profiling of plant samples. In this review, the separation and identification of phenolic acids and flavonoids from GLVs by LC-MS have been discussed along with the general extraction procedures and other sources of mass spectrometer used. The review is devoted to the understanding of the structural configuration, nature and accumulation pattern of phenolic acids and flavonoids in plants and to highlighting the recent developments in the chemical investigation of these compounds by chromatographic and spectroscopic techniques. It concludes with the advantages of the combination of these two methods and prospects.

Field theory of pattern identification

NASA Astrophysics Data System (ADS)

Agu, Masahiro

1988-06-01

Based on the psychological experimental fact that images in mental space are transformed into other images for pattern identification, a field theory of pattern identification of geometrical patterns is developed with the use of gauge field theory in Euclidean space. Here, the ``image'' or state function ψ[χ] of the brain reacting to a geometrical pattern χ is made to correspond to the electron's wave function in Minkowski space. The pattern identification of the pattern χ with the modified pattern χ+Δχ is assumed to be such that their images ψ[χ] and ψ[χ+Δχ] in the brain are transformable with each other through suitable transformation groups such as parallel transformation, dilatation, or rotation. The transformation group is called the ``image potential'' which corresponds to the vector potential of the gauge field. An ``image field'' derived from the image potential is found to be induced in the brain when the two images ψ[χ] and ψ[χ+Δχ] are not transformable through suitable transformation groups or gauge transformations. It is also shown that, when the image field exists, the final state of the image ψ[χ] is expected to be different, depending on the paths of modifications of the pattern χ leading to a final pattern. The above fact is interpreted as a version of the Aharonov and Bohm effect of the electron's wave function [A. Aharonov and D. Bohm, Phys. Rev. 115, 485 (1959)]. An excitation equation of the image field is also derived by postulating that patterns are identified maximally for the purpose of minimizing the number of memorized standard patterns.

Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spectral Fingerprints with Aid of Pattern Recognition Methods

PubMed Central

Fu, Haiyan; Fan, Yao; Zhang, Xu; Lan, Hanyue; Yang, Tianming; Shao, Mei; Li, Sihan

2015-01-01

As an effective method, the fingerprint technique, which emphasized the whole compositions of samples, has already been used in various fields, especially in identifying and assessing the quality of herbal medicines. High-performance liquid chromatography (HPLC) and near-infrared (NIR), with their unique characteristics of reliability, versatility, precision, and simple measurement, played an important role among all the fingerprint techniques. In this paper, a supervised pattern recognition method based on PLSDA algorithm by HPLC and NIR has been established to identify the information of Hibiscus mutabilis L. and Berberidis radix, two common kinds of herbal medicines. By comparing component analysis (PCA), linear discriminant analysis (LDA), and particularly partial least squares discriminant analysis (PLSDA) with different fingerprint preprocessing of NIR spectra variables, PLSDA model showed perfect functions on the analysis of samples as well as chromatograms. Most important, this pattern recognition method by HPLC and NIR can be used to identify different collection parts, collection time, and different origins or various species belonging to the same genera of herbal medicines which proved to be a promising approach for the identification of complex information of herbal medicines. PMID:26345990

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

PubMed

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

2012-04-01

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

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

NASA Technical Reports Server (NTRS)

Logan, T. L.; Huning, J. R.; Glackin, D. L.

1983-01-01

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Comparative genomic hybridisation as a supportive tool in diagnostic pathology

PubMed Central

Weiss, M M; Kuipers, E J; Meuwissen, S G M; van Diest, P J; Meijer, G A

2003-01-01

Aims: Patients with multiple tumour localisations pose a particular problem to the pathologist when the traditional combination of clinical data, morphology, and immunohistochemistry does not provide conclusive evidence to differentiate between metastasis or second primary, or does not identify the primary location in cases of metastases and two primary tumours. Because this is crucial to decide on further treatment, molecular techniques are increasingly being used as ancillary tools. Methods: The value of comparative genomic hybridisation (CGH) to differentiate between metastasis and second primary, or to identify the primary location in cases of metastases and two primary tumours was studied in seven patients. CGH is a cytogenetic technique that allows the analysis of genome wide amplifications, gains, and losses (deletions) in a tumour within a single experiment. The patterns of these chromosomal aberrations at the different tumour localisations were compared. Results: In all seven cases, CGH patterns of gains and losses supported the differentiation between metastasis and second primary, or the identification of the primary location in cases of metastases and two primary tumours. Conclusion: The results illustrate the diagnostic value of CGH in patients with multiple tumours. PMID:12835298

X-ray topographic studies and measurement of lattice parameter differences within synthetic diamonds grown by the reconstitution technique

NASA Astrophysics Data System (ADS)

Wierzchowski, W.; Moore, M.; Makepeace, A. P. W.; Yacoot, A.

1991-10-01

A 4 x 4 x 1.5 cu mm cuboctahedral diamond and two 0.7 mm thick slabs cut from a truncated octahedral diamond grown by the reconstitution technique were studied in different double-crystal arrangements with both conventional and synchrotron X-ray sources. The back-reflection double crystal topographs of large polished 001-plane-oriented faces intersecting different growth sectors, together with cathodoluminescence patterns, allowed identification of these sectors. A double-crystal arrangement, employing the -3 2 5 quartz reflection matching the symmetrical 004 diamond reflection in CuK(alpha 1) radiation, was used for measurement of lattice parameter differences with an accuracy of one and a half parts per million. The simultaneous investigation by means of Lang projection and section topography provided complementary information about the crystallographic defects and internal structures of growth sectors. Observation of the cuboctahedral diamond with a filter of peak transmittance at 430 nm revealed a 'Maltese cross' growth feature in the central (001) growth sector, which also affected the birefringence pattern. However, this feature only very slightly affected the double-crystal topographs.

A prototype methodology combining surface-enhanced laser desorption/ionization protein chip technology and artificial neural network algorithms to predict the chemoresponsiveness of breast cancer cell lines exposed to Paclitaxel and Doxorubicin under in vitro conditions.

PubMed

Mian, Shahid; Ball, Graham; Hornbuckle, Jo; Holding, Finn; Carmichael, James; Ellis, Ian; Ali, Selman; Li, Geng; McArdle, Stephanie; Creaser, Colin; Rees, Robert

2003-09-01

An ability to predict the likelihood of cellular response towards particular chemotherapeutic agents based upon protein expression patterns could facilitate the identification of biological molecules with previously undefined roles in the process of chemoresistance/chemosensitivity, and if robust enough these patterns might also be exploited towards the development of novel predictive assays. To ascertain whether proteomic based molecular profiling in conjunction with artificial neural network (ANN) algorithms could be applied towards the specific recognition of phenotypic patterns between either control or drug treated and chemosensitive or chemoresistant cellular populations, a combined approach involving MALDI-TOF matrix-assisted laser desorption/ionization-time of flight mass spectrometry, Ciphergen protein chip technology and ANN algorithms have been applied to specifically identify proteomic 'fingerprints' indicative of treatment regimen for chemosensitive (MCF-7, T47D) and chemoresistant (MCF-7/ADR) breast cancer cell lines following exposure to Doxorubicin or Paclitaxel. The results indicate that proteomic patterns can be identified by ANN algorithms to correctly assign 'class' for treatment regimen (e.g. control/drug treated or chemosensitive/chemoresistant) with a high degree of accuracy using boot-strap statistical validation techniques and that biomarker ion patterns indicative of response/non-response phenotypes are associated with MCF-7 and MCF-7/ADR cells exposed to Doxorubicin. We have also examined the predictive capability of this approach towards MCF-7 and T47D cells to ascertain whether prediction could be made based upon treatment regimen irrespective of cell lineage. Models were identified that could correctly assign class (control or Paclitaxel treatment) for 35/38 samples of an independent dataset. A similar level of predictive capability was also found (> 92%; n = 28) when proteomic patterns derived from the drug resistant cell line MCF-7/ADR were compared against those derived from MCF-7 and T47D as a model system of drug resistant and drug sensitive phenotypes. This approach might offer a potential methodology for predicting the biological behaviour of cancer cells towards particular chemotherapeutics and through protein isolation and sequence identification could result in the identification of biological molecules associated with chemosensitive/chemoresistance tumour phenotypes.

Computational modeling and experimental characterization of bacterial microcolonies for rapid detection using light scattering

NASA Astrophysics Data System (ADS)

Bai, Nan

A label-free and nondestructive optical elastic forward light scattering method has been extended for the analysis of microcolonies for food-borne bacteria detection and identification. To understand the forward light scattering phenomenon, a model based on the scalar diffraction theory has been employed: a bacterial colony is considered as a biological spatial light modulator with amplitude and phase modulation to the incoming light, which continues to propagate to the far-field to form a distinct scattering 'fingerprint'. Numerical implementation via angular spectrum method (ASM) and Fresnel approximation have been carried out through Fast Fourier Transform (FFT) to simulate this optical model. Sampling criteria to achieve unbiased and un-aliased simulation results have been derived and the effects of violating these conditions have been studied. Diffraction patterns predicted by these two methods (ASM and Fresnel) have been compared to show their applicability to different simulation settings. Through the simulation work, the correlation between the colony morphology and its forward scattering pattern has been established to link the number of diffraction rings and the half cone angle with the diameter and the central height of the Gaussian-shaped colonies. In order to experimentally prove the correlation, a colony morphology analyzer has been built and used to characterize the morphology of different bacteria genera and investigate their growth dynamics. The experimental measurements have demonstrated the possibility of differentiating bacteria Salmonella, Listeria, Escherichia in their early growth stage (100˜500 µm) based on their phenotypic characteristics. This conclusion has important implications in microcolony detection, as most bacteria of our interest need much less incubation time (8˜12 hours) to grow into this size range. The original forward light scatterometer has been updated to capture scattering patterns from microcolonies. Experiments have been performed to reveal the time dependent nature of scattering patterns. The experimental work has been compared with simulation results and demonstrated the feasibility of extending this technique for microcolony identification. Lastly, a quantitative phase imaging technique based on the phase gradient driven intensity variation has been studied and implemented to render the 2D phase map of the colony sample.

[Methods of a posteriori identification of food patterns in Brazilian children: a systematic review].

PubMed

Carvalho, Carolina Abreu de; Fonsêca, Poliana Cristina de Almeida; Nobre, Luciana Neri; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2016-01-01

The objective of this study is to provide guidance for identifying dietary patterns using the a posteriori approach, and analyze the methodological aspects of the studies conducted in Brazil that identified the dietary patterns of children. Articles were selected from the Latin American and Caribbean Literature on Health Sciences, Scientific Electronic Library Online and Pubmed databases. The key words were: Dietary pattern; Food pattern; Principal Components Analysis; Factor analysis; Cluster analysis; Reduced rank regression. We included studies that identified dietary patterns of children using the a posteriori approach. Seven studies published between 2007 and 2014 were selected, six of which were cross-sectional and one cohort, Five studies used the food frequency questionnaire for dietary assessment; one used a 24-hour dietary recall and the other a food list. The method of exploratory approach used in most publications was principal components factor analysis, followed by cluster analysis. The sample size of the studies ranged from 232 to 4231, the values of the Kaiser-Meyer-Olkin test from 0.524 to 0.873, and Cronbach's alpha from 0.51 to 0.69. Few Brazilian studies identified dietary patterns of children using the a posteriori approach and principal components factor analysis was the technique most used.

Comparing results of X-ray diffraction, µ-Raman spectroscopy and neutron diffraction when identifying chemical phases in seized nuclear material, during a comparative nuclear forensics exercise.

PubMed

Rondahl, Stina Holmgren; Pointurier, Fabien; Ahlinder, Linnea; Ramebäck, Henrik; Marie, Olivier; Ravat, Brice; Delaunay, François; Young, Emma; Blagojevic, Ned; Hester, James R; Thorogood, Gordon; Nelwamondo, Aubrey N; Ntsoane, Tshepo P; Roberts, Sarah K; Holliday, Kiel S

2018-01-01

This work presents the results for identification of chemical phases obtained by several laboratories as a part of an international nuclear forensic round-robin exercise. In this work powder X-ray diffraction (p-XRD) is regarded as the reference technique. Neutron diffraction produced a superior high-angle diffraction pattern relative to p-XRD. Requiring only small amounts of sample, µ-Raman spectroscopy was used for the first time in this context as a potentially complementary technique to p-XRD. The chemical phases were identified as pure UO 2 in two materials, and as a mixture of UO 2 , U 3 O 8 and an intermediate species U 3 O 7 in the third material.

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Microscopy techniques in flavivirus research.

PubMed

Chong, Mun Keat; Chua, Anthony Jin Shun; Tan, Terence Tze Tong; Tan, Suat Hoon; Ng, Mah Lee

2014-04-01

The Flavivirus genus is composed of many medically important viruses that cause high morbidity and mortality, which include Dengue and West Nile viruses. Various molecular and biochemical techniques have been developed in the endeavour to study flaviviruses. However, microscopy techniques still have irreplaceable roles in the identification of novel virus pathogens and characterization of morphological changes in virus-infected cells. Fluorescence microscopy contributes greatly in understanding the fundamental viral protein localizations and virus-host protein interactions during infection. Electron microscopy remains the gold standard for visualizing ultra-structural features of virus particles and infected cells. New imaging techniques and combinatory applications are continuously being developed to push the limit of resolution and extract more quantitative data. Currently, correlative live cell imaging and high resolution three-dimensional imaging have already been achieved through the tandem use of optical and electron microscopy in analyzing biological specimens. Microscopy techniques are also used to measure protein binding affinities and determine the mobility pattern of proteins in cells. This chapter will consolidate on the applications of various well-established microscopy techniques in flavivirus research, and discuss how recently developed microscopy techniques can potentially help advance our understanding in these membrane viruses. Copyright © 2013 Elsevier Ltd. All rights reserved.

Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibration

NASA Astrophysics Data System (ADS)

Yang, Haiqing; Wu, Di; He, Yong

2007-11-01

Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work. The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component (PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the calibration set is small.

Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.

PubMed

Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis

2016-03-01

Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community.

Translational research in pediatrics III: bronchoalveolar lavage.

PubMed

Radhakrishnan, Dhenuka; Yamashita, Cory; Gillio-Meina, Carolina; Fraser, Douglas D

2014-07-01

The role of flexible bronchoscopy and bronchoalveolar lavage (BAL) for the care of children with airway and pulmonary diseases is well established, with collected BAL fluid most often used clinically for microbiologic pathogen identification and cellular analyses. More recently, powerful analytic research methods have been used to investigate BAL samples to better understand the pathophysiological basis of pediatric respiratory disease. Investigations have focused on the cellular components contained in BAL fluid, such as macrophages, lymphocytes, neutrophils, eosinophils, and mast cells, as well as the noncellular components such as serum molecules, inflammatory proteins, and surfactant. Molecular techniques are frequently used to investigate BAL fluid for the presence of infectious pathologies and for cellular gene expression. Recent advances in proteomics allow identification of multiple protein expression patterns linked to specific respiratory diseases, whereas newer analytic techniques allow for investigations on surfactant quantification and function. These translational research studies on BAL fluid have aided our understanding of pulmonary inflammation and the injury/repair responses in children. We review the ethics and practices for the execution of BAL in children for translational research purposes, with an emphasis on the optimal handling and processing of BAL samples. Copyright © 2014 by the American Academy of Pediatrics.

Comparison between fingerprints of the epidermis and dermis: Perspectives in the identifying of corpses.

PubMed

Mizokami, Leila Lopes; Silva, Lara Rosana Vieira; Kückelhaus, Selma Aparecida Souza

2015-07-01

In forensic science, the putrefaction, maceration, mummification or burning make it difficult to collect the fingerprints of the epidermis for identification purposes. In such cases, the comparison between fingerprints collected from the dermal surface and the ante mortem pattern of the epidermal surface archived in databases must be performed. Therefore, considering that the identification of corpses is done by comparison of fingerprints on different surfaces, this study aimed to compare the epidermal and the dermal fingerprints to determine the discrepancies between the minutiae of both surfaces. The study was conducted with excised fingers of 19 fresh adult corpses. Once selected, excised and photographed, the fingers were subjected to maceration with 0.5% acetic acid solution for the removal of the epidermal glove and for registering the dermal fingerprint. Then, an area of 1cm(2) in the epidermal and dermal photographies was selected and the minutiae of each were separately marked by an expert in identification. The comparison between minutiae of the epidermal and dermal surfaces showed that: (1) both surfaces maintained the patterns and characteristics of fingerprints (arch, whorl or loop) and the characteristics related to the systems and the disposal of the lines, meaning the formation or not of deltas; (2) the total number of marked minutiae did not differ between both surfaces for the group of individuals (paired t test, p=0.48); (3) the percentage of coincidences and divergences (minutiae present on only one surface) between minutiae were 63.0±20.0% and 37.0±20.0%, respectively; (4) identification was possible for 16 fingers/individuals, but not for 3 of them; (5) the increase in the number of marked minutiae does not affect the percentage of coincidences. Our results demonstrate the feasibility of the dermal surface for identification purposes due to the high percentage of matching minutiae, but considering the discrepancies and the inconclusive identification of 3 fingers/individuals, our study points to the use of more fingers per individual, as well as the possibility of further studies to improve on the techniques for increasing the identification of corpses, or even to deploy new technologies to ensure their rapid and safe identification. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development of a reproducible method for determining quantity of water and its configuration in a marsh landscape

USGS Publications Warehouse

Suir, Glenn M.; Evers, D. Elaine; Steyer, Gregory D.; Sasser, Charles E.

2013-01-01

Coastal Louisiana is a dynamic and ever-changing landscape. From 1956 to 2010, over 3,734 km2 of Louisiana's coastal wetlands have been lost due to a combination of natural and human-induced activities. The resulting landscape constitutes a mosaic of conditions from highly deteriorated to relatively stable with intact landmasses. Understanding how and why coastal landscapes change over time is critical to restoration and rehabilitation efforts. Historically, changes in marsh pattern (i.e., size and spatial distribution of marsh landmasses and water bodies) have been distinguished using visual identification by individual researchers. Difficulties associated with this approach include subjective interpretation, uncertain reproducibility, and laborious techniques. In order to minimize these limitations, this study aims to expand existing tools and techniques via a computer-based method, which uses geospatial technologies for determining shifts in landscape patterns. Our method is based on a raster framework and uses landscape statistics to develop conditions and thresholds for a marsh classification scheme. The classification scheme incorporates land and water classified imagery and a two-part classification system: (1) ratio of water to land, and (2) configuration and connectivity of water within wetland landscapes to evaluate changes in marsh patterns. This analysis system can also be used to trace trajectories in landscape patterns through space and time. Overall, our method provides a more automated means of quantifying landscape patterns and may serve as a reliable landscape evaluation tool for future investigations of wetland ecosystem processes in the northern Gulf of Mexico.

Automatic detection of protected health information from clinic narratives.

PubMed

Yang, Hui; Garibaldi, Jonathan M

2015-12-01

This paper presents a natural language processing (NLP) system that was designed to participate in the 2014 i2b2 de-identification challenge. The challenge task aims to identify and classify seven main Protected Health Information (PHI) categories and 25 associated sub-categories. A hybrid model was proposed which combines machine learning techniques with keyword-based and rule-based approaches to deal with the complexity inherent in PHI categories. Our proposed approaches exploit a rich set of linguistic features, both syntactic and word surface-oriented, which are further enriched by task-specific features and regular expression template patterns to characterize the semantics of various PHI categories. Our system achieved promising accuracy on the challenge test data with an overall micro-averaged F-measure of 93.6%, which was the winner of this de-identification challenge. Copyright © 2015 Elsevier Inc. All rights reserved.

Detection of mycoloylglycerol by thin-layer chromatography as a tool for the rapid inclusion of corynebacteria of clinical origin in the genus Corynebacterium.

PubMed

Yagüe, G; Segovia, M; Valero-Guillén, P L

2000-01-28

A chemotaxonomic study of some corynebacteria isolated from clinical samples revealed characteristic thin-layer chromatographic patterns for meso-diaminopimelic acid containing species included in the genera Corynebacterium, Dermabacter and Brevibacterium. Notably, a specific compound was consistently detected in mycolic acid containing species of the genus Corynebacterium. This compound was composed by glycerol and mycolic acids and structural analyses carried out by fast atom bombardment mass spectrometry in C. minutissimum confirmed its identification as mycoloylglycerol. The chain length of mycoloyl groups in this molecule ranged from 28 to 34 carbon atoms, being mono-, di- or triunsaturated. Detection of mycoloylglycerol by thin-layer chromatography may be thus useful for the rapid inclusion of a great variety of corynebacteria of clinical origin in the genus Corynebacterium in laboratories employing chromatographic techniques as an adjunct for the identification of these microorganisms.

Analysis of cosmetic residues on a single human hair by ATR FT-IR microspectroscopy

NASA Astrophysics Data System (ADS)

Pienpinijtham, Prompong; Thammacharoen, Chuchaat; Naranitad, Suwimol; Ekgasit, Sanong

2018-05-01

In this work, ATR FT-IR spectra of single human hair and cosmetic residues on hair surface are successfully collected using a homemade dome-shaped Ge μIRE accessary installed on an infrared microscope. By collecting ATR spectra of hairs from the same person, the spectral patterns are identical and superimposed while different spectral features are observed from ATR spectra of hairs collected from different persons. The spectral differences depend on individual hair characteristics, chemical treatments, and cosmetics on hair surface. The "Contact-and-Collect" technique that transfers remarkable materials on the hair surface to the tip of the Ge μIRE enables an identification of cosmetics on a single hair. Moreover, the differences between un-split and split hairs are also studied in this report. These highly specific spectral features can be employed for unique identification or for differentiation of hairs based on the molecular structures of hairs and cosmetics on hairs.

Role of cognitive theory in the study of learning disability in mathematics.

PubMed

Geary, David C

2005-01-01

Gersten, Jordan, and Flojo (in this issue) provide the beginnings of an essential bridge between basic research on mathematical disabilities (MD) in young children and the application of this research for the early identification and remediation of these forms of learning disability. As they acknowledge, the field of MD is in the early stages of development, and thus recommendations regarding identification measures and remedial techniques must be considered preliminary. I discuss the importance of maintaining a tight link between theoretical and empirical research on children's developing numerical, arithmetical, and mathematical competencies and future research on learning disabilities in mathematics. This link will provide the foundation for transforming experimental procedures into assessment measures, understanding the cognitive strengths and weaknesses of children with these forms of learning disability, and developing remedial approaches based on the pattern of cognitive strengths and weaknesses for individual children.

Interdisciplinary applications and interpretations of ERTS data within the Susquehanna River Basin; resources inventory, land use and pollution

NASA Technical Reports Server (NTRS)

Mcmurtry, G. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Identification and mapping of three major kinds of coal refuse targets based on spectral signatures in channels four through seven of the ERTS-1 MSS were conducted. Correlation of the placement of the coal refuse targets with an existing map of their location was accomplished. Digital processing of ERTS-1 data permitted identification of stripped areas including ones that are not discernible by visual analysis of ERTS imagery. Combined visual and digital techniques of analyzing ERTS-1 data for geologic formations have been tried on selected areas of Pennsylvania. Mapping of two major agriculture counties to show land forms, drainage patterns, water, and urban areas were made using positive transparencies of MSS data. Two frames of the same central Pennsylvania area were brought into registration by translation and then merged even though the frames were obtained 71 days apart.

THz-wave parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We have also developed a novel basic technology for THz imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral trasillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Detailed analysis and group-type separation of natural fats and oils using comprehensive two-dimensional gas chromatography.

PubMed

Mondello, Luigi; Casilli, Alessandro; Tranchida, Peter Quinto; Dugo, Paola; Dugo, Giovanni

2003-11-26

Comprehensive gas chromatography (GC x GC) is an adequate methodology for the separation and identification of very complex samples. It is based on the coupling of two capillary columns that each give a different but substantial contribution to the unprecedented resolving power of this technique. The 2D space chromatograms that derive from GC x GC analysis have great potential for identification. This is due to the fact that the contour plot positions, pinpointed by two retention time coordinates, give characteristic patterns for specific families of compounds that can be mathematically translated. This investigation concerned the application of this principle to fatty acid methyl esters that were grouped on an equal double bond number basis. The ester samples were derived from various lipids and all underwent bidimensional analysis on two sets of columns. Peak attribution was supported by mass spectra, linear retention indices and information reported in the literature.

Bacteremia due to Moraxella atlantae in a cancer patient.

PubMed

De Baere, Thierry; Muylaert, An; Everaert, Els; Wauters, Georges; Claeys, Geert; Verschraegen, Gerda; Vaneechoutte, Mario

2002-07-01

A gram-negative alkaline phosphatase- and pyrrolidone peptidase-positive rod-shaped bacterium (CCUG 45702) was isolated from two aerobic blood cultures from a female cancer patient. No identification could be reached using phenotypic techniques. Amplification of the tRNA intergenic spacers revealed fragments with lengths of 116, 133, and 270 bp, but no such pattern was present in our reference library. Sequencing of the 16S rRNA gene revealed its identity as Moraxella atlantae, a species isolated only rarely and published only once as causing infection. In retrospect, the phenotypic characteristics fit the identification as M. atlantae (formerly known as CDC group M-3). Comparative 16S rRNA sequence analysis indicates that M. atlantae, M. lincolnii, and M. osloensis might constitute three separate genera within the MORAXELLACEAE: After treatment with amoxicillin-clavulanic acid for 2 days, fever subsided and the patient was dismissed.

Bacteremia Due to Moraxella atlantae in a Cancer Patient

PubMed Central

De Baere, Thierry; Muylaert, An; Everaert, Els; Wauters, Georges; Claeys, Geert; Verschraegen, Gerda; Vaneechoutte, Mario

2002-01-01

A gram-negative alkaline phosphatase- and pyrrolidone peptidase-positive rod-shaped bacterium (CCUG 45702) was isolated from two aerobic blood cultures from a female cancer patient. No identification could be reached using phenotypic techniques. Amplification of the tRNA intergenic spacers revealed fragments with lengths of 116, 133, and 270 bp, but no such pattern was present in our reference library. Sequencing of the 16S rRNA gene revealed its identity as Moraxella atlantae, a species isolated only rarely and published only once as causing infection. In retrospect, the phenotypic characteristics fit the identification as M. atlantae (formerly known as CDC group M-3). Comparative 16S rRNA sequence analysis indicates that M. atlantae, M. lincolnii, and M. osloensis might constitute three separate genera within the Moraxellaceae. After treatment with amoxicillin-clavulanic acid for 2 days, fever subsided and the patient was dismissed. PMID:12089312

Atmospheric solids analysis probe mass spectrometry for the rapid identification of pollens and semi-quantification of flavonoid fingerprints

DOE PAGES

Xiao, Xiaoyin; Miller, Lance L.; Parchert, Kylea J.; ...

2016-06-08

From allergies to plant reproduction, pollens have important impacts on the health of human and plant populations, yet identification of pollen grains remains difficult and time-consuming. Low-volatility flavonoids generated from pollens cannot be easily characterized and quantified with current analytical techniques. Here we demonstrate the novel use of atmospheric solids analysis probe mass spectrometry (ASAP-MS) for the characterization of flavonoids in pollens. Flavonoid patterns were generated for pollens collected from different plant types (trees and bushes) in addition to bee pollens from distinct geographic regions. Standard flavonoids (kaempferol and rhamnazin) and those produced from pollens were compared and assessed withmore » ASAP-MS using low-energy collision MS/MS. Results for a semi-quantitative method for assessing the amount of a flavonoid in pollens are also presented.« less

Atmospheric solids analysis probe mass spectrometry for the rapid identification of pollens and semi-quantification of flavonoid fingerprints

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

Xiao, Xiaoyin; Miller, Lance L.; Parchert, Kylea J.

From allergies to plant reproduction, pollens have important impacts on the health of human and plant populations, yet identification of pollen grains remains difficult and time-consuming. Low-volatility flavonoids generated from pollens cannot be easily characterized and quantified with current analytical techniques. Here we demonstrate the novel use of atmospheric solids analysis probe mass spectrometry (ASAP-MS) for the characterization of flavonoids in pollens. Flavonoid patterns were generated for pollens collected from different plant types (trees and bushes) in addition to bee pollens from distinct geographic regions. Standard flavonoids (kaempferol and rhamnazin) and those produced from pollens were compared and assessed withmore » ASAP-MS using low-energy collision MS/MS. Results for a semi-quantitative method for assessing the amount of a flavonoid in pollens are also presented.« less

Integration of Real-Time Intraoperative Contrast-Enhanced Ultrasound and Color Doppler Ultrasound in the Surgical Treatment of Spinal Cord Dural Arteriovenous Fistulas.

PubMed

Della Pepa, Giuseppe Maria; Sabatino, Giovanni; Sturiale, Carmelo Lucio; Marchese, Enrico; Puca, Alfredo; Olivi, Alessandro; Albanese, Alessio

2018-04-01

In the surgical treatment of spinal dural arteriovenous fistulas (DAVFs), intraoperative definition of anatomic characteristics of the DAVF and identification of the fistulous point is mandatory to effectively exclude the DAVF. Intraoperative ultrasound and contrast-enhanced ultrasound integrated with color Doppler ultrasound was applied in the surgical setting for a cervical DAVF to identify the fistulous point and evaluate correct occlusion of the fistula. Integration of intraoperative ultrasound and contrast-enhanced ultrasound is a simple, cost-effective technique that provides an opportunity for real-time dynamic visualization of DAVF vascular patterns, identification of the fistulous point, and assessment of correct exclusion. Compared with other intraoperative tools, such as indocyanine green videoangiography, it allows the surgeon to visualize hidden anatomic and vascular structures, minimizing surgical manipulation and guiding the surgeon during resection. Copyright © 2018 Elsevier Inc. All rights reserved.

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Quantifying Traces of Tool Use: A Novel Morphometric Analysis of Damage Patterns on Percussive Tools

PubMed Central

Caruana, Matthew V.; Carvalho, Susana; Braun, David R.; Presnyakova, Darya; Haslam, Michael; Archer, Will; Bobe, Rene; Harris, John W. K.

2014-01-01

Percussive technology continues to play an increasingly important role in understanding the evolution of tool use. Comparing the archaeological record with extractive foraging behaviors in nonhuman primates has focused on percussive implements as a key to investigating the origins of lithic technology. Despite this, archaeological approaches towards percussive tools have been obscured by a lack of standardized methodologies. Central to this issue have been the use of qualitative, non-diagnostic techniques to identify percussive tools from archaeological contexts. Here we describe a new morphometric method for distinguishing anthropogenically-generated damage patterns on percussive tools from naturally damaged river cobbles. We employ a geomatic approach through the use of three-dimensional scanning and geographical information systems software to statistically quantify the identification process in percussive technology research. This will strengthen current technological analyses of percussive tools in archaeological frameworks and open new avenues for translating behavioral inferences of early hominins from percussive damage patterns. PMID:25415303

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Recognition of complex human behaviours using 3D imaging for intelligent surveillance applications

NASA Astrophysics Data System (ADS)

Yao, Bo; Lepley, Jason J.; Peall, Robert; Butler, Michael; Hagras, Hani

2016-10-01

We introduce a system that exploits 3-D imaging technology as an enabler for the robust recognition of the human form. We combine this with pose and feature recognition capabilities from which we can recognise high-level human behaviours. We propose a hierarchical methodology for the recognition of complex human behaviours, based on the identification of a set of atomic behaviours, individual and sequential poses (e.g. standing, sitting, walking, drinking and eating) that provides a framework from which we adopt time-based machine learning techniques to recognise complex behaviour patterns.

Source identification of PM10, collected at a heavy-traffic roadside, by analyzing individual particles using synchrotron radiation.

PubMed

Yue, Weisheng; Li, Yan; Li, Xiaolin; Yu, Xiaohan; Deng, Biao; Liu, Jiangfeng; Wan, Tianmin; Zhang, Guilin; Huang, Yuying; He, Wei; Hua, Wei

2004-09-01

Synchrotron radiation microbeam X-ray fluorescence (micro-SXRF) was used to analyze individual aerosol particles collected at a height of 2 m above a heavy-traffic roadside in a heavy-industrial area of Shanghai. A pattern recognition technique, which took micro-SXRF spectra of single aerosol particles as its fingerprint, was used to identify the origins of the particles. The particles collected from the environmental monitoring site are mainly from metallurgic industry (26%), unleaded gasoline automobile exhaust (15%), coal combustion (10%), cement dust (10%) and motorcycle exhaust (8%).

Non-destructive terahertz imaging of illicit drugs using spectral fingerprints

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuuki; Inoue, Hiroyuki

2003-10-01

The absence of non-destructive inspection techniques for illicit drugs hidden in mail envelopes has resulted in such drugs being smuggled across international borders freely. We have developed a novel basic technology for terahertz imaging, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. The spatial distributions of the targets are obtained from terahertz multispectral transillumination images, using absorption spectra measured with a tunable terahertz-wave source. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Capturing the vital vascular fingerprint with optical coherence tomography

PubMed Central

Liu, Gangjun; Chen, Zhongping

2014-01-01

Using fingerprints as a method to identify an individual has been accepted in forensics since the nineteenth century, and the fingerprint has become one of the most widely used biometric characteristics. Most of the modern fingerprint recognition systems are based on the print pattern of the finger surface and are not robust against spoof attaching. We demonstrate a novel vital vascular fingerprint system using Doppler optical coherence tomography that provides highly sensitive and reliable personal identification. Because the system is based on blood flow, which only exists in a livng person, the technique is robust against spoof attaching. PMID:23913068

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.

Application of identification techniques to remote manipulator system flight data

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Automated Coronal Loop Identification using Digital Image Processing Techniques

NASA Astrophysics Data System (ADS)

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

2003-05-01

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

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

PubMed

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

2016-01-01

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

Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns.

PubMed

Lee, Wonki; Kim, Seulgee; Kim, Daeeun

2018-03-28

The electrocardiogram (ECG) waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG). To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.

Examining relations of entertainment with social interaction motives and team identification.

PubMed

Gau, Li-Shiue; Wann, Daniel L; James, Jeffrey D

2010-10-01

The goal was to investigate a potential causal pattern between the motives of sport spectators and team identification by using a cross-lagged panel design. Questionnaires were completed by 229 participants at the beginning and end of one NCAA (National Collegiate Athletic Association) college football season for 4 mo. in the USA. The questionnaire included three items for each motive (Social Interaction and Entertainment), three items measuring team identification, and demographic items. The relation of Entertainment at Time 1 to team identification at Time 2 was larger than the relation of team identification at Time 1 to Entertainment at Time 2. This suggests that the motivation of Entertainment may lead to the formation of team identification more than team identification leads to Entertainment. However, the motive of Social Interaction did not show the same pattern. As results of this study suggested some spectator sport motives might lead to identification with a team, the hypothesis that all motives would be the basis of team identification might not be correct.

System Identification of Mistuned Bladed Disks from Traveling Wave Response Measurements

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Laser micro-etching of metal prostheses for personal identification

PubMed Central

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

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

Laser micro-etching of metal prostheses for personal identification.

PubMed

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

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

Nurses' Behaviors and Visual Scanning Patterns May Reduce Patient Identification Errors

ERIC Educational Resources Information Center

Marquard, Jenna L.; Henneman, Philip L.; He, Ze; Jo, Junghee; Fisher, Donald L.; Henneman, Elizabeth A.

2011-01-01

Patient identification (ID) errors occurring during the medication administration process can be fatal. The aim of this study is to determine whether differences in nurses' behaviors and visual scanning patterns during the medication administration process influence their capacities to identify patient ID errors. Nurse participants (n = 20)…

An overview of recent advances in system identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1994-01-01

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

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

PubMed

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

2016-01-01

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

Characterization and isolation of a T-DNA tagged banana promoter active during in vitro culture and low temperature stress.

PubMed

Santos, Efrén; Remy, Serge; Thiry, Els; Windelinckx, Saskia; Swennen, Rony; Sági, László

2009-06-24

Next-generation transgenic plants will require a more precise regulation of transgene expression, preferably under the control of native promoters. A genome-wide T-DNA tagging strategy was therefore performed for the identification and characterization of novel banana promoters. Embryogenic cell suspensions of a plantain-type banana were transformed with a promoterless, codon-optimized luciferase (luc+) gene and low temperature-responsive luciferase activation was monitored in real time. Around 16,000 transgenic cell colonies were screened for baseline luciferase activity at room temperature 2 months after transformation. After discarding positive colonies, cultures were re-screened in real-time at 26 degrees C followed by a gradual decrease to 8 degrees C. The baseline activation frequency was 0.98%, while the frequency of low temperature-responsive luciferase activity was 0.61% in the same population of cell cultures. Transgenic colonies with luciferase activity responsive to low temperature were regenerated to plantlets and luciferase expression patterns monitored during different regeneration stages. Twenty four banana DNA sequences flanking the right T-DNA borders in seven independent lines were cloned via PCR walking. RT-PCR analysis in one line containing five inserts allowed the identification of the sequence that had activated luciferase expression under low temperature stress in a developmentally regulated manner. This activating sequence was fused to the uidA reporter gene and back-transformed into a commercial dessert banana cultivar, in which its original expression pattern was confirmed. This promoter tagging and real-time screening platform proved valuable for the identification of novel promoters and genes in banana and for monitoring expression patterns throughout in vitro development and low temperature treatment. Combination of PCR walking techniques was efficient for the isolation of candidate promoters even in a multicopy T-DNA line. Qualitative and quantitative GUS expression analyses of one tagged promoter in a commercial cultivar demonstrated a reproducible promoter activity pattern during in vitro culture. Thus, this promoter could be used during in vitro selection and generation of commercial transgenic plants.

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Comparing results of X-ray diffraction, µ-Raman spectroscopy and neutron diffraction when identifying chemical phases in seized nuclear material, during a comparative nuclear forensics exercise

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

Rondahl, Stina Holmgren; Pointurier, Fabien; Ahlinder, Linnea

This work presents the results for identification of chemical phases obtained by several laboratories as a part of an international nuclear forensic round-robin exercise. In this work powder X-ray diffraction (p-XRD) is regarded as the reference technique. Neutron diffraction produced a superior high-angle diffraction pattern relative to p-XRD. Requiring only small amounts of sample, µ-Raman spectroscopy was used for the first time in this context as a potentially complementary technique to p-XRD. The chemical phases were identified as pure UO 2 in two materials, and as a mixture of UO 2, U 3O 8 and an intermediate species U 3Omore » 7 in the third material.« less

Comparing results of X-ray diffraction, µ-Raman spectroscopy and neutron diffraction when identifying chemical phases in seized nuclear material, during a comparative nuclear forensics exercise

DOE PAGES

Rondahl, Stina Holmgren; Pointurier, Fabien; Ahlinder, Linnea; ...

2018-01-24

This work presents the results for identification of chemical phases obtained by several laboratories as a part of an international nuclear forensic round-robin exercise. In this work powder X-ray diffraction (p-XRD) is regarded as the reference technique. Neutron diffraction produced a superior high-angle diffraction pattern relative to p-XRD. Requiring only small amounts of sample, µ-Raman spectroscopy was used for the first time in this context as a potentially complementary technique to p-XRD. The chemical phases were identified as pure UO 2 in two materials, and as a mixture of UO 2, U 3O 8 and an intermediate species U 3Omore » 7 in the third material.« less

Analysis of skin oil by FT-IR spectroscopy

NASA Astrophysics Data System (ADS)

Dasarathy, Keshava B.; Chittur, Krishnan K.; Dasarathy, Belur V.

1996-11-01

Secreted skin oil is a complex mixture of lipids, cholesterol, fatty acids, and a large number of other components. Its composition varies among individuals and with changes in physiology. In this paper, the feasibility of obtaining reproducible spectra of skin oils from individuals with a very simple, noninvasive technique is reported. Using pattern recognition algorithms, spectra could be classified on the basis of ethnicity and gender. Differences in spectra between individuals were larger than those between replicate samples taken from the same individual. While there are easier techniques for gender and ethnic identification, our purpose in this paper is to show that information of some value exists in skin-oil spectra. We believe that this approach could be used for such practical discrimination problems such as the determination of high and low cholesterol levels if confirmatory information for training such classifiers were available.

Elastic light scattering for clinical pathogens identification: application to early screening of Staphylococcus aureus on specific medium

NASA Astrophysics Data System (ADS)

Schultz, E.; Genuer, V.; Marcoux, P.; Gal, O.; Belafdil, C.; Decq, D.; Maurin, Max; Morales, S.

2018-02-01

Elastic Light Scattering (ELS) is an innovative technique to identify bacterial pathogens directly on culture plates. Compelling results have already been reported for agri-food applications. Here, we have developed ELS for clinical diagnosis, starting with Staphylococcus aureus early screening. Our goal is to bring a result (positive/negative) after only 6 h of growth to fight surgical-site infections. The method starts with the acquisition of the scattering pattern arising from the interaction between a laser beam and a single bacterial colony growing on a culture medium. Then, the resulting image, considered as the bacterial species signature, is analyzed using statistical learning techniques. We present a custom optical setup able to target bacterial colonies with various sizes (30-500 microns). This system was used to collect a reference dataset of 38 strains of S. aureus and other Staphyloccocus species (5459 images) on ChromIDSAID/ MRSA bi-plates. A validation set from 20 patients has then been acquired and clinically-validated according to chromogenic enzymatic tests. The best correct-identification rate between S. aureus and S. non-aureus (94.7%) has been obtained using a support vector machine classifier trained on a combination of Fourier-Bessel moments and Local- Binary-Patterns extracted features. This statistical model applied to the validation set provided a sensitivity and a specificity of 90.0% and 56.9%, or alternatively, a positive predictive value of 47% and a negative predictive value of 93%. From a clinical point of view, the results head in the right direction and pave the way toward the WHO's requirements for rapid, low-cost, and automated diagnosis tools.

Bilateral symmetry aspects in computer-aided Alzheimer's disease diagnosis by single-photon emission-computed tomography imaging.

PubMed

Illán, Ignacio Alvarez; Górriz, Juan Manuel; Ramírez, Javier; Lang, Elmar W; Salas-Gonzalez, Diego; Puntonet, Carlos G

2012-11-01

This paper explores the importance of the latent symmetry of the brain in computer-aided systems for diagnosing Alzheimer's disease (AD). Symmetry and asymmetry are studied from two points of view: (i) the development of an effective classifier within the scope of machine learning techniques, and (ii) the assessment of its relevance to the AD diagnosis in the early stages of the disease. The proposed methodology is based on eigenimage decomposition of single-photon emission-computed tomography images, using an eigenspace extension to accommodate odd and even eigenvectors separately. This feature extraction technique allows for support-vector-machine classification and image analysis. Identification of AD patterns is improved when the latent symmetry of the brain is considered, with an estimated 92.78% accuracy (92.86% sensitivity, 92.68% specificity) using a linear kernel and a leave-one-out cross validation strategy. Also, asymmetries may be used to define a test for AD that is very specific (90.24% specificity) but not especially sensitive. Two main conclusions are derived from the analysis of the eigenimage spectrum. Firstly, the recognition of AD patterns is improved when considering only the symmetric part of the spectrum. Secondly, asymmetries in the hypo-metabolic patterns, when present, are more pronounced in subjects with AD. Copyright © 2012 Elsevier B.V. All rights reserved.

A Parallel Genetic Algorithm to Discover Patterns in Genetic Markers that Indicate Predisposition to Multifactorial Disease

PubMed Central

Rausch, Tobias; Thomas, Alun; Camp, Nicola J.; Cannon-Albright, Lisa A.; Facelli, Julio C.

2008-01-01

This paper describes a novel algorithm to analyze genetic linkage data using pattern recognition techniques and genetic algorithms (GA). The method allows a search for regions of the chromosome that may contain genetic variations that jointly predispose individuals for a particular disease. The method uses correlation analysis, filtering theory and genetic algorithms (GA) to achieve this goal. Because current genome scans use from hundreds to hundreds of thousands of markers, two versions of the method have been implemented. The first is an exhaustive analysis version that can be used to visualize, explore, and analyze small genetic data sets for two marker correlations; the second is a GA version, which uses a parallel implementation allowing searches of higher-order correlations in large data sets. Results on simulated data sets indicate that the method can be informative in the identification of major disease loci and gene-gene interactions in genome-wide linkage data and that further exploration of these techniques is justified. The results presented for both variants of the method show that it can help genetic epidemiologists to identify promising combinations of genetic factors that might predispose to complex disorders. In particular, the correlation analysis of IBD expression patterns might hint to possible gene-gene interactions and the filtering might be a fruitful approach to distinguish true correlation signals from noise. PMID:18547558

["Dual Guidance"? - parallel combination of ultrasound-guidance and nerve stimulation - Contra].

PubMed

Maecken, Tim

2015-07-01

Sonography is a highly user-dependent technology. It presupposes a considerable degree of sonoanatomic and sonographic knowledge and requires good practical skills of the examiner. Sonography allows the identification of the puncture target, observes the needle feed and assesses the spread pattern of the local anesthetic in real time. Peripheral electrical nerve stimulation (PNS) cannot offer these advantages to the same degree, but may allow nerve localization under difficult sonographic conditions. The combination of the two locating techniques is complex in its practical implementation. Partially, the use of one location technique is made even more difficult by the combination with the second. PNS in parallel to sonography serves primarily as a warning technology in the case of an invisible cannula tip. It should not be construed as a compensation technique for the lack of sonographic skills or knowledge. However, PNS may be helpful in the sense of a bridging technology as long as the user is aware of its limitations. © Georg Thieme Verlag Stuttgart · New York.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique

PubMed Central

Ardila-Rey, Jorge Alfredo; Montaña, Johny; Schurch, Roger; Covolan Ulson, José Alfredo; Bani, Nurul Aini

2018-01-01

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals. PMID:29596337

An Integrated Approach to Change the Outcome Part II: Targeted Neuromuscular Training Techniques to Reduce Identified ACL Injury Risk Factors

PubMed Central

Myer, Gregory D.; Ford, Kevin R.; Brent, Jensen L.; Hewett, Timothy E.

2014-01-01

Prior reports indicate that female athletes who demonstrate high knee abduction moments (KAMs) during landing are more responsive to neuromuscular training designed to reduce KAM. Identification of female athletes who demonstrate high KAM, which accurately identifies those at risk for noncontact anterior cruciate ligament (ACL) injury, may be ideal for targeted neuromuscular training. Specific neuromuscular training targeted to the underlying biomechanical components that increase KAM may provide the most efficient and effective training strategy to reduce noncontact ACL injury risk. The purpose of the current commentary is to provide an integrative approach to identify and target mechanistic underpinnings to increased ACL injury in female athletes. Specific neuromuscular training techniques will be presented that address individual algorithm components related to high knee load landing patterns. If these integrated techniques are employed on a widespread basis, prevention strategies for noncontact ACL injury among young female athletes may prove both more effective and efficient. PMID:22580980

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.

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.

Symbolic dynamic filtering and language measure for behavior identification of mobile robots.

PubMed

Mallapragada, Goutham; Ray, Asok; Jin, Xin

2012-06-01

This paper presents a procedure for behavior identification of mobile robots, which requires limited or no domain knowledge of the underlying process. While the features of robot behavior are extracted by symbolic dynamic filtering of the observed time series, the behavior patterns are classified based on language measure theory. The behavior identification procedure has been experimentally validated on a networked robotic test bed by comparison with commonly used tools, namely, principal component analysis for feature extraction and Bayesian risk analysis for pattern classification.

Direct mapping of symbolic DNA sequence into frequency domain in global repeat map algorithm

PubMed Central

Glunčić, Matko; Paar, Vladimir

2013-01-01

The main feature of global repeat map (GRM) algorithm (www.hazu.hr/grm/software/win/grm2012.exe) is its ability to identify a broad variety of repeats of unbounded length that can be arbitrarily distant in sequences as large as human chromosomes. The efficacy is due to the use of complete set of a K-string ensemble which enables a new method of direct mapping of symbolic DNA sequence into frequency domain, with straightforward identification of repeats as peaks in GRM diagram. In this way, we obtain very fast, efficient and highly automatized repeat finding tool. The method is robust to substitutions and insertions/deletions, as well as to various complexities of the sequence pattern. We present several case studies of GRM use, in order to illustrate its capabilities: identification of α-satellite tandem repeats and higher order repeats (HORs), identification of Alu dispersed repeats and of Alu tandems, identification of Period 3 pattern in exons, implementation of ‘magnifying glass’ effect, identification of complex HOR pattern, identification of inter-tandem transitional dispersed repeat sequences and identification of long segmental duplications. GRM algorithm is convenient for use, in particular, in cases of large repeat units, of highly mutated and/or complex repeats, and of global repeat maps for large genomic sequences (chromosomes and genomes). PMID:22977183

Flow Pattern Phenomena in Two-Phase Flow in Microchannels

NASA Astrophysics Data System (ADS)

Keska, Jerry K.; Simon, William E.

2004-02-01

Space transportation systems require high-performance thermal protection and fluid management techniques for systems ranging from cryogenic fluid management devices to primary structures and propulsion systems exposed to extremely high temperatures, as well as for other space systems such as cooling or environment control for advanced space suits and integrated circuits. Although considerable developmental effort is being expended to bring potentially applicable technologies to a readiness level for practical use, new and innovative methods are still needed. One such method is the concept of Advanced Micro Cooling Modules (AMCMs), which are essentially compact two-phase heat exchangers constructed of microchannels and designed to remove large amounts of heat rapidly from critical systems by incorporating phase transition. The development of AMCMs requires fundamental technological advancement in many areas, including: (1) development of measurement methods/systems for flow-pattern measurement/identification for two-phase mixtures in microchannels; (2) development of a phenomenological model for two-phase flow which includes the quantitative measure of flow patterns; and (3) database development for multiphase heat transfer/fluid dynamics flows in microchannels. This paper focuses on the results of experimental research in the phenomena of two-phase flow in microchannels. The work encompasses both an experimental and an analytical approach to incorporating flow patterns for air-water mixtures flowing in a microchannel, which are necessary tools for the optimal design of AMCMs. Specifically, the following topics are addressed: (1) design and construction of a sensitive test system for two-phase flow in microchannels, one which measures ac and dc components of in-situ physical mixture parameters including spatial concentration using concomitant methods; (2) data acquisition and analysis in the amplitude, time, and frequency domains; and (3) analysis of results including evaluation of data acquisition techniques and their validity for application in flow pattern determination.

Pattern identification in time-course gene expression data with the CoGAPS matrix factorization.

PubMed

Fertig, Elana J; Stein-O'Brien, Genevieve; Jaffe, Andrew; Colantuoni, Carlo

2014-01-01

Patterns in time-course gene expression data can represent the biological processes that are active over the measured time period. However, the orthogonality constraint in standard pattern-finding algorithms, including notably principal components analysis (PCA), confounds expression changes resulting from simultaneous, non-orthogonal biological processes. Previously, we have shown that Markov chain Monte Carlo nonnegative matrix factorization algorithms are particularly adept at distinguishing such concurrent patterns. One such matrix factorization is implemented in the software package CoGAPS. We describe the application of this software and several technical considerations for identification of age-related patterns in a public, prefrontal cortex gene expression dataset.

Identification of dietary patterns associated with obesity in a nationally representative survey of Canadian adults: application of a priori, hybrid, and simplified dietary pattern techniques.

PubMed

Jessri, Mahsa; Wolfinger, Russell D; Lou, Wendy Y; L'Abbé, Mary R

2017-03-01

Background: Analyzing the effects of dietary patterns is an important approach for examining the complex role of nutrition in the etiology of obesity and chronic diseases. Objectives: The objectives of this study were to characterize the dietary patterns of Canadians with the use of a priori, hybrid, and simplified dietary pattern techniques, and to compare the associations of these patterns with obesity risk in individuals with and without chronic diseases (unhealthy and healthy obesity). Design: Dietary recalls from 11,748 participants (≥18 y of age) in the cross-sectional, nationally representative Canadian Community Health Survey 2.2 were used. A priori dietary pattern was characterized with the use of the previously validated 2015 Dietary Guidelines for Americans Adherence Index (DGAI). Weighted partial least squares (hybrid method) was used to derive an energy-dense (ED), high-fat (HF), low-fiber density (LFD) dietary pattern with the use of 38 food groups. The associations of derived dietary patterns with disease outcomes were then tested with the use of multinomial logistic regression. Results: An ED, HF, and LFD dietary pattern had high positive loadings for fast foods, carbonated drinks, and refined grains, and high negative loadings for whole fruits and vegetables (≥|0.17|). Food groups with a high loading were summed to form a simplified dietary pattern score. Moving from the first (healthiest) to the fourth (least healthy) quartiles of the ED, HF, and LFD pattern and the simplified dietary pattern scores was associated with increasingly elevated ORs for unhealthy obesity, with individuals in quartile 4 having an OR of 2.57 (95% CI: 1.75, 3.76) and 2.73 (95% CI: 1.88, 3.98), respectively ( P -trend < 0.0001). Individuals who adhered the most to the 2015 DGAI recommendations (quartile 4) had a 53% lower OR of unhealthy obesity ( P -trend < 0.0001). The associations of dietary patterns with healthy obesity and unhealthy nonobesity were weaker, albeit significant. Conclusions: Consuming an ED, HF, and LFD dietary pattern and lack of adherence to the recommendations of the 2015 DGAI were associated with a significantly higher risk of obesity with and without accompanying chronic diseases. © 2017 American Society for Nutrition.

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

ERIC Educational Resources Information Center

DeMers, Michael N.; Vincent, Jeffrey S.

2007-01-01

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

Regression equations for sex and population detection using the lip print pattern among Egyptian and Malaysian adult.

PubMed

Abdel Aziz, Manal H; Badr El Dine, Fatma M M; Saeed, Nourhan M M

2016-11-01

Identification of sex and ethnicity has always been a challenge in the fields of forensic medicine and criminal investigations. Fingerprinting and DNA comparisons are probably the most common techniques used in this context. However, since they cannot always be used, it is necessary to apply different and less known techniques such as lip prints. Is to study the pattern of lip print in Egyptian and Malaysian populations and its relation to sex and populations difference. Also, to develop equations for sex and populations detection using lip print pattern by different populations (Egyptian and Malaysian). The sample comprised of 120 adults volunteers divided into two ethnic groups; sixty adult Egyptians (30 males and 30 females) and sixty adult Malaysians (30 males and 30 females). The lip prints were collected on a white paper. Each lip print was divided into four compartments and were classified and scored according to Suzuki and Tsuchihashi classification. Data were statistically analyzed. The results showed that type III lip print pattern (intersected grooves) was the predominant type in both the Egyptian and Malaysian populations. Type II and III were the most frequent in Egyptian males (28.3% each), while in Egyptian females type III pattern was predominant (46.7%). As regards Malaysian males, type III lip print pattern was the predominant one (41.7%), while type II lip print pattern was predominant (30.8%) in Malaysian females. Statistical analysis of different quadrants showed significant differences between males and females in the Egyptian population in the third and fourth quadrants. On the other hand, significant differences were detected only in the second quadrant between Malaysian males and females. Also, a statistically significant difference was present in the second quadrant between Egyptian and Malaysian males. Using the regression analysis, four regression equations were obtained. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

NASA Technical Reports Server (NTRS)

Drew, Michael; Sheth, Kapil

2015-01-01

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

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

NASA Astrophysics Data System (ADS)

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

2004-05-01

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

Neural-network-based system for recognition of partially occluded shapes and patterns

NASA Astrophysics Data System (ADS)

Mital, Dinesh P.; Teoh, Eam-Khwang; Amarasinghe, S. K.; Suganthan, P. N.

1996-10-01

The purpose of this paper is to demonstrate how a structural matching approach can be used to perfonn effective rotational invariant fingerprint identification. In this approach, each of the exiracted features is correlated with Live of its nearest neighbouring features to form a local feature gmup for a first-stage matching. After that, the feature with the highest match is used as a central feature whereby all the other features are correlated to form a global feature group for a second.stage matching. The correlation between the features is in terms of distance and relative angle. This approach actually make the matching method rotational invariant A substantial amount of testing was carried out and it shows that this matching technique is capable of matching the four basic fingerprint patterns with an average matching time of4 seconds on a 66Mhz, 486 DX personal computer.

Differentiation of closely related isomers: application of data mining techniques in conjunction with variable wavelength infrared multiple photon dissociation mass spectrometry for identification of glucose-containing disaccharide ions.

PubMed

Stefan, Sarah E; Ehsan, Mohammad; Pearson, Wright L; Aksenov, Alexander; Boginski, Vladimir; Bendiak, Brad; Eyler, John R

2011-11-15

Data mining algorithms have been used to analyze the infrared multiple photon dissociation (IRMPD) patterns of gas-phase lithiated disaccharide isomers irradiated with either a line-tunable CO(2) laser or a free electron laser (FEL). The IR fragmentation patterns over the wavelength range of 9.2-10.6 μm have been shown in earlier work to correlate uniquely with the asymmetry at the anomeric carbon in each disaccharide. Application of data mining approaches for data analysis allowed unambiguous determination of the anomeric carbon configurations for each disaccharide isomer pair using fragmentation data at a single wavelength. In addition, the linkage positions were easily assigned. This combination of wavelength-selective IRMPD and data mining offers a powerful and convenient tool for differentiation of structurally closely related isomers, including those of gas-phase carbohydrate complexes.

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

PubMed Central

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

1994-01-01

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

Design of biometrics identification system on palm vein using infrared light

NASA Astrophysics Data System (ADS)

Syafiq, Muhammad; Nasution, Aulia M. T.

2016-11-01

Image obtained by the LED with wavelength 740nm and 810nm showed that the contrast gradient of vein pattern is low and palm pattern still exist. It means that 740nm and 810nm are less suitable for the detection of blood vessels in the palm of the hand. At a wavelength of 940nm, the pattern is clearly visible, and the pattern of the palms is mostly gone. Furthermore, the pre-processing performed using smoothing process which include Gaussian filter and median filter and contrast stretching. Image segmentation is done by getting the ROI area that would be obtained its information. The identification process of image features obtained by using MSE (Mean Suare Error) method ,LBP (Local Binary Pattern). Furthermore, we will use a database consists of 5 different palm vein pattern which will be used for testing the tool in the identification process. All the process above are done using Raspberry Pi device. The Obtained MSE parameter is 0.025 and LBP features score are less than 10-3 for image to be matched.

Signal and array processing techniques for RFID readers

NASA Astrophysics Data System (ADS)

Wang, Jing; Amin, Moeness; Zhang, Yimin

2006-05-01

Radio Frequency Identification (RFID) has recently attracted much attention in both the technical and business communities. It has found wide applications in, for example, toll collection, supply-chain management, access control, localization tracking, real-time monitoring, and object identification. Situations may arise where the movement directions of the tagged RFID items through a portal is of interest and must be determined. Doppler estimation may prove complicated or impractical to perform by RFID readers. Several alternative approaches, including the use of an array of sensors with arbitrary geometry, can be applied. In this paper, we consider direction-of-arrival (DOA) estimation techniques for application to near-field narrowband RFID problems. Particularly, we examine the use of a pair of RFID antennas to track moving RFID tagged items through a portal. With two antennas, the near-field DOA estimation problem can be simplified to a far-field problem, yielding a simple way for identifying the direction of the tag movement, where only one parameter, the angle, needs to be considered. In this case, tracking of the moving direction of the tag simply amounts to computing the spatial cross-correlation between the data samples received at the two antennas. It is pointed out that the radiation patterns of the reader and tag antennas, particularly their phase characteristics, have a significant effect on the performance of DOA estimation. Indoor experiments are conducted in the Radar Imaging and RFID Labs at Villanova University for validating the proposed technique for target movement direction estimations.

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

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

DTIC Science & Technology

1991-07-01

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

The perception of syllable affiliation of singleton stops in repetitive speech.

PubMed

de Jong, Kenneth J; Lim, Byung-Jin; Nagao, Kyoko

2004-01-01

Stetson (1951) noted that repeating singleton coda consonants at fast speech rates makes them be perceived as onset consonants affiliated with a following vowel. The current study documents the perception of rate-induced resyllabification, as well as what temporal properties give rise to the perception of syllable affiliation. Stimuli were extracted from a previous study of repeated stop + vowel and vowel + stop syllables (de Jong, 2001a, 2001b). Forced-choice identification tasks show that slow repetitions are clearly distinguished. As speakers increase rate, they reach a point after which listeners disagree as to the affiliation of the stop. This pattern is found for voiced and voiceless consonants using different stimulus extraction techniques. Acoustic models of the identifications indicate that the sudden shift in syllabification occurs with the loss of an acoustic hiatus between successive syllables. Acoustic models of the fast rate identifications indicate various other qualities, such as consonant voicing, affect the probability that the consonants will be perceived as onsets. These results indicate a model of syllabic affiliation where specific juncture-marking aspects of the signal dominate parsing, and in their absence other differences provide additional, weaker cues to syllabic affiliation.

Molecular identification and antifungal susceptibility profile of Candida species isolated from patients with vulvovaginitis in Tehran, Iran.

PubMed

Sharifynia, Somayeh; Falahati, Mehraban; Akhlaghi, Lame; Foroumadi, Alireza; Fateh, Roohollah

2017-01-01

Rapid and accurate identification and evaluation of antifungal susceptibility pattern of Candida isolates are crucial to determine suitable antifungal drugs for the treatment of patients with vulvovaginitis candidiasis. Vaginal samples were collected from 150 women with suspicious vaginal candidiasis, and then cultured on Sabouraoud's Dextrose Agar with chloramphenicol to isolate Candida species. After identification of Candida isolates using polymerase chain reaction-restriction fragment length polymorphism technique, antifungal susceptibility testing of four azolic antifungal drugs was carried out using broth microdilution method according to the CLSI M27-A3. Candida species were isolated from eighty suspected patients (61.79%). The most common pathogen was Candida albicans (63.75%). Resistance to fluconazole and ketoconazole was observed in 27.5% and 23.75% of Candida isolates, respectively, and only 2% of Candida isolates were resistant to miconazole. Interestingly, resistance to fluconazole in C. albicans was more than other Candida species. The results indicated that therapy should be selected according to the antifungal susceptibility tests for the prevention of treatment failure and miconazole therapy can be considered as the best therapeutic choice in the management of vulvovaginitis.

Facile Quantification and Identification Techniques for Reducing Gases over a Wide Concentration Range Using a MOS Sensor in Temperature-Cycled Operation.

PubMed

Schultealbert, Caroline; Baur, Tobias; Schütze, Andreas; Sauerwald, Tilman

2018-03-01

Dedicated methods for quantification and identification of reducing gases based on model-based temperature-cycled operation (TCO) using a single commercial MOS gas sensor are presented. During high temperature phases the sensor surface is highly oxidized, yielding a significant sensitivity increase after switching to lower temperatures (differential surface reduction, DSR). For low concentrations, the slope of the logarithmic conductance during this low-temperature phase is evaluated and can directly be used for quantification. For higher concentrations, the time constant for reaching a stable conductance during the same low-temperature phase is evaluated. Both signals represent the reaction rate of the reducing gas on the strongly oxidized surface at this low temperature and provide a linear calibration curve, which is exceptional for MOS sensors. By determining these reaction rates on different low-temperature plateaus and applying pattern recognition, the resulting footprint can be used for identification of different gases. All methods are tested over a wide concentration range from 10 ppb to 100 ppm (4 orders of magnitude) for four different reducing gases (CO, H₂, ammonia and benzene) using randomized gas exposures.

Molecular identification and antifungal susceptibility profile of Candida species isolated from patients with vulvovaginitis in Tehran, Iran

PubMed Central

Sharifynia, Somayeh; Falahati, Mehraban; Akhlaghi, Lame; Foroumadi, Alireza; Fateh, Roohollah

2017-01-01

Background: Rapid and accurate identification and evaluation of antifungal susceptibility pattern of Candida isolates are crucial to determine suitable antifungal drugs for the treatment of patients with vulvovaginitis candidiasis. Materials and Methods: Vaginal samples were collected from 150 women with suspicious vaginal candidiasis, and then cultured on Sabouraoud's Dextrose Agar with chloramphenicol to isolate Candida species. After identification of Candida isolates using polymerase chain reaction-restriction fragment length polymorphism technique, antifungal susceptibility testing of four azolic antifungal drugs was carried out using broth microdilution method according to the CLSI M27-A3. Results: Candida species were isolated from eighty suspected patients (61.79%). The most common pathogen was Candida albicans (63.75%). Resistance to fluconazole and ketoconazole was observed in 27.5% and 23.75% of Candida isolates, respectively, and only 2% of Candida isolates were resistant to miconazole. Interestingly, resistance to fluconazole in C. albicans was more than other Candida species. Conclusion: The results indicated that therapy should be selected according to the antifungal susceptibility tests for the prevention of treatment failure and miconazole therapy can be considered as the best therapeutic choice in the management of vulvovaginitis. PMID:29387119

Facile Quantification and Identification Techniques for Reducing Gases over a Wide Concentration Range Using a MOS Sensor in Temperature-Cycled Operation

PubMed Central

Schultealbert, Caroline; Baur, Tobias; Schütze, Andreas; Sauerwald, Tilman

2018-01-01

Dedicated methods for quantification and identification of reducing gases based on model-based temperature-cycled operation (TCO) using a single commercial MOS gas sensor are presented. During high temperature phases the sensor surface is highly oxidized, yielding a significant sensitivity increase after switching to lower temperatures (differential surface reduction, DSR). For low concentrations, the slope of the logarithmic conductance during this low-temperature phase is evaluated and can directly be used for quantification. For higher concentrations, the time constant for reaching a stable conductance during the same low-temperature phase is evaluated. Both signals represent the reaction rate of the reducing gas on the strongly oxidized surface at this low temperature and provide a linear calibration curve, which is exceptional for MOS sensors. By determining these reaction rates on different low-temperature plateaus and applying pattern recognition, the resulting footprint can be used for identification of different gases. All methods are tested over a wide concentration range from 10 ppb to 100 ppm (4 orders of magnitude) for four different reducing gases (CO, H2, ammonia and benzene) using randomized gas exposures. PMID:29494545

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine

PubMed Central

Hsiung, Chang; Pederson, Christopher G.; Zou, Peng; Smith, Valton; von Gunten, Marc; O’Brien, Nada A.

2016-01-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machine (SVM) modeling. We used a set of 19 pharmaceutical compounds including various active pharmaceutical ingredients (APIs) and excipients and six MicroNIR spectrometers to test model transferability. For the test of large-scale classification, we used another set of 253 pharmaceutical compounds comprised of both chemically and physically different APIs and excipients. We compared SVM with conventional chemometric modeling techniques, including soft independent modeling of class analogy, partial least squares discriminant analysis, linear discriminant analysis, and quadratic discriminant analysis. Support vector machine modeling using a linear kernel, especially when combined with a hierarchical scheme, exhibited excellent performance in both model transferability and large-scale classification. Hence, ultra-compact, portable and robust MicroNIR spectrometers coupled with SVM modeling can make on-site and in situ pharmaceutical RMID for large-volume applications highly achievable. PMID:27029624

The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

PubMed Central

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis. PMID:25705672

The novel quantitative technique for assessment of gait symmetry using advanced statistical learning algorithm.

PubMed

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

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

The connecting link! Lip prints and fingerprints.

PubMed

Negi, Amita; Negi, Anurag

2016-01-01

Lip prints and fingerprints are considered to be unique to each individual. The study of fingerprints and lip prints is very popular in personal identification of the deceased and in criminal investigations. This study was done to find the predominant lip and fingerprint patterns in males and females in the North Indian population and also to find any correlation between lip print and fingerprint patterns within a gender. Two hundred students (100 males, 100 females) were included in the study. Lip prints were recorded for each individual using a dark-colored lipstick and the right thumb impression was recorded using an ink pad. The lip prints and fingerprints were analyzed using a magnifying glass. The Chi-square test was used for statistical analysis. The branched pattern in males and the vertical pattern in females were the predominant lip print patterns. The predominant fingerprint pattern in both males and females was found to be the loop pattern, followed by the whorl pattern and then the arch pattern. No statistically significant correlation was found between lip prints and fingeprints. However, the arch type of fingerprint was found to be associated with different lip print patterns in males and females. Lip prints and fingerprints can be used for personal identification in a forensic scenario. Further correlative studies between lip prints and fingerprints could be useful in forensic science for gender identification.

Individual identification via electrocardiogram analysis.

PubMed

Fratini, Antonio; Sansone, Mario; Bifulco, Paolo; Cesarelli, Mario

2015-08-14

During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations.

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

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

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

2011-09-22

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

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

Identification of N-nitrosamines in treated drinking water using nanoelectrospray ionization high-field asymmetric waveform ion mobility spectrometry with quadrupole time-of-flight mass spectrometry.

PubMed

Zhao, Yuan Yuan; Liu, Xin; Boyd, Jessica M; Qin, Feng; Li, Jianjun; Li, Xing-Fang

2009-01-01

We report a nanoelectrospray ionization (nESI) with high-field asymmetric waveform ion mobility spectrometry (FAIMS) and tandem mass spectrometry (MS-MS) method for determination of small molecules of m/z 50 to 200 and its potential application in environmental analysis. Integration of nESI with FAIMS and MS-MS combines the advantages of these three techniques into one method. The nESI provides efficient sample introduction and ionization and allows for collection of multiple data from only microliters of samples. The FAIMS provides rapid separation, reduces or eliminates background interference, and improves the signal-to-noise ratio as much as 10-fold over nESI-MS-MS. The tandem quadrupole time-of-flight MS detection provides accurate mass and mass spectral measurements for structural identification. Characteristics of FAIMS compensation voltage (CV) spectra of seven nitrosamines, N-nitrosodimethylamine (NDMA), N-nitrosomethylethylamine (NMEA), N-nitrosodiethylamine (NDEA), N-nitrosodi-n-propylamine (NDPA), N-nitrosodi-n-butylamine (NDBA), N-nitrosopiperidine (NPip), and N-nitrosopyrrolidine (NPyr), were analyzed. The optimal CV of the nitrosamines (at DV -4000 V) were: -1.6 V, NDBA; 2.6 V, NDPA; 6.6 V, NPip; 8.8 V, NDEA; 13.2 V, NPyr; 14.4 V, NMEA; and 19.4 V, NDMA. Fragmentation patterns of the seven nitrosamines in the nESI-FAIMS-MS-MS were also obtained. The specific CV and MS-MS spectra resulted in positive identification of NPyr and NPip in a treated water sample, demonstrating the potential application of this technique in environmental analysis.

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.

The Effect of Achievement Test Selection on Identification of Learning Disabilities within a Patterns of Strengths and Weaknesses Framework

ERIC Educational Resources Information Center

Miciak, Jeremy; Taylor, W. Pat; Denton, Carolyn A.; Fletcher, Jack M.

2015-01-01

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 of LD classification decisions of the concordance/discordance method (C/DM) across different psychoeducational assessment batteries. C/DM criteria were…

Patterns in the Identification of and Outcomes for Children and Youth with Disabilities. Final Report. NCEE 2010-4005

ERIC Educational Resources Information Center

Blackorby, Jose; Schiller, Ellen; Mallik, Sangeeta; Hebbeler, Kathleen; Huang, Tracy; Javitz, Harold; Marder, Camille; Nagle, Katherine; Shaver, Debra; Wagner, Mary; Williamson, Cyndi

2010-01-01

Reported here are the results of analyses to describe the patterns of identification and academic and developmental outcomes for children with disabilities, conducted as part of the 2004 National Assessment of the implementation of the Individuals with Disabilities Education Act (IDEA). This report provides background context for National…

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

PubMed

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

2009-05-01

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

Toward faster and more accurate star sensors using recursive centroiding and star identification

NASA Astrophysics Data System (ADS)

Samaan, Malak Anees

The objective of this research is to study different novel developed techniques for spacecraft attitude determination methods using star tracker sensors. This dissertation addresses various issues on developing improved star tracker software, presents new approaches for better performance of star trackers, and considers applications to realize high precision attitude estimates. Star-sensors are often included in a spacecraft attitude-system instrument suite, where high accuracy pointing capability is required. Novel methods for image processing, camera parameters ground calibration, autonomous star pattern recognition, and recursive star identification are researched and implemented to achieve high accuracy and a high frame rate star tracker that can be used for many space missions. This dissertation presents the methods and algorithms implemented for the one Field of View 'FOV'Star NavI sensor that was tested aboard the STS-107 mission in spring 2003 and the two fields of view StarNavII sensor for the EO-3 spacecraft scheduled for launch in 2007. The results of this research enable advances in spacecraft attitude determination based upon real time star sensing and pattern recognition. Building upon recent developments in image processing, pattern recognition algorithms, focal plane detectors, electro-optics, and microprocessors, the star tracker concept utilized in this research has the following key objectives for spacecraft of the future: lower cost, lower mass and smaller volume, increased robustness to environment-induced aging and instrument response variations, increased adaptability and autonomy via recursive self-calibration and health-monitoring on-orbit. Many of these attributes are consequences of improved algorithms that are derived in this dissertation.

Ameloglyphics: A possible forensic tool for person identification following high temperature and acid exposure

PubMed Central

Juneja, Manjushree; Juneja, Saurabh; Rakesh, Nagaraju; Bhoomareddy Kantharaj, Yashoda Devi

2016-01-01

Introduction: Forensic odontology is a branch that is evolving over time and has opened newer avenues that may help in the identification of individuals. Tooth prints are the enamel rod end patterns on tooth surface and they are considered as a hard tissue analog to fingerprints. Teeth have the highest resistance to most environmental effects like fire, desiccation, and decomposition, and may be used as a forensic evidence. Aims and Objectives: The aim of the study was to evaluate if the tooth prints could be used for an individual's identification and reproducibility and permanency of these tooth prints after exposing the teeth to acid and various degrees of temperature. Materials and Methods: 90 tooth prints from 20 freshly extracted maxillary premolar teeth were obtained. Cellophane tape technique was used to record enamel rod end patterns on tooth surface. Ten teeth (one from each patient) were immersed in 36.46% hydrochloric acid and the tooth prints were obtained at various intervals (5 min, 10 min, and 20 min). The other 10 teeth (one from each patient) were incinerated and impression was made at various intervals (80° C, 400° C, 600° C, and 750° C). Tooth prints obtained from different teeth (total of 90 tooth prints) were analyzed using Verifinger® standard SDK version 5.0 software. Results: All the 20 original tooth prints were distinct from each other and no inter-individual or intra-individual similarity was found. The tooth prints from the same tooth after it was exposed to acid or heat were reproducible and showed high to very high similarity with the original tooth print of that particular tooth stored in the database. Conclusion: Tooth prints may be used as an effective aid in person identification even in adverse conditions such as burn and acid attack injuries. PMID:27051220

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments.

PubMed

Krami, Loghman Khoda; Amiri, Fazel; Sefiyanian, Alireza; Shariff, Abdul Rashid B Mohamed; Tabatabaie, Tayebeh; Pradhan, Biswajeet

2013-12-01

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF(G)) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF(G) techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF(G) technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.

Knowledge Discovery from Vibration Measurements

PubMed Central

Li, Jian; Wang, Daoyao

2014-01-01

The framework as well as the particular algorithms of pattern recognition process is widely adopted in structural health monitoring (SHM). However, as a part of the overall process of knowledge discovery from data bases (KDD), the results of pattern recognition are only changes and patterns of changes of data features. In this paper, based on the similarity between KDD and SHM and considering the particularity of SHM problems, a four-step framework of SHM is proposed which extends the final goal of SHM from detecting damages to extracting knowledge to facilitate decision making. The purposes and proper methods of each step of this framework are discussed. To demonstrate the proposed SHM framework, a specific SHM method which is composed by the second order structural parameter identification, statistical control chart analysis, and system reliability analysis is then presented. To examine the performance of this SHM method, real sensor data measured from a lab size steel bridge model structure are used. The developed four-step framework of SHM has the potential to clarify the process of SHM to facilitate the further development of SHM techniques. PMID:24574933

Identification and assessment of hazardous compounds in drinking water.

PubMed

Fawell, J K; Fielding, M

1985-12-01

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

Gram-positive anaerobic cocci--commensals and opportunistic pathogens.

PubMed

Murphy, Elizabeth Carmel; Frick, Inga-Maria

2013-07-01

Among the Gram-positive anaerobic bacteria associated with clinical infections, the Gram-positive anaerobic cocci (GPAC) are the most prominent and account for approximately 25-30% of all isolated anaerobic bacteria from clinical specimens. Still, routine culture and identification of these slowly growing anaerobes to the species level has been limited in the diagnostic laboratory, mainly due to the requirement of prolonged incubation times and time-consuming phenotypic identification. In addition, GPAC are mostly isolated from polymicrobial infections with known pathogens and therefore their relevance has often been overlooked. However, through improvements in diagnostic and in particular molecular techniques, the isolation and identification of individual genera and species of GPAC associated with specific infections have been enhanced. Furthermore, the taxonomy of GPAC has undergone considerable changes over the years, mainly due to the development of molecular identification methods. Existing species have been renamed and novel species have been added, resulting in changes of the nomenclature. As the abundance and significance of GPAC in clinical infections grow, knowledge of virulence factors and antibiotic resistance patterns of different species becomes more important. The present review describes recent advances of GPAC and what is known of the biology and pathogenic effects of Anaerococcus, Finegoldia, Parvimonas, Peptoniphilus and Peptostreptococcus, the most important GPAC genera isolated from human infections. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-02-01

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

Ant trophallactic networks: simultaneous measurement of interaction patterns and food dissemination

NASA Astrophysics Data System (ADS)

Greenwald, Efrat; Segre, Enrico; Feinerman, Ofer

2015-07-01

Eusocial societies and ants, in particular, maintain tight nutritional regulation at both individual and collective levels. The mechanisms that underlie this control are far from trivial since, in these distributed systems, information about the global supply and demand is not available to any single individual. Here we present a novel technique for non-intervening frequent measurement of the food load of all individuals in an ant colony, including during trophallactic events in which food is transferred by mouth-to-mouth feeding. Ants are imaged using a dual camera setup that produces both barcode-based identification and fluorescence measurement of labeled food. This system provides detailed measurements that enable one to quantitatively study the adaptive food distribution network. To demonstrate the capabilities of our method, we present sample observations that were unattainable using previous techniques, and could provide insight into the mechanisms underlying food exchange.

Evaluation and comparison of ERTS measurements of major crops and soil associations for selected test sites in the central United States. [Texas, Indiana, Kansas, Iowa, Nebraska, and North Dakota

NASA Technical Reports Server (NTRS)

Baumgardner, M. F. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Multispectral scanner data obtained by ERTS-1 over six test sites in the Central United States were analyzed and interpreted. ERTS-1 data for some of the test sites were geometrically corrected and temporally overlayed. Computer-implemented pattern recognition techniques were used in the analysis of all multispectral data. These techniques were used to evaluate ERTS-1 data as a tool for soil survey. Geology maps and land use inventories were prepared by digital analysis of multispectral data. Identification and mapping of crop species and rangelands were achieved throught the analysis of 1972 and 1973 ERTS-1 data. Multiple dates of ERTS-1 data were examined to determine the variation with time of the areal extent of surface water resources on the Southern Great Plain.

An intermediate level of abstraction for computational systems chemistry.

PubMed

Andersen, Jakob L; Flamm, Christoph; Merkle, Daniel; Stadler, Peter F

2017-12-28

Computational techniques are required for narrowing down the vast space of possibilities to plausible prebiotic scenarios, because precise information on the molecular composition, the dominant reaction chemistry and the conditions for that era are scarce. The exploration of large chemical reaction networks is a central aspect in this endeavour. While quantum chemical methods can accurately predict the structures and reactivities of small molecules, they are not efficient enough to cope with large-scale reaction systems. The formalization of chemical reactions as graph grammars provides a generative system, well grounded in category theory, at the right level of abstraction for the analysis of large and complex reaction networks. An extension of the basic formalism into the realm of integer hyperflows allows for the identification of complex reaction patterns, such as autocatalysis, in large reaction networks using optimization techniques.This article is part of the themed issue 'Reconceptualizing the origins of life'. © 2017 The Author(s).

Event Reconstruction Techniques in NOvA

NASA Astrophysics Data System (ADS)

Baird, M.; Bian, J.; Messier, M.; Niner, E.; Rocco, D.; Sachdev, K.

2015-12-01

The NOvA experiment is a long-baseline neutrino oscillation experiment utilizing the NuMI beam generated at Fermilab. The experiment will measure the oscillations within a muon neutrino beam in a 300 ton Near Detector located underground at Fermilab and a functionally-identical 14 kiloton Far Detector placed 810 km away. The detectors are liquid scintillator tracking calorimeters with a fine-grained cellular structure that provides a wealth of information for separating the different particle track and shower topologies. Each detector has its own challenges with the Near Detector seeing multiple overlapping neutrino interactions in each event and the Far Detector having a large background of cosmic rays due to being located on the surface. A series of pattern recognition techniques have been developed to go from event records, to spatially and temporally separating individual interactions, to vertexing and tracking, and particle identification. This combination of methods to achieve the full event reconstruction will be discussed.

The utility of ERTS-1 data for applications in land use classification. [Texas Gulf Coast

NASA Technical Reports Server (NTRS)

Dornbach, J. E.; Mckain, G. E.

1974-01-01

A comprehensive study has been undertaken to determine the extent to which conventional image interpretation and computer-aided (spectral pattern recognition) analysis techniques using ERTS-1 data could be used to detect, identify (classify), locate, and measure current land use over large geographic areas. It can be concluded that most of the level 1 and 2 categories in the USGS Circular no. 671 can be detected in the Houston-Gulf Coast area using a combination of both techniques for analysis. These capabilities could be exercised over larger geographic areas, however, certain factors such as different vegetative cover, topography, etc. may have to be considered in other geographic regions. The best results in identification (classification), location, and measurement of level 1 and 2 type categories appear to be obtainable through automatic data processing of multispectral scanner computer compatible tapes.

Giardia/giardiasis - a perspective on diagnostic and analytical tools.

PubMed

Koehler, Anson V; Jex, Aaron R; Haydon, Shane R; Stevens, Melita A; Gasser, Robin B

2014-01-01

Giardiasis is a gastrointestinal disease of humans and other animals caused by species of parasitic protists of the genus Giardia. This disease is transmitted mainly via the faecal-oral route (e.g., in water or food) and is of socioeconomic importance worldwide. The accurate detection and genetic characterisation of the different species and population variants (usually referred to as assemblages and/or sub-assemblages) of Giardia are central to understanding their transmission patterns and host spectra. The present article provides a background on Giardia and giardiasis, and reviews some key techniques employed for the identification and genetic characterisation of Giardia in biological samples, the diagnosis of infection and the analysis of genetic variation within and among species of Giardia. Advances in molecular techniques provide a solid basis for investigating the systematics, population genetics, ecology and epidemiology of Giardia species and genotypes as well as the prevention and control of giardiasis. Copyright © 2013 Elsevier Inc. All rights reserved.

Advances in segmentation modeling for health communication and social marketing campaigns.

PubMed

Albrecht, T L; Bryant, C

1996-01-01

Large-scale communication campaigns for health promotion and disease prevention involve analysis of audience demographic and psychographic factors for effective message targeting. A variety of segmentation modeling techniques, including tree-based methods such as Chi-squared Automatic Interaction Detection and logistic regression, are used to identify meaningful target groups within a large sample or population (N = 750-1,000+). Such groups are based on statistically significant combinations of factors (e.g., gender, marital status, and personality predispositions). The identification of groups or clusters facilitates message design in order to address the particular needs, attention patterns, and concerns of audience members within each group. We review current segmentation techniques, their contributions to conceptual development, and cost-effective decision making. Examples from a major study in which these strategies were used are provided from the Texas Women, Infants and Children Program's Comprehensive Social Marketing Program.

Proanthocyanidin screening by LC-ESI-MS of Portuguese red wines made with teinturier grapes.

PubMed

Teixeira, Natércia; Azevedo, Joana; Mateus, Nuno; de Freitas, Victor

2016-01-01

Proanthocyanidins (PAs) are one of the most important polyphenolic compounds in wine. Among PAs, prodelphinidin (PD) dimers and trimers have not been widely detected in wines due to the lack of available commercial standards and the difficulty to detect and isolate them from natural sources. LC-ESI-MS (liquid chromatography-electrospray ionization-mass spectrometry) with the right chromatographic conditions has proven to be a powerful tool for PAs detection and identification in complex samples. This technique has been applied to an exhaustive study of PA composition of two Portuguese red wines made with teinturier grapes, especially for the identification of PD dimers and trimers. Tandem mass spectrometry (MS/MS) with ion trap provided additional information about the structures of these compounds through the fragmentation patterns of the pseudomolecular ions. A LC-ESI-MS method was optimized and 41 different compounds were found. Among them are included 8 PD dimers and 13 PD trimers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Performance analysis and prediction in triathlon.

PubMed

Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

2016-01-01

Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

Study on the criteria for assessing skull-face correspondence in craniofacial superimposition.

PubMed

Ibáñez, Oscar; Valsecchi, Andrea; Cavalli, Fabio; Huete, María Isabel; Campomanes-Alvarez, Blanca Rosario; Campomanes-Alvarez, Carmen; Vicente, Ricardo; Navega, David; Ross, Ann; Wilkinson, Caroline; Jankauskas, Rimantas; Imaizumi, Kazuhiko; Hardiman, Rita; Jayaprakash, Paul Thomas; Ruiz, Elena; Molinero, Francisco; Lestón, Patricio; Veselovskaya, Elizaveta; Abramov, Alexey; Steyn, Maryna; Cardoso, Joao; Humpire, Daniel; Lusnig, Luca; Gibelli, Daniele; Mazzarelli, Debora; Gaudio, Daniel; Collini, Federica; Damas, Sergio

2016-11-01

Craniofacial superimposition has the potential to be used as an identification method when other traditional biological techniques are not applicable due to insufficient quality or absence of ante-mortem and post-mortem data. Despite having been used in many countries as a method of inclusion and exclusion for over a century it lacks standards. Thus, the purpose of this research is to provide forensic practitioners with standard criteria for analysing skull-face relationships. Thirty-seven experts from 16 different institutions participated in this study, which consisted of evaluating 65 criteria for assessing skull-face anatomical consistency on a sample of 24 different skull-face superimpositions. An unbiased statistical analysis established the most objective and discriminative criteria. Results did not show strong associations, however, important insights to address lack of standards were provided. In addition, a novel methodology for understanding and standardizing identification methods based on the observation of morphological patterns has been proposed. Crown Copyright © 2016. Published by Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2014-11-15

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

Informatics for Metabolomics.

PubMed

Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

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

ERIC Educational Resources Information Center

Hammonds, S. J.

1990-01-01

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

Comparison of modal identification techniques using a hybrid-data approach

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1986-01-01

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

Precise design-based defect characterization and root cause analysis

NASA Astrophysics Data System (ADS)

Xie, Qian; Venkatachalam, Panneerselvam; Lee, Julie; Chen, Zhijin; Zafar, Khurram

2017-03-01

As semiconductor manufacturing continues its march towards more advanced technology nodes, it becomes increasingly important to identify and characterize design weak points, which is typically done using a combination of inline inspection data and the physical layout (or design). However, the employed methodologies have been somewhat imprecise, relying greatly on statistical techniques to signal excursions. For example, defect location error that is inherent to inspection tools prevents them from reporting the true locations of defects. Therefore, common operations such as background-based binning that are designed to identify frequently failing patterns cannot reliably identify specific weak patterns. They can only identify an approximate set of possible weak patterns, but within these sets there are many perfectly good patterns. Additionally, characterizing the failure rate of a known weak pattern based on inline inspection data also has a lot of fuzziness due to coordinate uncertainty. SEM (Scanning Electron Microscope) Review attempts to come to the rescue by capturing high resolution images of the regions surrounding the reported defect locations, but SEM images are reviewed by human operators and the weak patterns revealed in those images must be manually identified and classified. Compounding the problem is the fact that a single Review SEM image may contain multiple defective patterns and several of those patterns might not appear defective to the human eye. In this paper we describe a significantly improved methodology that brings advanced computer image processing and design-overlay techniques to better address the challenges posed by today's leading technology nodes. Specifically, new software techniques allow the computer to analyze Review SEM images in detail, to overlay those images with reference design to detect every defect that might be present in all regions of interest within the overlaid reference design (including several classes of defects that human operators will typically miss), to obtain the exact defect location on design, to compare all defective patterns thus detected against a library of known patterns, and to classify all defective patterns as either new or known. By applying the computer to these tasks, we automate the entire process from defective pattern identification to pattern classification with high precision, and we perform this operation en masse during R & D, ramp, and volume production. By adopting the methodology, whenever a specific weak pattern is identified, we are able to run a series of characterization operations to ultimately arrive at the root cause. These characterization operations can include (a) searching all pre-existing Review SEM images for the presence of the specific weak pattern to determine whether there is any spatial (within die or within wafer) or temporal (within any particular date range, before or after a mask revision, etc.) correlation and (b) understanding the failure rate of the specific weak pattern to prioritize the urgency of the problem, (c) comparing the weak pattern against an OPC (Optical Procimity Correction) Verification report or a PWQ (Process Window Qualification)/FEM (Focus Exposure Matrix) result to assess the likelihood of it being a litho-sensitive pattern, etc. After resolving the specific weak pattern, we will categorize it as known pattern, and the engineer will move forward with discovering new weak patterns.

Chapter 01: Wood identification and pattern recognition

Treesearch

Alex Wiedenhoeft

2011-01-01

Wood identification is a combination of art and science. Although the bulk of this manual focuses on the scientific characteristics used to make accurate field identifications of wood, the contribution of the artistic component to the identification process should be neither overlooked nor understated. Though the accumulation of scientific knowledge and experience is...

Subcritical flutter testing and system identification

NASA Technical Reports Server (NTRS)

Houbolt, J. C.

1974-01-01

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

Identifying Pre-High School Students' Science Class Motivation Profiles to Increase Their Science Identification and Persistence

ERIC Educational Resources Information Center

Chittum, Jessica R.; Jones, Brett D.

2017-01-01

One purpose of this study was to determine whether patterns existed in pre-high school students' motivation-related perceptions of their science classes. Another purpose was to examine the extent to which these patterns were related to their science identification, gender, grade level, class effort, and intentions to persist in science. We…

Anti-nuclear antibody screening using HEp-2 cells.

PubMed

Buchner, Carol; Bryant, Cassandra; Eslami, Anna; Lakos, Gabriella

2014-06-23

The American College of Rheumatology position statement on ANA testing stipulates the use of IIF as the gold standard method for ANA screening(1). Although IIF is an excellent screening test in expert hands, the technical difficulties of processing and reading IIF slides--such as the labor intensive slide processing, manual reading, the need for experienced, trained technologists and the use of dark room--make the IIF method difficult to fit in the workflow of modern, automated laboratories. The first and crucial step towards high quality ANA screening is careful slide processing. This procedure is labor intensive, and requires full understanding of the process, as well as attention to details and experience. Slide reading is performed by fluorescent microscopy in dark rooms, and is done by trained technologists who are familiar with the various patterns, in the context of cell cycle and the morphology of interphase and dividing cells. Provided that IIF is the first line screening tool for SARD, understanding the steps to correctly perform this technique is critical. Recently, digital imaging systems have been developed for the automated reading of IIF slides. These systems, such as the NOVA View Automated Fluorescent Microscope, are designed to streamline the routine IIF workflow. NOVA View acquires and stores high resolution digital images of the wells, thereby separating image acquisition from interpretation; images are viewed an interpreted on high resolution computer monitors. It stores images for future reference and supports the operator's interpretation by providing fluorescent light intensity data on the images. It also preliminarily categorizes results as positive or negative, and provides pattern recognition for positive samples. In summary, it eliminates the need for darkroom, and automates and streamlines the IIF reading/interpretation workflow. Most importantly, it increases consistency between readers and readings. Moreover, with the use of barcoded slides, transcription errors are eliminated by providing sample traceability and positive patient identification. This results in increased patient data integrity and safety. The overall goal of this video is to demonstrate the IIF procedure, including slide processing, identification of common IIF patterns, and the introduction of new advancements to simplify and harmonize this technique.

X-Ray Diffraction for In-Situ Mineralogical Analysis of Planetesimals.

NASA Astrophysics Data System (ADS)

Sarrazin, P.; Blake, D. F.; Dera, P.; Downs, R. T.; Taylor, J.

2017-12-01

X-ray diffraction (XRD) is a general purpose technique for definitive, quantitative mineralogical analysis. When combined with XRF data for sample chemistry, XRD analyses yield as complete a characterization as is possible by any spacecraft-capable techniques. The MSL CheMin instrument, the first XRD instrument flown in space, has been used to establish the quantitative mineralogy of the Mars global soil, to discover the first habitable environment on another planet, and to provide the first in-situ evidence of silicic volcanism on Mars. CheMin is now used to characterize the depositional and diagenetic environments associated with the mudstone sediments of lower strata of Mt. Sharp. Conventional powder XRD requires samples comprised of small grains presented in random orientations. In CheMin, sample cells are vibrated to cause loose powder to flow within the cell, driven by granular convection, which relaxes the requirement for fine grained samples. Nevertheless, CheMin still requires mechanisms to collect, crush, sieve and deliver samples before analysis. XTRA (Extraterrestrial Regolith Analyzer) is an evolution of CheMin intended to analyze fines in as-delivered surface regolith, without sample preparation. Fine-grained regolith coats the surfaces of most airless bodies in the solar system, and because this fraction is typically comminuted from the rocky regolith, it can often be used as a proxy for the surface as a whole. HXRD (Hybrid-XRD) is concept under development to analyze rocks or soils without sample preparation. Like in CheMin, the diffracted signal is collected with direct illumination CCD's. If the material is sufficiently fine-grained, a powder XRD pattern of the characteristic X-ray tube emission is obtained, similar to CheMin or XTRA. With coarse grained crystals, the white bremsstrahlung radiation of the tube is diffracted into Laue patterns. Unlike typical Laue applications, HXRD uses the CCD's capability to distinguish energy and analyze the "colors" of each Laue spot, which enable phase identification. The concept was demonstrated with prototypes and dedicated crystallographic software was developed for identification the minerals responsible for the Laue patterns. High TRL subsystems are under development for future deployment opportunities of these new XRD instruments.

Estimation of hysteretic damping of structures by stochastic subspace identification

NASA Astrophysics Data System (ADS)

Bajrić, Anela; Høgsberg, Jan

2018-05-01

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

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

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Microorganism Identification Based On MALDI-TOF-MS Fingerprints

NASA Astrophysics Data System (ADS)

Elssner, Thomas; Kostrzewa, Markus; Maier, Thomas; Kruppa, Gary

Advances in MALDI-TOF mass spectrometry have enabled the ­development of a rapid, accurate and specific method for the identification of bacteria directly from colonies picked from culture plates, which we have named the MALDI Biotyper. The picked colonies are placed on a target plate, a drop of matrix solution is added, and a pattern of protein molecular weights and intensities, "the protein fingerprint" of the bacteria, is produced by the MALDI-TOF mass spectrometer. The obtained protein mass fingerprint representing a molecular signature of the microorganism is then matched against a database containing a library of previously measured protein mass fingerprints, and scores for the match to every library entry are produced. An ID is obtained if a score is returned over a pre-set threshold. The sensitivity of the techniques is such that only approximately 104 bacterial cells are needed, meaning that an overnight culture is sufficient, and the results are obtained in minutes after culture. The improvement in time to result over biochemical methods, and the capability to perform a non-targeted identification of bacteria and spores, potentially makes this method suitable for use in the detect-to-treat timeframe in a bioterrorism event. In the case of white-powder samples, the infectious spore is present in sufficient quantity in the powder so that the MALDI Biotyper result can be obtained directly from the white powder, without the need for culture. While spores produce very different patterns from the vegetative colonies of the corresponding bacteria, this problem is overcome by simply including protein fingerprints of the spores in the library. Results on spores can be returned within minutes, making the method suitable for use in the "detect-to-protect" timeframe.

CoLIde: a bioinformatics tool for CO-expression-based small RNA Loci Identification using high-throughput sequencing data.

PubMed

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-07-01

Small RNAs (sRNAs) are 20-25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci. To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus. CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques. CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk.

Developing indicators of pattern identification in patients with stroke using traditional Korean medicine

PubMed Central

2012-01-01

Background The traditional Korean medical diagnoses employ pattern identification (PI), a diagnostic system that entails the comprehensive analysis of symptoms and signs. The PI needs to be standardized due to its ambiguity. Therefore, this study was performed to establish standard indicators of the PI for stroke through the traditional Korean medical literature, expert consensus and a clinical field test. Methods We sorted out stroke patterns with an expert committee organized by the Korean Institute of Oriental Medicine. The expert committee composed a document for a standardized pattern of identification for stroke based on the traditional Korean medical literature, and we evaluated the clinical significance of the document through a field test. Results We established five stroke patterns from the traditional Korean medical literature and extracted 117 indicators required for diagnosis. The indicators were evaluated by a field test and verified by the expert committee. Conclusions This study sought to develop indicators of PI based on the traditional Korean medical literature. This process contributed to the standardization of traditional Korean medical diagnoses. PMID:22410195

Gender variation in morphological patterns of lip prints among some north Indian populations.

PubMed

Vats, Yogesh; Dhall, Jasmine Kaur; Kapoor, Ak

2012-01-01

Personal identification is an integral part of forensic investigations. For the same, DNA profiling and fingerprints are the most commonly used tools. But these evidences are not ubiquitous and may not necessarily be obtained from the crime scene. In such a scenario, other physical and trace evidences play a pivotal role and subsequently the branches employed are forensic osteology, odontology, biometrics, etc. A relatively recent field in the branch of forensic odontology is cheiloscopy or the study of lip prints. A comparison of lip prints from the crime scene and those obtained from the suspects may be useful in the identification or narrowing down the investigation. The purpose of the present study is to determine the gender and population variability in the morphological patterns of lip prints among brahmins, Jats, and scheduled castes of Delhi and Haryana, India. Samples were collected from Jats, brahmins, and scheduled castes of Delhi and Haryana. The total sample size consisted of 1399 individuals including 781 males and 618 females in the age group of 8-60 years. Care was taken not to collect samples from genetically related individuals. The technique was standardized by recording lip prints of 20 persons and analyzing them. Lip prints were collected by using a corporate's invisible tape and analyzed using a hand lens. The patterns were studied along the entire length and breadth of both the upper and the lower lip. The data were analyzed by SPSS statistical package version 17 to determine the frequencies and percentages of occurrence of the pattern types in each population group and a comparison between males and females among the groups was carried out by using the z test. The z-test comparison between patterns of males and females shows significant differences with respect to pattern types I', II, III, and IV among brahmins; I', II, III, IV, and Y among Jats; and I, I', II, III, and V among scheduled castes. Thus, it can be concluded that the variability of the lip print pattern can help sex differentiation among groups and that more studies on the lip print pattern should be carried out to bring new dimensions to forensic anthropology and to aid the law enforcement agencies.

Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.

PubMed

Nugent, Allison C; Luber, Bruce; Carver, Frederick W; Robinson, Stephen E; Coppola, Richard; Zarate, Carlos A

2017-02-01

Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robust in both MEG and functional magnetic resonance imaging (fMRI) resting state data. Synthetic aperture magnetometry (SAM) was used to project signals into anatomical source space separately in each band before a group temporal ICA was performed over all subjects and bands. This method preserved the inherent correlation structure of the data and reflected connectivity derived from single-band ICA, but also allowed identification of spatial spectral modes that are consistent across subjects. The implications of these results on our understanding of sensorimotor function are discussed, as are the potential applications of this technique. Hum Brain Mapp 38:779-791, 2017. © 2016 Wiley Periodicals, Inc. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Biometric analysis of the palm vein distribution by means two different techniques of feature extraction

NASA Astrophysics Data System (ADS)

Castro-Ortega, R.; Toxqui-Quitl, C.; Solís-Villarreal, J.; Padilla-Vivanco, A.; Castro-Ramos, J.

2014-09-01

Vein patterns can be used for accessing, identifying, and authenticating purposes; which are more reliable than classical identification way. Furthermore, these patterns can be used for venipuncture in health fields to get on to veins of patients when they cannot be seen with the naked eye. In this paper, an image acquisition system is implemented in order to acquire digital images of people hands in the near infrared. The image acquisition system consists of a CCD camera and a light source with peak emission in the 880 nm. This radiation can penetrate and can be strongly absorbed by the desoxyhemoglobin that is presented in the blood of the veins. Our method of analysis is composed by several steps and the first one of all is the enhancement of acquired images which is implemented by spatial filters. After that, adaptive thresholding and mathematical morphology operations are used in order to obtain the distribution of vein patterns. The above process is focused on the people recognition through of images of their palm-dorsal distributions obtained from the near infrared light. This work has been directed for doing a comparison of two different techniques of feature extraction as moments and veincode. The classification task is achieved using Artificial Neural Networks. Two databases are used for the analysis of the performance of the algorithms. The first database used here is owned of the Hong Kong Polytechnic University and the second one is our own database.

System Identification for the Clipper Liberty C96 Wind Turbine

NASA Astrophysics Data System (ADS)

Showers, Daniel

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

Artificial neural network model for photosynthetic pigments identification using multi wavelength chromatographic data

NASA Astrophysics Data System (ADS)

Prilianti, K. R.; Hariyanto, S.; Natali, F. D. D.; Indriatmoko, Adhiwibawa, M. A. S.; Limantara, L.; Brotosudarmo, T. H. P.

2016-04-01

The development of rapid and automatic pigment characterization method become an important issue due to the fact that there are only less than 1% of plant pigments in the earth have been explored. In this research, a mathematical model based on artificial intelligence approach was developed to simplify and accelerate pigment characterization process from HPLC (high-performance liquid chromatography) procedure. HPLC is a widely used technique to separate and identify pigments in a mixture. Input of the model is chromatographic data from HPLC device and output of the model is a list of pigments which is the spectrum pattern is discovered in it. This model provides two dimensional (retention time and wavelength) fingerprints for pigment characterization which is proven to be more accurate than one dimensional fingerprint (fixed wavelength). Moreover, by mimicking interconnection of the neuron in the nervous systems of the human brain, the model have learning ability that could be replacing expert judgement on evaluating spectrum pattern. In the preprocessing step, principal component analysis (PCA) was used to reduce the huge dimension of the chromatographic data. The aim of this step is to simplify the model and accelerate the identification process. Six photosynthetic pigments i.e. zeaxantin, pheophytin a, α-carotene, β-carotene, lycopene and lutein could be well identified by the model with accuracy up to 85.33% and processing time less than 1 second.

TOXICITY IDENTIFICATION EVALUATION (TIE) RESULTS FOR METAL CONTAMINATED SEDIMENTS

EPA Science Inventory

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

Do Processing Patterns of Strengths and Weaknesses Predict Differential Treatment Response?

ERIC Educational Resources Information Center

Miciak, Jeremy; Williams, Jacob L.; Taylor, W. Pat; Cirino, Paul T.; Fletcher, Jack M.; Vaughn, Sharon

2016-01-01

No previous empirical study has investigated whether the learning disabilities (LD) identification decisions of proposed methods to operationalize processing strengths and weaknesses approaches for LD identification are associated with differential treatment response. We investigated whether the identification decisions of the…

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

NASA Astrophysics Data System (ADS)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

Food purchase patterns: empirical identification and analysis of their association with diet quality, socio-economic factors, and attitudes.

PubMed

Thiele, Silke; Peltner, Jonas; Richter, Almut; Mensink, Gert B M

2017-10-12

Empirically derived food purchase patterns provide information about which combinations of foods were purchased from households. The objective of this study was to identify what kinds of patterns exist, which level of diet quality they represent and which factors are associated with the patterns. The study made use of representative German consumption data in which approximately 12 million food purchases from 13,125 households are recorded. In accordance with healthy diet criteria the food purchases were assigned to 18 food groups of the German Food Pyramid. Based on these groups a factor analysis with a principal component technique was applied to identify food patterns. For these patterns nutrient and energy densities were examined. Using regression analysis, associations between pattern scores and socio-economic as well as attitude variables, reflecting personal statements about healthy eating, were analyzed. In total, three food purchase patterns could be identified: a natural, a processed and a traditional one. The first one was characterized by a higher purchasing of natural foods, the second by an increased purchasing of processed foods and the third by a meat-oriented diet. In each pattern there were specific diet quality criteria that could be improved whereas others were in line with actual dietary guidelines. In addition to socio-demographic factors, attitudes were significantly associated with the purchase patterns. The findings of this study are interesting from a public health perspective, as it can be assumed that measures focusing on specific aspects of diet quality are more promising than general ones. However, it is a major challenge to identify the population groups with their specific needs of improvement. As the patterns were associated with both socio-economic and attitude variables these grouping criteria could be used to define target groups.

Contribution to the study of the vasculature of submandibular and sublingual glands and lymph nodes of rats by corrosion cast technique combined with scanning electron microscopy.

PubMed

Rossi-Schneider, Tíssiana Rachel; Verli, Flaviana Dornela; Yurgel, Liliane Soares; De Souza, Maria Antonieta Lopes; Cherubini, Karen

2008-10-01

The study of anatomical structures in their normal state allows the identification of pathological changes that can occur in them. Angiogenesis and the vasculature have been widely studied, mainly because of their association with the development of neoplasms. One of the methods applied for such purposes is the corrosion cast technique, which provides a copy of the vessels with normal as well as pathological structures. The replica of the vasculature provided by this technique allows the three-dimensional analysis of vessels by means of scanning electron microscopy. The aim of the present study was to demonstrate, by means of corrosion casts, the angioarchitecture of the submandibular and sublingual glands and lymph nodes. Scanning electron microscopy showed that the three structures have distinct vascular patterns. The corrosion cast technique can be employed in the study of the angioarchitecture of the submandibular and sublingual glands and lymph nodes, but requires specific precautions. The removal of the structures en bloc and the handling of the replicas with the aid of a stereoscopic magnifier reduce the risk of fractures. (c) 2008 Wiley-Liss, Inc.

Development of an Intelligent Videogrammetric Wind Tunnel Measurement System

NASA Technical Reports Server (NTRS)

Graves, Sharon S.; Burner, Alpheus W.

2004-01-01

A videogrammetric technique developed at NASA Langley Research Center has been used at five NASA facilities at the Langley and Ames Research Centers for deformation measurements on a number of sting mounted and semispan models. These include high-speed research and transport models tested over a wide range of aerodynamic conditions including subsonic, transonic, and supersonic regimes. The technique, based on digital photogrammetry, has been used to measure model attitude, deformation, and sting bending. In addition, the technique has been used to study model injection rate effects and to calibrate and validate methods for predicting static aeroelastic deformations of wind tunnel models. An effort is currently underway to develop an intelligent videogrammetric measurement system that will be both useful and usable in large production wind tunnels while providing accurate data in a robust and timely manner. Designed to encode a higher degree of knowledge through computer vision, the system features advanced pattern recognition techniques to improve automated location and identification of targets placed on the wind tunnel model to be used for aerodynamic measurements such as attitude and deformation. This paper will describe the development and strategy of the new intelligent system that was used in a recent test at a large transonic wind tunnel.

High-Throughput Block Optical DNA Sequence Identification.

PubMed

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

2018-01-01

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

Validation of the (GTG)(5)-rep-PCR fingerprinting technique for rapid classification and identification of acetic acid bacteria, with a focus on isolates from Ghanaian fermented cocoa beans.

PubMed

De Vuyst, Luc; Camu, Nicholas; De Winter, Tom; Vandemeulebroecke, Katrien; Van de Perre, Vincent; Vancanneyt, Marc; De Vos, Paul; Cleenwerck, Ilse

2008-06-30

Amplification of repetitive bacterial DNA elements through the polymerase chain reaction (rep-PCR fingerprinting) using the (GTG)(5) primer, referred to as (GTG)(5)-PCR fingerprinting, was found a promising genotypic tool for rapid and reliable speciation of acetic acid bacteria (AAB). The method was evaluated with 64 AAB reference strains, including 31 type strains, and 132 isolates from Ghanaian, fermented cocoa beans, and was validated with DNA:DNA hybridization data. Most reference strains, except for example all Acetobacter indonesiensis strains and Gluconacetobacter liquefaciens LMG 1509, grouped according to their species designation, indicating the usefulness of this technique for identification to the species level. Moreover, exclusive patterns were obtained for most strains, suggesting that the technique can also be used for characterization below species level or typing of AAB strains. The (GTG)(5)-PCR fingerprinting allowed us to differentiate four major clusters among the fermented cocoa bean isolates, namely A. pasteurianus (cluster I, 100 isolates), A. syzygii- or A. lovaniensis-like (cluster II, 23 isolates), and A. tropicalis-like (clusters III and IV containing 4 and 5 isolates, respectively). A. syzygii-like and A. tropicalis-like strains from cocoa bean fermentations were reported for the first time. Validation of the method and indications for reclassifications of AAB species and existence of new Acetobacter species were obtained through 16S rRNA sequencing analyses and DNA:DNA hybridizations. Reclassifications refer to A. aceti LMG 1531, Ga. xylinus LMG 1518, and Ga. xylinus subsp. sucrofermentans LMG 18788(T).

Geological and Structural Patterns on Titan Enhanced Through Cassini's SAR PCA and High-Resolution Radiometry

NASA Astrophysics Data System (ADS)

Paganelli, F.; Schubert, G.; Lopes, R. M. C.; Malaska, M.; Le Gall, A. A.; Kirk, R. L.

2016-12-01

The current SAR data coverage on Titan encompasses several areas in which multiple radar passes are present and overlapping, providing additional information to aid the interpretation of geological and structural features. We exploit the different combinations of look direction and variable incidence angle to examine Cassini Synthetic Aperture RADAR (SAR) data using the Principal Component Analysis (PCA) technique and high-resolution radiometry, as a tool to aid in the interpretation of geological and structural features. Look direction and variable incidence angle is of particular importance in the analysis of variance in the images, which aid in the perception and identification of geological and structural features, as extensively demonstrated in Earth and planetary examples. The PCA enhancement technique uses projected non-ortho-rectified SAR imagery in order to maintain the inherent differences in scattering and geometric properties due to the different look directions, while enhancing the geometry of surface features. The PC2 component provides a stereo view of the areas in which complex surface features and structural patterns can be enhanced and outlined. We focus on several areas of interest, in older and recently acquired flybys, in which evidence of geological and structural features can be enhanced and outlined in the PC1 and PC2 components. Results of this technique provide enhanced geometry and insights into the interpretation of the observed geological and structural features, thus allowing a better understanding towards the geology and tectonics on Titan.

GESA--a two-dimensional processing system using knowledge base techniques.

PubMed

Rowlands, D G; Flook, A; Payne, P I; van Hoff, A; Niblett, T; McKee, S

1988-12-01

The successful analysis of two-dimensional (2-D) polyacrylamide electrophoresis gels demands considerable experience and understanding of the protein system under investigation as well as knowledge of the separation technique itself. The present work concerns the development of a computer system for analysing 2-D electrophoretic separations which incorporates concepts derived from artificial intelligence research such that non-experts can use the technique as a diagnostic or identification tool. Automatic analysis of 2-D gel separations has proved to be extremely difficult using statistical methods. Non-reproducibility of gel separations is also difficult to overcome using automatic systems. However, the human eye is extremely good at recognising patterns in images, and human intervention in semi-automatic computer systems can reduce the computational complexities of fully automatic systems. Moreover, the expertise and understanding of an "expert" is invaluable in reducing system complexity if it can be encapsulated satisfactorily in an expert system. The combination of user-intervention in the computer system together with the encapsulation of expert knowledge characterises the present system. The domain within which the system has been developed is that of wheat grain storage proteins (gliadins) which exhibit polymorphism to such an extent that cultivars can be uniquely identified by their gliadin patterns. The system can be adapted to other domains where a range of polymorpic protein sub-units exist. In its generalised form, the system can also be used for comparing more complex 2-D gel electrophoretic separations.

Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

PubMed

Karimi, Mohammad H; Asemani, Davud

2014-05-01

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Methods for assessing movement path recursion with application to African buffalo in South Africa

USGS Publications Warehouse

Bar-David, S.; Bar-David, I.; Cross, P.C.; Ryan, S.J.; Knechtel, C.U.; Getz, W.M.

2009-01-01

Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus coffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. ?? 2009 by the Ecological Society of America.

Mechanisms for pattern specificity of deep-brain stimulation in Parkinson’s disease

PubMed Central

Mato, Germán; Dellavale, Damián

2017-01-01

Deep brain stimulation (DBS) has become a widely used technique for treating advanced stages of neurological and psychiatric illness. In the case of motor disorders related to basal ganglia (BG) dysfunction, several mechanisms of action for the DBS therapy have been identified which might be involved simultaneously or in sequence. However, the identification of a common key mechanism underlying the clinical relevant DBS configurations has remained elusive due to the inherent complexity related to the interaction between the electrical stimulation and the neural tissue, and the intricate circuital structure of the BG-thalamocortical network. In this work, it is shown that the clinically relevant range for both, the frequency and intensity of the electrical stimulation pattern, is an emergent property of the BG anatomy at the system-level that can be addressed using mean-field descriptive models of the BG network. Moreover, it is shown that the activity resetting mechanism elicited by electrical stimulation provides a natural explanation to the ineffectiveness of irregular (i.e., aperiodic) stimulation patterns, which has been commonly observed in previously reported pathophysiology models of Parkinson’s disease. Using analytical and numerical techniques, these results have been reproduced in both cases: 1) a reduced mean-field model that can be thought as an elementary building block capable to capture the underlying fundamentals of the relevant loops constituting the BG-thalamocortical network, and 2) a detailed model constituted by the direct and hyperdirect loops including one-dimensional spatial structure of the BG nuclei. We found that the optimal ranges for the essential parameters of the stimulation patterns can be understood without taking into account biophysical details of the relevant structures. PMID:28813460

Symbolic dynamics for arrhythmia identification from heart variability of rats with cardiac failures

NASA Astrophysics Data System (ADS)

Letellier, C.; Roulin, E.; Loriot, S.; Morin, J.-P.; Dionnet, F.

2004-12-01

Heart rate variability of rats is investigated using concepts from the nonlinear dynamical system theory. Among the important techniques offered, symbolic dynamics is very appealing by its power to investigate patterns which can be repeated in a time series. The present analysis was performed in six control rats and six chronic cardiac insufficient rats (myocardial infarction due to left descendent coronary artery ligation). Rats are left in clean atmosphere or exposed to atmosphere containing diluted engine emission pollutants. The evolution of the heart rate variability is then investigated with a three element symbolic dynamics which allows to distinguish extrasystoles from tachycardia or bradycardia using the symbol sequences.

Assembling evidence for identifying reservoirs of infection

PubMed Central

Viana, Mafalda; Mancy, Rebecca; Biek, Roman; Cleaveland, Sarah; Cross, Paul C.; Lloyd-Smith, James O.; Haydon, Daniel T.

2014-01-01

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems. PMID:24726345

Assembling evidence for identifying reservoirs of infection

USGS Publications Warehouse

Mafalda, Viana; Rebecca, Mancy; Roman, Biek; Sarah, Cleaveland; Cross, Paul C.; James O, Lloyd-Smith; Daniel T, Haydon

2014-01-01

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems.

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

Greenberg, S.D.; Smith, S.; Swank, P.R.

Visual cell profiles were used to analyze the distribution of atypical bronchial cells in sputum specimens from cigarette-smoking volunteers, cigarette-smoking asbestos workers and cigarette-smoking uranium miners. The preliminary results of these sputum visual cell profile studies have demonstrated distinctive distributions of bronchial cell atypias in progressive patterns of squamous metaplasia, mild, moderate and severe atypias and carcinoma, similar to those the authors have previously reported using cell image analysis techniques to determine an atypia status index (ASI). The information gained from this study will be helpful in further validating this ASI and subsequently achieving the ultimate goal of employing cellmore » image analysis for the rapid and precise identification of premalignant atypias in sputum.« less

A Vision-Based System for Object Identification and Information Retrieval in a Smart Home

NASA Astrophysics Data System (ADS)

Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo

This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.

A new way to protect privacy in large-scale genome-wide association studies.

PubMed

Kamm, Liina; Bogdanov, Dan; Laur, Sven; Vilo, Jaak

2013-04-01

Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. Supplementary data are available at Bioinformatics online.

A novel method to characterize silica bodies in grasses.

PubMed

Dabney, Clemon; Ostergaard, Jason; Watkins, Eric; Chen, Changbin

2016-01-01

The deposition of silicon into epidermal cells of grass species is thought to be an important mechanism that plants use as a defense against pests and environmental stresses. There are a number of techniques available to study the size, density and distribution pattern of silica bodies in grass leaves. However, none of those techniques can provide a high-throughput analysis, especially for a great number of samples. We developed a method utilizing the autofluorescence of silica bodies to investigate their size and distribution, along with the number of carbon inclusions within the silica bodies of perennial grass species Koeleria macrantha. Fluorescence images were analyzed by image software Adobe Photoshop CS5 or ImageJ that remarkably facilitated the quantification of silica bodies in the dry ash. We observed three types of silica bodies or silica body related mineral structures. Silica bodies were detected on both abaxial and adaxial epidermis of K. macrantha leaves, although their sizes, density, and distribution patterns were different. No auto-fluorescence was detected from carbon inclusions. The combination of fluorescence microscopy and image processing software displayed efficient utilization in the identification and quantification of silica bodies in K. macrantha leaf tissues, which should applicable to biological, ecological and geological studies of grasses including forage, turf grasses and cereal crops.

Clustering Algorithms: Their Application to Gene Expression Data

PubMed Central

Oyelade, Jelili; Isewon, Itunuoluwa; Oladipupo, Funke; Aromolaran, Olufemi; Uwoghiren, Efosa; Ameh, Faridah; Achas, Moses; Adebiyi, Ezekiel

2016-01-01

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure. PMID:27932867

Pattern recognition in volcano seismology - Reducing spectral dimensionality

NASA Astrophysics Data System (ADS)

Unglert, K.; Radic, V.; Jellinek, M.

2015-12-01

Variations in the spectral content of volcano seismicity can relate to changes in volcanic activity. Low-frequency seismic signals often precede or accompany volcanic eruptions. However, they are commonly manually identified in spectra or spectrograms, and their definition in spectral space differs from one volcanic setting to the next. Increasingly long time series of monitoring data at volcano observatories require automated tools to facilitate rapid processing and aid with pattern identification related to impending eruptions. Furthermore, knowledge transfer between volcanic settings is difficult if the methods to identify and analyze the characteristics of seismic signals differ. To address these challenges we evaluate whether a machine learning technique called Self-Organizing Maps (SOMs) can be used to characterize the dominant spectral components of volcano seismicity without the need for any a priori knowledge of different signal classes. This could reduce the dimensions of the spectral space typically analyzed by orders of magnitude, and enable rapid processing and visualization. Preliminary results suggest that the temporal evolution of volcano seismicity at Kilauea Volcano, Hawai`i, can be reduced to as few as 2 spectral components by using a combination of SOMs and cluster analysis. We will further refine our methodology with several datasets from Hawai`i and Alaska, among others, and compare it to other techniques.

[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.

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).

PubMed

Sudarshan, Vidya K; Acharya, U Rajendra; Ng, E Y K; Tan, Ru San; Chou, Siaw Meng; Ghista, Dhanjoo N

2016-04-01

Early expansion of infarcted zone after Acute Myocardial Infarction (AMI) has serious short and long-term consequences and contributes to increased mortality. Thus, identification of moderate and severe phases of AMI before leading to other catastrophic post-MI medical condition is most important for aggressive treatment and management. Advanced image processing techniques together with robust classifier using two-dimensional (2D) echocardiograms may aid for automated classification of the extent of infarcted myocardium. Therefore, this paper proposes novel algorithms namely Curvelet Transform (CT) and Local Configuration Pattern (LCP) for an automated detection of normal, moderately infarcted and severely infarcted myocardium using 2D echocardiograms. The methodology extracts the LCP features from CT coefficients of echocardiograms. The obtained features are subjected to Marginal Fisher Analysis (MFA) dimensionality reduction technique followed by fuzzy entropy based ranking method. Different classifiers are used to differentiate ranked features into three classes normal, moderate and severely infarcted based on the extent of damage to myocardium. The developed algorithm has achieved an accuracy of 98.99%, sensitivity of 98.48% and specificity of 100% for Support Vector Machine (SVM) classifier using only six features. Furthermore, we have developed an integrated index called Myocardial Infarction Risk Index (MIRI) to detect the normal, moderately and severely infarcted myocardium using a single number. The proposed system may aid the clinicians in faster identification and quantification of the extent of infarcted myocardium using 2D echocardiogram. This system may also aid in identifying the person at risk of developing heart failure based on the extent of infarcted myocardium. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of lithofacies using Kohonen self-organizing maps

USGS Publications Warehouse

Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.

2002-01-01

Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

Identification of substances migrating from plastic baby bottles using a combination of low-resolution and high-resolution mass spectrometric analysers coupled to gas and liquid chromatography.

PubMed

Onghena, Matthias; Van Hoeck, Els; Van Loco, Joris; Ibáñez, María; Cherta, Laura; Portolés, Tania; Pitarch, Elena; Hernandéz, Félix; Lemière, Filip; Covaci, Adrian

2015-11-01

This work presents a strategy for elucidation of unknown migrants from plastic food contact materials (baby bottles) using a combination of analytical techniques in an untargeted approach. First, gas chromatography (GC) coupled to mass spectrometry (MS) in electron ionisation mode was used to identify migrants through spectral library matching. When no acceptable match was obtained, a second analysis by GC-(electron ionisation) high resolution mass spectrometry time of flight (TOF) was applied to obtain accurate mass fragmentation spectra and isotopic patterns. Databases were then searched to find a possible elemental composition for the unknown compounds. Finally, a GC hybrid quadrupole-TOF-MS with an atmospheric pressure chemical ionisation source was used to obtain the molecular ion or the protonated molecule. Accurate mass data also provided additional information on the fragmentation behaviour as two acquisition functions with different collision energies were available (MS(E) approach). In the low-energy function, limited fragmentation took place, whereas for the high-energy function, fragmentation was enhanced. For less volatile unknowns, ultra-high pressure liquid chromatography-quadrupole-TOF-MS was additionally applied. Using a home-made database containing common migrating compounds and plastic additives, tentative identification was made for several positive findings based on accurate mass of the (de)protonated molecule, product ion fragments and characteristic isotopic ions. Six illustrative examples are shown to demonstrate the modus operandi and the difficulties encountered during identification. The combination of these techniques was proven to be a powerful tool for the elucidation of unknown migrating compounds from plastic baby bottles. Copyright © 2015 John Wiley & Sons, Ltd.

Learning Disabilities and Young Children: Identification and Intervention

ERIC Educational Resources Information Center

Learning Disability Quarterly, 2007

2007-01-01

This paper addresses early identification, services, supports, and intervention for young children, birth through 4 years, who demonstrate delays in development that may place them at risk for later identification as having a learning disability (LD). Such delays include atypical patterns of development in cognition, communication, emergent…

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

NASA Technical Reports Server (NTRS)

Mehra, Raman K.

1991-01-01

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

Benefits of using culturally unfamiliar stimuli in ambiguous emotion identification: A cross-cultural study.

PubMed

Koelkebeck, Katja; Kohl, Waldemar; Luettgenau, Julia; Triantafillou, Susanna; Ohrmann, Patricia; Satoh, Shinji; Minoshita, Seiko

2015-07-30

A novel emotion recognition task that employs photos of a Japanese mask representing a highly ambiguous stimulus was evaluated. As non-Asians perceive and/or label emotions differently from Asians, we aimed to identify patterns of task-performance in non-Asian healthy volunteers with a view to future patient studies. The Noh mask test was presented to 42 adult German participants. Reaction times and emotion attribution patterns were recorded. To control for emotion identification abilities, a standard emotion recognition task was used among others. Questionnaires assessed personality traits. Finally, results were compared to age- and gender-matched Japanese volunteers. Compared to other tasks, German participants displayed slowest reaction times on the Noh mask test, indicating higher demands of ambiguous emotion recognition. They assigned more positive emotions to the mask than Japanese volunteers, demonstrating culture-dependent emotion identification patterns. As alexithymic and anxious traits were associated with slower reaction times, personality dimensions impacted on performance, as well. We showed an advantage of ambiguous over conventional emotion recognition tasks. Moreover, we determined emotion identification patterns in Western individuals impacted by personality dimensions, suggesting performance differences in clinical samples. Due to its properties, the Noh mask test represents a promising tool in the differential diagnosis of psychiatric disorders, e.g. schizophrenia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Identification and deconvolution of carbohydrates with gas chromatography-vacuum ultraviolet spectroscopy.

PubMed

Schenk, Jamie; Nagy, Gabe; Pohl, Nicola L B; Leghissa, Allegra; Smuts, Jonathan; Schug, Kevin A

2017-09-01

Methodology for qualitative and quantitative determination of carbohydrates with gas chromatography coupled to vacuum ultraviolet detection (GC-VUV) is presented. Saccharides have been intently studied and are commonly analyzed by gas chromatography-mass spectrometry (GC-MS), but not always effectively. This can be attributed to their high degree of structural complexity: α/β anomers from their axial/equatorial hydroxyl group positioning at the C1-OH and flexible ring structures that lead to the open chain, five-membered ring furanose, and six-membered ring pyranose configurations. This complexity can result in convoluted chromatograms, ambiguous fragmentation patterns and, ultimately, analyte misidentification. In this study, mono-, di, and tri-saccharides were derivatized by two different methods-permethylation and oximation/pertrimethylsilylation-and analyzed by GC-VUV. These two derivatization methods were then compared for their efficiency, ease of use, and robustness. Permethylation proved to be a useful technique for the analysis of ketopentoses and pharmaceuticals soluble in dimethyl sulfoxide (DMSO), while the oximation/pertrimethylsilylation method prevailed as the more promising, overall, derivatization method. VUV spectra have been shown to be distinct and allow for efficient differentiation of isomeric species such as ketopentoses and reducing versus non-reducing sugars. In addition to identification, pharmaceutical samples containing several compounds were derivatized and analyzed for their sugar content with the GC-VUV technique to provide data for qualitative analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of water-deficit responsive genes in maritime pine (Pinus pinaster Ait.) roots.

PubMed

Dubos, Christian; Plomion, Christophe

2003-01-01

Root adaptation to soil environmental factors is very important to maritime pine, the main conifer species used for reforestation in France. The range of climates in the sites where this species is established varies from flooded in winter to drought-prone in summer. No studies have yet focused on the morphological, physiological or molecular variability of the root system to adapt its growth to such an environment. We developed a strategy to isolate drought-responsive genes in the root tissue in order to identify the molecular mechanisms that trees have evolved to cope with drought (the main problem affecting wood productivity), and to exploit this information to improve drought stress tolerance. In order to provide easy access to the root system, seedlings were raised in hydroponic solution. Polyethylene glycol was used as an osmoticum to induce water deficit. Using the cDNA-AFLP technique, we screened more than 2500 transcript derived fragments, of which 33 (1.2%) showed clear variation in presence/absence between non stressed and stressed medium. The relative abundance of these transcripts was then analysed by reverse northern. Only two out of these 33 genes showed significant opposite behaviour between both techniques. The identification and characterization of water-deficit responsive genes in roots provide the emergence of physiological understanding of the patterns of gene expression and regulation involved in the drought stress response of maritime pine.

Effects of inter-stimulus interval and intensity on the perceived urgency of tactile patterns.

PubMed

White, Timothy L; Krausman, Andrea S

2015-05-01

This research examines the feasibility of coding urgency into tactile patterns. Four tactile patterns were presented at either, 12 or 23.5 dB above mean threshold, with an ISI of either 0 (no interval) or 500 msec. Measures included pattern identification and urgency rating on a scale of 1 (least urgent) to 10 (most urgent). Two studies were conducted, a laboratory study and a field study. In the laboratory study, participants received the tactile patterns while seated in front of a computer. For the field study, participants performed dismounted Soldier maneuvers while receiving the tactile patterns. Higher identification rates were found for the 23.5 dB intensity. Patterns presented at the 23.5 dB intensity and no ISI were rated most urgent. No differences in urgency ratings were found for 12 dB based on ISI. Findings support the notion of coding urgency into tactile patterns as a way of augmenting tactile communication. Published by Elsevier Ltd.

Identification of Isthmin 1 as a Novel Clefting and Craniofacial Patterning Gene in Humans.

PubMed

Lansdon, Lisa A; Darbro, Benjamin W; Petrin, Aline L; Hulstrand, Alissa M; Standley, Jennifer M; Brouillette, Rachel B; Long, Abby; Mansilla, M Adela; Cornell, Robert A; Murray, Jeffrey C; Houston, Douglas W; Manak, J Robert

2018-01-01

Orofacial clefts are one of the most common birth defects, affecting 1-2 per 1000 births, and have a complex etiology. High-resolution array-based comparative genomic hybridization has increased the ability to detect copy number variants (CNVs) that can be causative for complex diseases such as cleft lip and/or palate. Utilizing this technique on 97 nonsyndromic cleft lip and palate cases and 43 cases with cleft palate only, we identified a heterozygous deletion of Isthmin 1 in one affected case, as well as a deletion in a second case that removes putative 3' regulatory information. Isthmin 1 is a strong candidate for clefting, as it is expressed in orofacial structures derived from the first branchial arch and is also in the same "synexpression group" as fibroblast growth factor 8 and sprouty RTK signaling antagonist 1a and 2 , all of which have been associated with clefting. CNVs affecting Isthmin 1 are exceedingly rare in control populations, and Isthmin 1 scores as a likely haploinsufficiency locus. Confirming its role in craniofacial development, knockdown or clustered randomly interspaced short palindromic repeats/Cas9-generated mutation of isthmin 1 in Xenopus laevis resulted in mild to severe craniofacial dysmorphologies, with several individuals presenting with median clefts. Moreover, knockdown of isthmin 1 produced decreased expression of LIM homeobox 8 , itself a gene associated with clefting, in regions of the face that pattern the maxilla. Our study demonstrates a successful pipeline from CNV identification of a candidate gene to functional validation in a vertebrate model system, and reveals Isthmin 1 as both a new human clefting locus as well as a key craniofacial patterning gene. Copyright © 2018 by the Genetics Society of America.

An integrated approach to the Taxonomic identification of prehistoric shell ornaments

USGS Publications Warehouse

Demarchi, Beatrice; O'Connor, Sonia; Ponzoni, Andre de Lima; Ponzoni, Raquel de Almeida Roch; Sheridan, Alison; Penkman, Kirsty; Hancock, Y.; Wilson, Julie

2014-01-01

Shell beads appear to have been one of the earliest examples of personal adornments. Marine shells identified far from the shore evidence long-distance transport and imply networks of exchange and negotiation. However, worked beads lose taxonomic clues to identification, and this may be compounded by taphonomic alteration. Consequently, the significance of this key early artefact may be underestimated. We report the use of bulk amino acid composition of the stable intra-crystalline proteins preserved in shell biominerals and the application of pattern recognition methods to a large dataset (777 samples) to demonstrate that taxonomic identification can be achieved at genus level. Amino acid analyses are fast (<2 hours per sample) and micro-destructive (sample size <2 mg). Their integration with non-destructive techniques provides a valuable and affordable tool, which can be used by archaeologists and museum curators to gain insight into early exploitation of natural resources by humans. Here we combine amino acid analyses, macro- and microstructural observations (by light microscopy and scanning electron microscopy) and Raman spectroscopy to try to identify the raw material used for beads discovered at the Early Bronze Age site of Great Cornard (UK). Our results show that at least two shell taxa were used and we hypothesise that these were sourced locally.

Pyrosequencing for Microbial Identification and Characterization

PubMed Central

Cummings, Patrick J.; Ahmed, Ray; Durocher, Jeffrey A.; Jessen, Adam; Vardi, Tamar; Obom, Kristina M.

2013-01-01

Pyrosequencing is a versatile technique that facilitates microbial genome sequencing that can be used to identify bacterial species, discriminate bacterial strains and detect genetic mutations that confer resistance to anti-microbial agents. The advantages of pyrosequencing for microbiology applications include rapid and reliable high-throughput screening and accurate identification of microbes and microbial genome mutations. Pyrosequencing involves sequencing of DNA by synthesizing the complementary strand a single base at a time, while determining the specific nucleotide being incorporated during the synthesis reaction. The reaction occurs on immobilized single stranded template DNA where the four deoxyribonucleotides (dNTP) are added sequentially and the unincorporated dNTPs are enzymatically degraded before addition of the next dNTP to the synthesis reaction. Detection of the specific base incorporated into the template is monitored by generation of chemiluminescent signals. The order of dNTPs that produce the chemiluminescent signals determines the DNA sequence of the template. The real-time sequencing capability of pyrosequencing technology enables rapid microbial identification in a single assay. In addition, the pyrosequencing instrument, can analyze the full genetic diversity of anti-microbial drug resistance, including typing of SNPs, point mutations, insertions, and deletions, as well as quantification of multiple gene copies that may occur in some anti-microbial resistance patterns. PMID:23995536

Pose invariant face recognition: 3D model from single photo

NASA Astrophysics Data System (ADS)

Napoléon, Thibault; Alfalou, Ayman

2017-02-01

Face recognition is widely studied in the literature for its possibilities in surveillance and security. In this paper, we report a novel algorithm for the identification task. This technique is based on an optimized 3D modeling allowing to reconstruct faces in different poses from a limited number of references (i.e. one image by class/person). Particularly, we propose to use an active shape model to detect a set of keypoints on the face necessary to deform our synthetic model with our optimized finite element method. Indeed, in order to improve our deformation, we propose a regularization by distances on graph. To perform the identification we use the VanderLugt correlator well know to effectively address this task. On the other hand we add a difference of Gaussian filtering step to highlight the edges and a description step based on the local binary patterns. The experiments are performed on the PHPID database enhanced with our 3D reconstructed faces of each person with an azimuth and an elevation ranging from -30° to +30°. The obtained results prove the robustness of our new method with 88.76% of good identification when the classic 2D approach (based on the VLC) obtains just 44.97%.

Pyrosequencing for microbial identification and characterization.

PubMed

Cummings, Patrick J; Ahmed, Ray; Durocher, Jeffrey A; Jessen, Adam; Vardi, Tamar; Obom, Kristina M

2013-08-22

Pyrosequencing is a versatile technique that facilitates microbial genome sequencing that can be used to identify bacterial species, discriminate bacterial strains and detect genetic mutations that confer resistance to anti-microbial agents. The advantages of pyrosequencing for microbiology applications include rapid and reliable high-throughput screening and accurate identification of microbes and microbial genome mutations. Pyrosequencing involves sequencing of DNA by synthesizing the complementary strand a single base at a time, while determining the specific nucleotide being incorporated during the synthesis reaction. The reaction occurs on immobilized single stranded template DNA where the four deoxyribonucleotides (dNTP) are added sequentially and the unincorporated dNTPs are enzymatically degraded before addition of the next dNTP to the synthesis reaction. Detection of the specific base incorporated into the template is monitored by generation of chemiluminescent signals. The order of dNTPs that produce the chemiluminescent signals determines the DNA sequence of the template. The real-time sequencing capability of pyrosequencing technology enables rapid microbial identification in a single assay. In addition, the pyrosequencing instrument, can analyze the full genetic diversity of anti-microbial drug resistance, including typing of SNPs, point mutations, insertions, and deletions, as well as quantification of multiple gene copies that may occur in some anti-microbial resistance patterns.

Homing behaviour and individual identification of the pipefish Nerophis lumbriciformis (Pisces; Syngnathidae): a true intertidal resident?

NASA Astrophysics Data System (ADS)

Monteiro, Nuno Miguel; Vieira, Maria da Natividade; Almada, Vitor

2005-04-01

Syngnathids have been the focus of growing interest due to their peculiar reproductive biology and vulnerability to environmental degradation and overcollecting. In this study, near the south limit of the species' geographic distribution, a description of the homing behaviour of the worm pipefish, Nerophis lumbriciformis, based on the unique facial pigmentation patterns, is presented. Even though the amount of facial pigmentation was substantially higher in larger adult females, suggesting that it can be part of the secondary sexual repertoire of this sex role reversed species, this technique allowed for the positive identification of adult individuals (males and females) during at least 19 months. Recaptures showed that this pipefish shows a strong homing behaviour, with individuals being regularly captured within less than 2 m of the original identification event. The absence of horizontal migrations to adjacent areas and the observation of adults in the subtidal, together with the overall low number of recaptures (even though some individuals were cyclically resighted) highlighted the fact that the intertidal is not N. lumbriciformis' permanent residence. This observation also demonstrates that the estimation of the population size, important for conservation purposes, based solely on intertidal data can be misleading because captured individuals are only a fraction of a larger, mainly subtidal, population.

High-accuracy user identification using EEG biometrics.

PubMed

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

2016-08-01

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

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…

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.

Thermal Skin fabrication technology

NASA Technical Reports Server (NTRS)

Milam, T. B.

1972-01-01

Advanced fabrication techniques applicable to Thermal Skin structures were investigated, including: (1) chemical machining; (2) braze bonding; (3) diffusion bonding; and (4) electron beam welding. Materials investigated were nickel and nickel alloys. Sample Thermal Skin panels were manufactured using the advanced fabrication techniques studied and were structurally tested. Results of the program included: (1) development of improved chemical machining processes for nickel and several nickel alloys; (2) identification of design geometry limits; (3) identification of diffusion bonding requirements; (4) development of a unique diffusion bonding tool; (5) identification of electron beam welding limits; and (6) identification of structural properties of Thermal Skin material.

Patterns across multiple memories are identified over time.

PubMed

Richards, Blake A; Xia, Frances; Santoro, Adam; Husse, Jana; Woodin, Melanie A; Josselyn, Sheena A; Frankland, Paul W

2014-07-01

Memories are not static but continue to be processed after encoding. This is thought to allow the integration of related episodes via the identification of patterns. Although this idea lies at the heart of contemporary theories of systems consolidation, it has yet to be demonstrated experimentally. Using a modified water-maze paradigm in which platforms are drawn stochastically from a spatial distribution, we found that mice were better at matching platform distributions 30 d compared to 1 d after training. Post-training time-dependent improvements in pattern matching were associated with increased sensitivity to new platforms that conflicted with the pattern. Increased sensitivity to pattern conflict was reduced by pharmacogenetic inhibition of the medial prefrontal cortex (mPFC). These results indicate that pattern identification occurs over time, which can lead to conflicts between new information and existing knowledge that must be resolved, in part, by computations carried out in the mPFC.

DNA barcodes reveal microevolutionary signals in fire response trait in two legume genera

PubMed Central

Bello, Abubakar; Daru, Barnabas H.; Stirton, Charles H.; Chimphango, Samson B. M.; van der Bank, Michelle; Maurin, Olivier; Muasya, A. Muthama

2015-01-01

Large-scale DNA barcoding provides a new technique for species identification and evaluation of relationships across various levels (populations and species) and may reveal fundamental processes in recently diverged species. Here, we analysed DNA sequence variation in the recently diverged legumes from the Psoraleeae (Fabaceae) occurring in the Cape Floristic Region (CFR) of southern Africa to test the utility of DNA barcodes in species identification and discrimination. We further explored the phylogenetic signal on fire response trait (reseeding and resprouting) at species and generic levels. We showed that Psoraleoid legumes of the CFR exhibit a barcoding gap yielding the combination of matK and rbcLa (matK + rbcLa) data set as a better barcode than single regions. We found a high score (100 %) of correct identification of individuals to their respective genera but a very low score (<50 %) in identifying them to species. We found a considerable match (54 %) between genetic species and morphologically delimited species. We also found that different lineages showed a weak but significant phylogenetic conservatism in their response to fire as reseeders or resprouters, with more clustering of resprouters than would be expected by chance. These novel microevolutionary patterns might be acting continuously over time to produce multi-scale regularities of biodiversity. This study provides the first insight into the DNA barcoding campaign of land plants in species identification and detection of the phylogenetic signal in recently diverged lineages of the CFR. PMID:26507570

Differentiation of Colletotrichum species responsible for anthracnose of strawberry by arbitrarily primed PCR

USGS Publications Warehouse

Freeman, S.; Rodriguez, R.J.

1995-01-01

A collection of 39 isolates of Colletotrichum acutatum, C. fragariae and C. gloeosporioides, which cause anthracnose on strawberry, was grouped into species based on the arbitrarily primed polymerase chain reaction (ap-PCR). All isolates used had previously been identified according to classical taxonomic morphology. Ap-PCR amplification of genomic DNA using four different primers allowed for reliable differentiation between isolates of C. acutatum, C. fragariae and two genotypes of C. gloeosporioides. Fifteen of the 18 C. acutatum isolates were very similar, although three isolates which produced a red pigment had distinctly different banding patterns. Nearly identical banding patterns were observed for all nine isolates of C. fragariae. The 12 C. gloeosporioides isolates were more diverse and two separate genotypes, Cgl-1 (six isolates) and Cgl-2 (five isolates) were distinguished by ap-PCR. An additional isolate did not conform to either the Cgl-1 or Cgl-2 genotypes. The utility of ap-PCR compared with other molecular techniques for reliable identification of Colletotrichum isolates pathogenic on strawberry is discussed.

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades

PubMed Central

Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean

2017-01-01

The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency−frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency−MARSE, and average frequency−peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes. PMID:29104245

A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades.

PubMed

Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean

2017-11-01

The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency-frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency-MARSE, and average frequency-peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes.

Rapid determination of floral aroma compounds of lilac blossom by fast gas chromatography combined with surface acoustic wave sensor.

PubMed

Oh, Se Yeon; Shin, Hyun Du; Kim, Sung Jean; Hong, Jongki

2008-03-07

A novel analytical method using fast gas chromatography combined with surface acoustic wave sensor (GC/SAW) has been developed for the detection of volatile aroma compounds emanated from lilac blossom (Syringa species: Syringa vulgaris variginata and Syringa dilatata). GC/SAW could detect and quantify various fragrance emitted from lilac blossom, enabling to provide fragrance pattern analysis results. The fragrance pattern analysis could easily characterize the delicate differences in aromas caused by the substantial difference of chemical composition according to different color and shape of petals. Moreover, the method validation of GC/SAW was performed for the purpose of volatile floral actual aroma analysis, achieving a high reproducibility and excellent sensitivity. From the validation results, GC/SAW could serve as an alternative analytical technique for the analysis of volatile floral actual aroma of lilac. In addition, headspace solid-phase microextraction (HS-SPME) GC-MS was employed to further confirm the identification of fragrances emitted from lilac blossom and compared to GC/SAW.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

Techniques for air pollution source identification are reviewed, and some results obtained with them are evaluated. Described techniques include remote sensing from satellites and aircraft, on-site monitoring, and the use of injected tracers and pollutants themselves as tracers. The use of a large number of trace elements in ambient airborne particulate matter as a practical means of identifying sources is discussed in detail. Sampling and analysis techniques are described, and it is shown that elemental constituents can be related to specific source types such as those found in the earth's crust and those associated with specific industries. Source identification sytems are noted which utilize charged particle X-ray fluorescence analysis of original field data.

Disparities in drinking patterns and risks among ethnic majority and minority groups in China: The roles of acculturation, religion, family and friends.

PubMed

He, Jianhui; Assanangkornchai, Sawitri; Cai, Le; McNeil, Edward

2016-02-01

Studies investigating alcohol consumption related factors have rarely focused on the relationship between acculturation, religion and drinking patterns. The objective of this study is to explore the predictors of drinking patterns and their mutual relationships, especially acculturation, ethnicity and religion. A cross-sectional household survey using a multistage systematic sampling technique was conducted in Yunnan Province of China. A revised Vancouver Index of Acculturation (VIA) and Alcohol Use Disorder Identification Test (AUDIT) Chinese version were used to measure acculturation and drinking patterns. Structural equation modeling (SEM) was used to explore the structures of how predictors affect drinking patterns. A total of 977 subjects aged 12-35 years were surveyed. A higher percentage of binge drinking was found among Lisu people. However, the proportion of drinking until intoxication was highest among Han. Gender and enculturation had both direct (standardized β=-0.193, -0.079) and indirect effects (standardized β=-0.126, 0.033) on risky drinking pattern; perceived risk of alcohol consumption (-0.065), family drinking environment (0.061), and friend drinking environment (0.352) affected risky drinking pattern directly, while education level (0.066), ethnicity (-0.038), acculturation (0.012), religious belief (-0.038), and age group (0.088) had indirect effects. Risky drinking pattern was associated with gender and aboriginal culture enculturation both directly and indirectly, and related to mainstream culture acculturation and religious belief indirectly. Other demographic (such as education level) and social family factors (friend drinking environment for example) also had effects on risky drinking pattern. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Digital direct electron imaging of energy-filtered electron backscatter diffraction patterns

NASA Astrophysics Data System (ADS)

Vespucci, S.; Winkelmann, A.; Naresh-Kumar, G.; Mingard, K. P.; Maneuski, D.; Edwards, P. R.; Day, A. P.; O'Shea, V.; Trager-Cowan, C.

2015-11-01

Electron backscatter diffraction is a scanning electron microscopy technique used to obtain crystallographic information on materials. It allows the nondestructive mapping of crystal structure, texture, and strain with a lateral and depth resolution on the order of tens of nanometers. Electron backscatter diffraction patterns (EBSPs) are presently acquired using a detector comprising a scintillator coupled to a digital camera, and the crystallographic information obtainable is limited by the conversion of electrons to photons and then back to electrons again. In this article we will report the direct acquisition of energy-filtered EBSPs using a digital complementary metal-oxide-semiconductor hybrid pixel detector, Timepix. We show results from a range of samples with different mass and density, namely diamond, silicon, and GaN. Direct electron detection allows the acquisition of EBSPs at lower (≤5 keV) electron beam energies. This results in a reduction in the depth and lateral extension of the volume of the specimen contributing to the pattern and will lead to a significant improvement in lateral and depth resolution. Direct electron detection together with energy filtering (electrons having energy below a specific value are excluded) also leads to an improvement in spatial resolution but in addition provides an unprecedented increase in the detail in the acquired EBSPs. An increase in contrast and higher-order diffraction features are observed. In addition, excess-deficiency effects appear to be suppressed on energy filtering. This allows the fundamental physics of pattern formation to be interrogated and will enable a step change in the use of electron backscatter diffraction (EBSD) for crystal phase identification and the mapping of strain. The enhancement in the contrast in high-pass energy-filtered EBSD patterns is found to be stronger for lighter, less dense materials. The improved contrast for such materials will enable the application of the EBSD technique to be expanded to materials for which conventional EBSD analysis is not presently practicable.

[Contribution of Leishmania identification using polymerase chain reaction--restriction fragment length polymerase for epidemiological studies of cutaneous leishmaniasis in Tunisia].

PubMed

Bousslimi, N; Ben Abda, I; Ben Mously, R; Siala, E; Harrat, Z; Zallagua, N; Bouratbine, A; Aoun, K

2014-02-01

Three forms of cutaneous leishmaniasis (CL) are endemic in Tunisia. The identification of the causative species is useful to complete epidemiological data and to manage the cases. The aim of this study is to assess PCR-RFLP technique in the identification of Leishmania species responsible of CL in Tunisia and to compare the results of this technique to those of isoenzyme analysis. Sixty-one CL lesions were sampled. Dermal samples were tested by culture on NNN medium and analyzed by PCR-RFLP assay targeting the ITS1 region of ribosomal DNA. Species identification was performed by both iso-enzymatic typing for positive cultures and analysis of restriction profiles after enzymatic digestion by HaeIII of the obtained amplicons. Thirty-eight (62%) samples were positive by culture. The iso-enzymatic typing of 32 isolates identified 3 L. infantum, 23 L. major MON-25 and 6 L. tropica MON-8. Sixty samples were positive by PCR. The PCR-RFLP digestion profiles of the 56 PCR products identified 12 L. infantum, 38 L. major and 6 L. tropica. The results of both techniques were concordant in the 32 strains identified by both techniques. Species identification correlated with the geographical distribution of CL forms endemic in Tunisia. Results of PCR-RFLP revealed highly concordant with those of isoenzyme electrophoresis. Thanks to its simplicity, rapidity and ability to be performed directly on biological samples, this technique appears as an interesting alternative for the identification of Leishmania strains responsible of CL in Tunisia. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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.

Image processing techniques revealing the relationship between the field-measured ambient gamma dose equivalent rate and geological conditions at a granitic area, Velence Mountains, Hungary

NASA Astrophysics Data System (ADS)

Beltran Torres, Silvana; Petrik, Attila; Zsuzsanna Szabó, Katalin; Jordan, Gyozo; Szabó, Csaba

2017-04-01

In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, dykes, faults, soil conditions, etc.). A detailed spatial analysis of ambient gamma dose equivalent rate was performed in the western side of Velence Mountains, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of ambient gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 14.7 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference showed that different gamma dose rate levels are associated with the rock types (i.e., Carboniferous granite, Pleistocene colluvial, proluvial, deluvial sediments and talus, and Pannonian sand and pebble), with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing revealed that linear gamma dose rate spatial features are parallel to the SW-NE dyke system and possibly to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

A novel analytical technique suitable for the identification of plastics.

PubMed

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

2013-01-01

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

Usefullness of palatal rugae patterns in establishing identity: Preliminary results from Bengaluru city, India.

PubMed

Indira, Ap; Gupta, Manish; David, Maria Priscilla

2012-01-01

Palatal rugoscopy is the name given to the study of palatal rugae. Rugae pattern are widely considered to remain unchanged during an individual's lifetime. The rugae pattern has the potential to remain intact by virtue of their internal position in the head when most other anatomical structures are destroyed or burned. Moreover, rugae pattern are considered to be unique similar to fingerprints and are advocated in personal identification. The purpose of the study is to establish, individual identity using palatal rugae patterns. The study group consisted of 100 study models all of whom were subjects above 14 years old. Martin dos Santos' classification was followed based on form and position to assess the individuality of rugae pattern. Each individual had different rugae patterns including dizygous twins and the rugae patterns were not symmetrical, both in number and in its distribution. The preliminary study undertaken here shows no two palates are alike in terms of their rugae pattern. Palatal rugae possess unique characteristics as they are absolutely individualistic and therefore, can be used as a personal soft-tissue 'oral' print for identification in forensic cases.

Isotope Identification

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

Karpius, Peter Joseph

2017-09-18

The objective of this training modules is to examine the process of using gamma spectroscopy for radionuclide identification; apply pattern recognition to gamma spectra; identify methods of verifying energy calibration; and discuss potential causes of isotope misidentification.

Large-area imaging reveals biologically driven non-random spatial patterns of corals at a remote reef

NASA Astrophysics Data System (ADS)

Edwards, Clinton B.; Eynaud, Yoan; Williams, Gareth J.; Pedersen, Nicole E.; Zgliczynski, Brian J.; Gleason, Arthur C. R.; Smith, Jennifer E.; Sandin, Stuart A.

2017-12-01

For sessile organisms such as reef-building corals, differences in the degree of dispersion of individuals across a landscape may result from important differences in life-history strategies or may reflect patterns of habitat availability. Descriptions of spatial patterns can thus be useful not only for the identification of key biological and physical mechanisms structuring an ecosystem, but also by providing the data necessary to generate and test ecological theory. Here, we used an in situ imaging technique to create large-area photomosaics of 16 plots at Palmyra Atoll, central Pacific, each covering 100 m2 of benthic habitat. We mapped the location of 44,008 coral colonies and identified each to the lowest taxonomic level possible. Using metrics of spatial dispersion, we tested for departures from spatial randomness. We also used targeted model fitting to explore candidate processes leading to differences in spatial patterns among taxa. Most taxa were clustered and the degree of clustering varied by taxon. A small number of taxa did not significantly depart from randomness and none revealed evidence of spatial uniformity. Importantly, taxa that readily fragment or tolerate stress through partial mortality were more clustered. With little exception, clustering patterns were consistent with models of fragmentation and dispersal limitation. In some taxa, dispersion was linearly related to abundance, suggesting density dependence of spatial patterning. The spatial patterns of stony corals are non-random and reflect fundamental life-history characteristics of the taxa, suggesting that the reef landscape may, in many cases, have important elements of spatial predictability.

Time Pattern Locking Scheme for Secure Multimedia Contents in Human-Centric Device

PubMed Central

Kim, Hyun-Woo; Kim, Jun-Ho; Park, Jong Hyuk; Jeong, Young-Sik

2014-01-01

Among the various smart multimedia devices, multimedia smartphones have become the most widespread due to their convenient portability and real-time information sharing, as well as various other built-in features. Accordingly, since personal and business activities can be carried out using multimedia smartphones without restrictions based on time and location, people have more leisure time and convenience than ever. However, problems such as loss, theft, and information leakage because of convenient portability have also increased proportionally. As a result, most multimedia smartphones are equipped with various built-in locking features. Pattern lock, personal identification numbers, and passwords are the most used locking features on current smartphones, but these are vulnerable to shoulder surfing and smudge attacks, allowing malicious users to bypass the security feature easily. In particular, the smudge attack technique is a convenient way to unlock multimedia smartphones after they have been stolen. In this paper, we propose the secure locking screen using time pattern (SLSTP) focusing on improved security and convenience for users to support human-centric multimedia device completely. The SLSTP can provide a simple interface to users and reduce the risk factors pertaining to security leakage to malicious third parties. PMID:25202737

Molecular and immunogenetic analysis of major histocompatibility haplotypes in Northern Bobwhite enable direct identification of corresponding haplotypes in an endangered subspecies, the Masked Bobwhite

USGS Publications Warehouse

Drake, B.M.; Goto, R.M.; Miller, M.M.; Gee, G.F.; Briles, W.E.

1999-01-01

The major histocompatibility complex (MHC) is a group of genetic loci coding for haplotypes that have been associated with fitness traits in mammals and birds. Such associations suggest that MHC diversity may be an indicator of overall genetic fitness of endangered or threatened species. The MHC haplotypes of a captive population of 12 families of northern bobwhites (Colinus virginianus) were identified using a combination of immunogenetic and molecular techniques. Alloantisera were produced within families of northern bobwhites and were then tested for differential agglutination of erythrocytes of all members of each family. The pattern of reactions determined from testing these alloantisera identified a single genetic system of alloantigens in the northern bobwhites, resulting in the assignment of a tentative genotype to each individual within the quail families. Restriction fragment patterns of the DNA of each bird were determined using the chicken MHC B-G cDNA probe bg11. The concordance between the restriction fragment patterns and the alloantisera reactions showed that the alloantisera had identified the MHC of the northern bobwhite and supported the tentative genotype assignments, identifying at least 12 northern bobwhite MHC haplotypes.

New techniques enable comparative analysis of microtubule orientation, wall texture, and growth rate in intact roots of Arabidopsis.

PubMed

Sugimoto, K; Williamson, R E; Wasteneys, G O

2000-12-01

This article explores root epidermal cell elongation and its dependence on two structural elements of cells, cortical microtubules and cellulose microfibrils. The recent identification of Arabidopsis morphology mutants with putative cell wall or cytoskeletal defects demands a procedure for examining and comparing wall architecture and microtubule organization patterns in this species. We developed methods to examine cellulose microfibrils by field emission scanning electron microscopy and microtubules by immunofluorescence in essentially intact roots. We were able to compare cellulose microfibril and microtubule alignment patterns at equivalent stages of cell expansion. Field emission scanning electron microscopy revealed that Arabidopsis root epidermal cells have typical dicot primary cell wall structure with prominent transverse cellulose microfibrils embedded in pectic substances. Our analysis showed that microtubules and microfibrils have similar orientation only during the initial phase of elongation growth. Microtubule patterns deviate from a predominantly transverse orientation while cells are still expanding, whereas cellulose microfibrils remain transverse until well after expansion finishes. We also observed microtubule-microfibril alignment discord before cells enter their elongation phase. This study and the new technology it presents provide a starting point for further investigations on the physical properties of cell walls and their mechanisms of assembly.

Time pattern locking scheme for secure multimedia contents in human-centric device.

PubMed

Kim, Hyun-Woo; Kim, Jun-Ho; Park, Jong Hyuk; Jeong, Young-Sik

2014-01-01

Among the various smart multimedia devices, multimedia smartphones have become the most widespread due to their convenient portability and real-time information sharing, as well as various other built-in features. Accordingly, since personal and business activities can be carried out using multimedia smartphones without restrictions based on time and location, people have more leisure time and convenience than ever. However, problems such as loss, theft, and information leakage because of convenient portability have also increased proportionally. As a result, most multimedia smartphones are equipped with various built-in locking features. Pattern lock, personal identification numbers, and passwords are the most used locking features on current smartphones, but these are vulnerable to shoulder surfing and smudge attacks, allowing malicious users to bypass the security feature easily. In particular, the smudge attack technique is a convenient way to unlock multimedia smartphones after they have been stolen. In this paper, we propose the secure locking screen using time pattern (SLSTP) focusing on improved security and convenience for users to support human-centric multimedia device completely. The SLSTP can provide a simple interface to users and reduce the risk factors pertaining to security leakage to malicious third parties.

Applications of Remote Sensing and GIS(Geographic Information System) in Crime Analysis of Gujranwala City.

NASA Astrophysics Data System (ADS)

Munawar, Iqra

2016-07-01

Crime mapping is a dynamic process. It can be used to assist all stages of the problem solving process. Mapping crime can help police protect citizens more effectively. The decision to utilize a certain type of map or design element may change based on the purpose of a map, the audience or the available data. If the purpose of the crime analysis map is to assist in the identification of a particular problem, selected data may be mapped to identify patterns of activity that have been previously undetected. The main objective of this research was to study the spatial distribution patterns of the four common crimes i.e Narcotics, Arms, Burglary and Robbery in Gujranwala City using spatial statistical techniques to identify the hotspots. Hotspots or location of clusters were identified using Getis-Ord Gi* Statistic. Crime analysis mapping can be used to conduct a comprehensive spatial analysis of the problem. Graphic presentations of such findings provide a powerful medium to communicate conditions, patterns and trends thus creating an avenue for analysts to bring about significant policy changes. Moreover Crime mapping also helps in the reduction of crime rate.

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

Treesearch

Frank N. Martin; Paul W. Tooley

2006-01-01

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

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

EPA Science Inventory

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

Problem Identification Survey Handbook for Parish Rural Development Committees.

ERIC Educational Resources Information Center

Koch, Kenneth A.

The Task Force on Resource Development of the Cooperative Extension Service, Louisiana State University, decided to utilize the leader identification technique as a means of assisting the parish rural development committees in the rural development process. The technique is a procedure to stimulate effective citizen participation to identify…

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

48 CFR 1852.245-74 - Identification and marking of Government equipment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Technical Handbook (NASA-HDBK) 6003, Application of Data Matrix Identification Symbols to Aerospace Parts... Identification Symbols on Aerospace Parts or through the use of commercial marking techniques that: (1) are...

Benefits and challenges to using DNA-based identification methods: An example study of larval fish from nearshore areas of Lake Superior

EPA Science Inventory

DNA-based identification methods could increase the ability of aquatic resource managers to track patterns of invasive species, especially for taxa that are difficult to identify morphologically. Nonetheless, use of DNA-based identification methods in aquatic surveys is still unc...

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

NASA Technical Reports Server (NTRS)

Kehoe, Michael W.

1988-01-01

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

Patterns of family identification and self-congruence in childhood separation anxiety disorder.

PubMed

Blatter-Meunier, Judith C; Lavallee, Kristen L; Schneider, Silvia

2014-01-01

Patterns of identification among family members may differ in families with children with separation anxiety disorder (SAD) as compared with healthy children. However, this has not been explored to date. The present study examines identification processes in 199 families: 100 families of children with SAD, 43 families of children with other anxiety disorders, and 56 families of nondisordered children, using the Family Identification Test. Children with SAD and their parents generally identify significantly less with each other and report less desire to be similar to each other than nondisordered children and their parents. Further, children with SAD are less self-congruent than healthy children. There were no significant differences between children with SAD and with other anxiety disorders. Identification and self-congruence distinguish families of children with SAD from families of healthy children. Future studies should aim to determine the direction of effects over time, as well as to determine the contribution of identification and coherence in explaining SAD after accounting for other factors such as attachment and self-esteem. Copyright © 2013 S. Karger AG, Basel.

Visual control of flight speed in Drosophila melanogaster.

PubMed

Fry, Steven N; Rohrseitz, Nicola; Straw, Andrew D; Dickinson, Michael H

2009-04-01

Flight control in insects depends on self-induced image motion (optic flow), which the visual system must process to generate appropriate corrective steering maneuvers. Classic experiments in tethered insects applied rigorous system identification techniques for the analysis of turning reactions in the presence of rotating pattern stimuli delivered in open-loop. However, the functional relevance of these measurements for visual free-flight control remains equivocal due to the largely unknown effects of the highly constrained experimental conditions. To perform a systems analysis of the visual flight speed response under free-flight conditions, we implemented a 'one-parameter open-loop' paradigm using 'TrackFly' in a wind tunnel equipped with real-time tracking and virtual reality display technology. Upwind flying flies were stimulated with sine gratings of varying temporal and spatial frequencies, and the resulting speed responses were measured from the resulting flight speed reactions. To control flight speed, the visual system of the fruit fly extracts linear pattern velocity robustly over a broad range of spatio-temporal frequencies. The speed signal is used for a proportional control of flight speed within locomotor limits. The extraction of pattern velocity over a broad spatio-temporal frequency range may require more sophisticated motion processing mechanisms than those identified in flies so far. In Drosophila, the neuromotor pathways underlying flight speed control may be suitably explored by applying advanced genetic techniques, for which our data can serve as a baseline. Finally, the high-level control principles identified in the fly can be meaningfully transferred into a robotic context, such as for the robust and efficient control of autonomous flying micro air vehicles.

Surgical Anatomy of the Left Lateral Segment as Applied to Living-Donor and Split-Liver Transplantation

PubMed Central

Reichert, Paulo R.; Renz, John F.; D’Albuquerque, Luiz A. C.; Rosenthal, Philip; Lim, Robert C.; Roberts, John P.; Ascher, Nancy L.; Emond, Jean C.

2000-01-01

Objective To evaluate intrahepatic vascular and biliary anatomy of the left lateral segment (LLS) as applied to living-donor and split-liver transplantation. Summary Background Data Living-donor and split-liver transplantation are innovative surgical techniques that have expanded the donor pool. Fundamental to the application of these techniques is an understanding of intrahepatic vascular and biliary anatomy. Methods Pathologic data obtained from cadaveric liver corrosion casts and liver dissections were clinically correlated with the anatomical findings obtained during split-liver, living-donor, and reduced-liver transplants. Results The anatomical relation of the left bile duct system with respect to the left portal venous system was constant, with the left bile duct superior to the extrahepatic transverse portion of the left portal vein. Four specific patterns of left biliary anatomy and three patterns of left hepatic venous drainage were identified and described. Conclusions Although highly variable, the biliary and hepatic venous anatomy of the LLS can be broadly categorized into distinct patterns. The identification of the LLS duct origin lateral to the umbilical fissure in segment 4 in 50% of cast specimens is significant in the performance of split-liver and living-donor transplantation, because dissection of the graft pedicle at the level of the round ligament will result in separate ducts from segments 2 and 3 in most patients, with the further possibility of an anterior segment 4 duct. A connective tissue bile duct plate, which can be clinically identified, is described to guide dissection of the segment 2 and 3 biliary radicles. PMID:11066137

Identification of DWI behavior patterns and methods for change

DOT National Transportation Integrated Search

1982-09-01

The purpose of this study was to identify patterns of behavior leading to driving while intoxicated (DWI), and to propose countermeasures for altering these patterns before they result in DWI. Two samples were studied: Los Angeles high school student...

Detecting protein-protein interactions in the intact cell of Bacillus subtilis (ATCC 6633).

PubMed

Winters, Michael S; Day, R A

2003-07-01

The salt bridge, paired group-specific reagent cyanogen (ethanedinitrile; C(2)N(2)) converts naturally occurring pairs of functional groups into covalently linked products. Cyanogen readily permeates cell walls and membranes. When the paired groups are shared between associated proteins, isolation of the covalently linked proteins allows their identity to be assigned. Examination of organisms of known genome sequence permits identification of the linked proteins by mass spectrometric techniques applied to peptides derived from them. The cyanogen-linked proteins were isolated by polyacrylamide gel electrophoresis. Digestion of the isolated proteins with proteases of known specificity afforded sets of peptides that could be analyzed by mass spectrometry. These data were compared with those derived theoretically from the Swiss Protein Database by computer-based comparisons (Protein Prospector; http://prospector.ucsf.edu). Identification of associated proteins in the ribosome of Bacillus subtilis strain ATCC 6633 showed that there is an association homology with the association patterns of the ribosomal proteins of Haloarcula marismortui and Thermus thermophilus. In addition, other proteins involved in protein biosynthesis were shown to be associated with ribosomal proteins.

Detecting Protein-Protein Interactions in the Intact Cell of Bacillus subtilis (ATCC 6633)

PubMed Central

Winters, Michael S.; Day, R. A.

2003-01-01

The salt bridge, paired group-specific reagent cyanogen (ethanedinitrile; C2N2) converts naturally occurring pairs of functional groups into covalently linked products. Cyanogen readily permeates cell walls and membranes. When the paired groups are shared between associated proteins, isolation of the covalently linked proteins allows their identity to be assigned. Examination of organisms of known genome sequence permits identification of the linked proteins by mass spectrometric techniques applied to peptides derived from them. The cyanogen-linked proteins were isolated by polyacrylamide gel electrophoresis. Digestion of the isolated proteins with proteases of known specificity afforded sets of peptides that could be analyzed by mass spectrometry. These data were compared with those derived theoretically from the Swiss Protein Database by computer-based comparisons (Protein Prospector; http://prospector.ucsf.edu). Identification of associated proteins in the ribosome of Bacillus subtilis strain ATCC 6633 showed that there is an association homology with the association patterns of the ribosomal proteins of Haloarcula marismortui and Thermus thermophilus. In addition, other proteins involved in protein biosynthesis were shown to be associated with ribosomal proteins. PMID:12837803

Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes Using HMMs and Hierarchical Bayesian Modeling Approaches.

PubMed

Oh, Sunghee; Song, Seongho

2017-01-01

In gene expression profile, data analysis pipeline is categorized into four levels, major downstream tasks, i.e., (1) identification of differential expression; (2) clustering co-expression patterns; (3) classification of subtypes of samples; and (4) detection of genetic regulatory networks, are performed posterior to preprocessing procedure such as normalization techniques. To be more specific, temporal dynamic gene expression data has its inherent feature, namely, two neighboring time points (previous and current state) are highly correlated with each other, compared to static expression data which samples are assumed as independent individuals. In this chapter, we demonstrate how HMMs and hierarchical Bayesian modeling methods capture the horizontal time dependency structures in time series expression profiles by focusing on the identification of differential expression. In addition, those differential expression genes and transcript variant isoforms over time detected in core prerequisite steps can be generally further applied in detection of genetic regulatory networks to comprehensively uncover dynamic repertoires in the aspects of system biology as the coupled framework.

Differentiating Positional Isomers of Nucleoside Modifications by Higher-Energy Collisional Dissociation Mass Spectrometry (HCD MS)

NASA Astrophysics Data System (ADS)

Jora, Manasses; Burns, Andrew P.; Ross, Robert L.; Lobue, Peter A.; Zhao, Ruoxia; Palumbo, Cody M.; Beal, Peter A.; Addepalli, Balasubrahmanyam; Limbach, Patrick A.

2018-06-01

The analytical identification of positional isomers (e.g., 3-, N 4-, 5-methylcytidine) within the > 160 different post-transcriptional modifications found in RNA can be challenging. Conventional liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) approaches rely on chromatographic separation for accurate identification because the collision-induced dissociation (CID) mass spectra of these isomers nearly exclusively yield identical nucleobase ions (BH2 +) from the same molecular ion (MH+). Here, we have explored higher-energy collisional dissociation (HCD) as an alternative fragmentation technique to generate more informative product ions that can be used to differentiate positional isomers. LC-MS/MS of modified nucleosides characterized using HCD led to the creation of structure- and HCD energy-specific fragmentation patterns that generated unique fingerprints, which can be used to identify individual positional isomers even when they cannot be separated chromatographically. While particularly useful for identifying positional isomers, the fingerprinting capabilities enabled by HCD also offer the potential to generate HPLC-independent spectral libraries for the rapid analysis of modified ribonucleosides. [Figure not available: see fulltext.

Identification of Terrestrial Reflectance From Remote Sensing

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

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

PubMed

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

2016-01-01

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

Conceptualizing the Dynamics between Bicultural Identification and Personal Social Networks

PubMed Central

Repke, Lydia; Benet-Martínez, Verónica

2017-01-01

An adequate understanding of the acculturation processes affecting immigrants and their descendants involves ascertaining the dynamic interplay between the way these individuals manage their multiple (and sometimes conflictual) cultural value systems and identifications and possible changes in their social networks. To fill this gap, the present research examines how key acculturation variables (e.g., strength of ethnic/host cultural identifications, bicultural identity integration or BII) relate to the composition and structure of bicultural individuals’ personal social networks. In Study 1, we relied on a generationally and culturally diverse community sample of 123 Latinos residing in the US. Participants nominated eight individuals (i.e., alters) from their habitual social networks and across two relational domains: friendships and colleagues. Results indicated that the interconnection of same ethnicity alters across different relationship domains is linked to cultural identifications, while the amount of coethnic and host individuals in the network is not. In particular, higher interconnection between Latino friends and colleagues was linked to lower levels of U.S. identification. Conversely, the interconnection of non-Latino friends and colleagues was associated with lower levels of Latino identification. This pattern of results suggests that the relational context for each type of cultural identification works in a subtractive and inverse manner. Further, time spent in the US was linked to both Latino and U.S. cultural identifications, but this relationship was moderated by the level of BII. Specifically, the association between time in the US and strength of both cultural identities was stronger for individuals reporting low levels of BII. Taking the findings from Study 1 as departure point, Study 2 used an agent-based model data simulation approach to explore the dynamic ways in which the content and the structure of an immigrant’s social network might matter over time in predicting three possible identity patterns: coexisting cultural identifications, conflicting cultural identifications, and a mixture of the two. These simulations allowed us to detect network constellations, which lead to identification or disidentification with both cultures. We showed that distinct patterns of social relations do not lead to identity outcomes in a deterministic fashion, but that often many different outcomes are probable. PMID:28408892

Forensics for flatbed scanners

NASA Astrophysics Data System (ADS)

Gloe, Thomas; Franz, Elke; Winkler, Antje

2007-02-01

Within this article, we investigate possibilities for identifying the origin of images acquired with flatbed scanners. A current method for the identification of digital cameras takes advantage of image sensor noise, strictly speaking, the spatial noise. Since flatbed scanners and digital cameras use similar technologies, the utilization of image sensor noise for identifying the origin of scanned images seems to be possible. As characterization of flatbed scanner noise, we considered array reference patterns and sensor line reference patterns. However, there are particularities of flatbed scanners which we expect to influence the identification. This was confirmed by extensive tests: Identification was possible to a certain degree, but less reliable than digital camera identification. In additional tests, we simulated the influence of flatfielding and down scaling as examples for such particularities of flatbed scanners on digital camera identification. One can conclude from the results achieved so far that identifying flatbed scanners is possible. However, since the analyzed methods are not able to determine the image origin in all cases, further investigations are necessary.

Real-time flutter identification

NASA Technical Reports Server (NTRS)

Roy, R.; Walker, R.

1985-01-01

The techniques and a FORTRAN 77 MOdal Parameter IDentification (MOPID) computer program developed for identification of the frequencies and damping ratios of multiple flutter modes in real time are documented. Physically meaningful model parameterization was combined with state of the art recursive identification techniques and applied to the problem of real time flutter mode monitoring. The performance of the algorithm in terms of convergence speed and parameter estimation error is demonstrated for several simulated data cases, and the results of actual flight data analysis from two different vehicles are presented. It is indicated that the algorithm is capable of real time monitoring of aircraft flutter characteristics with a high degree of reliability.

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

PubMed

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

2014-03-01

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

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

PubMed

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

2015-01-01

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

Metabolomics Characterization of U.S. and Japanese F-15 and C-130 Flight Line Crews Exposed to Jet Fuel Volatile Organic Compounds and Aerosols

DTIC Science & Technology

2014-09-30

resulted in the identification of metabolite patterns indicative of flight line exposure when compared to non -flight line control subjects...virtually non -invasive sample collection, minimal sample processing, robust and stable analytical platform, with excellent analytical and biological...identification of metabolite patterns indicative of flight line exposure when compared to non -flight line control subjects. Regardless of fuel (JP-4 or

Automatic pattern identification of rock moisture based on the Staff-RF model

NASA Astrophysics Data System (ADS)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

Dual multispectral and 3D structured light laparoscope

NASA Astrophysics Data System (ADS)

Clancy, Neil T.; Lin, Jianyu; Arya, Shobhit; Hanna, George B.; Elson, Daniel S.

2015-03-01

Intraoperative feedback on tissue function, such as blood volume and oxygenation would be useful to the surgeon in cases where current clinical practice relies on subjective measures, such as identification of ischaemic bowel or tissue viability during anastomosis formation. Also, tissue surface profiling may be used to detect and identify certain pathologies, as well as diagnosing aspects of tissue health such as gut motility. In this paper a dual modality laparoscopic system is presented that combines multispectral reflectance and 3D surface imaging. White light illumination from a xenon source is detected by a laparoscope-mounted fast filter wheel camera to assemble a multispectral image (MSI) cube. Surface shape is then calculated using a spectrally-encoded structured light (SL) pattern detected by the same camera and triangulated using an active stereo technique. Images of porcine small bowel were acquired during open surgery. Tissue reflectance spectra were acquired and blood volume was calculated at each spatial pixel across the bowel wall and mesentery. SL features were segmented and identified using a `normalised cut' algoritm and the colour vector of each spot. Using the 3D geometry defined by the camera coordinate system the multispectral data could be overlaid onto the surface mesh. Dual MSI and SL imaging has the potential to provide augmented views to the surgeon supplying diagnostic information related to blood supply health and organ function. Future work on this system will include filter optimisation to reduce noise in tissue optical property measurement, and minimise spot identification errors in the SL pattern.

Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

PubMed

Zare, Marzieh; Rezvani, Zahra; Benasich, April A

2016-07-01

This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Recall of briefly presented chess positions and its relation to chess skill.

PubMed

Gong, Yanfei; Ericsson, K Anders; Moxley, Jerad H

2015-01-01

Individual differences in memory performance in a domain of expertise have traditionally been accounted for by previously acquired chunks of knowledge and patterns. These accounts have been examined experimentally mainly in chess. The role of chunks (clusters of chess pieces recalled in rapid succession during recall of chess positions) and their relations to chess skill are, however, under debate. By introducing an independent chunk-identification technique, namely repeated-recall technique, this study identified individual chunks for particular chess players. The study not only tested chess players with increasing chess expertise, but also tested non-chess players who should not have previously acquired any chess related chunks in memory. For recall of game positions significant differences between players and non-players were found in virtually all the characteristics of chunks recalled. Size of the largest chunks also correlates with chess skill within the group of rated chess players. Further research will help us understand how these memory encodings can explain large differences in chess skill.

Recall of Briefly Presented Chess Positions and Its Relation to Chess Skill

PubMed Central

Moxley, Jerad H.

2015-01-01

Individual differences in memory performance in a domain of expertise have traditionally been accounted for by previously acquired chunks of knowledge and patterns. These accounts have been examined experimentally mainly in chess. The role of chunks (clusters of chess pieces recalled in rapid succession during recall of chess positions) and their relations to chess skill are, however, under debate. By introducing an independent chunk-identification technique, namely repeated-recall technique, this study identified individual chunks for particular chess players. The study not only tested chess players with increasing chess expertise, but also tested non-chess players who should not have previously acquired any chess related chunks in memory. For recall of game positions significant differences between players and non-players were found in virtually all the characteristics of chunks recalled. Size of the largest chunks also correlates with chess skill within the group of rated chess players. Further research will help us understand how these memory encodings can explain large differences in chess skill. PMID:25774693

Gas Discharge Visualization: An Imaging and Modeling Tool for Medical Biometrics

PubMed Central

Kostyuk, Nataliya; Cole, Phyadragren; Meghanathan, Natarajan; Isokpehi, Raphael D.; Cohly, Hari H. P.

2011-01-01

The need for automated identification of a disease makes the issue of medical biometrics very current in our society. Not all biometric tools available provide real-time feedback. We introduce gas discharge visualization (GDV) technique as one of the biometric tools that have the potential to identify deviations from the normal functional state at early stages and in real time. GDV is a nonintrusive technique to capture the physiological and psychoemotional status of a person and the functional status of different organs and organ systems through the electrophotonic emissions of fingertips placed on the surface of an impulse analyzer. This paper first introduces biometrics and its different types and then specifically focuses on medical biometrics and the potential applications of GDV in medical biometrics. We also present our previous experience with GDV in the research regarding autism and the potential use of GDV in combination with computer science for the potential development of biological pattern/biomarker for different kinds of health abnormalities including cancer and mental diseases. PMID:21747817

Unveiling the Biometric Potential of Finger-Based ECG Signals

PubMed Central

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

Gas discharge visualization: an imaging and modeling tool for medical biometrics.

PubMed

Kostyuk, Nataliya; Cole, Phyadragren; Meghanathan, Natarajan; Isokpehi, Raphael D; Cohly, Hari H P

2011-01-01

The need for automated identification of a disease makes the issue of medical biometrics very current in our society. Not all biometric tools available provide real-time feedback. We introduce gas discharge visualization (GDV) technique as one of the biometric tools that have the potential to identify deviations from the normal functional state at early stages and in real time. GDV is a nonintrusive technique to capture the physiological and psychoemotional status of a person and the functional status of different organs and organ systems through the electrophotonic emissions of fingertips placed on the surface of an impulse analyzer. This paper first introduces biometrics and its different types and then specifically focuses on medical biometrics and the potential applications of GDV in medical biometrics. We also present our previous experience with GDV in the research regarding autism and the potential use of GDV in combination with computer science for the potential development of biological pattern/biomarker for different kinds of health abnormalities including cancer and mental diseases.

Unveiling the biometric potential of finger-based ECG signals.

PubMed

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

Identification of Microorganisms by Modern Analytical Techniques.

PubMed

Buszewski, Bogusław; Rogowska, Agnieszka; Pomastowski, Paweł; Złoch, Michał; Railean-Plugaru, Viorica

2017-11-01

Rapid detection and identification of microorganisms is a challenging and important aspect in a wide range of fields, from medical to industrial, affecting human lives. Unfortunately, classical methods of microorganism identification are based on time-consuming and labor-intensive approaches. Screening techniques require the rapid and cheap grouping of bacterial isolates; however, modern bioanalytics demand comprehensive bacterial studies at a molecular level. Modern approaches for the rapid identification of bacteria use molecular techniques, such as 16S ribosomal RNA gene sequencing based on polymerase chain reaction or electromigration, especially capillary zone electrophoresis and capillary isoelectric focusing. However, there are still several challenges with the analysis of microbial complexes using electromigration technology, such as uncontrolled aggregation and/or adhesion to the capillary surface. Thus, an approach using capillary electrophoresis of microbial aggregates with UV and matrix-assisted laser desorption ionization time-of-flight MS detection is presented.

Model correlation and damage location for large space truss structures: Secant method development and evaluation

NASA Technical Reports Server (NTRS)

Smith, Suzanne Weaver; Beattie, Christopher A.

1991-01-01

On-orbit testing of a large space structure will be required to complete the certification of any mathematical model for the structure dynamic response. The process of establishing a mathematical model that matches measured structure response is referred to as model correlation. Most model correlation approaches have an identification technique to determine structural characteristics from the measurements of the structure response. This problem is approached with one particular class of identification techniques - matrix adjustment methods - which use measured data to produce an optimal update of the structure property matrix, often the stiffness matrix. New methods were developed for identification to handle problems of the size and complexity expected for large space structures. Further development and refinement of these secant-method identification algorithms were undertaken. Also, evaluation of these techniques is an approach for model correlation and damage location was initiated.

Edge detection techniques for iris recognition system

NASA Astrophysics Data System (ADS)

Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

2013-12-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

Identification of pilot-vehicle dynamics from simulation and flight test

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1990-01-01

The paper discusses an identification problem in which a basic feedback control structure, or pilot control strategy, is hypothesized. Identification algorithms are employed to determine the particular form of pilot equalization in each feedback loop. It was found that both frequency- and time-domain identification techniques provide useful information.

Effect of attention on the detection and identification of masked spatial patterns.

PubMed

Põder, Endel

2005-01-01

The effect of attention on the detection and identification of vertically and horizontally oriented Gabor patterns in the condition of simultaneous masking with obliquely oriented Gabors was studied. Attention was manipulated by varying the set size in a visual-search experiment. In the first experiment, small target Gabors were presented on the background of larger masking Gabors. In the detection task, the effect of set size was as predicted by unlimited-capacity signal detection theory. In the orientation identification task, increasing the set size from 1 to 8 resulted in a much larger decline in performance. The results of the additional experiments suggest that attention can reduce the crowding effect of maskers.

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.

Comparison of gamma densitometry and electrical capacitance measurements applied to hold-up prediction of oil–water flow patterns in horizontal and slightly inclined pipes

NASA Astrophysics Data System (ADS)

Perera, Kshanthi; Kumara, W. A. S.; Hansen, Fredrik; Mylvaganam, Saba; Time, Rune W.

2018-06-01

Measurement techniques are vital for the control and operation of multiphase oil–water flow in pipes. The development of such techniques depends on laboratory experiments involving flow visualization, liquid fraction (‘hold-up’), phase slip and pressure drop measurements. They provide valuable information by revealing the physics, spatial and temporal structures of complex multiphase flow phenomena. This paper presents the hold-up measurement of oil–water flow in pipelines using gamma densitometry and electrical capacitance tomography (ECT) sensors. The experiments were carried out with different pipe inclinations from  ‑5° to  +6° for selected mixture velocities (0.2–1.5 m s‑1), and at selected watercuts (0.05–0.95). Mineral oil (Exxsol D60) and water were used as test fluids. Nine flow patterns were identified including a new pattern called stratified wavy and mixed interface flow. As a third direct method, visual observations and high-speed videos were used for the flow regime and interface identification. ECT and gamma densitometry hold-up measurements show similar trends for changes in pipeline inclinations. Changing the pipe inclination affected the flow mostly at lower mixture velocities and caused a change of flow patterns, allowing the highest change of hold-up. ECT hold-up measurements overpredict the gamma densitometry measurements at higher input water cuts and underpredict at intermediate water cuts. Gamma hold-up results showed good agreement with the literature results, having a maximum deviation of 6%, while it was as high as 22% for ECT in comparison to gamma densitometry. Uncertainty analysis of the measurement techniques was carried out with single-phase oil flow. This shows that the measurement error associated with gamma densitometry is approximately 3.2%, which includes 1.3% statistical error and 2.9% error identified as electromagnetically induced noise in electronics. Thus, gamma densitometry can predict hold-up with a higher accuracy in comparison to ECT when applied to oil–water systems at minimized electromagnetic noise.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Riverscape patterns among years of juvenile coho salmon in midcoastal Oregon: implications for conservation

Treesearch

R. Flitcroft; K. Burnett; J. Snyder; G. Reeves; L. Ganio

2014-01-01

Patterns of salmon distribution throughout a riverscape may be expected to change over time in response to environmental conditions and population sizes. Changing patterns of use, including identification of consistently occupied locations, are informative for conservation and recovery planning. We explored interannual patterns of distribution by juvenile Coho Salmon...

Disentangling dynamic networks: Separated and joint expressions of functional connectivity patterns in time.

PubMed

Leonardi, Nora; Shirer, William R; Greicius, Michael D; Van De Ville, Dimitri

2014-12-01

Resting-state functional connectivity (FC) is highly variable across the duration of a scan. Groups of coevolving connections, or reproducible patterns of dynamic FC (dFC), have been revealed in fluctuating FC by applying unsupervised learning techniques. Based on results from k-means clustering and sliding-window correlations, it has recently been hypothesized that dFC may cycle through several discrete FC states. Alternatively, it has been proposed to represent dFC as a linear combination of multiple FC patterns using principal component analysis. As it is unclear whether sparse or nonsparse combinations of FC patterns are most appropriate, and as this affects their interpretation and use as markers of cognitive processing, the goal of our study was to evaluate the impact of sparsity by performing an empirical evaluation of simulated, task-based, and resting-state dFC. To this aim, we applied matrix factorizations subject to variable constraints in the temporal domain and studied both the reproducibility of ensuing representations of dFC and the expression of FC patterns over time. During subject-driven tasks, dFC was well described by alternating FC states in accordance with the nature of the data. The estimated FC patterns showed a rich structure with combinations of known functional networks enabling accurate identification of three different tasks. During rest, dFC was better described by multiple FC patterns that overlap. The executive control networks, which are critical for working memory, appeared grouped alternately with externally or internally oriented networks. These results suggest that combinations of FC patterns can provide a meaningful way to disentangle resting-state dFC. © 2014 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

Evaluating authentication options for mobile health applications in younger and older adults

PubMed Central

Khan, Hassan; Hengartner, Urs; Ong, Stephanie; Logan, Alexander G.; Vogel, Daniel; Gebotys, Robert; Yang, Jilan

2018-01-01

Objective Apps promoting patient self-management may improve health outcomes. However, methods to secure stored information on mobile devices may adversely affect usability. We tested the reliability and usability of common user authentication techniques in younger and older adults. Methodology Usability testing was conducted in two age groups, 18 to 30 years and 50 years and older. After completing a demographic questionnaire, each participant tested four authentication options in random order: four-digit personal identification number (PIN), graphical password (GRAPHICAL), Android pattern-lock (PATTERN), and a swipe-style Android fingerprint scanner (FINGERPRINT). Participants rated each option using the Systems Usability Scale (SUS). Results A total of 59 older and 43 younger participants completed the study. Overall, PATTERN was the fastest option (3.44s), and PIN had the fewest errors per attempt (0.02). Participants were able to login using PIN, PATTERN, and GRAPHICAL at least 98% of the time. FINGERPRINT was the slowest (26.97s), had an average of 1.46 errors per attempt, and had a successful login rate of 85%. Overall, PIN and PATTERN had higher SUS scores than FINGERPRINT and GRAPHICAL. Compared to younger participants, older participants were also less likely to find PATTERN to be tiring, annoying or time consuming and less likely to consider PIN to be time consuming. Younger participants were more likely to rate GRAPHICAL as annoying, time consuming and tiring than older participants. Conclusions On mobile devices, PIN and pattern-lock outperformed graphical passwords and swipe-style fingerprints. All participants took longer to authenticate using the swipe-style fingerprint compared to other options. Older participants also took two to three seconds longer to authenticate using the PIN, pattern and graphical passwords though this did not appear to affect perceived usability. PMID:29300736

Evaluating authentication options for mobile health applications in younger and older adults.

PubMed

Grindrod, Kelly; Khan, Hassan; Hengartner, Urs; Ong, Stephanie; Logan, Alexander G; Vogel, Daniel; Gebotys, Robert; Yang, Jilan

2018-01-01

Apps promoting patient self-management may improve health outcomes. However, methods to secure stored information on mobile devices may adversely affect usability. We tested the reliability and usability of common user authentication techniques in younger and older adults. Usability testing was conducted in two age groups, 18 to 30 years and 50 years and older. After completing a demographic questionnaire, each participant tested four authentication options in random order: four-digit personal identification number (PIN), graphical password (GRAPHICAL), Android pattern-lock (PATTERN), and a swipe-style Android fingerprint scanner (FINGERPRINT). Participants rated each option using the Systems Usability Scale (SUS). A total of 59 older and 43 younger participants completed the study. Overall, PATTERN was the fastest option (3.44s), and PIN had the fewest errors per attempt (0.02). Participants were able to login using PIN, PATTERN, and GRAPHICAL at least 98% of the time. FINGERPRINT was the slowest (26.97s), had an average of 1.46 errors per attempt, and had a successful login rate of 85%. Overall, PIN and PATTERN had higher SUS scores than FINGERPRINT and GRAPHICAL. Compared to younger participants, older participants were also less likely to find PATTERN to be tiring, annoying or time consuming and less likely to consider PIN to be time consuming. Younger participants were more likely to rate GRAPHICAL as annoying, time consuming and tiring than older participants. On mobile devices, PIN and pattern-lock outperformed graphical passwords and swipe-style fingerprints. All participants took longer to authenticate using the swipe-style fingerprint compared to other options. Older participants also took two to three seconds longer to authenticate using the PIN, pattern and graphical passwords though this did not appear to affect perceived usability.

A Statistical Methodology for Detecting and Monitoring Change in Forest Ecosystems Using Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Mills, R. T.; Kumar, J.; Hoffman, F. M.; Hargrove, W. W.; Spruce, J.

2011-12-01

Variations in vegetation phenology, the annual temporal pattern of leaf growth and senescence, can be a strong indicator of ecological change or disturbance. However, phenology is also strongly influenced by seasonal, interannual, and long-term trends in climate, making identification of changes in forest ecosystems a challenge. Forest ecosystems are vulnerable to extreme weather events, insect and disease attacks, wildfire, harvesting, and other land use change. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a proxy for phenology. NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) at 250 m resolution was used in this study to develop phenological signatures of ecological regimes called phenoregions. By applying a quantitative data mining technique to the NDVI measurements for every eight days over the entire MODIS record, annual maps of phenoregions were developed. This geospatiotemporal cluster analysis technique employs high performance computing resources, enabling analysis of such very large data sets. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. Analysis of the shifts among phenological states yields information about responses to interannual climate variability and, more importantly, changes in ecosystem health due to disturbances. Moreover, a large change in the phenological states occupied by a single location over time indicates a significant disturbance or ecological shift. This methodology has been applied for identification of various forest disturbance events, including wildfire, tree mortality due to Mountain Pine Beetle, and other insect infestation and diseases, as well as extreme events like storms and hurricanes in the U.S. Presented will be results from analysis of phenological state dynamics, along with disturbance and validation data.

Pattern-based information portal for business plan co-creation

NASA Astrophysics Data System (ADS)

Bontchev, Boyan; Ruskov, Petko; Tanev, Stoyan

2011-03-01

Creation of business plans helps entrepreneurs in managing identification of business opportunities and committing necessary resources for process evolution. Applying patterns in business plan creation facilitates the identification of effective solutions that were adopted in the past and may provide a basis for adopting similar solutions in the future within given business context. The article presents the system design of an information portal for business plan co-creation based on patterns. The portal is going to provide start-up and entrepreneurs with ready-to-modify business plan patterns in order to help them in development of effective and efficient business plans. It will facilitate entrepreneurs in co-experimenting and co-learning more frequently and faster. Moreover, the paper focuses on the software architecture of the pattern based portal and explains the functionality of its modules, namely the pattern designer, pattern repository services and agent-based pattern implementers. It explains their role for business process co-creation, storing and managing patterns described formally, and selecting patterns best suited for specific business case. Thus, innovative entrepreneurs will be guided by the portal in co-writing winning business plans and staying competitive in the present day dynamic globalized environment.

Pattern-based information portal for business plan co-creation

NASA Astrophysics Data System (ADS)

Bontchev, Boyan; Ruskov, Petko; Tanev, Stoyan

2010-10-01

Creation of business plans helps entrepreneurs in managing identification of business opportunities and committing necessary resources for process evolution. Applying patterns in business plan creation facilitates the identification of effective solutions that were adopted in the past and may provide a basis for adopting similar solutions in the future within given business context. The article presents the system design of an information portal for business plan co-creation based on patterns. The portal is going to provide start-up and entrepreneurs with ready-to-modify business plan patterns in order to help them in development of effective and efficient business plans. It will facilitate entrepreneurs in co-experimenting and co-learning more frequently and faster. Moreover, the paper focuses on the software architecture of the pattern based portal and explains the functionality of its modules, namely the pattern designer, pattern repository services and agent-based pattern implementers. It explains their role for business process co-creation, storing and managing patterns described formally, and selecting patterns best suited for specific business case. Thus, innovative entrepreneurs will be guided by the portal in co-writing winning business plans and staying competitive in the present day dynamic globalized environment.

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

NASA Technical Reports Server (NTRS)

Molusis, J. A.

1982-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

In Situ Identification of Nanoparticle Structural Information Using Optical Microscopy.

PubMed

Culver, Kayla S B; Liu, Tingting; Hryn, Alexander J; Fang, Ning; Odom, Teri W

2018-05-11

Diffraction-limited optical microscopy lacks the resolution to characterize directly nanoscale features of single nanoparticles. This paper describes how surprisingly rich structural features of small gold nanostars can be identified using differential interference contrast (DIC) microscopy. First, we established a library of structure-property relationships between nanoparticle shape and DIC optical image and then validated the correlation with electrodynamic simulations and electron microscopy. We found that DIC image patterns of single nanostars could be differentiated between 2D and 3D geometries. Also, DIC images could elucidate the symmetry properties and orientation of nanoparticles. Finally, we demonstrated how this wide-field optical technique can be used for in situ characterization of single nanoparticles rotating at a glass-water interface.

A novel method of identifying motor primitives using wavelet decomposition*

PubMed Central

Popov, Anton; Olesh, Erienne V.; Yakovenko, Sergiy; Gritsenko, Valeriya

2018-01-01

This study reports a new technique for extracting muscle synergies using continuous wavelet transform. The method allows to quantify coincident activation of muscle groups caused by the physiological processes of fixed duration, thus enabling the extraction of wavelet modules of arbitrary groups of muscles. Hierarchical clustering and identification of the repeating wavelet modules across subjects and across movements, was used to identify consistent muscle synergies. Results indicate that the most frequently repeated wavelet modules comprised combinations of two muscles that are not traditional agonists and span different joints. We have also found that these wavelet modules were flexibly combined across different movement directions in a pattern resembling directional tuning. This method is extendable to multiple frequency domains and signal modalities.

Neurobehavioral Development of Common Marmoset Monkeys

PubMed Central

Schultz-Darken, Nancy; Braun, Katarina M.; Emborg, Marina E.

2016-01-01

Common marmoset (Callithrix jacchus) monkeys are a resource for biomedical research and their use is predicted to increase due to the suitability of this species for transgenic approaches. Identification of abnormal neurodevelopment due to genetic modification relies upon the comparison with validated patterns of normal behavior defined by unbiased methods. As scientists unfamiliar with nonhuman primate development are interested to apply genomic editing techniques in marmosets, it would be beneficial to the field that the investigators use validated methods of postnatal evaluation that are age and species appropriate. This review aims to analyze current available data on marmoset physical and behavioral postnatal development, describe the methods used and discuss next steps to better understand and evaluate marmoset normal and abnormal postnatal neurodevelopment PMID:26502294

Assembling evidence for identifying reservoirs of infection.

PubMed

Viana, Mafalda; Mancy, Rebecca; Biek, Roman; Cleaveland, Sarah; Cross, Paul C; Lloyd-Smith, James O; Haydon, Daniel T

2014-05-01

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evolution of the empirical and theoretical foundations of eyewitness identification reform.

PubMed

Clark, Steven E; Moreland, Molly B; Gronlund, Scott D

2014-04-01

Scientists in many disciplines have begun to raise questions about the evolution of research findings over time (Ioannidis in Epidemiology, 19, 640-648, 2008; Jennions & Møller in Proceedings of the Royal Society, Biological Sciences, 269, 43-48, 2002; Mullen, Muellerleile, & Bryan in Personality and Social Psychology Bulletin, 27, 1450-1462, 2001; Schooler in Nature, 470, 437, 2011), since many phenomena exhibit decline effects-reductions in the magnitudes of effect sizes as empirical evidence accumulates. The present article examines empirical and theoretical evolution in eyewitness identification research. For decades, the field has held that there are identification procedures that, if implemented by law enforcement, would increase eyewitness accuracy, either by reducing false identifications, with little or no change in correct identifications, or by increasing correct identifications, with little or no change in false identifications. Despite the durability of this no-cost view, it is unambiguously contradicted by data (Clark in Perspectives on Psychological Science, 7, 238-259, 2012a; Clark & Godfrey in Psychonomic Bulletin & Review, 16, 22-42, 2009; Clark, Moreland, & Rush, 2013; Palmer & Brewer in Law and Human Behavior, 36, 247-255, 2012), raising questions as to how the no-cost view became well-accepted and endured for so long. Our analyses suggest that (1) seminal studies produced, or were interpreted as having produced, the no-cost pattern of results; (2) a compelling theory was developed that appeared to account for the no-cost pattern; (3) empirical results changed over the years, and subsequent studies did not reliably replicate the no-cost pattern; and (4) the no-cost view survived despite the accumulation of contradictory empirical evidence. Theories of memory that were ruled out by early data now appear to be supported by data, and the theory developed to account for early data now appears to be incorrect.

Camouflage, detection and identification of moving targets

PubMed Central

Hall, Joanna R.; Cuthill, Innes C.; Baddeley, Roland; Shohet, Adam J.; Scott-Samuel, Nicholas E.

2013-01-01

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely ‘break’ camouflage. PMID:23486439

Camouflage, detection and identification of moving targets.

PubMed

Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

2013-05-07

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

Gait patterns for crime fighting: statistical evaluation

NASA Astrophysics Data System (ADS)

Sulovská, Kateřina; Bělašková, Silvie; Adámek, Milan

2013-10-01

The criminality is omnipresent during the human history. Modern technology brings novel opportunities for identification of a perpetrator. One of these opportunities is an analysis of video recordings, which may be taken during the crime itself or before/after the crime. The video analysis can be classed as identification analyses, respectively identification of a person via externals. The bipedal locomotion focuses on human movement on the basis of their anatomical-physiological features. Nowadays, the human gait is tested by many laboratories to learn whether the identification via bipedal locomotion is possible or not. The aim of our study is to use 2D components out of 3D data from the VICON Mocap system for deep statistical analyses. This paper introduces recent results of a fundamental study focused on various gait patterns during different conditions. The study contains data from 12 participants. Curves obtained from these measurements were sorted, averaged and statistically tested to estimate the stability and distinctiveness of this biometrics. Results show satisfactory distinctness of some chosen points, while some do not embody significant difference. However, results presented in this paper are of initial phase of further deeper and more exacting analyses of gait patterns under different conditions.

THE ROLE OF FORENSIC DENTIST FOLLOWING MASS DISASTER

PubMed Central

Kolude, B.; Adeyemi, B.F.; Taiwo, J.O.; Sigbeku, O.F.; Eze, U.O.

2010-01-01

This review article focuses on mass disaster situations that may arise from natural or manmade circumstances and the significant role of forensic dental personnel in human identification following such occurrences. The various forensic dental modalities of identification that include matching techniques, postmortem profiling, genetic fingerprinting, dental fossil assessment and dental biometrics with digital subtraction were considered. The varying extent of use of forensic dental techniques and the resulting positive impact on human identification were considered. The importance of preparation by way of special training for forensic dental personnel, mock disaster rehearsal, and use of modern day technology was stressed. The need for international standardization of identification through the use of Interpol Disaster Victim Identification (DVI) for ms was further emphasized. Recommendations for improved human identification in Nigerian situation include reform of the National Emergency Management Association (NEMA), incorporation of dental care in primary health care to facilitate proper ante mortem database of the populace and commencement of identification at site of disaster. PMID:25161478

Is blue dye still required during sentinel lymph node biopsy for breast cancer?

PubMed

Peek, Mirjam Cl; Kovacs, Tibor; Baker, Rose; Hamed, Hisham; Kothari, Ash; Douek, Michael

2016-01-01

In early breast cancer, the optimal technique for sentinel lymph node biopsy (SLNB) is the combined technique (radioisotope and Patent Blue V) which achieves high identification rates. Despite this, many centres have decided to stop using blue dye due to blue-dye-related complications (tattoo, anaphylaxis). We evaluated the SLNB identification rate using the combined technique with and without Patent Blue V and the blue-dye-related complication rates. Clinical and histological data were analysed on patients undergoing SLNB between March 2014 and April 2015. SLNB was performed following standard hospital protocols using the combined technique. A total of 208 patients underwent SLNB and 160 patients (342 nodes) with complete operation notes were available for final analysis. The identification rate with the combined technique was 98.8% ( n = 158/160), with blue dye alone 92.5% ( n = 148/160) and with radioisotope alone 97.5% ( n = 156/160). A total of 76.9% (263/342) of nodes were radioactive and blue, 15.5% (53/342) only radioactive and 2.3% (8/342) only blue, 5.3% (18/342) were neither radioactive nor blue. No anaphylactic reactions were reported and blue skin staining was reported in six (3.8%) patients. The combined technique should continue be the preferred technique for SLNB and should be standardised. Radioisotope alone (but not blue dye alone) has comparable sentinel node identification rates in experienced hands. National guidelines are required to optimise operative documentation.

Countering imbalanced datasets to improve adverse drug event predictive models in labor and delivery.

PubMed

Taft, L M; Evans, R S; Shyu, C R; Egger, M J; Chawla, N; Mitchell, J A; Thornton, S N; Bray, B; Varner, M

2009-04-01

The IOM report, Preventing Medication Errors, emphasizes the overall lack of knowledge of the incidence of adverse drug events (ADE). Operating rooms, emergency departments and intensive care units are known to have a higher incidence of ADE. Labor and delivery (L&D) is an emergency care unit that could have an increased risk of ADE, where reported rates remain low and under-reporting is suspected. Risk factor identification with electronic pattern recognition techniques could improve ADE detection rates. The objective of the present study is to apply Synthetic Minority Over Sampling Technique (SMOTE) as an enhanced sampling method in a sparse dataset to generate prediction models to identify ADE in women admitted for labor and delivery based on patient risk factors and comorbidities. By creating synthetic cases with the SMOTE algorithm and using a 10-fold cross-validation technique, we demonstrated improved performance of the Naïve Bayes and the decision tree algorithms. The true positive rate (TPR) of 0.32 in the raw dataset increased to 0.67 in the 800% over-sampled dataset. Enhanced performance from classification algorithms can be attained with the use of synthetic minority class oversampling techniques in sparse clinical datasets. Predictive models created in this manner can be used to develop evidence based ADE monitoring systems.

Recent Advances in Mass Spectrometry for the Identification of Neuro-chemicals and their Metabolites in Biofluids.

PubMed

Kailasa, Suresh Kumar; Wu, Hui-Fen

2013-07-01

Recently, mass spectrometric related techniques have been widely applied for the identification and quantification of neurochemicals and their metabolites in biofluids. This article presents an overview of mass spectrometric techniques applied in the detection of neurological substances and their metabolites from biological samples. In addition, the advances of chromatographic methods (LC, GC and CE) coupled with mass spectrometric techniques for analysis of neurochemicals in pharmaceutical and biological samples are also discussed.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

PubMed Central

Jia, Chaolong; Wei, Lili; Wang, Hanning; Yang, Jiulin

2014-01-01

Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described. PMID:25435869

Progressively expanded neural network for automatic material identification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Paheding, Sidike

The science of hyperspectral remote sensing focuses on the exploitation of the spectral signatures of various materials to enhance capabilities including object detection, recognition, and material characterization. Hyperspectral imagery (HSI) has been extensively used for object detection and identification applications since it provides plenty of spectral information to uniquely identify materials by their reflectance spectra. HSI-based object detection algorithms can be generally classified into stochastic and deterministic approaches. Deterministic approaches are comparatively simple to apply since it is usually based on direct spectral similarity such as spectral angles or spectral correlation. In contrast, stochastic algorithms require statistical modeling and estimation for target class and non-target class. Over the decades, many single class object detection methods have been proposed in the literature, however, deterministic multiclass object detection in HSI has not been explored. In this work, we propose a deterministic multiclass object detection scheme, named class-associative spectral fringe-adjusted joint transform correlation. Human brain is capable of simultaneously processing high volumes of multi-modal data received every second of the day. In contrast, a machine sees input data simply as random binary numbers. Although machines are computationally efficient, they are inferior when comes to data abstraction and interpretation. Thus, mimicking the learning strength of human brain has been current trend in artificial intelligence. In this work, we present a biological inspired neural network, named progressively expanded neural network (PEN Net), based on nonlinear transformation of input neurons to a feature space for better pattern differentiation. In PEN Net, discrete fixed excitations are disassembled and scattered in the feature space as a nonlinear line. Each disassembled element on the line corresponds to a pattern with similar features. Unlike the conventional neural network where hidden neurons need to be iteratively adjusted to achieve better accuracy, our proposed PEN Net does not require hidden neurons tuning which achieves better computational efficiency, and it has also shown superior performance in HSI classification tasks compared to the state-of-the-arts. Spectral-spatial features based HSI classification framework has shown stronger strength compared to spectral-only based methods. In our lastly proposed technique, PEN Net is incorporated with multiscale spatial features (i.e., multiscale complete local binary pattern) to perform a spectral-spatial classification of HSI. Several experiments demonstrate excellent performance of our proposed technique compared to the more recent developed approaches.

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

PubMed

Thaikruea, Lakkana; Santidherakul, Sineenart

2018-05-01

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

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.

MULTISPECTRAL IDENTIFICATION OF CHLORINE DIOXIDE DISINFECTION BYPRODUCTS IN DRINKING WATER

EPA Science Inventory

This paper discusses the identification of organic disinfection byproducts (DBPs) at a pilot plant in Evansville, IN, which uses chlorine dioxide as a primary disinfectant. Unconventional multispectral identification techniques (gas chromatography combined with high- and low reso...

MULTISPECTRAL IDENTIFICATION OF CHLORINE DIOXIDE BYPRODUCTS IN DRINKING WATER

EPA Science Inventory

This paper discusses the identification of organic disinfectant byproducts (DNPS) at a pilot plant in Evansville, IN, that uses chlorine dioxide as a primary disinfectant. nconventional multispectral identification techniques (gas chromatography combined with high- and low-resolu...

Anatomical calibration for wearable motion capture systems: Video calibrated anatomical system technique.

PubMed

Bisi, Maria Cristina; Stagni, Rita; Caroselli, Alessio; Cappello, Angelo

2015-08-01

Inertial sensors are becoming widely used for the assessment of human movement in both clinical and research applications, thanks to their usability out of the laboratory. This work aims to propose a method for calibrating anatomical landmark position in the wearable sensor reference frame with an ease to use, portable and low cost device. An off-the-shelf camera, a stick and a pattern, attached to the inertial sensor, compose the device. The proposed technique is referred to as video Calibrated Anatomical System Technique (vCAST). The absolute orientation of a synthetic femur was tracked both using the vCAST together with an inertial sensor and using stereo-photogrammetry as reference. Anatomical landmark calibration showed mean absolute error of 0.6±0.5 mm: these errors are smaller than those affecting the in-vivo identification of anatomical landmarks. The roll, pitch and yaw anatomical frame orientations showed root mean square errors close to the accuracy limit of the wearable sensor used (1°), highlighting the reliability of the proposed technique. In conclusion, the present paper proposes and preliminarily verifies the performance of a method (vCAST) for calibrating anatomical landmark position in the wearable sensor reference frame: the technique is low time consuming, highly portable, easy to implement and usable outside laboratory. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Identification of understory invasive exotic plants with remote sensing in urban forests

NASA Astrophysics Data System (ADS)

Shouse, Michael; Liang, Liang; Fei, Songlin

2013-04-01

Invasive exotic plants (IEP) pose a significant threat to many ecosystems. To effectively manage IEP, it is important to efficiently detect their presences and determine their distribution patterns. Remote sensing has been a useful tool to map IEP but its application is limited in urban forests, which are often the sources and sinks for IEP. In this study, we examined the feasibility and tradeoffs of species level IEP mapping using multiple remote sensing techniques in a highly complex urban forest setting. Bush honeysuckle (Lonicera maackii), a pervasive IEP in eastern North America, was used as our modeling species. Both medium spatial resolution (MSR) and high spatial resolution (HSR) imagery were employed in bush honeysuckle mapping. The importance of spatial scale was also examined using an up-scaling simulation from the HSR object based classification. Analysis using both MSR and HSR imagery provided viable results for IEP distribution mapping in urban forests. Overall mapping accuracy ranged from 89.8% to 94.9% for HSR techniques and from 74.6% to 79.7% for MSR techniques. As anticipated, classification accuracy reduces as pixel size increases. HSR based techniques produced the most desirable results, therefore is preferred for precise management of IEP in heterogeneous environment. However, the use of MSR techniques should not be ruled out given their wide availability and moderate accuracy.

Echocardiographic diagnosis of rare pathological patterns of sinus of Valsalva aneurysm

PubMed Central

Wang, Xinfang; Lü, Qing; He, Lin; Wang, Jing; Wang, Bin; Li, Ling; Yuan, Li; Liu, Jinfeng; Ge, Shuping; Xie, Mingxing

2017-01-01

Objective To evaluate the value and improve the diagnostic accuracy of echocardiography in the diagnosis of a sinus of Valsalva aneurysm (SVA) with rare pathological patterns. Methods Echocardiographic features and surgical findings from 270 Chinese patients with SVA treated in the last 18 years (1995–2013) at the Union Hospital were compared retrospectively; 22 of 270 cases had rare patterns. Results The patients with SVA, a rare origin, a rare extending position, or a rare course accounted for 3.4%, 7.4%, and 0.4% of the 270 cases, respectively. The three most common aneurysmal complications of the patients with rare patterns were severe aortic regurgitation (16), obstruction of the ventricular outflow tract or valvular orifice (3), and conduction disturbance (3). The origin, course, extending position and rupture status of the SVAs determined by echocardiography were entirely consistent with surgical findings in 81.8% of the 22 cases. With the exception of one failed diagnosis of an aneurysmal wall dissection and one misdiagnosis of a descending aortic dissection, the echocardiographic results of SVA complications and associated cardiovascular lesions were also confirmed. Conclusion We could accurately diagnose SVAs with rare pathological patterns by echocardiographic identification of distinguishing features. However, for several conditions, we could not accurately identify the origin or course of the aneurysm or define its relationship to adjacent structures using conventional echocardiography alone. Therefore, we recommend combining conventional echocardiography with different imaging techniques, such as transesophageal echocardiography, three-dimensional echocardiography, computed tomography angiography, and aortic angiography. PMID:28291779

Feature extraction via KPCA for classification of gait patterns.

PubMed

Wu, Jianning; Wang, Jue; Liu, Li

2007-06-01

Automated recognition of gait pattern change is important in medical diagnostics as well as in the early identification of at-risk gait in the elderly. We evaluated the use of Kernel-based Principal Component Analysis (KPCA) to extract more gait features (i.e., to obtain more significant amounts of information about human movement) and thus to improve the classification of gait patterns. 3D gait data of 24 young and 24 elderly participants were acquired using an OPTOTRAK 3020 motion analysis system during normal walking, and a total of 36 gait spatio-temporal and kinematic variables were extracted from the recorded data. KPCA was used first for nonlinear feature extraction to then evaluate its effect on a subsequent classification in combination with learning algorithms such as support vector machines (SVMs). Cross-validation test results indicated that the proposed technique could allow spreading the information about the gait's kinematic structure into more nonlinear principal components, thus providing additional discriminatory information for the improvement of gait classification performance. The feature extraction ability of KPCA was affected slightly with different kernel functions as polynomial and radial basis function. The combination of KPCA and SVM could identify young-elderly gait patterns with 91% accuracy, resulting in a markedly improved performance compared to the combination of PCA and SVM. These results suggest that nonlinear feature extraction by KPCA improves the classification of young-elderly gait patterns, and holds considerable potential for future applications in direct dimensionality reduction and interpretation of multiple gait signals.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

NASA Astrophysics Data System (ADS)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors.

PubMed

Cenek, Martin; Dahl, Spencer K

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Identification of active fault using analysis of derivatives with vertical second based on gravity anomaly data (Case study: Seulimeum fault in Sumatera fault system)

NASA Astrophysics Data System (ADS)

Hududillah, Teuku Hafid; Simanjuntak, Andrean V. H.; Husni, Muhammad

2017-07-01

Gravity is a non-destructive geophysical technique that has numerous application in engineering and environmental field like locating a fault zone. The purpose of this study is to spot the Seulimeum fault system in Iejue, Aceh Besar (Indonesia) by using a gravity technique and correlate the result with geologic map and conjointly to grasp a trend pattern of fault system. An estimation of subsurface geological structure of Seulimeum fault has been done by using gravity field anomaly data. Gravity anomaly data which used in this study is from Topex that is processed up to Free Air Correction. The step in the Next data processing is applying Bouger correction and Terrin Correction to obtain complete Bouger anomaly that is topographically dependent. Subsurface modeling is done using the Gav2DC for windows software. The result showed a low residual gravity value at a north half compared to south a part of study space that indicated a pattern of fault zone. Gravity residual was successfully correlate with the geologic map that show the existence of the Seulimeum fault in this study space. The study of earthquake records can be used for differentiating the active and non active fault elements, this gives an indication that the delineated fault elements are active.

Usefullness of palatal rugae patterns in establishing identity: Preliminary results from Bengaluru city, India

PubMed Central

Indira, AP; Gupta, Manish; David, Maria Priscilla

2012-01-01

Introduction: Palatal rugoscopy is the name given to the study of palatal rugae. Rugae pattern are widely considered to remain unchanged during an individual's lifetime. The rugae pattern has the potential to remain intact by virtue of their internal position in the head when most other anatomical structures are destroyed or burned. Moreover, rugae pattern are considered to be unique similar to fingerprints and are advocated in personal identification. Objectives: The purpose of the study is to establish, individual identity using palatal rugae patterns. Materials and Methods: The study group consisted of 100 study models all of whom were subjects above 14 years old. Martin dos Santos’ classification was followed based on form and position to assess the individuality of rugae pattern. Results: Each individual had different rugae patterns including dizygous twins and the rugae patterns were not symmetrical, both in number and in its distribution. Conclusion: The preliminary study undertaken here shows no two palates are alike in terms of their rugae pattern. Palatal rugae possess unique characteristics as they are absolutely individualistic and therefore, can be used as a personal soft-tissue ‘oral’ print for identification in forensic cases. PMID:23087574

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

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

PubMed

Cheng, Ching-Min; Hwang, Sheue-Ling

2015-03-01

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

Thermal and Chemical Characterization of Composite Materials. MSFC Center Director's Discretionary Fund Final Report, Project No. ED36-18

NASA Technical Reports Server (NTRS)

Stanley, D. C.; Huff, T. L.

2003-01-01

The purpose of this research effort was to: (1) provide a concise and well-defined property profile of current and developing composite materials using thermal and chemical characterization techniques and (2) optimize analytical testing requirements of materials. This effort applied a diverse array of methodologies to ascertain composite material properties. Often, a single method of technique will provide useful, but nonetheless incomplete, information on material composition and/or behavior. To more completely understand and predict material properties, a broad-based analytical approach is required. By developing a database of information comprised of both thermal and chemical properties, material behavior under varying conditions may be better understood. THis is even more important in the aerospace community, where new composite materials and those in the development stage have little reference data. For example, Fourier transform infrared (FTIR) spectroscopy spectral databases available for identification of vapor phase spectra, such as those generated during experiments, generally refer to well-defined chemical compounds. Because this method renders a unique thermal decomposition spectral pattern, even larger, more diverse databases, such as those found in solid and liquid phase FTIR spectroscopy libraries, cannot be used. By combining this and other available methodologies, a database specifically for new materials and materials being developed at Marshall Space Flight Center can be generated . In addition, characterizing materials using this approach will be extremely useful in the verification of materials and identification of anomalies in NASA-wide investigations.

Flight Test Results of a GPS-Based Pitot-Static Calibration Method Using Output-Error Optimization for a Light Twin-Engine Airplane

NASA Technical Reports Server (NTRS)

Martos, Borja; Kiszely, Paul; Foster, John V.

2011-01-01

As part of the NASA Aviation Safety Program (AvSP), a novel pitot-static calibration method was developed to allow rapid in-flight calibration for subscale aircraft while flying within confined test areas. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. This method has been demonstrated in subscale flight tests and has shown small 2- error bounds with significant reduction in test time compared to other methods. The current research was motivated by the desire to further evaluate and develop this method for full-scale aircraft. A goal of this research was to develop an accurate calibration method that enables reductions in test equipment and flight time, thus reducing costs. The approach involved analysis of data acquisition requirements, development of efficient flight patterns, and analysis of pressure error models based on system identification methods. Flight tests were conducted at The University of Tennessee Space Institute (UTSI) utilizing an instrumented Piper Navajo research aircraft. In addition, the UTSI engineering flight simulator was used to investigate test maneuver requirements and handling qualities issues associated with this technique. This paper provides a summary of piloted simulation and flight test results that illustrates the performance and capabilities of the NASA calibration method. Discussion of maneuver requirements and data analysis methods is included as well as recommendations for piloting technique.

Development of a systematic strategy for the global identification and classification of the chemical constituents and metabolites of Kai-Xin-San based on liquid chromatography with quadrupole time-of-flight mass spectrometry combined with multiple data-processing approaches.

PubMed

Wang, Xiaotong; Liu, Jing; Yang, Xiaomei; Zhang, Qian; Zhang, Yiwen; Li, Qing; Bi, Kaishun

2018-03-30

To rapidly identify and classify complicated components and metabolites for traditional Chinese medicines, a liquid chromatography with quadrupole time-of-flight mass spectrometry method combined with multiple data-processing approaches was established. In this process, Kai-Xin-San, a widely used classic traditional Chinese medicine preparation, was chosen as a model prescription. Initially, the fragmentation patterns, diagnostic product ions and neutral loss of each category of compounds were summarized by collision-induced dissociation analysis of representative standards. In vitro, the multiple product ions filtering technique was utilized to identify the chemical constituents for globally covering trace components. With this strategy, 108 constituents were identified, and compounds database was successfully established. In vivo, the prototype compounds were extracted based on the established database, and the neutral loss filtering technique combined with the drug metabolism reaction rules was employed to identify metabolites. Overall, 69 constituents including prototype and metabolites were characterized in rat plasma and nine constituents were firstly characterized in rat brain, which may be the potential active constituents resulting in curative effects by synergistic interaction. In conclusion, this study provides a generally applicable strategy to global metabolite identification for the complicated components in complex matrix and a chemical basis for further pharmacological research of Kai-Xin-San. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ribosomal subunit protein typing using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification and discrimination of Aspergillus species.

PubMed

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Kusuya, Yoko; Takahashi, Hiroki; Yaguchi, Takashi

2017-04-26

Accurate identification of Aspergillus species is a very important subject. Mass spectral fingerprinting using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is generally employed for the rapid identification of fungal isolates. However, the results are based on simple mass spectral pattern-matching, with no peak assignment and no taxonomic input. We propose here a ribosomal subunit protein (RSP) typing technique using MALDI-TOF MS for the identification and discrimination of Aspergillus species. The results are concluded to be phylogenetic in that they reflect the molecular evolution of housekeeping RSPs. The amino acid sequences of RSPs of genome-sequenced strains of Aspergillus species were first verified and compared to compile a reliable biomarker list for the identification of Aspergillus species. In this process, we revealed that many amino acid sequences of RSPs (about 10-60%, depending on strain) registered in the public protein databases needed to be corrected or newly added. The verified RSPs were allocated to RSP types based on their mass. Peak assignments of RSPs of each sample strain as observed by MALDI-TOF MS were then performed to set RSP type profiles, which were then further processed by means of cluster analysis. The resulting dendrogram based on RSP types showed a relatively good concordance with the tree based on β-tubulin gene sequences. RSP typing was able to further discriminate the strains belonging to Aspergillus section Fumigati. The RSP typing method could be applied to identify Aspergillus species, even for species within section Fumigati. The discrimination power of RSP typing appears to be comparable to conventional β-tubulin gene analysis. This method would therefore be suitable for species identification and discrimination at the strain to species level. Because RSP typing can characterize the strains within section Fumigati, this method has potential as a powerful and reliable tool in the field of clinical microbiology.

Studies of the micromorphology of sputtered TiN thin films by autocorrelation techniques

NASA Astrophysics Data System (ADS)

Smagoń, Kamil; Stach, Sebastian; Ţălu, Ştefan; Arman, Ali; Achour, Amine; Luna, Carlos; Ghobadi, Nader; Mardani, Mohsen; Hafezi, Fatemeh; Ahmadpourian, Azin; Ganji, Mohsen; Grayeli Korpi, Alireza

2017-12-01

Autocorrelation techniques are crucial tools for the study of the micromorphology of surfaces: They provide the description of anisotropic properties and the identification of repeated patterns on the surface, facilitating the comparison of samples. In the present investigation, some fundamental concepts of these techniques including the autocorrelation function and autocorrelation length have been reviewed and applied in the study of titanium nitride thin films by atomic force microscopy (AFM). The studied samples were grown on glass substrates by reactive magnetron sputtering at different substrate temperatures (from 25 {}°C to 400 {}°C , and their micromorphology was studied by AFM. The obtained AFM data were analyzed using MountainsMap Premium software obtaining the correlation function, the structure of isotropy and the spatial parameters according to ISO 25178 and EUR 15178N. These studies indicated that the substrate temperature during the deposition process is an important parameter to modify the micromorphology of sputtered TiN thin films and to find optimized surface properties. For instance, the autocorrelation length exhibited a maximum value for the sample prepared at a substrate temperature of 300 {}°C , and the sample obtained at 400 {}°C presented a maximum angle of the direction of the surface structure.

Big Data Analytics for Demand Response: Clustering Over Space and Time

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

Chelmis, Charalampos; Kolte, Jahanvi; Prasanna, Viktor K.

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. Inmore » this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.« less

Detection of protein deposition within latent fingerprints by surface-enhanced Raman spectroscopy imaging

NASA Astrophysics Data System (ADS)

Song, Wei; Mao, Zhu; Liu, Xiaojuan; Lu, Yong; Li, Zhishi; Zhao, Bing; Lu, Lehui

2012-03-01

The detection of metabolites is very important for the estimation of the health of human beings. Latent fingerprint contains many constituents and specific contaminants, which give much information of the individual, such as health status, drug abuse etc. For a long time, many efforts have been focused on visualizing latent fingerprints, but little attention has been paid to the detection of such substances at the same time. In this article, we have devised a versatile approach for the ultra-sensitive detection and identification of specific biomolecules deposited within fingerprints via a large-area SERS imaging technique. The antibody bound to the Raman probe modified silver nanoparticles enables the binding to specific proteins within the fingerprints to afford high-definition SERS images of the fingerprint pattern. The SERS spectra and images of Raman probes indirectly provide chemical information regarding the given proteins. By taking advantage of the high sensitivity and the capability of SERS technique to obtain abundant vibrational signatures of biomolecules, we have successfully detected minute quantities of protein present within a latent fingerprint. This technique provides a versatile and effective model to detect biomarkers within fingerprints for medical diagnostics, criminal investigation and other fields.

Mandarin Chinese Tone Identification in Cochlear Implants: Predictions from Acoustic Models

PubMed Central

Morton, Kenneth D.; Torrione, Peter A.; Throckmorton, Chandra S.; Collins, Leslie M.

2015-01-01

It has been established that current cochlear implants do not supply adequate spectral information for perception of tonal languages. Comprehension of a tonal language, such as Mandarin Chinese, requires recognition of lexical tones. New strategies of cochlear stimulation such as variable stimulation rate and current steering may provide the means of delivering more spectral information and thus may provide the auditory fine structure required for tone recognition. Several cochlear implant signal processing strategies are examined in this study, the continuous interleaved sampling (CIS) algorithm, the frequency amplitude modulation encoding (FAME) algorithm, and the multiple carrier frequency algorithm (MCFA). These strategies provide different types and amounts of spectral information. Pattern recognition techniques can be applied to data from Mandarin Chinese tone recognition tasks using acoustic models as a means of testing the abilities of these algorithms to transmit the changes in fundamental frequency indicative of the four lexical tones. The ability of processed Mandarin Chinese tones to be correctly classified may predict trends in the effectiveness of different signal processing algorithms in cochlear implants. The proposed techniques can predict trends in performance of the signal processing techniques in quiet conditions but fail to do so in noise. PMID:18706497

People Patterns: Fingerprinting. Environmental Module for Use in a Mathematics Laboratory Setting.

ERIC Educational Resources Information Center

Trojan, Arthur; Zastrocky, Mike

This module uses concepts of fingerprinting to illustrate and apply selected mathematical ideas. Specifically, students participate in activities that require pattern recognition, measuring using mm and cm, and identification of similar patterns. Inking of students' prints is done. Teaching suggestions are provided. (MK)

Developmental staging of male murine embryonic gonad by SAGE analysis

PubMed Central

Lee, Tin-Lap; Li, Yunmin; Alba, Diana; Vong, Queenie P.; Wu, Shao-Ming; Baxendale, Vanessa; Rennert, Owen M.; Lau, Yun-Fai Chris; Chan, Wai-Yee

2012-01-01

Despite the identification of key genes such as Sry integral to embryonic gonadal development, the genomic classification and identification of chromosomal activation of this process is still poorly understood. To better understand the genetic regulation of gonadal development, we performed Serial Analysis of Gene Expression (SAGE) to profile the genes and novel transcripts, and an average of 152,000 tags from male embryonic gonads at E10.5 (embryonic day 10.5), E11.5, E12.5, E13.5, E15.5 and E17.5 were analyzed. A total of 275,583 non-singleton tags that do not map to any annotated sequence were identified in the six gonad libraries, and 47,255 tags were mapped to 24,975 annotated sequences, among which 987 sequences were uncharacterized. Utilizing an unsupervised pattern identification technique, we established molecular staging of male gonadal development. Rather than providing a static descriptive analysis, we developed algorithms to cluster the SAGE data and assign SAGE tags to a corresponding chromosomal position; these data are displayed in chromosome graphic format. A prominent increase in global genomic activity from E10.5 to E17.5 was observed. Important chromosomal regions related to the developmental processes were identified and validated based on established mouse models with developmental disorders. These regions may represent markers for early diagnosis for disorders of male gonad development as well as potential treatment targets. PMID:19376482

Floor Covering and Surface Identification for Assistive Mobile Robotic Real-Time Room Localization Application

PubMed Central

Gillham, Michael; Howells, Gareth; Spurgeon, Sarah; McElroy, Ben

2013-01-01

Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms' flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification. PMID:24351647

Qualitative analysis of seized synthetic cannabinoids and synthetic cathinones by gas chromatography triple quadrupole tandem mass spectrometry.

PubMed

Gwak, Seongshin; Arroyo-Mora, Luis E; Almirall, José R

2015-02-01

Designer drugs are analogues or derivatives of illicit drugs with a modification of their chemical structure in order to circumvent current legislation for controlled substances. Designer drugs of abuse have increased dramatically in popularity all over the world for the past couple of years. Currently, the qualitative seized-drug analysis is mainly performed by gas chromatography-electron ionization-mass spectrometry (GC-EI-MS) in which most of these emerging designer drug derivatives are extensively fragmented not presenting a molecular ion in their mass spectra. The absence of molecular ion and/or similar fragmentation pattern among these derivatives may cause the equivocal identification of unknown seized-substances. In this study, the qualitative identification of 34 designer drugs, mainly synthetic cannabinoids and synthetic cathinones, were performed by gas chromatography-triple quadrupole-tandem mass spectrometry with two different ionization techniques, including electron ionization (EI) and chemical ionization (CI) only focusing on qualitative seized-drug analysis, not from the toxicological point of view. The implementation of CI source facilitates the determination of molecular mass and the identification of seized designer drugs. Developed multiple reaction monitoring (MRM) mode may increase sensitivity and selectivity in the analysis of seized designer drugs. In addition, CI mass spectra and MRM mass spectra of these designer drug derivatives can be used as a potential supplemental database along with EI mass spectral database. Copyright © 2014 John Wiley & Sons, Ltd.