ELEMENTAL COMPOSITION OF FRESHLY NUCLEATED PARTICLES

EPA Science Inventory

The main objective of this work is to develop a method for real-time sampling and analysis of individual airborne nanoparticles in the 5 - 20 nm diameter range. The size range covered by this method is much smaller than existing single particle methods for chemical analysis. S...

Fault Tree Analysis Application for Safety and Reliability

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

Many commercial software tools exist for fault tree analysis (FTA), an accepted method for mitigating risk in systems. The method embedded in the tools identifies a root as use in system components, but when software is identified as a root cause, it does not build trees into the software component. No commercial software tools have been built specifically for development and analysis of software fault trees. Research indicates that the methods of FTA could be applied to software, but the method is not practical without automated tool support. With appropriate automated tool support, software fault tree analysis (SFTA) may be a practical technique for identifying the underlying cause of software faults that may lead to critical system failures. We strive to demonstrate that existing commercial tools for FTA can be adapted for use with SFTA, and that applied to a safety-critical system, SFTA can be used to identify serious potential problems long before integrator and system testing.

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

Recent advances in (soil moisture) triple collocation analysis

USDA-ARS?s Scientific Manuscript database

To date, triple collocation (TC) analysis is one of the most important methods for the global scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method....

Numerical computation of orbits and rigorous verification of existence of snapback repellers.

PubMed

Peng, Chen-Chang

2007-03-01

In this paper we show how analysis from numerical computation of orbits can be applied to prove the existence of snapback repellers in discrete dynamical systems. That is, we present a computer-assisted method to prove the existence of a snapback repeller of a specific map. The existence of a snapback repeller of a dynamical system implies that it has chaotic behavior [F. R. Marotto, J. Math. Anal. Appl. 63, 199 (1978)]. The method is applied to the logistic map and the discrete predator-prey system.

Self-adaptive method for high frequency multi-channel analysis of surface wave method

USDA-ARS?s Scientific Manuscript database

When the high frequency multi-channel analysis of surface waves (MASW) method is conducted to explore soil properties in the vadose zone, existing rules for selecting the near offset and spread lengths cannot satisfy the requirements of planar dominant Rayleigh waves for all frequencies of interest ...

An Analysis of Measured Pressure Signatures From Two Theory-Validation Low-Boom Models

NASA Technical Reports Server (NTRS)

Mack, Robert J.

2003-01-01

Two wing/fuselage/nacelle/fin concepts were designed to check the validity and the applicability of sonic-boom minimization theory, sonic-boom analysis methods, and low-boom design methodology in use at the end of the 1980is. Models of these concepts were built, and the pressure signatures they generated were measured in the wind-tunnel. The results of these measurements lead to three conclusions: (1) the existing methods could adequately predict sonic-boom characteristics of wing/fuselage/fin(s) configurations if the equivalent area distributions of each component were smooth and continuous; (2) these methods needed revision so the engine-nacelle volume and the nacelle-wing interference lift disturbances could be accurately predicted; and (3) current nacelle-configuration integration methods had to be updated. With these changes in place, the existing sonic-boom analysis and minimization methods could be effectively applied to supersonic-cruise concepts for acceptable/tolerable sonic-boom overpressures during cruise.

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

PubMed Central

Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

2017-01-01

Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

Why conventional detection methods fail in identifying the existence of contamination events.

PubMed

Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

2016-04-15

Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading. Copyright © 2016 Elsevier Ltd. All rights reserved.

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Interpretive focus groups: a participatory method for interpreting and extending secondary analysis of qualitative data.

PubMed

Redman-MacLaren, Michelle; Mills, Jane; Tommbe, Rachael

2014-01-01

Participatory approaches to qualitative research practice constantly change in response to evolving research environments. Researchers are increasingly encouraged to undertake secondary analysis of qualitative data, despite epistemological and ethical challenges. Interpretive focus groups can be described as a more participative method for groups to analyse qualitative data. To facilitate interpretive focus groups with women in Papua New Guinea to extend analysis of existing qualitative data and co-create new primary data. The purpose of this was to inform a transformational grounded theory and subsequent health promoting action. A two-step approach was used in a grounded theory study about how women experience male circumcision in Papua New Guinea. Participants analysed portions or 'chunks' of existing qualitative data in story circles and built upon this analysis by using the visual research method of storyboarding. New understandings of the data were evoked when women in interpretive focus groups analysed the data 'chunks'. Interpretive focus groups encouraged women to share their personal experiences about male circumcision. The visual method of storyboarding enabled women to draw pictures to represent their experiences. This provided an additional focus for whole-of-group discussions about the research topic. Interpretive focus groups offer opportunity to enhance trustworthiness of findings when researchers undertake secondary analysis of qualitative data. The co-analysis of existing data and co-generation of new data between research participants and researchers informed an emergent transformational grounded theory and subsequent health promoting action.

Interpretive focus groups: a participatory method for interpreting and extending secondary analysis of qualitative data

PubMed Central

Redman-MacLaren, Michelle; Mills, Jane; Tommbe, Rachael

2014-01-01

Background Participatory approaches to qualitative research practice constantly change in response to evolving research environments. Researchers are increasingly encouraged to undertake secondary analysis of qualitative data, despite epistemological and ethical challenges. Interpretive focus groups can be described as a more participative method for groups to analyse qualitative data. Objective To facilitate interpretive focus groups with women in Papua New Guinea to extend analysis of existing qualitative data and co-create new primary data. The purpose of this was to inform a transformational grounded theory and subsequent health promoting action. Design A two-step approach was used in a grounded theory study about how women experience male circumcision in Papua New Guinea. Participants analysed portions or ‘chunks’ of existing qualitative data in story circles and built upon this analysis by using the visual research method of storyboarding. Results New understandings of the data were evoked when women in interpretive focus groups analysed the data ‘chunks’. Interpretive focus groups encouraged women to share their personal experiences about male circumcision. The visual method of storyboarding enabled women to draw pictures to represent their experiences. This provided an additional focus for whole-of-group discussions about the research topic. Conclusions Interpretive focus groups offer opportunity to enhance trustworthiness of findings when researchers undertake secondary analysis of qualitative data. The co-analysis of existing data and co-generation of new data between research participants and researchers informed an emergent transformational grounded theory and subsequent health promoting action. PMID:25138532

Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation.

PubMed

Yang, Jian-Yi; Peng, Zhen-Ling; Yu, Zu-Guo; Zhang, Rui-Jie; Anh, Vo; Wang, Desheng

2009-04-21

In this paper, we intend to predict protein structural classes (alpha, beta, alpha+beta, or alpha/beta) for low-homology data sets. Two data sets were used widely, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence homology being 40% and 25%, respectively. We propose to decompose the chaos game representation of proteins into two kinds of time series. Then, a novel and powerful nonlinear analysis technique, recurrence quantification analysis (RQA), is applied to analyze these time series. For a given protein sequence, a total of 16 characteristic parameters can be calculated with RQA, which are treated as feature representation of protein sequences. Based on such feature representation, the structural class for each protein is predicted with Fisher's linear discriminant algorithm. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies with step-by-step procedure are 65.8% and 64.2% for 1189 and 25PDB data sets, respectively. With one-against-others procedure used widely, we compare our method with five other existing methods. Especially, the overall accuracies of our method are 6.3% and 4.1% higher for the two data sets, respectively. Furthermore, only 16 parameters are used in our method, which is less than that used by other methods. This suggests that the current method may play a complementary role to the existing methods and is promising to perform the prediction of protein structural classes.

Phylogenetic rooting using minimal ancestor deviation.

PubMed

Tria, Fernando Domingues Kümmel; Landan, Giddy; Dagan, Tal

2017-06-19

Ancestor-descendent relations play a cardinal role in evolutionary theory. Those relations are determined by rooting phylogenetic trees. Existing rooting methods are hampered by evolutionary rate heterogeneity or the unavailability of auxiliary phylogenetic information. Here we present a rooting approach, the minimal ancestor deviation (MAD) method, which accommodates heterotachy by using all pairwise topological and metric information in unrooted trees. We demonstrate the performance of the method, in comparison to existing rooting methods, by the analysis of phylogenies from eukaryotes and prokaryotes. MAD correctly recovers the known root of eukaryotes and uncovers evidence for the origin of cyanobacteria in the ocean. MAD is more robust and consistent than existing methods, provides measures of the root inference quality and is applicable to any tree with branch lengths.

Utility-preserving anonymization for health data publishing.

PubMed

Lee, Hyukki; Kim, Soohyung; Kim, Jong Wook; Chung, Yon Dohn

2017-07-11

Publishing raw electronic health records (EHRs) may be considered as a breach of the privacy of individuals because they usually contain sensitive information. A common practice for the privacy-preserving data publishing is to anonymize the data before publishing, and thus satisfy privacy models such as k-anonymity. Among various anonymization techniques, generalization is the most commonly used in medical/health data processing. Generalization inevitably causes information loss, and thus, various methods have been proposed to reduce information loss. However, existing generalization-based data anonymization methods cannot avoid excessive information loss and preserve data utility. We propose a utility-preserving anonymization for privacy preserving data publishing (PPDP). To preserve data utility, the proposed method comprises three parts: (1) utility-preserving model, (2) counterfeit record insertion, (3) catalog of the counterfeit records. We also propose an anonymization algorithm using the proposed method. Our anonymization algorithm applies full-domain generalization algorithm. We evaluate our method in comparison with existence method on two aspects, information loss measured through various quality metrics and error rate of analysis result. With all different types of quality metrics, our proposed method show the lower information loss than the existing method. In the real-world EHRs analysis, analysis results show small portion of error between the anonymized data through the proposed method and original data. We propose a new utility-preserving anonymization method and an anonymization algorithm using the proposed method. Through experiments on various datasets, we show that the utility of EHRs anonymized by the proposed method is significantly better than those anonymized by previous approaches.

Participatory Design Methods for C2 Systems (Proceedings/Presentation)

DTIC Science & Technology

2006-01-01

Cognitive Task Analysis (CTA) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION 18. NUMBER 19a. NAME OF RESPONSIBLE PERSON OF ABSTRACT OF PAGES Janet E. Miller...systems to support cognitive work such as is accomplished in a network-centric -environment. Cognitive task analysis (CTA) methods are used to...of cognitive task analysis methodologies exist (Schraagen et al., 2000). However, many of these methods are skeptically viewed by a domain’s

A Cost-Effectiveness/Benefit Analysis Model for Postsecondary Vocational Programs. Technical Report.

ERIC Educational Resources Information Center

Kim, Jin Eun

A cost-effectiveness/benefit analysis is defined as a technique for measuring the outputs of existing and new programs in relation to their specified program objectives, against the costs of those programs. In terms of its specific use, the technique is conceptualized as a systems analysis method, an evaluation method, and a planning tool for…

Methods for the Joint Meta-Analysis of Multiple Tests

ERIC Educational Resources Information Center

Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H.

2014-01-01

Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…

A simple method for plasma total vitamin C analysis suitable for routine clinical laboratory use.

PubMed

Robitaille, Line; Hoffer, L John

2016-04-21

In-hospital hypovitaminosis C is highly prevalent but almost completely unrecognized. Medical awareness of this potentially important disorder is hindered by the inability of most hospital laboratories to determine plasma vitamin C concentrations. The availability of a simple, reliable method for analyzing plasma vitamin C could increase opportunities for routine plasma vitamin C analysis in clinical medicine. Plasma vitamin C can be analyzed by high performance liquid chromatography (HPLC) with electrochemical (EC) or ultraviolet (UV) light detection. We modified existing UV-HPLC methods for plasma total vitamin C analysis (the sum of ascorbic and dehydroascorbic acid) to develop a simple, constant-low-pH sample reduction procedure followed by isocratic reverse-phase HPLC separation using a purely aqueous low-pH non-buffered mobile phase. Although EC-HPLC is widely recommended over UV-HPLC for plasma total vitamin C analysis, the two methods have never been directly compared. We formally compared the simplified UV-HPLC method with EC-HPLC in 80 consecutive clinical samples. The simplified UV-HPLC method was less expensive, easier to set up, required fewer reagents and no pH adjustments, and demonstrated greater sample stability than many existing methods for plasma vitamin C analysis. When compared with the gold-standard EC-HPLC method in 80 consecutive clinical samples exhibiting a wide range of plasma vitamin C concentrations, it performed equivalently. The easy set up, simplicity and sensitivity of the plasma vitamin C analysis method described here could make it practical in a normally equipped hospital laboratory. Unlike any prior UV-HPLC method for plasma total vitamin C analysis, it was rigorously compared with the gold-standard EC-HPLC method and performed equivalently. Adoption of this method could increase the availability of plasma vitamin C analysis in clinical medicine.

Selection of remedial alternatives for mine sites: a multicriteria decision analysis approach.

PubMed

Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon

2013-04-15

The selection of remedial alternatives for mine sites is a complex task because it involves multiple criteria and often with conflicting objectives. However, an existing framework used to select remedial alternatives lacks multicriteria decision analysis (MCDA) aids and does not consider uncertainty in the selection of alternatives. The objective of this paper is to improve the existing framework by introducing deterministic and probabilistic MCDA methods. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods have been implemented in this study. The MCDA analysis involves processing inputs to the PROMETHEE methods that are identifying the alternatives, defining the criteria, defining the criteria weights using analytical hierarchical process (AHP), defining the probability distribution of criteria weights, and conducting Monte Carlo Simulation (MCS); running the PROMETHEE methods using these inputs; and conducting a sensitivity analysis. A case study was presented to demonstrate the improved framework at a mine site. The results showed that the improved framework provides a reliable way of selecting remedial alternatives as well as quantifying the impact of different criteria on selecting alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.

Rail Inspection Systems Analysis and Technology Survey

DOT National Transportation Integrated Search

1977-09-01

The study was undertaken to identify existing rail inspection system capabilities and methods which might be used to improve these capabilities. Task I was a study to quantify existing inspection parameters and Task II was a cost effectiveness study ...

Sociometric Indicators of Leadership: An Exploratory Analysis

DTIC Science & Technology

2018-01-01

streamline existing observational protocols and assessment methods . This research provides an initial test of sociometric badges in the context of the U.S...understand, the requirements of the mission. Traditional research and assessment methods focusing on leader and follower interactions require direct...based methods of social network analysis. Novel Measures of Leadership Building on these findings and earlier research , it is apparent that

Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

PubMed

De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

2017-06-01

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

A simplified method in comparison with comprehensive interaction incremental dynamic analysis to assess seismic performance of jacket-type offshore platforms

NASA Astrophysics Data System (ADS)

Zolfaghari, M. R.; Ajamy, A.; Asgarian, B.

2015-12-01

The primary goal of seismic reassessment procedures in oil platform codes is to determine the reliability of a platform under extreme earthquake loading. Therefore, in this paper, a simplified method is proposed to assess seismic performance of existing jacket-type offshore platforms (JTOP) in regions ranging from near-elastic to global collapse. The simplified method curve exploits well agreement between static pushover (SPO) curve and the entire summarized interaction incremental dynamic analysis (CI-IDA) curve of the platform. Although the CI-IDA method offers better understanding and better modelling of the phenomenon, it is a time-consuming and challenging task. To overcome the challenges, the simplified procedure, a fast and accurate approach, is introduced based on SPO analysis. Then, an existing JTOP in the Persian Gulf is presented to illustrate the procedure, and finally a comparison is made between the simplified method and CI-IDA results. The simplified method is very informative and practical for current engineering purposes. It is able to predict seismic performance elasticity to global dynamic instability with reasonable accuracy and little computational effort.

Application of the probabilistic approximate analysis method to a turbopump blade analysis. [for Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Thacker, B. H.; Mcclung, R. C.; Millwater, H. R.

1990-01-01

An eigenvalue analysis of a typical space propulsion system turbopump blade is presented using an approximate probabilistic analysis methodology. The methodology was developed originally to investigate the feasibility of computing probabilistic structural response using closed-form approximate models. This paper extends the methodology to structures for which simple closed-form solutions do not exist. The finite element method will be used for this demonstration, but the concepts apply to any numerical method. The results agree with detailed analysis results and indicate the usefulness of using a probabilistic approximate analysis in determining efficient solution strategies.

Analysis of 2-alkylcyclobutanones in cashew nut, nutmeg, apricot kernel, and pine nut samples: re-evaluating the uniqueness of 2-alkylcyclobutanones for irradiated food identification.

PubMed

Leung, Elvis M K; Tang, Phyllis N Y; Ye, Yuran; Chan, Wan

2013-10-16

2-Alkylcyclobutanones (2-ACBs) have long been considered as unique radiolytic products that can be used as indicators for irradiated food identification. A recent report on the natural existence of 2-ACB in non-irradiated nutmeg and cashew nut samples aroused worldwide concern because it contradicts the general belief that 2-ACBs are specific to irradiated food. The goal of this study is to test the natural existence of 2-ACBs in nut samples using our newly developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method with enhanced analytical sensitivity and selectivity ( Ye , Y. ; Liu , H. ; Horvatovich , P. ; Chan , W. Liquid chromatography-electrospray ionization tandem mass spectrometric analysis of 2-alkylcyclobutanones in irradiated chicken by precolumn derivatization with hydroxylamine . J. Agric. Food Chem. 2013 , 61 , 5758 - 5763 ). The validated method was applied to identify 2-dodecylcyclobutanone (2-DCB) and 2-tetradecylcyclobutanone (2-TCB) in nutmeg, cashew nut, pine nut, and apricot kernel samples (n = 22) of different origins. Our study reveals that 2-DCB and 2-TCB either do not exist naturally or exist at concentrations below the detection limit of the existing method. Thus, 2-DCB and 2-TCB are still valid to be used as biomarkers for identifying irradiated food.

The QAP weighted network analysis method and its application in international services trade

NASA Astrophysics Data System (ADS)

Xu, Helian; Cheng, Long

2016-04-01

Based on QAP (Quadratic Assignment Procedure) correlation and complex network theory, this paper puts forward a new method named QAP Weighted Network Analysis Method. The core idea of the method is to analyze influences among relations in a social or economic group by building a QAP weighted network of networks of relations. In the QAP weighted network, a node depicts a relation and an undirect edge exists between any pair of nodes if there is significant correlation between relations. As an application of the QAP weighted network, we study international services trade by using the QAP weighted network, in which nodes depict 10 kinds of services trade relations. After the analysis of international services trade by QAP weighted network, and by using distance indicators, hierarchy tree and minimum spanning tree, the conclusion shows that: Firstly, significant correlation exists in all services trade, and the development of any one service trade will stimulate the other nine. Secondly, as the economic globalization goes deeper, correlations in all services trade have been strengthened continually, and clustering effects exist in those services trade. Thirdly, transportation services trade, computer and information services trade and communication services trade have the most influence and are at the core in all services trade.

Forestry sector analysis for developing countries: issues and methods.

Treesearch

R.W. Haynes

1993-01-01

A satellite meeting of the 10th Forestry World Congress focused on the methods used for forest sector analysis and their applications in both developed and developing countries. The results of that meeting are summarized, and a general approach for forest sector modeling is proposed. The approach includes models derived from the existing...

Techniques for Forecasting Air Passenger Traffic

NASA Technical Reports Server (NTRS)

Taneja, N.

1972-01-01

The basic techniques of forecasting the air passenger traffic are outlined. These techniques can be broadly classified into four categories: judgmental, time-series analysis, market analysis and analytical. The differences between these methods exist, in part, due to the degree of formalization of the forecasting procedure. Emphasis is placed on describing the analytical method.

Assessment of the transportation route of oversize and excessive loads in relation to the load-bearing capacity of existing bridges

NASA Astrophysics Data System (ADS)

Doležel, Jiří; Novák, Drahomír; Petrů, Jan

2017-09-01

Transportation routes of oversize and excessive loads are currently planned in relation to ensure the transit of a vehicle through critical points on the road. Critical points are level-intersection of roads, bridges etc. This article presents a comprehensive procedure to determine a reliability and a load-bearing capacity level of the existing bridges on highways and roads using the advanced methods of reliability analysis based on simulation techniques of Monte Carlo type in combination with nonlinear finite element method analysis. The safety index is considered as a main criterion of the reliability level of the existing construction structures and the index is described in current structural design standards, e.g. ISO and Eurocode. An example of a single-span slab bridge made of precast prestressed concrete girders of the 60 year current time and its load bearing capacity is set for the ultimate limit state and serviceability limit state. The structure’s design load capacity was estimated by the full probability nonlinear MKP analysis using a simulation technique Latin Hypercube Sampling (LHS). Load-bearing capacity values based on a fully probabilistic analysis are compared with the load-bearing capacity levels which were estimated by deterministic methods of a critical section of the most loaded girders.

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Structure and information in spatial segregation

PubMed Central

2017-01-01

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software. PMID:29078323

Structure and information in spatial segregation.

PubMed

Chodrow, Philip S

2017-10-31

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software. Published under the PNAS license.

A Novel Method for Block Size Forensics Based on Morphological Operations

NASA Astrophysics Data System (ADS)

Luo, Weiqi; Huang, Jiwu; Qiu, Guoping

Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2×2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average.

LITERATURE REVIEW OF REMEDIATION METHODS FOR PCBS IN BUILDINGS

EPA Science Inventory

This literature review contains a description and analysis of existing methods for management of PCBs in construction materials. Information on the strengths and limitations, efficacy, cost, and byproducts of each remediation method is presented, where available. The report is ba...

Human error mitigation initiative (HEMI) : summary report.

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

Stevens, Susan M.; Ramos, M. Victoria; Wenner, Caren A.

2004-11-01

Despite continuing efforts to apply existing hazard analysis methods and comply with requirements, human errors persist across the nuclear weapons complex. Due to a number of factors, current retroactive and proactive methods to understand and minimize human error are highly subjective, inconsistent in numerous dimensions, and are cumbersome to characterize as thorough. An alternative and proposed method begins with leveraging historical data to understand what the systemic issues are and where resources need to be brought to bear proactively to minimize the risk of future occurrences. An illustrative analysis was performed using existing incident databases specific to Pantex weapons operationsmore » indicating systemic issues associated with operating procedures that undergo notably less development rigor relative to other task elements such as tooling and process flow. Future recommended steps to improve the objectivity, consistency, and thoroughness of hazard analysis and mitigation were delineated.« less

COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples

PubMed Central

Yamagata, Koichi; Yamanishi, Ayako; Kokubu, Chikara; Takeda, Junji; Sese, Jun

2016-01-01

An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis. PMID:26833260

Adapting Human Reliability Analysis from Nuclear Power to Oil and Gas Applications

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

Boring, Ronald Laurids

2015-09-01

ABSTRACT: Human reliability analysis (HRA), as currently used in risk assessments, largely derives its methods and guidance from application in the nuclear energy domain. While there are many similarities be-tween nuclear energy and other safety critical domains such as oil and gas, there remain clear differences. This paper provides an overview of HRA state of the practice in nuclear energy and then describes areas where refinements to the methods may be necessary to capture the operational context of oil and gas. Many key distinctions important to nuclear energy HRA such as Level 1 vs. Level 2 analysis may prove insignifi-cantmore » for oil and gas applications. On the other hand, existing HRA methods may not be sensitive enough to factors like the extensive use of digital controls in oil and gas. This paper provides an overview of these con-siderations to assist in the adaptation of existing nuclear-centered HRA methods to the petroleum sector.« less

BDA: A novel method for identifying defects in body-centered cubic crystals.

PubMed

Möller, Johannes J; Bitzek, Erik

2016-01-01

The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain low-index surfaces. For body-centered cubic (bcc) metals, on the other hand, a robust way to identify such defects is currently not easily available. We therefore introduce a new method for analyzing atomistic configurations of bcc metals, the BCC Defect Analysis (BDA). It uses existing structure analysis algorithms and combines their results to uniquely distinguish between typical defects in bcc metals. In essence, the BDA method offers the following features:•Identification of typical defect structures in bcc metals.•Reduction of erroneously identified defects by iterative comparison to the defects in the atom's neighborhood.•Availability as ready-to-use Python script for the widespread visualization tool OVITO [http://ovito.org].

Structure identification methods for atomistic simulations of crystalline materials

DOE PAGES

Stukowski, Alexander

2012-05-28

Here, we discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as common neighbor analysis (CNA), centrosymmetry analysis, bond angle analysis, bond order analysis and Voronoi analysis. In addition we propose a simple extension to the CNA method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.

Information retrieval for nonstationary data records

NASA Technical Reports Server (NTRS)

Su, M. Y.

1971-01-01

A review and a critical discussion are made on the existing methods for analysis of nonstationary time series, and a new algorithm for splitting nonstationary time series, is applied to the analysis of sunspot data.

Analysis of Bonded Joints Between the Facesheet and Flange of Corrugated Composite Panels

NASA Technical Reports Server (NTRS)

Yarrington, Phillip W.; Collier, Craig S.; Bednarcyk, Brett A.

2008-01-01

This paper outlines a method for the stress analysis of bonded composite corrugated panel facesheet to flange joints. The method relies on the existing HyperSizer Joints software, which analyzes the bonded joint, along with a beam analogy model that provides the necessary boundary loading conditions to the joint analysis. The method is capable of predicting the full multiaxial stress and strain fields within the flange to facesheet joint and thus can determine ply-level margins and evaluate delamination. Results comparing the method to NASTRAN finite element model stress fields are provided illustrating the accuracy of the method.

Influence analysis in quantitative trait loci detection.

PubMed

Dou, Xiaoling; Kuriki, Satoshi; Maeno, Akiteru; Takada, Toyoyuki; Shiroishi, Toshihiko

2014-07-01

This paper presents systematic methods for the detection of influential individuals that affect the log odds (LOD) score curve. We derive general formulas of influence functions for profile likelihoods and introduce them into two standard quantitative trait locus detection methods-the interval mapping method and single marker analysis. Besides influence analysis on specific LOD scores, we also develop influence analysis methods on the shape of the LOD score curves. A simulation-based method is proposed to assess the significance of the influence of the individuals. These methods are shown useful in the influence analysis of a real dataset of an experimental population from an F2 mouse cross. By receiver operating characteristic analysis, we confirm that the proposed methods show better performance than existing diagnostics. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pathway analysis with next-generation sequencing data.

PubMed

Zhao, Jinying; Zhu, Yun; Boerwinkle, Eric; Xiong, Momiao

2015-04-01

Although pathway analysis methods have been developed and successfully applied to association studies of common variants, the statistical methods for pathway-based association analysis of rare variants have not been well developed. Many investigators observed highly inflated false-positive rates and low power in pathway-based tests of association of rare variants. The inflated false-positive rates and low true-positive rates of the current methods are mainly due to their lack of ability to account for gametic phase disequilibrium. To overcome these serious limitations, we develop a novel statistic that is based on the smoothed functional principal component analysis (SFPCA) for pathway association tests with next-generation sequencing data. The developed statistic has the ability to capture position-level variant information and account for gametic phase disequilibrium. By intensive simulations, we demonstrate that the SFPCA-based statistic for testing pathway association with either rare or common or both rare and common variants has the correct type 1 error rates. Also the power of the SFPCA-based statistic and 22 additional existing statistics are evaluated. We found that the SFPCA-based statistic has a much higher power than other existing statistics in all the scenarios considered. To further evaluate its performance, the SFPCA-based statistic is applied to pathway analysis of exome sequencing data in the early-onset myocardial infarction (EOMI) project. We identify three pathways significantly associated with EOMI after the Bonferroni correction. In addition, our preliminary results show that the SFPCA-based statistic has much smaller P-values to identify pathway association than other existing methods.

Determining the Number of Components from the Matrix of Partial Correlations

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

A method is presented for determining the number of components to retain in a principal components or image components analysis which utilizes a matrix of partial correlations. Advantages and uses of the method are discussed and a comparison of the proposed method with existing methods is presented. (JKS)

Hybrid Tracking Algorithm Improvements and Cluster Analysis Methods.

DTIC Science & Technology

1982-02-26

UPGMA ), and Ward’s method. Ling’s papers describe a (k,r) clustering method. Each of these methods have individual characteristics which make them...Reference 7), UPGMA is probably the most frequently used clustering strategy. UPGMA tries to group new points into an existing cluster by using an

More than Method?: A Discussion of Paradigm Differences within Mixed Methods Research

ERIC Educational Resources Information Center

Harrits, Gitte Sommer

2011-01-01

This article challenges the idea that mixed methods research (MMR) constitutes a coherent research paradigm and explores how different research paradigms exist within MMR. Tracing paradigmatic differences at the level of methods, ontology, and epistemology, two MMR strategies are discussed: nested analysis, recently presented by the American…

The coordinate-based meta-analysis of neuroimaging data.

PubMed

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E; Johnson, Timothy D

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research.

The coordinate-based meta-analysis of neuroimaging data

PubMed Central

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E.; Johnson, Timothy D.

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research. PMID:29545671

An Abstraction-Based Data Model for Information Retrieval

NASA Astrophysics Data System (ADS)

McAllister, Richard A.; Angryk, Rafal A.

Language ontologies provide an avenue for automated lexical analysis that may be used to supplement existing information retrieval methods. This paper presents a method of information retrieval that takes advantage of WordNet, a lexical database, to generate paths of abstraction, and uses them as the basis for an inverted index structure to be used in the retrieval of documents from an indexed corpus. We present this method as a entree to a line of research on using ontologies to perform word-sense disambiguation and improve the precision of existing information retrieval techniques.

Draft Environmental Impact Statement: Peacekeeper Rail Garrison Program

DTIC Science & Technology

1988-06-01

2-13 3.0 ENVIRONMENTAL ANALYSIS METHODS ................................ 3-1 3.1 Methods for Assessing Nationwide Impacts...3-2 3.1.1 Methods for Assessing National Economic Impacts ........... 3-2 3.1.2 Methods for Assessing Railroad Network...3.2.4 Methods for Assessing Existing and Future Baseline Conditions .......................................... 3-6 3.2.5 Methods for Assessing

Prototype of a computer method for designing and analyzing heating, ventilating and air conditioning proportional, electronic control systems

NASA Astrophysics Data System (ADS)

Barlow, Steven J.

1986-09-01

The Air Force needs a better method of designing new and retrofit heating, ventilating and air conditioning (HVAC) control systems. Air Force engineers currently use manual design/predict/verify procedures taught at the Air Force Institute of Technology, School of Civil Engineering, HVAC Control Systems course. These existing manual procedures are iterative and time-consuming. The objectives of this research were to: (1) Locate and, if necessary, modify an existing computer-based method for designing and analyzing HVAC control systems that is compatible with the HVAC Control Systems manual procedures, or (2) Develop a new computer-based method of designing and analyzing HVAC control systems that is compatible with the existing manual procedures. Five existing computer packages were investigated in accordance with the first objective: MODSIM (for modular simulation), HVACSIM (for HVAC simulation), TRNSYS (for transient system simulation), BLAST (for building load and system thermodynamics) and Elite Building Energy Analysis Program. None were found to be compatible or adaptable to the existing manual procedures, and consequently, a prototype of a new computer method was developed in accordance with the second research objective.

Analytical Fuselage and Wing Weight Estimation of Transport Aircraft

NASA Technical Reports Server (NTRS)

Chambers, Mark C.; Ardema, Mark D.; Patron, Anthony P.; Hahn, Andrew S.; Miura, Hirokazu; Moore, Mark D.

1996-01-01

A method of estimating the load-bearing fuselage weight and wing weight of transport aircraft based on fundamental structural principles has been developed. This method of weight estimation represents a compromise between the rapid assessment of component weight using empirical methods based on actual weights of existing aircraft, and detailed, but time-consuming, analysis using the finite element method. The method was applied to eight existing subsonic transports for validation and correlation. Integration of the resulting computer program, PDCYL, has been made into the weights-calculating module of the AirCraft SYNThesis (ACSYNT) computer program. ACSYNT has traditionally used only empirical weight estimation methods; PDCYL adds to ACSYNT a rapid, accurate means of assessing the fuselage and wing weights of unconventional aircraft. PDCYL also allows flexibility in the choice of structural concept, as well as a direct means of determining the impact of advanced materials on structural weight. Using statistical analysis techniques, relations between the load-bearing fuselage and wing weights calculated by PDCYL and corresponding actual weights were determined.

Development of Advanced Methods of Structural and Trajectory Analysis for Transport Aircraft

NASA Technical Reports Server (NTRS)

Ardema, Mark D.

1996-01-01

In this report the author describes: (1) development of advanced methods of structural weight estimation, and (2) development of advanced methods of flight path optimization. A method of estimating the load-bearing fuselage weight and wing weight of transport aircraft based on fundamental structural principles has been developed. This method of weight estimation represents a compromise between the rapid assessment of component weight using empirical methods based on actual weights of existing aircraft and detailed, but time-consuming, analysis using the finite element method. The method was applied to eight existing subsonic transports for validation and correlation. Integration of the resulting computer program, PDCYL, has been made into the weights-calculating module of the AirCraft SYNThesis (ACSYNT) computer program. ACSYNT bas traditionally used only empirical weight estimation methods; PDCYL adds to ACSYNT a rapid, accurate means of assessing the fuselage and wing weights of unconventional aircraft. PDCYL also allows flexibility in the choice of structural concept, as well as a direct means of determining the impact of advanced materials on structural weight.

Heuristics to Facilitate Understanding of Discriminant Analysis.

ERIC Educational Resources Information Center

Van Epps, Pamela D.

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Generalized disequilibrium test for association in qualitative traits incorporating imprinting effects based on extended pedigrees.

PubMed

Li, Jian-Long; Wang, Peng; Fung, Wing Kam; Zhou, Ji-Yuan

2017-10-16

For dichotomous traits, the generalized disequilibrium test with the moment estimate of the variance (GDT-ME) is a powerful family-based association method. Genomic imprinting is an important epigenetic phenomenon and currently, there has been increasing interest of incorporating imprinting to improve the test power of association analysis. However, GDT-ME does not take imprinting effects into account, and it has not been investigated whether it can be used for association analysis when the effects indeed exist. In this article, based on a novel decomposition of the genotype score according to the paternal or maternal source of the allele, we propose the generalized disequilibrium test with imprinting (GDTI) for complete pedigrees without any missing genotypes. Then, we extend GDTI and GDT-ME to accommodate incomplete pedigrees with some pedigrees having missing genotypes, by using a Monte Carlo (MC) sampling and estimation scheme to infer missing genotypes given available genotypes in each pedigree, denoted by MCGDTI and MCGDT-ME, respectively. The proposed GDTI and MCGDTI methods evaluate the differences of the paternal as well as maternal allele scores for all discordant relative pairs in a pedigree, including beyond first-degree relative pairs. Advantages of the proposed GDTI and MCGDTI test statistics over existing methods are demonstrated by simulation studies under various simulation settings and by application to the rheumatoid arthritis dataset. Simulation results show that the proposed tests control the size well under the null hypothesis of no association, and outperform the existing methods under various imprinting effect models. The existing GDT-ME and the proposed MCGDT-ME can be used to test for association even when imprinting effects exist. For the application to the rheumatoid arthritis data, compared to the existing methods, MCGDTI identifies more loci statistically significantly associated with the disease. Under complete and incomplete imprinting effect models, our proposed GDTI and MCGDTI methods, by considering the information on imprinting effects and all discordant relative pairs within each pedigree, outperform all the existing test statistics and MCGDTI can recapture much of the missing information. Therefore, MCGDTI is recommended in practice.

Analysis and optimization of cross-immunity epidemic model on complex networks

NASA Astrophysics Data System (ADS)

Chen, Chao; Zhang, Hao; Wu, Yin-Hua; Feng, Wei-Qiang; Zhang, Jian

2015-09-01

There are various infectious diseases in real world, and these diseases often spread on a network of population and compete for the limited hosts. Cross-immunity is an important disease competing pattern, which has attracted the attention of many researchers. In this paper, we discovered an important conclusion for two cross-immunity epidemics on a network. When the infectious ability of the second epidemic takes a fixed value, the infectious ability of the first epidemic has an optimal value which minimizes the sum of the infection sizes of the two epidemics. We also proposed a simple mathematical analysis method for the infection size of the second epidemic using the cavity method. The proposed method and conclusion are verified by simulation results. Minor inaccuracies of the existing mathematical methods for the infection size of the second epidemic are also found and discussed in experiments, which have not been noticed in existing research.

Vessel extraction in retinal images using automatic thresholding and Gabor Wavelet.

PubMed

Ali, Aziah; Hussain, Aini; Wan Zaki, Wan Mimi Diyana

2017-07-01

Retinal image analysis has been widely used for early detection and diagnosis of multiple systemic diseases. Accurate vessel extraction in retinal image is a crucial step towards a fully automated diagnosis system. This work affords an efficient unsupervised method for extracting blood vessels from retinal images by combining existing Gabor Wavelet (GW) method with automatic thresholding. Green channel image is extracted from color retinal image and used to produce Gabor feature image using GW. Both green channel image and Gabor feature image undergo vessel-enhancement step in order to highlight blood vessels. Next, the two vessel-enhanced images are transformed to binary images using automatic thresholding before combined to produce the final vessel output. Combining the images results in significant improvement of blood vessel extraction performance compared to using individual image. Effectiveness of the proposed method was proven via comparative analysis with existing methods validated using publicly available database, DRIVE.

Existence of the sugar-bisulfite adducts and its inhibiting effect on degradation of monosaccharide in acid system.

PubMed

Shi, Yan

2014-02-01

Degradation of fermentable monosaccharides is one of the primary concerns for acid prehydrolysis of lignocellulosic biomass. Recently, in our research on degradation of pure monosaccharides in aqueous SO₂ solution by gas chromatography (GC) analysis, we found that detected yield was not actual yield of each monosaccharide due to the existence of sugar-bisulfite adducts, and a new method was developed by ourselves which led to accurate detection of recovery yield of each monosaccharide in aqueous SO₂ solution by GC analysis. By the use of this method, degradation of each monosaccharide in aqueous SO₂ was investigated and results showed that sugar-bisulfite adducts have different inhibiting effect on degradation of each monosaccharide in aqueous SO₂ because of their different stability. In addition, NMR testing also demonstrated possible existence of reaction between conjugated based HSO₃(-) and aldehyde group of sugars in acid system.

NEAT: an efficient network enrichment analysis test.

PubMed

Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C

2016-09-05

Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat ).

Comparative Analysis of Various Single-tone Frequency Estimation Techniques in High-order Instantaneous Moments Based Phase Estimation Method

NASA Astrophysics Data System (ADS)

Rajshekhar, G.; Gorthi, Sai Siva; Rastogi, Pramod

2010-04-01

For phase estimation in digital holographic interferometry, a high-order instantaneous moments (HIM) based method was recently developed which relies on piecewise polynomial approximation of phase and subsequent evaluation of the polynomial coefficients using the HIM operator. A crucial step in the method is mapping the polynomial coefficient estimation to single-tone frequency determination for which various techniques exist. The paper presents a comparative analysis of the performance of the HIM operator based method in using different single-tone frequency estimation techniques for phase estimation. The analysis is supplemented by simulation results.

Looking for trees in the forest: summary tree from posterior samples

PubMed Central

2013-01-01

Background Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist for selecting a representative topology for a set of unrooted trees, few exist for assigning branch lengths to a fixed topology, and even fewer for simultaneously setting the topology and branch lengths. However, there is very little research into locating a good representative for a set of rooted time trees like the ones obtained from a BEAST analysis. Results We empirically compare new and known methods for generating a summary tree. Some new methods are motivated by mathematical constructions such as tree metrics, while the rest employ tree concepts which work well in practice. These use more of the posterior than existing methods, which discard information not directly mapped to the chosen topology. Using results from a large number of simulations we assess the quality of a summary tree, measuring (a) how well it explains the sequence data under the model and (b) how close it is to the “truth”, i.e to the tree used to generate the sequences. Conclusions Our simulations indicate that no single method is “best”. Methods producing good divergence time estimates have poor branch lengths and lower model fit, and vice versa. Using the results presented here, a user can choose the appropriate method based on the purpose of the summary tree. PMID:24093883

Looking for trees in the forest: summary tree from posterior samples.

PubMed

Heled, Joseph; Bouckaert, Remco R

2013-10-04

Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist for selecting a representative topology for a set of unrooted trees, few exist for assigning branch lengths to a fixed topology, and even fewer for simultaneously setting the topology and branch lengths. However, there is very little research into locating a good representative for a set of rooted time trees like the ones obtained from a BEAST analysis. We empirically compare new and known methods for generating a summary tree. Some new methods are motivated by mathematical constructions such as tree metrics, while the rest employ tree concepts which work well in practice. These use more of the posterior than existing methods, which discard information not directly mapped to the chosen topology. Using results from a large number of simulations we assess the quality of a summary tree, measuring (a) how well it explains the sequence data under the model and (b) how close it is to the "truth", i.e to the tree used to generate the sequences. Our simulations indicate that no single method is "best". Methods producing good divergence time estimates have poor branch lengths and lower model fit, and vice versa. Using the results presented here, a user can choose the appropriate method based on the purpose of the summary tree.

Traffic Flow Density Distribution Based on FEM

NASA Astrophysics Data System (ADS)

Ma, Jing; Cui, Jianming

In analysis of normal traffic flow, it usually uses the static or dynamic model to numerical analyze based on fluid mechanics. However, in such handling process, the problem of massive modeling and data handling exist, and the accuracy is not high. Finite Element Method (FEM) is a production which is developed from the combination of a modern mathematics, mathematics and computer technology, and it has been widely applied in various domain such as engineering. Based on existing theory of traffic flow, ITS and the development of FEM, a simulation theory of the FEM that solves the problems existing in traffic flow is put forward. Based on this theory, using the existing Finite Element Analysis (FEA) software, the traffic flow is simulated analyzed with fluid mechanics and the dynamics. Massive data processing problem of manually modeling and numerical analysis is solved, and the authenticity of simulation is enhanced.

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2010-06-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 80's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The r-largest annual maxima method provides more reliable predictions of the extreme values especially for small return periods (<100 years). Finally, the study statistically proves the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

Bias Characterization in Probabilistic Genotype Data and Improved Signal Detection with Multiple Imputation

PubMed Central

Palmer, Cameron; Pe’er, Itsik

2016-01-01

Missing data are an unavoidable component of modern statistical genetics. Different array or sequencing technologies cover different single nucleotide polymorphisms (SNPs), leading to a complicated mosaic pattern of missingness where both individual genotypes and entire SNPs are sporadically absent. Such missing data patterns cannot be ignored without introducing bias, yet cannot be inferred exclusively from nonmissing data. In genome-wide association studies, the accepted solution to missingness is to impute missing data using external reference haplotypes. The resulting probabilistic genotypes may be analyzed in the place of genotype calls. A general-purpose paradigm, called Multiple Imputation (MI), is known to model uncertainty in many contexts, yet it is not widely used in association studies. Here, we undertake a systematic evaluation of existing imputed data analysis methods and MI. We characterize biases related to uncertainty in association studies, and find that bias is introduced both at the imputation level, when imputation algorithms generate inconsistent genotype probabilities, and at the association level, when analysis methods inadequately model genotype uncertainty. We find that MI performs at least as well as existing methods or in some cases much better, and provides a straightforward paradigm for adapting existing genotype association methods to uncertain data. PMID:27310603

Analysis of Existing Guidelines for the Systematic Planning Process of Clinical Registries.

PubMed

Löpprich, Martin; Knaup, Petra

2016-01-01

Clinical registries are a powerful method to observe the clinical practice and natural disease history. In contrast to clinical trials, where guidelines and standardized methods exist and are mandatory, only a few initiatives have published methodological guidelines for clinical registries. The objective of this paper was to review these guidelines and systematically assess their completeness, usability and feasibility according to a SWOT analysis. The results show that each guideline has its own strengths and weaknesses. While one supports the systematic planning process, the other discusses clinical registries in great detail. However, the feasibility was mostly limited and the special requirements of clinical registries, their flexible, expandable and adaptable technological structure was not addressed consistently.

Buckling Analysis of Single and Multi Delamination In Composite Beam Using Finite Element Method

NASA Astrophysics Data System (ADS)

Simanjorang, Hans Charles; Syamsudin, Hendri; Giri Suada, Muhammad

2018-04-01

Delamination is one type of imperfection in structure which found usually in the composite structure. Delamination may exist due to some factors namely in-service condition where the foreign objects hit the composite structure and creates inner defect and poor manufacturing that causes the initial imperfections. Composite structure is susceptible to the compressive loading. Compressive loading leads the instability phenomenon in the composite structure called buckling. The existence of delamination inside of the structure will cause reduction in buckling strength. This paper will explain the effect of delamination location to the buckling strength. The analysis will use the one-dimensional modelling approach using two- dimensional finite element method.

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Probabilistic classification method on multi wavelength chromatographic data for photosynthetic pigments identification

NASA Astrophysics Data System (ADS)

Prilianti, K. R.; Setiawan, Y.; Indriatmoko, Adhiwibawa, M. A. S.; Limantara, L.; Brotosudarmo, T. H. P.

2014-02-01

Environmental and health problem caused by artificial colorant encourages the increasing usage of natural colorant nowadays. Natural colorant refers to the colorant that is derivate from living organism or minerals. Extensive research topic has been done to exploit these colorant, but recent data shows that only 0.5% of the wide range of plant pigments in the earth has been exhaustively used. Hence development of the pigment characterization technique is an important consideration. High-performance liquid chromatography (HPLC) is a widely used technique to separate pigments in a mixture and identify it. In former HPLC fingerprinting, pigment characterization was based on a single chromatogram from a fixed wavelength (one dimensional) and discard the information contained at other wavelength. Therefore, two dimensional fingerprints have been proposed to use more chromatographic information. Unfortunately this method leads to the data processing problem due to the size of its data matrix. The other common problem in the chromatogram analysis is the subjectivity of the researcher in recognizing the chromatogram pattern. In this research an automated analysis method of the multi wavelength chromatographic data was proposed. Principal component analysis (PCA) was used to compress the data matrix and Maximum Likelihood (ML) classification was applied to identify the chromatogram pattern of the existing pigments in a mixture. Three photosynthetic pigments were selected to show the proposed method. Those pigments are β-carotene, fucoxanthin and zeaxanthin. The result suggests that the method could well inform the existence of the pigments in a particular mixture. A simple computer application was also developed to facilitate real time analysis. Input of the application is multi wavelength chromatographic data matrix and the output is information about the existence of the three pigments.

Analysis of Classes of Superlinear Semipositone Problems with Nonlinear Boundary Conditions

NASA Astrophysics Data System (ADS)

Morris, Quinn A.

We study positive radial solutions for classes of steady state reaction diffusion problems on the exterior of a ball with both Dirichlet and nonlinear boundary conditions. We consider p-Laplacian problems (p > 1) with reaction terms which are superlinear at infinity and semipositone. In the case p = 2, using variational methods, we establish the existence of a solution, and via detailed analysis of the Green's function, we prove the positivity of the solution. In the case p ≠ 2, we again use variational methods to establish the existence of a solution, but the positivity of the solution is achieved via sophisticated a priori estimates. In the case p ≠ 2, the Green's function analysis is no longer available. Our results significantly enhance the literature on superlinear semipositone problems. Finally, we provide algorithms for the numerical generation of exact bifurcation curves for one-dimensional problems. In the autonomous case, we extend and analyze a quadrature method, and using nonlinear solvers in Mathematica, generate bifurcation curves. In the nonautonomous case, we employ shooting methods in Mathematica to generate bifurcation curves.

The Filament Sensor for Near Real-Time Detection of Cytoskeletal Fiber Structures

PubMed Central

Eltzner, Benjamin; Wollnik, Carina; Gottschlich, Carsten; Huckemann, Stephan; Rehfeldt, Florian

2015-01-01

A reliable extraction of filament data from microscopic images is of high interest in the analysis of acto-myosin structures as early morphological markers in mechanically guided differentiation of human mesenchymal stem cells and the understanding of the underlying fiber arrangement processes. In this paper, we propose the filament sensor (FS), a fast and robust processing sequence which detects and records location, orientation, length, and width for each single filament of an image, and thus allows for the above described analysis. The extraction of these features has previously not been possible with existing methods. We evaluate the performance of the proposed FS in terms of accuracy and speed in comparison to three existing methods with respect to their limited output. Further, we provide a benchmark dataset of real cell images along with filaments manually marked by a human expert as well as simulated benchmark images. The FS clearly outperforms existing methods in terms of computational runtime and filament extraction accuracy. The implementation of the FS and the benchmark database are available as open source. PMID:25996921

COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples.

PubMed

Yamagata, Koichi; Yamanishi, Ayako; Kokubu, Chikara; Takeda, Junji; Sese, Jun

2016-05-05

An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Laser Spot Tracking Based on Modified Circular Hough Transform and Motion Pattern Analysis

PubMed Central

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-01-01

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas–Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development. PMID:25350502

Laser spot tracking based on modified circular Hough transform and motion pattern analysis.

PubMed

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-10-27

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas-Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development.

Examining, Documenting, and Modeling the Problem Space of a Variable Domain

DTIC Science & Technology

2002-06-14

Feature-Oriented Domain Analysis ( FODA ) .............................................................................................. 9...development of this proposed process include: Feature-Oriented Domain Analysis ( FODA ) [3,4], Organization Domain Modeling (ODM) [2,5,6], Family-Oriented...configuration knowledge using generators [2]. 8 Existing Methods of Domain Engineering Feature-Oriented Domain Analysis ( FODA ) FODA is a domain

Numerical simulation on dimension decrease for annular casing of one centrifugal boiler circulation pump

NASA Astrophysics Data System (ADS)

Fan, Y. Z.; Zuo, Z. G.; Liu, S. H.; Wu, Y. L.; Sha, Y. J.

2012-11-01

Primary formulation derivation indicates that the dimension of one existing centrifugal boiler circulation pump casing is too large. As great manufacture cost can be saved by dimension decrease, a numerical simulation research is developed in this paper on dimension decrease for annular casing of this pump with a specific speed equaling to 189, which aims at finding an appropriately smaller dimension of the casing while hydraulic performance and strength performance will hardly be changed according to the requirements of the cooperative company. The research object is one existing centrifugal pump with a diffuser and a semi-spherical annular casing, working as the boiler circulation pump for (ultra) supercritical units in power plants. Dimension decrease, the modification method, is achieved by decreasing the existing casing's internal radius (marked as "Ri0") while keeping the wall thickness. The research analysis is based on primary formulation derivation, CFD (Computational Fluid Dynamics) simulation and FEM (Finite Element Method) simulation. Primary formulation derivation estimates that a design casing's internal radius should be less than 0.75 Ri0. CFD analysis indicates that smaller casing with 0.75 Ri0 has a worse hydraulic performance when working at large flow rates and a better hydraulic performance when working at small flow rates. In consideration of hydraulic performance and dimension decrease, an appropriate casing's internal radius is determined, which equals to 0.875 Ri0. FEM analysis then confirms that modified pump casing has nearly the same strength performance as the existing pump casing. It is concluded that dimension decrease can be an economical method as well as a practical method for large pumps in engineering fields.

An online database for plant image analysis software tools.

PubMed

Lobet, Guillaume; Draye, Xavier; Périlleux, Claire

2013-10-09

Recent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research. We present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions. The plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.

Efficient option valuation of single and double barrier options

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Milev, Mariyan; Koleva-Petkova, Dessislava; Vladev, Veselin

2017-12-01

In this paper we present an implementation of pricing algorithm for single and double barrier options using Mellin transformation with Maximum Entropy Inversion and its suitability for real-world applications. A detailed analysis of the applied algorithm is accompanied by implementation in C++ that is then compared to existing solutions in terms of efficiency and computational power. We then compare the applied method with existing closed-form solutions and well known methods of pricing barrier options that are based on finite differences.

Analysis of regional brain mitochondrial bioenergetics and susceptibility to mitochondrial inhibition utilizing a microplate based system

PubMed Central

Sauerbeck, Andrew; Pandya, Jignesh; Singh, Indrapal; Bittman, Kevin; Readnower, Ryan; Bing, Guoying; Sullivan, Patrick

2012-01-01

The analysis of mitochondrial bioenergetic function typically has required 50–100 μg of protein per sample and at least 15 min per run when utilizing a Clark-type oxygen electrode. In the present work we describe a method utilizing the Seahorse Biosciences XF24 Flux Analyzer for measuring mitochondrial oxygen consumption simultaneously from multiple samples and utilizing only 5 μg of protein per sample. Utilizing this method we have investigated whether regionally based differences exist in mitochondria isolated from the cortex, striatum, hippocampus, and cerebellum. Analysis of basal mitochondrial bioenergetics revealed that minimal differences exist between the cortex, striatum, and hippocampus. However, the cerebellum exhibited significantly slower basal rates of Complex I and Complex II dependent oxygen consumption (p < 0.05). Mitochondrial inhibitors affected enzyme activity proportionally across all samples tested and only small differences existed in the effect of inhibitors on oxygen consumption. Investigation of the effect of rotenone administration on Complex I dependent oxygen consumption revealed that exposure to 10 pM rotenone led to a clear time dependent decrease in oxygen consumption beginning 12 min after administration (p < 0.05). These studies show that the utilization of this microplate based method for analysis of mitochondrial bioenergetics is effective at quantifying oxygen consumption simultaneously from multiple samples. Additionally, these studies indicate that minimal regional differences exist in mitochondria isolated from the cortex, striatum, or hippocampus. Furthermore, utilization of the mitochondrial inhibitors suggests that previous work indicating regionally specific deficits following systemic mitochondrial toxin exposure may not be the result of differences in the individual mitochondria from the affected regions. PMID:21402103

A collocation-shooting method for solving fractional boundary value problems

NASA Astrophysics Data System (ADS)

Al-Mdallal, Qasem M.; Syam, Muhammed I.; Anwar, M. N.

2010-12-01

In this paper, we discuss the numerical solution of special class of fractional boundary value problems of order 2. The method of solution is based on a conjugating collocation and spline analysis combined with shooting method. A theoretical analysis about the existence and uniqueness of exact solution for the present class is proven. Two examples involving Bagley-Torvik equation subject to boundary conditions are also presented; numerical results illustrate the accuracy of the present scheme.

Survey of Existing and Promising New Methods of Surface Preparation

DTIC Science & Technology

1982-04-01

and abroad, a description and analysis are givev of applicable methods including: • Equipment employing recycled steel shot and grit. • wet blast...requirements that must be met by these methods. 23. Barrillom, P., “Preservation of Materials in the Marine Environment— Analysis of Replies TO The Enquiry on...conditions, can hydrolyze or give sulfuric acid, causing renewed corrosion. Wet blasting or the use of high pressure water jets appears to be useful in

Investigation of 2‐stage meta‐analysis methods for joint longitudinal and time‐to‐event data through simulation and real data application

PubMed Central

Tudur Smith, Catrin; Gueyffier, François; Kolamunnage‐Dona, Ruwanthi

2017-01-01

Background Joint modelling of longitudinal and time‐to‐event data is often preferred over separate longitudinal or time‐to‐event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time‐to‐event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta‐analysis of joint model estimates from multiple studies. Methods We propose a 2‐stage method for meta‐analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta‐analyses of separate longitudinal or time‐to‐event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Results Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta‐analytic setting where association exists between the longitudinal and time‐to‐event outcomes. Conclusions Where evidence of association between longitudinal and time‐to‐event outcomes exists, results from joint models over standalone analyses should be pooled in 2‐stage meta‐analyses. PMID:29250814

A SINDA thermal model using CAD/CAE technologies

NASA Technical Reports Server (NTRS)

Rodriguez, Jose A.; Spencer, Steve

1992-01-01

The approach to thermal analysis described by this paper is a technique that incorporates Computer Aided Design (CAD) and Computer Aided Engineering (CAE) to develop a thermal model that has the advantages of Finite Element Methods (FEM) without abandoning the unique advantages of Finite Difference Methods (FDM) in the analysis of thermal systems. The incorporation of existing CAD geometry, the powerful use of a pre and post processor and the ability to do interdisciplinary analysis, will be described.

Python package for model STructure ANalysis (pySTAN)

NASA Astrophysics Data System (ADS)

Van Hoey, Stijn; van der Kwast, Johannes; Nopens, Ingmar; Seuntjens, Piet

2013-04-01

The selection and identification of a suitable hydrological model structure is more than fitting parameters of a model structure to reproduce a measured hydrograph. The procedure is highly dependent on various criteria, i.e. the modelling objective, the characteristics and the scale of the system under investigation as well as the available data. Rigorous analysis of the candidate model structures is needed to support and objectify the selection of the most appropriate structure for a specific case (or eventually justify the use of a proposed ensemble of structures). This holds both in the situation of choosing between a limited set of different structures as well as in the framework of flexible model structures with interchangeable components. Many different methods to evaluate and analyse model structures exist. This leads to a sprawl of available methods, all characterized by different assumptions, changing conditions of application and various code implementations. Methods typically focus on optimization, sensitivity analysis or uncertainty analysis, with backgrounds from optimization, machine-learning or statistics amongst others. These methods also need an evaluation metric (objective function) to compare the model outcome with some observed data. However, for current methods described in literature, implementations are not always transparent and reproducible (if available at all). No standard procedures exist to share code and the popularity (and amount of applications) of the methods is sometimes more dependent on the availability than the merits of the method. Moreover, new implementations of existing methods are difficult to verify and the different theoretical backgrounds make it difficult for environmental scientists to decide about the usefulness of a specific method. A common and open framework with a large set of methods can support users in deciding about the most appropriate method. Hence, it enables to simultaneously apply and compare different methods on a fair basis. We developed and present pySTAN (python framework for STructure Analysis), a python package containing a set of functions for model structure evaluation to provide the analysis of (hydrological) model structures. A selected set of algorithms for optimization, uncertainty and sensitivity analysis is currently available, together with a set of evaluation (objective) functions and input distributions to sample from. The methods are implemented model-independent and the python language provides the wrapper functions to apply administer external model codes. Different objective functions can be considered simultaneously with both statistical metrics and more hydrology specific metrics. By using so-called reStructuredText (sphinx documentation generator) and Python documentation strings (docstrings), the generation of manual pages is semi-automated and a specific environment is available to enhance both the readability and transparency of the code. It thereby enables a larger group of users to apply and compare these methods and to extend the functionalities.

Prediction and Validation of Disease Genes Using HeteSim Scores.

PubMed

Zeng, Xiangxiang; Liao, Yuanlu; Liu, Yuansheng; Zou, Quan

2017-01-01

Deciphering the gene disease association is an important goal in biomedical research. In this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate disease genes. Two methods based on heterogeneous networks constructed using protein-protein interaction, gene-phenotype associations, and phenotype-phenotype similarity, are presented. In HeteSim_MultiPath (HSMP), HeteSim scores of different paths are combined with a constant that dampens the contributions of longer paths. In HeteSim_SVM (HSSVM), HeteSim scores are combined with a machine learning method. The 3-fold experiments show that our non-machine learning method HSMP performs better than the existing non-machine learning methods, our machine learning method HSSVM obtains similar accuracy with the best existing machine learning method CATAPULT. From the analysis of the top 10 predicted genes for different diseases, we found that HSSVM avoid the disadvantage of the existing machine learning based methods, which always predict similar genes for different diseases. The data sets and Matlab code for the two methods are freely available for download at http://lab.malab.cn/data/HeteSim/index.jsp.

Computerized Spiral Analysis Using the iPad

PubMed Central

Sisti, Jonathan A.; Christophe, Brandon; Seville, Audrey Rakovich; Garton, Andrew L.A.; Gupta, Vivek P.; Bandin, Alexander J.; Yu, Qiping; Pullman, Seth L.

2017-01-01

Background Digital analysis of writing and drawing has become a valuable research and clinical tool for the study of upper limb motor dysfunction in patients with essential tremor, Parkinson’s disease, dystonia, and related disorders. We developed a validated method of computerized spiral analysis of hand-drawn Archimedean spirals that provides insight into movement dynamics beyond subjective visual assessment using a Wacom graphics tablet. While the Wacom tablet method provides robust data, more widely available mobile technology platforms exist. New Method We introduce a novel adaptation of the Wacom-based method for the collection of hand-drawn kinematic data using an Apple iPad. This iPad-based system is stand-alone, easy-to-use, can capture drawing data with either a finger or capacitive stylus, is precise, and potentially ubiquitous. Results The iPad-based system acquires position and time data that is fully compatible with our original spiral analysis program. All of the important indices including degree of severity, speed, presence of tremor, tremor amplitude, tremor frequency, variability of pressure, and tightness are calculated from the digital spiral data, which the application is able to transmit. Comparison with Existing Method While the iPad method is limited by current touch screen technology, it does collect data with acceptable congruence compared to the current Wacom-based method while providing the advantages of accessibility and ease of use. Conclusions The iPad is capable of capturing precise digital spiral data for analysis of motor dysfunction while also providing a convenient, easy-to-use modality in clinics and potentially at home. PMID:27840146

Graphical methods for the sensitivity analysis in discriminant analysis

DOE PAGES

Kim, Youngil; Anderson-Cook, Christine M.; Dae-Heung, Jang

2015-09-30

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretative compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern ofmore » the change.« less

Conditions for the existence of Kelvin-Helmholtz instability in a CME

NASA Astrophysics Data System (ADS)

Jatenco-Pereira, Vera; Páez, Andrés; Falceta-Gonçalves, Diego; Opher, Merav

2015-08-01

The presence of Kelvin-Helmholtz instability (KHI) in the sheaths of the Coronal Mass Ejection (CME) has motivated several analysis and simulations to test their existence. In the present work we assume the existence of the KHI and propose a method to identify the regions where it is possible the development of KHI for a CME propagating in a fast and slow solar wind. We build functions for the velocities, densities and magnetic fields for two different zones of interaction between the solar wind and a CME. Based on the theory of magnetic KHI proposed by Chandrasekhar (1961) and we found conditions for the existence of KHI in the CME sheaths. Using this method it is possible to determine the range of parameters, in particular CME magnetic fields in which the KHI could exist. We conclude that KHI may exist in the two CME flanks and it is perceived that the zone with boundaries with the slow solar wind is more appropriated for the formation of the KHI.

Recommended Practice for Securing Control System Modems

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

James R. Davidson; Jason L. Wright

2008-01-01

This paper addresses an often overlooked “backdoor” into critical infrastructure control systems created by modem connections. A modem’s connection to the public telephone system is similar to a corporate network connection to the Internet. By tracing typical attack paths into the system, this paper provides the reader with an analysis of the problem and then guides the reader through methods to evaluate existing modem security. Following the analysis, a series of methods for securing modems is provided. These methods are correlated to well-known networking security methods.

Pathways to Lean Software Development: An Analysis of Effective Methods of Change

ERIC Educational Resources Information Center

Hanson, Richard D.

2014-01-01

This qualitative Delphi study explored the challenges that exist in delivering software on time, within budget, and with the original scope identified. The literature review identified many attempts over the past several decades to reform the methods used to develop software. These attempts found that the classical waterfall method, which is…

Conformal mapping for multiple terminals

PubMed Central

Wang, Weimin; Ma, Wenying; Wang, Qiang; Ren, Hao

2016-01-01

Conformal mapping is an important mathematical tool that can be used to solve various physical and engineering problems in many fields, including electrostatics, fluid mechanics, classical mechanics, and transformation optics. It is an accurate and convenient way to solve problems involving two terminals. However, when faced with problems involving three or more terminals, which are more common in practical applications, existing conformal mapping methods apply assumptions or approximations. A general exact method does not exist for a structure with an arbitrary number of terminals. This study presents a conformal mapping method for multiple terminals. Through an accurate analysis of boundary conditions, additional terminals or boundaries are folded into the inner part of a mapped region. The method is applied to several typical situations, and the calculation process is described for two examples of an electrostatic actuator with three electrodes and of a light beam splitter with three ports. Compared with previously reported results, the solutions for the two examples based on our method are more precise and general. The proposed method is helpful in promoting the application of conformal mapping in analysis of practical problems. PMID:27830746

Generalized Appended Product Indicator Procedure for Nonlinear Structural Equation Analysis.

ERIC Educational Resources Information Center

Wall, Melanie M.; Amemiya, Yasuo

2001-01-01

Considers the estimation of polynomial structural models and shows a limitation of an existing method. Introduces a new procedure, the generalized appended product indicator procedure, for nonlinear structural equation analysis. Addresses statistical issues associated with the procedure through simulation. (SLD)

Component-based subspace linear discriminant analysis method for face recognition with one training sample

NASA Astrophysics Data System (ADS)

Huang, Jian; Yuen, Pong C.; Chen, Wen-Sheng; Lai, J. H.

2005-05-01

Many face recognition algorithms/systems have been developed in the last decade and excellent performances have also been reported when there is a sufficient number of representative training samples. In many real-life applications such as passport identification, only one well-controlled frontal sample image is available for training. Under this situation, the performance of existing algorithms will degrade dramatically or may not even be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples with lower dimension than the original image, but also consider the face detection localization error while training. After that, we propose a subspace LDA method, which is tailor-made for a small number of training samples, for the local feature projection to maximize the discrimination power. Theoretical analysis and experiment results show that our proposed subspace LDA is efficient and overcomes the limitations in existing LDA methods. Finally, we combine the contributions of each local component bunch with a weighted combination scheme to draw the recognition decision. A FERET database is used for evaluating the proposed method and results are encouraging.

What Touched Your Heart? Collaborative Story Analysis Emerging From an Apsáalooke Cultural Context.

PubMed

Hallett, John; Held, Suzanne; McCormick, Alma Knows His Gun; Simonds, Vanessa; Real Bird, Sloane; Martin, Christine; Simpson, Colleen; Schure, Mark; Turnsplenty, Nicole; Trottier, Coleen

2017-07-01

Community-based participatory research and decolonizing research share some recommendations for best practices for conducting research. One commonality is partnering on all stages of research; co-developing methods of data analysis is one stage with a deficit of partnering examples. We present a novel community-based and developed method for analyzing qualitative data within an Indigenous health study and explain incompatibilities of existing methods for our purposes and community needs. We describe how we explored available literature, received counsel from community Elders and experts in the field, and collaboratively developed a data analysis method consonant with community values. The method of analysis, in which interview/story remained intact, team members received story, made meaning through discussion, and generated a conceptual framework to inform intervention development, is detailed. We offer the development process and method as an example for researchers working with communities who want to keep stories intact during qualitative data analysis.

Least Principal Components Analysis (LPCA): An Alternative to Regression Analysis.

ERIC Educational Resources Information Center

Olson, Jeffery E.

Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…

PROOF OF CONCEPT FOR A HUMAN RELIABILITY ANALYSIS METHOD FOR HEURISTIC USABILITY EVALUATION OF SOFTWARE

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

Ronald L. Boring; David I. Gertman; Jeffrey C. Joe

2005-09-01

An ongoing issue within human-computer interaction (HCI) is the need for simplified or “discount” methods. The current economic slowdown has necessitated innovative methods that are results driven and cost effective. The myriad methods of design and usability are currently being cost-justified, and new techniques are actively being explored that meet current budgets and needs. Recent efforts in human reliability analysis (HRA) are highlighted by the ten-year development of the Standardized Plant Analysis Risk HRA (SPAR-H) method. The SPAR-H method has been used primarily for determining humancentered risk at nuclear power plants. The SPAR-H method, however, shares task analysis underpinnings withmore » HCI. Despite this methodological overlap, there is currently no HRA approach deployed in heuristic usability evaluation. This paper presents an extension of the existing SPAR-H method to be used as part of heuristic usability evaluation in HCI.« less

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Colombano, Silvano; Scargle, Jeff; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2003-01-01

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

Evaluating Gene Set Enrichment Analysis Via a Hybrid Data Model

PubMed Central

Hua, Jianping; Bittner, Michael L.; Dougherty, Edward R.

2014-01-01

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance. PMID:24558298

Lipid Adjustment for Chemical Exposures: Accounting for Concomitant Variables

PubMed Central

Li, Daniel; Longnecker, Matthew P.; Dunson, David B.

2013-01-01

Background Some environmental chemical exposures are lipophilic and need to be adjusted by serum lipid levels before data analyses. There are currently various strategies that attempt to account for this problem, but all have their drawbacks. To address such concerns, we propose a new method that uses Box-Cox transformations and a simple Bayesian hierarchical model to adjust for lipophilic chemical exposures. Methods We compared our Box-Cox method to existing methods. We ran simulation studies in which increasing levels of lipid-adjusted chemical exposure did and did not increase the odds of having a disease, and we looked at both single-exposure and multiple-exposures cases. We also analyzed an epidemiology dataset that examined the effects of various chemical exposures on the risk of birth defects. Results Compared with existing methods, our Box-Cox method produced unbiased estimates, good coverage, similar power, and lower type-I error rates. This was the case in both single- and multiple-exposure simulation studies. Results from analysis of the birth-defect data differed from results using existing methods. Conclusion Our Box-Cox method is a novel and intuitive way to account for the lipophilic nature of certain chemical exposures. It addresses some of the problems with existing methods, is easily extendable to multiple exposures, and can be used in any analyses that involve concomitant variables. PMID:24051893

Approximations to the distribution of a test statistic in covariance structure analysis: A comprehensive study.

PubMed

Wu, Hao

2018-05-01

In structural equation modelling (SEM), a robust adjustment to the test statistic or to its reference distribution is needed when its null distribution deviates from a χ 2 distribution, which usually arises when data do not follow a multivariate normal distribution. Unfortunately, existing studies on this issue typically focus on only a few methods and neglect the majority of alternative methods in statistics. Existing simulation studies typically consider only non-normal distributions of data that either satisfy asymptotic robustness or lead to an asymptotic scaled χ 2 distribution. In this work we conduct a comprehensive study that involves both typical methods in SEM and less well-known methods from the statistics literature. We also propose the use of several novel non-normal data distributions that are qualitatively different from the non-normal distributions widely used in existing studies. We found that several under-studied methods give the best performance under specific conditions, but the Satorra-Bentler method remains the most viable method for most situations. © 2017 The British Psychological Society.

A method of power analysis based on piecewise discrete Fourier transform

NASA Astrophysics Data System (ADS)

Xin, Miaomiao; Zhang, Yanchi; Xie, Da

2018-04-01

The paper analyzes the existing feature extraction methods. The characteristics of discrete Fourier transform and piecewise aggregation approximation are analyzed. Combining with the advantages of the two methods, a new piecewise discrete Fourier transform is proposed. And the method is used to analyze the lighting power of a large customer in this paper. The time series feature maps of four different cases are compared with the original data, discrete Fourier transform, piecewise aggregation approximation and piecewise discrete Fourier transform. This new method can reflect both the overall trend of electricity change and its internal changes in electrical analysis.

A seismic analysis for masonry constructions: The different schematization methods of masonry walls

NASA Astrophysics Data System (ADS)

Olivito, Renato. S.; Codispoti, Rosamaria; Scuro, Carmelo

2017-11-01

Seismic analysis of masonry structures is usually analyzed through the use of structural calculation software based on equivalent frames method or to macro-elements method. In these approaches, the masonry walls are divided into vertical elements, masonry walls, and horizontal elements, so-called spandrel elements, interconnected by rigid nodes. The aim of this work is to make a critical comparison between different schematization methods of masonry wall underlining the structural importance of the spandrel elements. In order to implement the methods, two different structural calculation software were used and an existing masonry building has been examined.

Methodology for processing pressure traces used as inputs for combustion analyses in diesel engines

NASA Astrophysics Data System (ADS)

Rašić, Davor; Vihar, Rok; Žvar Baškovič, Urban; Katrašnik, Tomaž

2017-05-01

This study proposes a novel methodology for designing an optimum equiripple finite impulse response (FIR) filter for processing in-cylinder pressure traces of a diesel internal combustion engine, which serve as inputs for high-precision combustion analyses. The proposed automated workflow is based on an innovative approach of determining the transition band frequencies and optimum filter order. The methodology is based on discrete Fourier transform analysis, which is the first step to estimate the location of the pass-band and stop-band frequencies. The second step uses short-time Fourier transform analysis to refine the estimated aforementioned frequencies. These pass-band and stop-band frequencies are further used to determine the most appropriate FIR filter order. The most widely used existing methods for estimating the FIR filter order are not effective in suppressing the oscillations in the rate- of-heat-release (ROHR) trace, thus hindering the accuracy of combustion analyses. To address this problem, an innovative method for determining the order of an FIR filter is proposed in this study. This method is based on the minimization of the integral of normalized signal-to-noise differences between the stop-band frequency and the Nyquist frequency. Developed filters were validated using spectral analysis and calculation of the ROHR. The validation results showed that the filters designed using the proposed innovative method were superior compared with those using the existing methods for all analyzed cases. Highlights • Pressure traces of a diesel engine were processed by finite impulse response (FIR) filters with different orders • Transition band frequencies were determined with an innovative method based on discrete Fourier transform and short-time Fourier transform • Spectral analyses showed deficiencies of existing methods in determining the FIR filter order • A new method of determining the FIR filter order for processing pressure traces was proposed • The efficiency of the new method was demonstrated by spectral analyses and calculations of rate-of-heat-release traces

Overview of U.S. EPA Office of Research and Development’s planned research on analysis and monitoring in fresh and coastal/estuarine environments

EPA Science Inventory

This research plan has several objectives: 1) develop new or refine existing chemical, instrument and biological methods for the detection of cyanobacteria and their toxins; test such methods in field studies in both HAB and non HAB environments; 2) determine the method(s) that c...

Design sensitivity analysis using EAL. Part 1: Conventional design parameters

NASA Technical Reports Server (NTRS)

Dopker, B.; Choi, Kyung K.; Lee, J.

1986-01-01

A numerical implementation of design sensitivity analysis of builtup structures is presented, using the versatility and convenience of an existing finite element structural analysis code and its database management system. The finite element code used in the implemenatation presented is the Engineering Analysis Language (EAL), which is based on a hybrid method of analysis. It was shown that design sensitivity computations can be carried out using the database management system of EAL, without writing a separate program and a separate database. Conventional (sizing) design parameters such as cross-sectional area of beams or thickness of plates and plane elastic solid components are considered. Compliance, displacement, and stress functionals are considered as performance criteria. The method presented is being extended to implement shape design sensitivity analysis using a domain method and a design component method.

Innovative techniques with multi-purpose survey vehicle for automated analysis of cross-slope data.

DOT National Transportation Integrated Search

2007-11-02

Manual surveying methods have long been used in the field of highway engineering to determine : the cross-slope, and longitudinal grade of an existing roadway. However, these methods are : slow, tedious and labor intensive. Moreover, manual survey me...

Development of Novel Noninvasive Methods of Stress Assessment in Baleen Whales

DTIC Science & Technology

2014-09-30

large whales. Few methods exist for assessment of physiological stress levels of free-swimming cetaceans (Amaral 2010, ONR 2010, Hunt et al. 2013...hormone aldosterone . Our aim in this project is to further develop both techniques - respiratory hormone analysis and fecal hormone analysis - for use...noninvasive aldosterone assay (for both feces and blow) that can be used as an alternative measure of adrenal gland activation relative to stress

Semiparametric methods to contrast gap time survival functions: Application to repeat kidney transplantation.

PubMed

Shu, Xu; Schaubel, Douglas E

2016-06-01

Times between successive events (i.e., gap times) are of great importance in survival analysis. Although many methods exist for estimating covariate effects on gap times, very few existing methods allow for comparisons between gap times themselves. Motivated by the comparison of primary and repeat transplantation, our interest is specifically in contrasting the gap time survival functions and their integration (restricted mean gap time). Two major challenges in gap time analysis are non-identifiability of the marginal distributions and the existence of dependent censoring (for all but the first gap time). We use Cox regression to estimate the (conditional) survival distributions of each gap time (given the previous gap times). Combining fitted survival functions based on those models, along with multiple imputation applied to censored gap times, we then contrast the first and second gap times with respect to average survival and restricted mean lifetime. Large-sample properties are derived, with simulation studies carried out to evaluate finite-sample performance. We apply the proposed methods to kidney transplant data obtained from a national organ transplant registry. Mean 10-year graft survival of the primary transplant is significantly greater than that of the repeat transplant, by 3.9 months (p=0.023), a result that may lack clinical importance. © 2015, The International Biometric Society.

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2009-09-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 70's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The study shows the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

A retrospective analysis of in vivo eye irritation, skin irritation and skin sensitisation studies with agrochemical formulations: Setting the scene for development of alternative strategies.

PubMed

Corvaro, M; Gehen, S; Andrews, K; Chatfield, R; Macleod, F; Mehta, J

2017-10-01

Analysis of the prevalence of health effects in large scale databases is key in defining testing strategies within the context of Integrated Approaches on Testing and Assessment (IATA), and is relevant to drive policy changes in existing regulatory toxicology frameworks towards non-animal approaches. A retrospective analysis of existing results from in vivo skin irritation, eye irritation, and skin sensitisation studies on a database of 223 agrochemical formulations is herein published. For skin or eye effects, high prevalence of mild to non-irritant formulations (i.e. per GHS, CLP or EPA classification) would generally suggest a bottom-up approach. Severity of erythema or corneal opacity, for skinor eye effects respectively, were the key drivers for classification, consistent with existing literature. The reciprocal predictivity of skin versus eye irritation and the good negative predictivity of the GHS additivity calculation approach (>85%) provided valuable non-testing evidence for irritation endpoints. For dermal sensitisation, concordance on data from three different methods confirmed the high false negative rate for the Buehler method in this product class. These results have been reviewed together with existing literature on the use of in vitro alternatives for agrochemical formulations, to propose improvements to current regulatory strategies and to identify further research needs. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of a Knowledge-Management-Based Process of Transferring Project Management Skills

ERIC Educational Resources Information Center

Ioi, Toshihiro; Ono, Masakazu; Ishii, Kota; Kato, Kazuhiko

2012-01-01

Purpose: The purpose of this paper is to propose a method for the transfer of knowledge and skills in project management (PM) based on techniques in knowledge management (KM). Design/methodology/approach: The literature contains studies on methods to extract experiential knowledge in PM, but few studies exist that focus on methods to convert…

Case Selection via Matching

ERIC Educational Resources Information Center

Nielsen, Richard A.

2016-01-01

This article shows how statistical matching methods can be used to select "most similar" cases for qualitative analysis. I first offer a methodological justification for research designs based on selecting most similar cases. I then discuss the applicability of existing matching methods to the task of selecting most similar cases and…

Who's in and why? A typology of stakeholder analysis methods for natural resource management.

PubMed

Reed, Mark S; Graves, Anil; Dandy, Norman; Posthumus, Helena; Hubacek, Klaus; Morris, Joe; Prell, Christina; Quinn, Claire H; Stringer, Lindsay C

2009-04-01

Stakeholder analysis means many things to different people. Various methods and approaches have been developed in different fields for different purposes, leading to confusion over the concept and practice of stakeholder analysis. This paper asks how and why stakeholder analysis should be conducted for participatory natural resource management research. This is achieved by reviewing the development of stakeholder analysis in business management, development and natural resource management. The normative and instrumental theoretical basis for stakeholder analysis is discussed, and a stakeholder analysis typology is proposed. This consists of methods for: i) identifying stakeholders; ii) differentiating between and categorising stakeholders; and iii) investigating relationships between stakeholders. The range of methods that can be used to carry out each type of analysis is reviewed. These methods and approaches are then illustrated through a series of case studies funded through the Rural Economy and Land Use (RELU) programme. These case studies show the wide range of participatory and non-participatory methods that can be used, and discuss some of the challenges and limitations of existing methods for stakeholder analysis. The case studies also propose new tools and combinations of methods that can more effectively identify and categorise stakeholders and help understand their inter-relationships.

Impact of including or excluding both-armed zero-event studies on using standard meta-analysis methods for rare event outcome: a simulation study

PubMed Central

Cheng, Ji; Pullenayegum, Eleanor; Marshall, John K; Thabane, Lehana

2016-01-01

Objectives There is no consensus on whether studies with no observed events in the treatment and control arms, the so-called both-armed zero-event studies, should be included in a meta-analysis of randomised controlled trials (RCTs). Current analytic approaches handled them differently depending on the choice of effect measures and authors' discretion. Our objective is to evaluate the impact of including or excluding both-armed zero-event (BA0E) studies in meta-analysis of RCTs with rare outcome events through a simulation study. Method We simulated 2500 data sets for different scenarios varying the parameters of baseline event rate, treatment effect and number of patients in each trial, and between-study variance. We evaluated the performance of commonly used pooling methods in classical meta-analysis—namely, Peto, Mantel-Haenszel with fixed-effects and random-effects models, and inverse variance method with fixed-effects and random-effects models—using bias, root mean square error, length of 95% CI and coverage. Results The overall performance of the approaches of including or excluding BA0E studies in meta-analysis varied according to the magnitude of true treatment effect. Including BA0E studies introduced very little bias, decreased mean square error, narrowed the 95% CI and increased the coverage when no true treatment effect existed. However, when a true treatment effect existed, the estimates from the approach of excluding BA0E studies led to smaller bias than including them. Among all evaluated methods, the Peto method excluding BA0E studies gave the least biased results when a true treatment effect existed. Conclusions We recommend including BA0E studies when treatment effects are unlikely, but excluding them when there is a decisive treatment effect. Providing results of including and excluding BA0E studies to assess the robustness of the pooled estimated effect is a sensible way to communicate the results of a meta-analysis when the treatment effects are unclear. PMID:27531725

Monte Carlo based statistical power analysis for mediation models: methods and software.

PubMed

Zhang, Zhiyong

2014-12-01

The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

Modeling and Analysis of Wrinkled Membranes: An Overview

NASA Technical Reports Server (NTRS)

Yang, B.; Ding, H.; Lou, M.; Fang, H.; Broduer, Steve (Technical Monitor)

2001-01-01

Thin-film membranes are basic elements of a variety of space inflatable/deployable structures. Wrinkling degrades the performance and reliability of these membrane structures, and hence has been a topic of continued interest. Wrinkling analysis of membranes for general geometry and arbitrary boundary conditions is quite challenging. The objective of this presentation is two-fold. Firstly, the existing models of wrinkled membranes and related numerical solution methods are reviewed. The important issues to be discussed are the capability of a membrane model to characterize taut, wrinkled and slack states of membranes in a consistent and physically reasonable manner; the ability of a wrinkling analysis method to predict the formation and growth of wrinkled regions, and to determine out-of-plane deformation and wrinkled waves; the convergence of a numerical solution method for wrinkling analysis; and the compatibility of a wrinkling analysis with general-purpose finite element codes. According to this review, several opening issues in modeling and analysis of wrinkled membranes that are to be addressed in future research are summarized, The second objective of this presentation is to discuss a newly developed membrane model of two viable parameters (2-VP model) and associated parametric finite element method (PFEM) for wrinkling analysis are introduced. The innovations and advantages of the proposed membrane model and PFEM-based wrinkling analysis are: (1) Via a unified stress-strain relation; the 2-VP model treat the taut, wrinkled, and slack states of membranes consistently; (2) The PFEM-based wrinkling analysis has guaranteed convergence; (3) The 2-VP model along with PFEM is capable of predicting membrane out-of-plane deformations; and (4) The PFEM can be integrated into any existing finite element code. Preliminary numerical examples are also included in this presentation to demonstrate the 2-VP model and PFEM-based wrinkling analysis approach.

Analyzing Association Mapping in Pedigree-Based GWAS Using a Penalized Multitrait Mixed Model

PubMed Central

Liu, Jin; Yang, Can; Shi, Xingjie; Li, Cong; Huang, Jian; Zhao, Hongyu; Ma, Shuangge

2017-01-01

Genome-wide association studies (GWAS) have led to the identification of many genetic variants associated with complex diseases in the past 10 years. Penalization methods, with significant numerical and statistical advantages, have been extensively adopted in analyzing GWAS. This study has been partly motivated by the analysis of Genetic Analysis Workshop (GAW) 18 data, which have two notable characteristics. First, the subjects are from a small number of pedigrees and hence related. Second, for each subject, multiple correlated traits have been measured. Most of the existing penalization methods assume independence between subjects and traits and can be suboptimal. There are a few methods in the literature based on mixed modeling that can accommodate correlations. However, they cannot fully accommodate the two types of correlations while conducting effective marker selection. In this study, we develop a penalized multitrait mixed modeling approach. It accommodates the two different types of correlations and includes several existing methods as special cases. Effective penalization is adopted for marker selection. Simulation demonstrates its satisfactory performance. The GAW 18 data are analyzed using the proposed method. PMID:27247027

Readiness of food composition databases and food component analysis systems for nutrigenomics

USDA-ARS?s Scientific Manuscript database

The study objective was to discuss the international implications of using nutrigenomics as the basis for individualized health promotion and chronic disease prevention and the challenges it presents to existing nutrient databases and nutrient analysis systems. Definitions and research methods of nu...

THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer's Disease.

PubMed

Kakati, Tulika; Kashyap, Hirak; Bhattacharyya, Dhruba K

2016-11-30

There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer's disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer's disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer's disease brains. The biological pathways associated with Alzheimer's disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature.

THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer’s Disease

PubMed Central

Kakati, Tulika; Kashyap, Hirak; Bhattacharyya, Dhruba K.

2016-01-01

There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer’s disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer’s disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer’s disease brains. The biological pathways associated with Alzheimer’s disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature. PMID:27901073

Complexity-reduced implementations of complete and null-space-based linear discriminant analysis.

PubMed

Lu, Gui-Fu; Zheng, Wenming

2013-10-01

Dimensionality reduction has become an important data preprocessing step in a lot of applications. Linear discriminant analysis (LDA) is one of the most well-known dimensionality reduction methods. However, the classical LDA cannot be used directly in the small sample size (SSS) problem where the within-class scatter matrix is singular. In the past, many generalized LDA methods has been reported to address the SSS problem. Among these methods, complete linear discriminant analysis (CLDA) and null-space-based LDA (NLDA) provide good performances. The existing implementations of CLDA are computationally expensive. In this paper, we propose a new and fast implementation of CLDA. Our proposed implementation of CLDA, which is the most efficient one, is equivalent to the existing implementations of CLDA in theory. Since CLDA is an extension of null-space-based LDA (NLDA), our implementation of CLDA also provides a fast implementation of NLDA. Experiments on some real-world data sets demonstrate the effectiveness of our proposed new CLDA and NLDA algorithms. Copyright © 2013 Elsevier Ltd. All rights reserved.

An automated and universal method for measuring mean grain size from a digital image of sediment

USGS Publications Warehouse

Buscombe, Daniel D.; Rubin, David M.; Warrick, Jonathan A.

2010-01-01

Existing methods for estimating mean grain size of sediment in an image require either complicated sequences of image processing (filtering, edge detection, segmentation, etc.) or statistical procedures involving calibration. We present a new approach which uses Fourier methods to calculate grain size directly from the image without requiring calibration. Based on analysis of over 450 images, we found the accuracy to be within approximately 16% across the full range from silt to pebbles. Accuracy is comparable to, or better than, existing digital methods. The new method, in conjunction with recent advances in technology for taking appropriate images of sediment in a range of natural environments, promises to revolutionize the logistics and speed at which grain-size data may be obtained from the field.

Development of Novel Noninvasive Methods of Stress Assessment in Baleen Whales

DTIC Science & Technology

2015-09-30

large whales. Few methods exist for assessment of physiological stress levels of free-swimming cetaceans (Amaral 2010, ONR 2010, Hunt et al. 2013...adrenal hormone aldosterone . Our aim in this project is to further develop both techniques - respiratory hormone analysis and fecal hormone analysis...development of a noninvasive aldosterone assay (for both feces and blow) that can be used as an alternative measure of adrenal gland activation relative to

Probabilistic finite elements for fatigue and fracture analysis

NASA Astrophysics Data System (ADS)

Belytschko, Ted; Liu, Wing Kam

Attenuation is focused on the development of Probabilistic Finite Element Method (PFEM), which combines the finite element method with statistics and reliability methods, and its application to linear, nonlinear structural mechanics problems and fracture mechanics problems. The computational tool based on the Stochastic Boundary Element Method is also given for the reliability analysis of a curvilinear fatigue crack growth. The existing PFEM's have been applied to solve for two types of problems: (1) determination of the response uncertainty in terms of the means, variance and correlation coefficients; and (2) determination the probability of failure associated with prescribed limit states.

Probabilistic finite elements for fatigue and fracture analysis

NASA Technical Reports Server (NTRS)

Belytschko, Ted; Liu, Wing Kam

1992-01-01

Attenuation is focused on the development of Probabilistic Finite Element Method (PFEM), which combines the finite element method with statistics and reliability methods, and its application to linear, nonlinear structural mechanics problems and fracture mechanics problems. The computational tool based on the Stochastic Boundary Element Method is also given for the reliability analysis of a curvilinear fatigue crack growth. The existing PFEM's have been applied to solve for two types of problems: (1) determination of the response uncertainty in terms of the means, variance and correlation coefficients; and (2) determination the probability of failure associated with prescribed limit states.

An Investigation of the Overlap Between the Statistical Discrete Gust and the Power Spectral Density Analysis Methods

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

1989-01-01

The results of a NASA investigation of a claimed Overlap between two gust response analysis methods: the Statistical Discrete Gust (SDG) Method and the Power Spectral Density (PSD) Method are presented. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented for several different airplanes at several different flight conditions indicate that such an Overlap does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

Advanced bridge safety initiative : recommended practices for live load testing of existing flat-slab concrete bridges - task 5.

DOT National Transportation Integrated Search

2012-12-01

Current AASHTO provisions for load rating flat-slab concrete bridges use the equivalent strip : width method, which is regarded as overly conservative compared to more advanced analysis : methods and field live load testing. It has been shown that li...

75 FR 16202 - Notice of Issuance of Regulatory Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-31

..., Revision 2, ``An Acceptable Model and Related Statistical Methods for the Analysis of Fuel Densification.... Introduction The U.S. Nuclear Regulatory Commission (NRC) is issuing a revision to an existing guide in the... nuclear power reactors. To meet these objectives, the guide describes statistical methods related to...

A basic guide to overlay design using nondestructive testing equipment data

NASA Astrophysics Data System (ADS)

Turner, Vernon R.

1990-08-01

The purpose of this paper is to provide a basic and concise guide to designing asphalt concrete (AC) overlays over existing AC pavements. The basis for these designs is deflection data obtained from nondestructive testing (NDT) equipment. This data is used in design procedures which produce required overlay thickness or an estimate of remaining pavement life. This guide enables one to design overlays or better monitor the designs being performed by others. This paper will discuss three types of NDT equipment, the Asphalt Institute Overlay Designs by Deflection Analysis and by the effective thickness method as well as a method of estimating remaining pavement life, correlations between NDT equipment and recent correlations in Washington State. Asphalt overlays provide one of the most cost effective methods of improving existing pavements. Asphalt overlays can be used to strengthen existing pavements, to reduce maintenance costs, to increase pavement life, to provide a smoother ride, and to improve skid resistance.

A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

PubMed

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely possible. Fruitful future directions may include investigating more sophisticated schemes for converting spectral counts to probabilities and applying the framework to direct protein complex prediction methods.

Non-Contacting Compliant Foil Seal for Gas Turbine Engine

NASA Technical Reports Server (NTRS)

Salehi, Mohsen; Heshmat, Hooshang

2002-01-01

The program is aimed at enhancing the existing analysis to include the turbulence effect. Several manufacturing methods are being investigated in order to apply our know-how in building the seal hardware. The contents include: 1) Test Facilities; 2) Analysis Enhancements; 3) Accomplishments/Status; and 4) Materials Study.

[Recurrence plot analysis of HRV for brain ischemia and asphyxia].

PubMed

Chen, Xiaoming; Qiu, Yihong; Zhu, Yisheng

2008-02-01

Heart rate variability (HRV) is the tiny variability existing in the cycles of the heart beats, which reflects the corresponding balance between sympathetic and vagus nerves. Since the nonlinear characteristic of HRV is confirmed, the Recurrence Plot method, a nonlinear dynamic analysis method based on the complexity, could be used to analyze HRV. The results showed the recurrence plot structures and some quantitative indices (L-Mean, L-Entr) during asphyxia insult vary significantly as compared to those in normal conditions, which offer a new method to monitor brain asphyxia injury.

TUBEs-Mass Spectrometry for Identification and Analysis of the Ubiquitin-Proteome.

PubMed

Azkargorta, Mikel; Escobes, Iraide; Elortza, Felix; Matthiesen, Rune; Rodríguez, Manuel S

2016-01-01

Mass spectrometry (MS) has become the method of choice for the large-scale analysis of protein ubiquitylation. There exist a number of proposed methods for mapping ubiquitin sites, each with different pros and cons. We present here a protocol for the MS analysis of the ubiquitin-proteome captured by TUBEs and subsequent data analysis. Using dedicated software and algorithms, specific information on the presence of ubiquitylated peptides can be obtained from the MS search results. In addition, a quantitative and functional analysis of the ubiquitylated proteins and their interacting partners helps to unravel the biological and molecular processes they are involved in.

A comparison of TSS and TRASYS in form factor calculation

NASA Technical Reports Server (NTRS)

Golliher, Eric

1993-01-01

As the workstation and personal computer become more popular than a centralized mainframe to perform thermal analysis, the methods for space vehicle thermal analysis will change. Already, many thermal analysis codes are now available for workstations, which were not in existence just five years ago. As these changes occur, some organizations will adopt the new codes and analysis techniques, while others will not. This might lead to misunderstandings between thermal shops in different organizations. If thermal analysts make an effort to understand the major differences between the new and old methods, a smoother transition to a more efficient and more versatile thermal analysis environment will be realized.

Sulfur in Cometary Dust

NASA Technical Reports Server (NTRS)

Fomenkova, M. N.

1997-01-01

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Tchebichef moment based restoration of Gaussian blurred images.

PubMed

Kumar, Ahlad; Paramesran, Raveendran; Lim, Chern-Loon; Dass, Sarat C

2016-11-10

With the knowledge of how edges vary in the presence of a Gaussian blur, a method that uses low-order Tchebichef moments is proposed to estimate the blur parameters: sigma (σ) and size (w). The difference between the Tchebichef moments of the original and the reblurred images is used as feature vectors to train an extreme learning machine for estimating the blur parameters (σ,w). The effectiveness of the proposed method to estimate the blur parameters is examined using cross-database validation. The estimated blur parameters from the proposed method are used in the split Bregman-based image restoration algorithm. A comparative analysis of the proposed method with three existing methods using all the images from the LIVE database is carried out. The results show that the proposed method in most of the cases performs better than the three existing methods in terms of the visual quality evaluated using the structural similarity index.

A hidden two-locus disease association pattern in genome-wide association studies

PubMed Central

2011-01-01

Background Recent association analyses in genome-wide association studies (GWAS) mainly focus on single-locus association tests (marginal tests) and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs). The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation. Results In this paper, we develop a computational method to detect this association pattern masked by unfaithfulness. We have applied our method to analyze seven data sets from the Wellcome Trust Case Control Consortium (WTCCC). The analysis for each data set takes about one week to finish the examination of all pairs of SNPs. Based on the empirical result of these real data, we show that this type of association masked by unfaithfulness widely exists in GWAS. Conclusions These newly identified associations enrich the discoveries of GWAS, which may provide new insights both in the analysis of tagSNPs and in the experiment design of GWAS. Since these associations may be easily missed by existing analysis tools, we can only connect some of them to publicly available findings from other association studies. As independent data set is limited at this moment, we also have difficulties to replicate these findings. More biological implications need further investigation. Availability The software is freely available at http://bioinformatics.ust.hk/hidden_pattern_finder.zip. PMID:21569557

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method

NASA Astrophysics Data System (ADS)

Tang, J.

2012-01-01

Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.

What Touched Your Heart? Collaborative Story Analysis Emerging From an Apsáalooke Cultural Context

PubMed Central

Hallett, John; Held, Suzanne; McCormick, Alma Knows His Gun; Simonds, Vanessa; Bird, Sloane Real; Martin, Christine; Simpson, Colleen; Schure, Mark; Turnsplenty, Nicole; Trottier, Coleen

2017-01-01

Community-based participatory research and decolonizing research share some recommendations for best practices for conducting research. One commonality is partnering on all stages of research; co-developing methods of data analysis is one stage with a deficit of partnering examples. We present a novel community-based and developed method for analyzing qualitative data within an Indigenous health study and explain incompatibilities of existing methods for our purposes and community needs. We describe how we explored available literature, received counsel from community Elders and experts in the field, and collaboratively developed a data analysis method consonant with community values. The method of analysis, in which interview/story remained intact, team members received story, made meaning through discussion, and generated a conceptual framework to inform intervention development, is detailed. We offer the development process and method as an example for researchers working with communities who want to keep stories intact during qualitative data analysis. PMID:27659019

Design and Analysis Tools for Supersonic Inlets

NASA Technical Reports Server (NTRS)

Slater, John W.; Folk, Thomas C.

2009-01-01

Computational tools are being developed for the design and analysis of supersonic inlets. The objective is to update existing tools and provide design and low-order aerodynamic analysis capability for advanced inlet concepts. The Inlet Tools effort includes aspects of creating an electronic database of inlet design information, a document describing inlet design and analysis methods, a geometry model for describing the shape of inlets, and computer tools that implement the geometry model and methods. The geometry model has a set of basic inlet shapes that include pitot, two-dimensional, axisymmetric, and stream-traced inlet shapes. The inlet model divides the inlet flow field into parts that facilitate the design and analysis methods. The inlet geometry model constructs the inlet surfaces through the generation and transformation of planar entities based on key inlet design factors. Future efforts will focus on developing the inlet geometry model, the inlet design and analysis methods, a Fortran 95 code to implement the model and methods. Other computational platforms, such as Java, will also be explored.

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

PubMed Central

Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

2013-01-01

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

Investigation of 2-stage meta-analysis methods for joint longitudinal and time-to-event data through simulation and real data application.

PubMed

Sudell, Maria; Tudur Smith, Catrin; Gueyffier, François; Kolamunnage-Dona, Ruwanthi

2018-04-15

Joint modelling of longitudinal and time-to-event data is often preferred over separate longitudinal or time-to-event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time-to-event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta-analysis of joint model estimates from multiple studies. We propose a 2-stage method for meta-analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta-analyses of separate longitudinal or time-to-event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta-analytic setting where association exists between the longitudinal and time-to-event outcomes. Where evidence of association between longitudinal and time-to-event outcomes exists, results from joint models over standalone analyses should be pooled in 2-stage meta-analyses. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Relaxation estimation of RMSD in molecular dynamics immunosimulations.

PubMed

Schreiner, Wolfgang; Karch, Rudolf; Knapp, Bernhard; Ilieva, Nevena

2012-01-01

Molecular dynamics simulations have to be sufficiently long to draw reliable conclusions. However, no method exists to prove that a simulation has converged. We suggest the method of "lagged RMSD-analysis" as a tool to judge if an MD simulation has not yet run long enough. The analysis is based on RMSD values between pairs of configurations separated by variable time intervals Δt. Unless RMSD(Δt) has reached a stationary shape, the simulation has not yet converged.

Textual blocks rectification method based on fast Hough transform analysis in identity documents recognition

NASA Astrophysics Data System (ADS)

Bezmaternykh, P. V.; Nikolaev, D. P.; Arlazarov, V. L.

2018-04-01

Textual blocks rectification or slant correction is an important stage of document image processing in OCR systems. This paper considers existing methods and introduces an approach for the construction of such algorithms based on Fast Hough Transform analysis. A quality measurement technique is proposed and obtained results are shown for both printed and handwritten textual blocks processing as a part of an industrial system of identity documents recognition on mobile devices.

Is the societal approach wide enough to include relatives? Incorporating relatives' costs and effects in a cost-effectiveness analysis.

PubMed

Davidson, Thomas; Levin, Lars-Ake

2010-01-01

It is important for economic evaluations in healthcare to cover all relevant information. However, many existing evaluations fall short of this goal, as they fail to include all the costs and effects for the relatives of a disabled or sick individual. The objective of this study was to analyse how relatives' costs and effects could be measured, valued and incorporated into a cost-effectiveness analysis. In this article, we discuss the theories underlying cost-effectiveness analyses in the healthcare arena; the general conclusion is that it is hard to find theoretical arguments for excluding relatives' costs and effects if a societal perspective is used. We argue that the cost of informal care should be calculated according to the opportunity cost method. To capture relatives' effects, we construct a new term, the R-QALY weight, which is defined as the effect on relatives' QALY weight of being related to a disabled or sick individual. We examine methods for measuring, valuing and incorporating the R-QALY weights. One suggested method is to estimate R-QALYs and incorporate them together with the patient's QALY in the analysis. However, there is no well established method as yet that can create R-QALY weights. One difficulty with measuring R-QALY weights using existing instruments is that these instruments are rarely focused on relative-related aspects. Even if generic quality-of-life instruments do cover some aspects relevant to relatives and caregivers, they may miss important aspects and potential altruistic preferences. A further development and validation of the existing caregiving instruments used for eliciting utility weights would therefore be beneficial for this area, as would further studies on the use of time trade-off or Standard Gamble methods for valuing R-QALY weights. Another potential method is to use the contingent valuation method to find a monetary value for all the relatives' costs and effects. Because cost-effectiveness analyses are used for decision making, and this is often achieved by comparing different cost-effectiveness ratios, we argue that it is important to find ways of incorporating all relatives' costs and effects into the analysis. This may not be necessary for every analysis of every intervention, but for treatments where relatives' costs and effects are substantial there may be some associated influence on the cost-effectiveness ratio.

Fluorescence-labeled methylation-sensitive amplified fragment length polymorphism (FL-MS-AFLP) analysis for quantitative determination of DNA methylation and demethylation status.

PubMed

Kageyama, Shinji; Shinmura, Kazuya; Yamamoto, Hiroko; Goto, Masanori; Suzuki, Koichi; Tanioka, Fumihiko; Tsuneyoshi, Toshihiro; Sugimura, Haruhiko

2008-04-01

The PCR-based DNA fingerprinting method called the methylation-sensitive amplified fragment length polymorphism (MS-AFLP) analysis is used for genome-wide scanning of methylation status. In this study, we developed a method of fluorescence-labeled MS-AFLP (FL-MS-AFLP) analysis by applying a fluorescence-labeled primer and fluorescence-detecting electrophoresis apparatus to the existing method of MS-AFLP analysis. The FL-MS-AFLP analysis enables quantitative evaluation of more than 350 random CpG loci per run. It was shown to allow evaluation of the differences in methylation level of blood DNA of gastric cancer patients and evaluation of hypermethylation and hypomethylation in DNA from gastric cancer tissue in comparison with adjacent non-cancerous tissue.

Missing data imputation: focusing on single imputation.

PubMed

Zhang, Zhongheng

2016-01-01

Complete case analysis is widely used for handling missing data, and it is the default method in many statistical packages. However, this method may introduce bias and some useful information will be omitted from analysis. Therefore, many imputation methods are developed to make gap end. The present article focuses on single imputation. Imputations with mean, median and mode are simple but, like complete case analysis, can introduce bias on mean and deviation. Furthermore, they ignore relationship with other variables. Regression imputation can preserve relationship between missing values and other variables. There are many sophisticated methods exist to handle missing values in longitudinal data. This article focuses primarily on how to implement R code to perform single imputation, while avoiding complex mathematical calculations.

Missing data imputation: focusing on single imputation

PubMed Central

2016-01-01

Complete case analysis is widely used for handling missing data, and it is the default method in many statistical packages. However, this method may introduce bias and some useful information will be omitted from analysis. Therefore, many imputation methods are developed to make gap end. The present article focuses on single imputation. Imputations with mean, median and mode are simple but, like complete case analysis, can introduce bias on mean and deviation. Furthermore, they ignore relationship with other variables. Regression imputation can preserve relationship between missing values and other variables. There are many sophisticated methods exist to handle missing values in longitudinal data. This article focuses primarily on how to implement R code to perform single imputation, while avoiding complex mathematical calculations. PMID:26855945

Progressive Failure Analysis Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Sleight, David W.

1999-01-01

A progressive failure analysis method has been developed for predicting the failure of laminated composite structures under geometrically nonlinear deformations. The progressive failure analysis uses C(exp 1) shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms and several options are available to degrade the material properties after failures. The progressive failure analysis method is implemented in the COMET finite element analysis code and can predict the damage and response of laminated composite structures from initial loading to final failure. The different failure criteria and material degradation methods are compared and assessed by performing analyses of several laminated composite structures. Results from the progressive failure method indicate good correlation with the existing test data except in structural applications where interlaminar stresses are important which may cause failure mechanisms such as debonding or delaminations.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Cyberprints: Identifying Cyber Attackers by Feature Analysis

ERIC Educational Resources Information Center

Blakely, Benjamin A.

2012-01-01

The problem of attributing cyber attacks is one of increasing importance. Without a solid method of demonstrating the origin of a cyber attack, any attempts to deter would-be cyber attackers are wasted. Existing methods of attribution make unfounded assumptions about the environment in which they will operate: omniscience (the ability to gather,…

Development of a Computer-Based Visualised Quantitative Learning System for Playing Violin Vibrato

ERIC Educational Resources Information Center

Ho, Tracy Kwei-Liang; Lin, Huann-shyang; Chen, Ching-Kong; Tsai, Jih-Long

2015-01-01

Traditional methods of teaching music are largely subjective, with the lack of objectivity being particularly challenging for violin students learning vibrato because of the existence of conflicting theories. By using a computer-based analysis method, this study found that maintaining temporal coincidence between the intensity peak and the target…

An Hypothesis on Thinking

ERIC Educational Resources Information Center

Maclennan, Ian

1977-01-01

Suggests that there exists a "finite" number of elementary concepts and distinguishable modes of thinking, that all human beings tend to acquire the same set of elements of thinking and the same strategies with which to understand and control their physical environment, and that the method of analysis used here is a standard scientific method.…

Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Levitsky, Lev I.; Gorshkov, Mikhail V.

2016-09-01

A number of proteomic database search engines implement multi-stage strategies aiming at increasing the sensitivity of proteome analysis. These approaches often employ a subset of the original database for the secondary stage of analysis. However, if target-decoy approach (TDA) is used for false discovery rate (FDR) estimation, the multi-stage strategies may violate the underlying assumption of TDA that false matches are distributed uniformly across the target and decoy databases. This violation occurs if the numbers of target and decoy proteins selected for the second search are not equal. Here, we propose a method of decoy database generation based on the previously reported decoy fusion strategy. This method allows unbiased TDA-based FDR estimation in multi-stage searches and can be easily integrated into existing workflows utilizing popular search engines and post-search algorithms.

Detection of molecular particles in live cells via machine learning.

PubMed

Jiang, Shan; Zhou, Xiaobo; Kirchhausen, Tom; Wong, Stephen T C

2007-08-01

Clathrin-coated pits play an important role in removing proteins and lipids from the plasma membrane and transporting them to the endosomal compartment. It is, however, still unclear whether there exist "hot spots" for the formation of Clathrin-coated pits or the pits and arrays formed randomly on the plasma membrane. To answer this question, first of all, many hundreds of individual pits need to be detected accurately and separated in live-cell microscope movies to capture and monitor how pits and vesicles were formed. Because of the noisy background and the low contrast of the live-cell movies, the existing image analysis methods, such as single threshold, edge detection, and morphological operation, cannot be used. Thus, this paper proposes a machine learning method, which is based on Haar features, to detect the particle's position. Results show that this method can successfully detect most of particles in the image. In order to get the accurate boundaries of these particles, several post-processing methods are applied and signal-to-noise ratio analysis is also performed to rule out the weak spots. Copyright 2007 International Society for Analytical Cytology.

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

NASA Astrophysics Data System (ADS)

Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho

2018-05-01

We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

An improved parameter estimation scheme for image modification detection based on DCT coefficient analysis.

PubMed

Yu, Liyang; Han, Qi; Niu, Xiamu; Yiu, S M; Fang, Junbin; Zhang, Ye

2016-02-01

Most of the existing image modification detection methods which are based on DCT coefficient analysis model the distribution of DCT coefficients as a mixture of a modified and an unchanged component. To separate the two components, two parameters, which are the primary quantization step, Q1, and the portion of the modified region, α, have to be estimated, and more accurate estimations of α and Q1 lead to better detection and localization results. Existing methods estimate α and Q1 in a completely blind manner, without considering the characteristics of the mixture model and the constraints to which α should conform. In this paper, we propose a more effective scheme for estimating α and Q1, based on the observations that, the curves on the surface of the likelihood function corresponding to the mixture model is largely smooth, and α can take values only in a discrete set. We conduct extensive experiments to evaluate the proposed method, and the experimental results confirm the efficacy of our method. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A Review On Missing Value Estimation Using Imputation Algorithm

NASA Astrophysics Data System (ADS)

Armina, Roslan; Zain, Azlan Mohd; Azizah Ali, Nor; Sallehuddin, Roselina

2017-09-01

The presence of the missing value in the data set has always been a major problem for precise prediction. The method for imputing missing value needs to minimize the effect of incomplete data sets for the prediction model. Many algorithms have been proposed for countermeasure of missing value problem. In this review, we provide a comprehensive analysis of existing imputation algorithm, focusing on the technique used and the implementation of global or local information of data sets for missing value estimation. In addition validation method for imputation result and way to measure the performance of imputation algorithm also described. The objective of this review is to highlight possible improvement on existing method and it is hoped that this review gives reader better understanding of imputation method trend.

Digital double random amplitude image encryption method based on the symmetry property of the parametric discrete Fourier transform

NASA Astrophysics Data System (ADS)

Bekkouche, Toufik; Bouguezel, Saad

2018-03-01

We propose a real-to-real image encryption method. It is a double random amplitude encryption method based on the parametric discrete Fourier transform coupled with chaotic maps to perform the scrambling. The main idea behind this method is the introduction of a complex-to-real conversion by exploiting the inherent symmetry property of the transform in the case of real-valued sequences. This conversion allows the encrypted image to be real-valued instead of being a complex-valued image as in all existing double random phase encryption methods. The advantage is to store or transmit only one image instead of two images (real and imaginary parts). Computer simulation results and comparisons with the existing double random amplitude encryption methods are provided for peak signal-to-noise ratio, correlation coefficient, histogram analysis, and key sensitivity.

Critical Analysis of Existing Recyclability Assessment Methods for New Products in Order to Define a Reference Method

NASA Astrophysics Data System (ADS)

Maris, E.; Froelich, D.

The designers of products subject to the European regulations on waste have an obligation to improve the recyclability of their products from the very first design stages. The statutory texts refer to ISO standard 22 628, which proposes a method to calculate vehicle recyclability. There are several scientific studies that propose other calculation methods as well. Yet the feedback from the CREER club, a group of manufacturers and suppliers expert in ecodesign and recycling, is that the product recyclability calculation method proposed in this standard is not satisfactory, since only a mass indicator is used, the calculation scope is not clearly defined, and common data on the recycling industry does not exist to allow comparable calculations to be made for different products. For these reasons, it is difficult for manufacturers to have access to a method and common data for calculation purposes.

Identification and confirmation of chemical residues by chromatography-mass spectrometry and other techniques

USDA-ARS?s Scientific Manuscript database

A quantitative answer cannot exist in an analysis without a qualitative component to give enough confidence that the result meets the analytical needs for the analysis (i.e. the result relates to the analyte and not something else). Just as a quantitative method must typically undergo an empirical ...

Interactive visual analysis promotes exploration of long-term ecological data

Treesearch

T.N. Pham; J.A. Jones; R. Metoyer; F.J. Swanson; R.J. Pabst

2013-01-01

Long-term ecological data are crucial in helping ecologists understand ecosystem function and environmental change. Nevertheless, these kinds of data sets are difficult to analyze because they are usually large, multivariate, and spatiotemporal. Although existing analysis tools such as statistical methods and spreadsheet software permit rigorous tests of pre-conceived...

Compensation of hospital-based physicians.

PubMed Central

Steinwald, B

1983-01-01

This study is concerned with methods of compensating hospital-based physicians (HBPs) in five medical specialties: anesthesiology, pathology, radiology, cardiology, and emergency medicine. Data on 2232 nonfederal, short-term general hospitals came from a mail questionnaire survey conducted in Fall 1979. The data indicate that numerous compensation methods exist but these methods, without much loss of precision, can be reduced to salary, percentage of department revenue, and fee-for-service. When HBPs are compensated by salary or percentage methods, most patient billing is conducted by the hospital. In contrast, most fee-for-service HBPs bill their patients directly. Determinants of HBP compensation methods are investigated via multinomial logit analysis. This analysis indicates that choice of HBP compensation methods are investigated via multinomial logit analysis. This analysis indicates that choice of HBP compensation methods is sensitive to a number of hospital characteristics and attributes of both the hospital and physicians' services markets. The empirical findings are discussed in light of past conceptual and empirical research on physician compensation, and current policy issues in the health services sector. PMID:6841112

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

A strategy for reducing turnaround time in design optimization using a distributed computer system

NASA Technical Reports Server (NTRS)

Young, Katherine C.; Padula, Sharon L.; Rogers, James L.

1988-01-01

There is a need to explore methods for reducing lengthly computer turnaround or clock time associated with engineering design problems. Different strategies can be employed to reduce this turnaround time. One strategy is to run validated analysis software on a network of existing smaller computers so that portions of the computation can be done in parallel. This paper focuses on the implementation of this method using two types of problems. The first type is a traditional structural design optimization problem, which is characterized by a simple data flow and a complicated analysis. The second type of problem uses an existing computer program designed to study multilevel optimization techniques. This problem is characterized by complicated data flow and a simple analysis. The paper shows that distributed computing can be a viable means for reducing computational turnaround time for engineering design problems that lend themselves to decomposition. Parallel computing can be accomplished with a minimal cost in terms of hardware and software.

Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis.

PubMed

Spain, Seth M; Miner, Andrew G; Kroonenberg, Pieter M; Drasgow, Fritz

2010-08-06

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of analyzing momentary work behavior using experience sampling methods. The article also examines a previously unused set of methods for analyzing data produced by experience sampling. These methods are known collectively as multiway component analysis. Two archetypal techniques of multimode factor analysis, the Parallel factor analysis and the Tucker3 models, are used to analyze data from Miner, Glomb, and Hulin's (2010) experience sampling study of work behavior. The efficacy of these techniques for analyzing experience sampling data is discussed as are the substantive multimode component models obtained.

A critical evaluation of various methods for the analysis of flow-solid interaction in a nest of thin cylinders subjected to cross flows

NASA Technical Reports Server (NTRS)

Kim, Sang-Wook

1987-01-01

Various experimental, analytical, and numerical analysis methods for flow-solid interaction of a nest of cylinders subjected to cross flows are reviewed. A nest of cylinders subjected to cross flows can be found in numerous engineering applications including the Space Shuttle Maine Engine-Main Injector Assembly (SSME-MIA) and nuclear reactor heat exchangers. Despite its extreme importance in engineering applications, understanding of the flow-solid interaction process is quite limited and design of the tube banks are mostly dependent on experiments and/or experimental correlation equations. For future development of major numerical analysis methods for the flow-solid interaction of a nest of cylinders subjected to cross flow, various turbulence models, nonlinear structural dynamics, and existing laminar flow-solid interaction analysis methods are included.

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

PubMed

Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

[Review of research design and statistical methods in Chinese Journal of Cardiology].

PubMed

Zhang, Li-jun; Yu, Jin-ming

2009-07-01

To evaluate the research design and the use of statistical methods in Chinese Journal of Cardiology. Peer through the research design and statistical methods in all of the original papers in Chinese Journal of Cardiology from December 2007 to November 2008. The most frequently used research designs are cross-sectional design (34%), prospective design (21%) and experimental design (25%). In all of the articles, 49 (25%) use wrong statistical methods, 29 (15%) lack some sort of statistic analysis, 23 (12%) have inconsistencies in description of methods. There are significant differences between different statistical methods (P < 0.001). The correction rates of multifactor analysis were low and repeated measurement datas were not used repeated measurement analysis. Many problems exist in Chinese Journal of Cardiology. Better research design and correct use of statistical methods are still needed. More strict review by statistician and epidemiologist is also required to improve the literature qualities.

An Evidential Reasoning-Based CREAM to Human Reliability Analysis in Maritime Accident Process.

PubMed

Wu, Bing; Yan, Xinping; Wang, Yang; Soares, C Guedes

2017-10-01

This article proposes a modified cognitive reliability and error analysis method (CREAM) for estimating the human error probability in the maritime accident process on the basis of an evidential reasoning approach. This modified CREAM is developed to precisely quantify the linguistic variables of the common performance conditions and to overcome the problem of ignoring the uncertainty caused by incomplete information in the existing CREAM models. Moreover, this article views maritime accident development from the sequential perspective, where a scenario- and barrier-based framework is proposed to describe the maritime accident process. This evidential reasoning-based CREAM approach together with the proposed accident development framework are applied to human reliability analysis of a ship capsizing accident. It will facilitate subjective human reliability analysis in different engineering systems where uncertainty exists in practice. © 2017 Society for Risk Analysis.

Statistical methods to estimate treatment effects from multichannel electroencephalography (EEG) data in clinical trials.

PubMed

Ma, Junshui; Wang, Shubing; Raubertas, Richard; Svetnik, Vladimir

2010-07-15

With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in the published literature, are first reviewed. A straightforward adjustment of the existing methods to handle multichannel EEG data is then introduced. In addition, based on the spatial smoothness property of EEG data, a new category of statistical methods is proposed. The new methods use a linear combination of low-degree spherical harmonic (SPHARM) basis functions to represent a spatially smoothed version of the EEG data on the scalp, which is close to a sphere in shape. In total, seven statistical methods, including both the existing and the newly proposed methods, are applied to two clinical datasets to compare their power to detect a drug effect. Contrary to the EEG community's recommendation, our results suggest that (1) the nonparametric method does not outperform its parametric counterpart; and (2) including baseline data in the analysis does not always improve the statistical power. In addition, our results recommend that (3) simple paired statistical tests should be avoided due to their poor power; and (4) the proposed spatially smoothed methods perform better than their unsmoothed versions. Copyright 2010 Elsevier B.V. All rights reserved.

Assessment of current state of the art in modeling techniques and analysis methods for large space structures

NASA Technical Reports Server (NTRS)

Noor, A. K.

1983-01-01

Advances in continuum modeling, progress in reduction methods, and analysis and modeling needs for large space structures are covered with specific attention given to repetitive lattice trusses. As far as continuum modeling is concerned, an effective and verified analysis capability exists for linear thermoelastic stress, birfurcation buckling, and free vibration problems of repetitive lattices. However, application of continuum modeling to nonlinear analysis needs more development. Reduction methods are very effective for bifurcation buckling and static (steady-state) nonlinear analysis. However, more work is needed to realize their full potential for nonlinear dynamic and time-dependent problems. As far as analysis and modeling needs are concerned, three areas are identified: loads determination, modeling and nonclassical behavior characteristics, and computational algorithms. The impact of new advances in computer hardware, software, integrated analysis, CAD/CAM stems, and materials technology is also discussed.

An investigation of the 'Overlap' between the Statistical-Discrete-Gust and the Power-Spectral-Density analysis methods

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

1989-01-01

This paper presents the results of a NASA investigation of a claimed 'Overlap' between two gust response analysis methods: the Statistical Discrete Gust (SDG) method and the Power Spectral Density (PSD) method. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented in this paper for several different airplanes at several different flight conditions indicate that such an 'Overlap' does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.

PubMed

Zhang, RuiJie; Li, Xia; Jiang, YongShuai; Liu, GuiYou; Li, ChuanXing; Zhang, Fan; Xiao, Yun; Gong, BinSheng

2009-02-01

High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.

Nouvelles techniques pratiques pour la modelisation du comportement dynamique des systèmes eau-structure

NASA Astrophysics Data System (ADS)

Miquel, Benjamin

The dynamic or seismic behavior of hydraulic structures is, as for conventional structures, essential to assure protection of human lives. These types of analyses also aim at limiting structural damage caused by an earthquake to prevent rupture or collapse of the structure. The particularity of these hydraulic structures is that not only the internal displacements are caused by the earthquake, but also by the hydrodynamic loads resulting from fluid-structure interaction. This thesis reviews the existing complex and simplified methods to perform such dynamic analysis for hydraulic structures. For the complex existing methods, attention is placed on the difficulties arising from their use. Particularly, interest is given in this work on the use of transmitting boundary conditions to simulate the semi infinity of reservoirs. A procedure has been developed to estimate the error that these boundary conditions can introduce in finite element dynamic analysis. Depending on their formulation and location, we showed that they can considerably affect the response of such fluid-structure systems. For practical engineering applications, simplified procedures are still needed to evaluate the dynamic behavior of structures in contact with water. A review of the existing simplified procedures showed that these methods are based on numerous simplifications that can affect the prediction of the dynamic behavior of such systems. One of the main objectives of this thesis has been to develop new simplified methods that are more accurate than those existing. First, a new spectral analysis method has been proposed. Expressions for the fundamental frequency of fluid-structure systems, key parameter of spectral analysis, have been developed. We show that this new technique can easily be implemented in a spreadsheet or program, and that its calculation time is near instantaneous. When compared to more complex analytical or numerical method, this new procedure yields excellent prediction of the dynamic behavior of fluid-structure systems. Spectral analyses ignore the transient and oscillatory nature of vibrations. When such dynamic analyses show that some areas of the studied structure undergo excessive stresses, time history analyses allow a better estimate of the extent of these zones as well as a time notion of these excessive stresses. Furthermore, the existing spectral analyses methods for fluid-structure systems account only for the static effect of higher modes. Thought this can generally be sufficient for dams, for flexible structures the dynamic effect of these modes should be accounted for. New methods have been developed for fluid-structure systems to account for these observations as well as the flexibility of foundations. A first method was developed to study structures in contact with one or two finite or infinite water domains. This new technique includes flexibility of structures and foundations as well as the dynamic effect of higher vibration modes and variations of the levels of the water domains. Extension of this method was performed to study beam structures in contact with fluids. These new developments have also allowed extending existing analytical formulations of the dynamic properties of a dry beam to a new formulation that includes effect of fluid-structure interaction. The method yields a very good estimate of the dynamic behavior of beam-fluid systems or beam like structures in contact with fluid. Finally, a Modified Accelerogram Method (MAM) has been developed to modify the design earthquake into a new accelerogram that directly accounts for the effect of fluid-structure interaction. This new accelerogram can therefore be applied directly to the dry structure (i.e. without water) in order to calculate the dynamic response of the fluid-structure system. This original technique can include numerous parameters that influence the dynamic response of such systems and allows to treat analytically the fluid-structure interaction while keeping the advantages of finite element modeling.

Technology Overview for Advanced Aircraft Armament System Program.

DTIC Science & Technology

1981-05-01

availability of methods or systems for improving stores and armament safety. Of particular importance are aspects of safety involving hazards analysis ...flutter virtually insensitive to inertia and center-of- gravity location of store - Simplifies and reduces analysis and testing required to flutter- clear...status. Nearly every existing reliability analysis and discipline that prom- ised a positive return on reliability performance was drawn out, dusted

Stability analysis of piecewise non-linear systems and its application to chaotic synchronisation with intermittent control

NASA Astrophysics Data System (ADS)

Wang, Qingzhi; Tan, Guanzheng; He, Yong; Wu, Min

2017-10-01

This paper considers a stability analysis issue of piecewise non-linear systems and applies it to intermittent synchronisation of chaotic systems. First, based on piecewise Lyapunov function methods, more general and less conservative stability criteria of piecewise non-linear systems in periodic and aperiodic cases are presented, respectively. Next, intermittent synchronisation conditions of chaotic systems are derived which extend existing results. Finally, Chua's circuit is taken as an example to verify the validity of our methods.

METHODS DEVELOPMENT FOR THE ANALYSIS OF CHIRAL PESTICIDES

EPA Science Inventory

Chiral compounds exist as a pair of nonsuperimposable mirror images called enantiomers. Enantiomers have identical physical-chemical properties, but their interactions with other chiral molecules, toxicity, biodegradation, and fate are often different. Many pharmaceutical com...

3D Surface Reconstruction and Automatic Camera Calibration

NASA Technical Reports Server (NTRS)

Jalobeanu, Andre

2004-01-01

Illustrations in this view-graph presentation are presented on a Bayesian approach to 3D surface reconstruction and camera calibration.Existing methods, surface analysis and modeling,preliminary surface reconstruction results, and potential applications are addressed.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

Radar analysis of free oscillations of rail for diagnostics defects

NASA Astrophysics Data System (ADS)

Shaydurov, G. Y.; Kudinov, D. S.; Kokhonkova, E. A.; Potylitsyn, V. S.

2018-05-01

One of the tasks of developing and implementing defectoscopy devices is the minimal influence of the human factor in their exploitation. At present, rail inspection systems do not have sufficient depth of rail research, and ultrasonic diagnostics systems need to contact the sensor with the surface being studied, which leads to low productivity. The article gives a comparative analysis of existing noncontact methods of flaw detection, offers a contactless method of diagnostics by excitation of acoustic waves and extraction of information about defects from the frequency of free rail oscillations using the radar method.

Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms

PubMed Central

Sunderland, Kevin; Haferman, Christopher; Chintalapani, Gouthami

2016-01-01

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ 2 and Q-criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments. PMID:27891172

Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms.

PubMed

Sunderland, Kevin; Haferman, Christopher; Chintalapani, Gouthami; Jiang, Jingfeng

2016-01-01

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in "patient-specific" geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ 2 and Q -criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments.

Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Fan, Qingju; Wu, Yonghong

2015-08-01

In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Adolescent judgment of sexual content on television: implications for future content analysis research.

PubMed

Manganello, Jennifer A; Henderson, Vani R; Jordan, Amy; Trentacoste, Nicole; Martin, Suzanne; Hennessy, Michael; Fishbein, Martin

2010-07-01

Many studies of sexual messages in media utilize content analysis methods. At times, this research assumes that researchers and trained coders using content analysis methods and the intended audience view and interpret media content similarly. This article compares adolescents' perceptions of the presence or absence of sexual content on television to those of researchers using three different coding schemes. Results from this formative research study suggest that participants and researchers are most likely to agree with content categories assessing manifest content, and that differences exist among adolescents who view sexual messages on television. Researchers using content analysis methods to examine sexual content in media and media effects on sexual behavior should consider identifying how audience characteristics may affect interpretation of content and account for audience perspectives in content analysis study protocols when appropriate for study goals.

Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis with Co-occurrence Data.

PubMed

Schouten, Kim; van der Weijde, Onne; Frasincar, Flavius; Dekker, Rommert

2018-04-01

Using online consumer reviews as electronic word of mouth to assist purchase-decision making has become increasingly popular. The Web provides an extensive source of consumer reviews, but one can hardly read all reviews to obtain a fair evaluation of a product or service. A text processing framework that can summarize reviews, would therefore be desirable. A subtask to be performed by such a framework would be to find the general aspect categories addressed in review sentences, for which this paper presents two methods. In contrast to most existing approaches, the first method presented is an unsupervised method that applies association rule mining on co-occurrence frequency data obtained from a corpus to find these aspect categories. While not on par with state-of-the-art supervised methods, the proposed unsupervised method performs better than several simple baselines, a similar but supervised method, and a supervised baseline, with an -score of 67%. The second method is a supervised variant that outperforms existing methods with an -score of 84%.

A simple analytical procedure to replace HPLC for monitoring treatment concentrations of chloramine-T on fish culture facilities

USGS Publications Warehouse

Dawson, Verdel K.; Meinertz, Jeffery R.; Schmidt, Larry J.; Gingerich, William H.

2003-01-01

Concentrations of chloramine-T must be monitored during experimental treatments of fish when studying the effectiveness of the drug for controlling bacterial gill disease. A surrogate analytical method for analysis of chloramine-T to replace the existing high-performance liquid chromatography (HPLC) method is described. A surrogate method was needed because the existing HPLC method is expensive, requires a specialist to use, and is not generally available at fish hatcheries. Criteria for selection of a replacement method included ease of use, analysis time, cost, safety, sensitivity, accuracy, and precision. The most promising approach was to use the determination of chlorine concentrations as an indicator of chloramine-T. Of the currently available methods for analysis of chlorine, the DPD (N,N-diethyl-p-phenylenediamine) colorimetric method best fit the established criteria. The surrogate method was evaluated under a variety of water quality conditions. Regression analysis of all DPD colorimetric analyses with the HPLC values produced a linear model (Y=0.9602 X+0.1259) with an r2 value of 0.9960. The average accuracy (percent recovery) of the DPD method relative to the HPLC method for the combined set of water quality data was 101.5%. The surrogate method was also evaluated with chloramine-T solutions that contained various concentrations of fish feed or selected densities of rainbow trout. When samples were analyzed within 2 h, the results of the surrogate method were consistent with those of the HPLC method. When samples with high concentrations of organic material were allowed to age more than 2 h before being analyzed, the DPD method seemed to be susceptible to interference, possibly from the development of other chloramine compounds. However, even after aging samples 6 h, the accuracy of the surrogate DPD method relative to the HPLC method was within the range of 80–120%. Based on the data comparing the two methods, the U.S. Food and Drug Administration has concluded that the DPD colorimetric method is appropriate to use to measure chloramine-T in water during pivotal efficacy trials designed to support the approval of chloramine-T for use in fish culture.

In Search of a Time Efficient Approach to Crack and Delamination Growth Predictions in Composites

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Carvalho, Nelson

2016-01-01

Analysis benchmarking was used to assess the accuracy and time efficiency of algorithms suitable for automated delamination growth analysis. First, the Floating Node Method (FNM) was introduced and its combination with a simple exponential growth law (Paris Law) and Virtual Crack Closure technique (VCCT) was discussed. Implementation of the method into a user element (UEL) in Abaqus/Standard(Registered TradeMark) was also presented. For the assessment of growth prediction capabilities, an existing benchmark case based on the Double Cantilever Beam (DCB) specimen was briefly summarized. Additionally, the development of new benchmark cases based on the Mixed-Mode Bending (MMB) specimen to assess the growth prediction capabilities under mixed-mode I/II conditions was discussed in detail. A comparison was presented, in which the benchmark cases were used to assess the existing low-cycle fatigue analysis tool in Abaqus/Standard(Registered TradeMark) in comparison to the FNM-VCCT fatigue growth analysis implementation. The low-cycle fatigue analysis tool in Abaqus/Standard(Registered TradeMark) was able to yield results that were in good agreement with the DCB benchmark example. Results for the MMB benchmark cases, however, only captured the trend correctly. The user element (FNM-VCCT) always yielded results that were in excellent agreement with all benchmark cases, at a fraction of the analysis time. The ability to assess the implementation of two methods in one finite element code illustrated the value of establishing benchmark solutions.

Preliminary Tests For Development Of A Non-Pertechnetate Analysis Method

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

Diprete, D.; McCabe, D.

2016-09-28

The objective of this task was to develop a non-pertechnetate analysis method that 222-S lab could easily implement. The initial scope involved working with 222-S laboratory personnel to adapt the existing Tc analytical method to fractionate the non-pertechnetate and pertechnetate. SRNL then developed and tested a method using commercial sorbents containing Aliquat ® 336 to extract the pertechnetate (thereby separating it from non-pertechnetate), followed by oxidation, extraction, and stripping steps, and finally analysis by beta counting and Mass Spectroscopy. Several additional items were partially investigated, including impacts of a 137Cs removal step. The method was initially tested on SRS tankmore » waste samples to determine its viability. Although SRS tank waste does not contain non-pertechnetate, testing with it was useful to investigate the compatibility, separation efficiency, interference removal efficacy, and method sensitivity.« less

Simultaneous determination of flubendiamide its metabolite desiodo flubendiamide residues in cabbage, tomato and pigeon pea by HPLC.

PubMed

Paramasivam, M; Banerjee, Hemanta

2011-10-01

A sensitive and simple method for simultaneous analysis of flubendiamide and its metabolite desiodo flubendiamide in cabbage, tomato and pigeon pea has been developed. The residues were extracted with QuEChERS method followed by dispersive solid-phase extraction with primary secondary amine sorbent to remove co extractives, prior to analysis by HPLC coupled with UV-Vis detector. The recoveries of flubendiamide and desiodo flubendiamide were ranged from 85.1 to 98.5% and 85.9 to 97.1% respectively with relative standard deviations (RSD) less than 5% and sensitivity of 0.01 μg g(-1). The method offers a less expensive and safer alternative to the existing residue analysis methods for vegetables. © Springer Science+Business Media, LLC 2011

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

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

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions.more » The experiments show that this method can improve the recognition rate and the time of feature extraction.« less

Further studies using matched filter theory and stochastic simulation for gust loads prediction

NASA Technical Reports Server (NTRS)

Scott, Robert C.; Pototzky, Anthony S.; Perry, Boyd Iii

1993-01-01

This paper describes two analysis methods -- one deterministic, the other stochastic -- for computing maximized and time-correlated gust loads for aircraft with nonlinear control systems. The first method is based on matched filter theory; the second is based on stochastic simulation. The paper summarizes the methods, discusses the selection of gust intensity for each method and presents numerical results. A strong similarity between the results from the two methods is seen to exist for both linear and nonlinear configurations.

Feasibility of using a seismic surface wave method to study seasonal and weather effects on shallow surface soils

USDA-ARS?s Scientific Manuscript database

The objective of the paper is to study the temporal variations of the subsurface soil properties due to seasonal and weather effects using a combination of a new seismic surface method and an existing acoustic probe system. A laser Doppler vibrometer (LDV) based multi-channel analysis of surface wav...

Analysis of Semiotic Principles in a Constructivist Learning Environment.

ERIC Educational Resources Information Center

Williams, Paul

To advance nuclear plant simulator training, the industry must focus on a more detailed and theoretical approach to conduct of this training. The use of semiotics is one method of refining the existing training and examining ways to diversify and blend it with new theoretical methods. Semiotics is the study of signs and how humans interpret them.…

SIMPLE SAMPLE CLEAN UP PROCEDURE AND HIGH PERFORMANCE LIQUID CHROMATOGRAPHIC METHOD FOR THE ANALYSIS OF CYANURIC ACID IN HUMAN URINE

EPA Science Inventory

Cyanuric acide (CA) is widely used as a chlorine stabilizer in outdoor pools. No simple method exists for CA measurement in the urine of exposed swimmers. The high hydrophilicity of CA makes usage of solid phase sorbents to extract it from urine nearly impossible because of samp...

Methodological Issues in Questionnaire Design.

PubMed

Song, Youngshin; Son, Youn Jung; Oh, Doonam

2015-06-01

The process of designing a questionnaire is complicated. Many questionnaires on nursing phenomena have been developed and used by nursing researchers. The purpose of this paper was to discuss questionnaire design and factors that should be considered when using existing scales. Methodological issues were discussed, such as factors in the design of questions, steps in developing questionnaires, wording and formatting methods for items, and administrations methods. How to use existing scales, how to facilitate cultural adaptation, and how to prevent socially desirable responding were discussed. Moreover, the triangulation method in questionnaire development was introduced. Steps were recommended for designing questions such as appropriately operationalizing key concepts for the target population, clearly formatting response options, generating items and confirming final items through face or content validity, sufficiently piloting the questionnaire using item analysis, demonstrating reliability and validity, finalizing the scale, and training the administrator. Psychometric properties and cultural equivalence should be evaluated prior to administration when using an existing questionnaire and performing cultural adaptation. In the context of well-defined nursing phenomena, logical and systematic methods will contribute to the development of simple and precise questionnaires.

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

PubMed Central

Yin, Zheng; Zhou, Xiaobo; Bakal, Chris; Li, Fuhai; Sun, Youxian; Perrimon, Norbert; Wong, Stephen TC

2008-01-01

Background The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms. Conclusion We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens. PMID:18534020

An Evaluation of Normal versus Lognormal Distribution in Data Description and Empirical Analysis

ERIC Educational Resources Information Center

Diwakar, Rekha

2017-01-01

Many existing methods of statistical inference and analysis rely heavily on the assumption that the data are normally distributed. However, the normality assumption is not fulfilled when dealing with data which does not contain negative values or are otherwise skewed--a common occurrence in diverse disciplines such as finance, economics, political…

Considerations for the Systematic Analysis and Use of Single-Case Research

ERIC Educational Resources Information Center

Horner, Robert H.; Swaminathan, Hariharan; Sugai, George; Smolkowski, Keith

2012-01-01

Single-case research designs provide a rigorous research methodology for documenting experimental control. If single-case methods are to gain wider application, however, a need exists to define more clearly (a) the logic of single-case designs, (b) the process and decision rules for visual analysis, and (c) an accepted process for integrating…

Nanodevices for Single Molecule Studies

NASA Astrophysics Data System (ADS)

Craighead, H. G.; Stavis, S. M.; Samiee, K. T.

During the last two decades, biotechnology research has resulted in progress in fields as diverse as the life sciences, agriculture and healthcare. While existing technology enables the analysis of a variety of biological systems, new tools are needed for increasing the efficiency of current methods, and for developing new ones altogether. Interest has grown in single molecule analysis for these reasons.

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

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

PubMed

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

2018-04-11

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

Improvement of Method for Estimation of Site Amplification Factor Based on Average Shear-wave Velocity of Ground

NASA Astrophysics Data System (ADS)

Yamaguchi, Makoto; Midorikawa, Saburoh

The empirical equation for estimating the site amplification factor of ground motion by the average shear-wave velocity of ground (AVS) is examined. In the existing equations, the coefficient on dependence of the amplification factor on the AVS was treated as constant. The analysis showed that the coefficient varies with change of the AVS for short periods. A new estimation equation was proposed considering the dependence on the AVS. The new equation can represent soil characteristics that the softer soil has the longer predominant period, and can make better estimations for short periods than the existing method.

Estimating clinical chemistry reference values based on an existing data set of unselected animals.

PubMed

Dimauro, Corrado; Bonelli, Piero; Nicolussi, Paola; Rassu, Salvatore P G; Cappio-Borlino, Aldo; Pulina, Giuseppe

2008-11-01

In an attempt to standardise the determination of biological reference values, the International Federation of Clinical Chemistry (IFCC) has published a series of recommendations on developing reference intervals. The IFCC recommends the use of an a priori sampling of at least 120 healthy individuals. However, such a high number of samples and laboratory analysis is expensive, time-consuming and not always feasible, especially in veterinary medicine. In this paper, an alternative (a posteriori) method is described and is used to determine reference intervals for biochemical parameters of farm animals using an existing laboratory data set. The method used was based on the detection and removal of outliers to obtain a large sample of animals likely to be healthy from the existing data set. This allowed the estimation of reliable reference intervals for biochemical parameters in Sarda dairy sheep. This method may also be useful for the determination of reference intervals for different species, ages and gender.

A Goal Oriented Approach for Modeling and Analyzing Security Trade-Offs

NASA Astrophysics Data System (ADS)

Elahi, Golnaz; Yu, Eric

In designing software systems, security is typically only one design objective among many. It may compete with other objectives such as functionality, usability, and performance. Too often, security mechanisms such as firewalls, access control, or encryption are adopted without explicit recognition of competing design objectives and their origins in stakeholder interests. Recently, there is increasing acknowledgement that security is ultimately about trade-offs. One can only aim for "good enough" security, given the competing demands from many parties. In this paper, we examine how conceptual modeling can provide explicit and systematic support for analyzing security trade-offs. After considering the desirable criteria for conceptual modeling methods, we examine several existing approaches for dealing with security trade-offs. From analyzing the limitations of existing methods, we propose an extension to the i* framework for security trade-off analysis, taking advantage of its multi-agent and goal orientation. The method was applied to several case studies used to exemplify existing approaches.

Lactase persistence genotyping on whole blood by loop-mediated isothermal amplification and melting curve analysis.

PubMed

Abildgaard, Anders; Tovbjerg, Sara K; Giltay, Axel; Detemmerman, Liselot; Nissen, Peter H

2018-03-26

The lactase persistence phenotype is controlled by a regulatory enhancer region upstream of the Lactase (LCT) gene. In northern Europe, specifically the -13910C > T variant has been associated with lactase persistence whereas other persistence variants, e.g. -13907C > G and -13915 T > G, have been identified in Africa and the Middle East. The aim of the present study was to compare a previously developed high resolution melting assay (HRM) with a novel method based on loop-mediated isothermal amplification and melting curve analysis (LAMP-MC) with both whole blood and DNA as input material. To evaluate the LAMP-MC method, we used 100 whole blood samples and 93 DNA samples in a two tiered study. First, we studied the ability of the LAMP-MC method to produce specific melting curves for several variants of the LCT enhancer region. Next, we performed a blinded comparison between the LAMP-MC method and our existing HRM method with clinical samples of unknown genotype. The LAMP-MC method produced specific melting curves for the variants at position -13909, -13910, -13913 whereas the -13907C > G and -13915 T > G variants produced indistinguishable melting profiles. The LAMP-MC assay is a simple method for lactase persistence genotyping and compares well with our existing HRM method. Copyright © 2018. Published by Elsevier B.V.

Review Article "Valuating the intangible effects of natural hazards - review and analysis of the costing methods"

NASA Astrophysics Data System (ADS)

Markantonis, V.; Meyer, V.; Schwarze, R.

2012-05-01

The "intangible" or "non-market" effects are those costs of natural hazards which are not, or at least not easily measurable in monetary terms, as for example, impacts on health, cultural heritage or the environment. The intangible effects are often not included in costs assessments of natural hazards leading to an incomplete and biased cost assessment. However, several methods exist which try to estimate these effects in a non-monetary or monetary form. The objective of the present paper is to review and evaluate methods for estimating the intangible effects of natural hazards, specifically related to health and environmental effects. Existing methods are analyzed and compared using various criteria, research gaps are identified, application recommendations are provided, and valuation issues that should be addressed by the scientific community are highlighted.

Global Mittag-Leffler stability analysis of fractional-order impulsive neural networks with one-side Lipschitz condition.

PubMed

Zhang, Xinxin; Niu, Peifeng; Ma, Yunpeng; Wei, Yanqiao; Li, Guoqiang

2017-10-01

This paper is concerned with the stability analysis issue of fractional-order impulsive neural networks. Under the one-side Lipschitz condition or the linear growth condition of activation function, the existence of solution is analyzed respectively. In addition, the existence, uniqueness and global Mittag-Leffler stability of equilibrium point of the fractional-order impulsive neural networks with one-side Lipschitz condition are investigated by the means of contraction mapping principle and Lyapunov direct method. Finally, an example with numerical simulation is given to illustrate the validity and feasibility of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving estimates of genetic maps: a meta-analysis-based approach.

PubMed

Stewart, William C L

2007-07-01

Inaccurate genetic (or linkage) maps can reduce the power to detect linkage, increase type I error, and distort haplotype and relationship inference. To improve the accuracy of existing maps, I propose a meta-analysis-based method that combines independent map estimates into a single estimate of the linkage map. The method uses the variance of each independent map estimate to combine them efficiently, whether the map estimates use the same set of markers or not. As compared with a joint analysis of the pooled genotype data, the proposed method is attractive for three reasons: (1) it has comparable efficiency to the maximum likelihood map estimate when the pooled data are homogeneous; (2) relative to existing map estimation methods, it can have increased efficiency when the pooled data are heterogeneous; and (3) it avoids the practical difficulties of pooling human subjects data. On the basis of simulated data modeled after two real data sets, the proposed method can reduce the sampling variation of linkage maps commonly used in whole-genome linkage scans. Furthermore, when the independent map estimates are also maximum likelihood estimates, the proposed method performs as well as or better than when they are estimated by the program CRIMAP. Since variance estimates of maps may not always be available, I demonstrate the feasibility of three different variance estimators. Overall, the method should prove useful to investigators who need map positions for markers not contained in publicly available maps, and to those who wish to minimize the negative effects of inaccurate maps. Copyright 2007 Wiley-Liss, Inc.

Spatial Lattice Modulation for MIMO Systems

NASA Astrophysics Data System (ADS)

Choi, Jiwook; Nam, Yunseo; Lee, Namyoon

2018-06-01

This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate information bits into a multi-dimensional signal set that consists oflattice points. One major finding is that SLM achieves a higher spectral efficiency than the existing spatial modulation and spatial multiplexing methods for the MIMO channel under the constraint ofM-ary pulseamplitude-modulation (PAM) input signaling per dimension. In particular, it is shown that when the SLM signal set is constructed by using dense lattices, a significant signal-to-noise-ratio (SNR) gain, i.e., a nominal coding gain, is attainable compared to the existing methods. In addition, closed-form expressions for both the average mutual information and average symbol-vector-error-probability (ASVEP) of generic SLM are derived under Rayleigh-fading environments. To reduce detection complexity, a low-complexity detection method for SLM, which is referred to as lattice sphere decoding, is developed by exploiting lattice theory. Simulation results verify the accuracy of the conducted analysis and demonstrate that the proposed SLM techniques achieve higher average mutual information and lower ASVEP than do existing methods.

On existence of the σ(600) Its physical implications and related problems

NASA Astrophysics Data System (ADS)

Ishida, Shin

1998-05-01

We make a re-analysis of 1=0 ππ scattering phase shift δ00 through a new method of S-matrix parametrization (IA; interfering amplitude method), and show a result suggesting strongly for the existence of σ-particle-long-sought Chiral partner of π-meson. Furthermore, through the phenomenological analyses of typical production processes of the 2π-system, the pp-central collision and the J/Ψ→ωππ decay, by applying an intuitive formula as sum of Breit-Wigner amplitudes, (VMW; variant mass and width method), the other evidences for the σ-existence are given. The validity of the methods used in the above analyses is investigated, using a simple field theoretical model, from the general viewpoint of unitarity and the applicability of final state interaction (FSI-) theorem, especially in relation to the "universality" argument. It is shown that the IA and VMW are obtained as the physical state representations of scattering and production amplitudes, respectively. The VMW is shown to be an effective method to obtain the resonance properties from production processes, which generally have the unknown strong-phases. The conventional analyses based on the "universality" seem to be powerless for this purpose.

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

PubMed Central

Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi

2016-01-01

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637

Using stable isotopes to monitor forms of sulfur during desulfurization processes: A quick screening method

USGS Publications Warehouse

Liu, Chao-Li; Hackley, Keith C.; Coleman, D.D.; Kruse, C.W.

1987-01-01

A method using stable isotope ratio analysis to monitor the reactivity of sulfur forms in coal during thermal and chemical desulfurization processes has been developed at the Illinois State Geological Survey. The method is based upon the fact that a significant difference exists in some coals between the 34S/32S ratios of the pyritic and organic sulfur. A screening method for determining the suitability of coal samples for use in isotope ratio analysis is described. Making these special coals available from coal sample programs would assist research groups in sorting out the complex sulfur chemistry which accompanies thermal and chemical processing of high sulfur coals. ?? 1987.

Fast algorithm for spectral mixture analysis of imaging spectrometer data

NASA Astrophysics Data System (ADS)

Schouten, Theo E.; Klein Gebbinck, Maurice S.; Liu, Z. K.; Chen, Shaowei

1996-12-01

Imaging spectrometers acquire images in many narrow spectral bands but have limited spatial resolution. Spectral mixture analysis (SMA) is used to determine the fractions of the ground cover categories (the end-members) present in each pixel. In this paper a new iterative SMA method is presented and tested using a 30 band MAIS image. The time needed for each iteration is independent of the number of bands, thus the method can be used for spectrometers with a large number of bands. Further a new method, based on K-means clustering, for obtaining endmembers from image data is described and compared with existing methods. Using the developed methods the available MAIS image was analyzed using 2 to 6 endmembers.

An improved method for predicting the lightning performance of high and extra-high-voltage substation shielding

NASA Astrophysics Data System (ADS)

Vinh, T.

1980-08-01

There is a need for better and more effective lightning protection for transmission and switching substations. In the past, a number of empirical methods were utilized to design systems to protect substations and transmission lines from direct lightning strokes. The need exists for convenient analytical lightning models adequate for engineering usage. In this study, analytical lightning models were developed along with a method for improved analysis of the physical properties of lightning through their use. This method of analysis is based upon the most recent statistical field data. The result is an improved method for predicting the occurrence of sheilding failure and for designing more effective protection for high and extra high voltage substations from direct strokes.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

A robust two-way semi-linear model for normalization of cDNA microarray data

PubMed Central

Wang, Deli; Huang, Jian; Xie, Hehuang; Manzella, Liliana; Soares, Marcelo Bento

2005-01-01

Background Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. Methods We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. Results The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method. Conclusions Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods. PMID:15663789

Review: Quantifying animal feeding behaviour with a focus on pigs.

PubMed

Maselyne, Jarissa; Saeys, Wouter; Van Nuffel, Annelies

2015-01-01

The study of animal feeding behaviour is of interest to understand feeding, to investigate the effect of treatments and conditions or to predict illness. This paper reviews the different steps to undertake when studying animal feeding behaviour, with illustrations for group-housed pigs. First, one must be aware of the mechanisms that control feeding and the various influences that can change feeding behaviour. Satiety is shown to largely influence free feeding (ad libitum and without an operant condition) in animals, but 'free' feeding seems a very fragile process, given the many factors that can influence feeding behaviour. Second, a measurement method must be chosen that is compatible with the goal of the research. Several measurement methods exist, which lead to different experimental set-ups and measurement data. Sensors are available for lab conditions, for research on group-housed pigs and also for on-farm use. Most of these methods result in a record of feeding visits. However, these feeding visits are often found to be clustered into meals. Thus, the third step is to choose which unit of feeding behaviour to use for analysis. Depending on the situation, either meals, feeding visits, other raw data, or a combination thereof can be suitable. Meals are more appropriate for analysing short-term feeding behaviour, but this may not be true for disease detection. Further research is therefore needed. To cluster visits into meals, an appropriate analysis method has to be selected. The last part of this paper provides a review and discussion of the existing methods for meal determination. A variety of methods exist, with the most recent methods based on the influence of satiety on feeding. More thorough validation of the recent methods, including validation from a behavioural point of view and uniformity in the applied methods is therefore necessary. Copyright © 2014 Elsevier Inc. All rights reserved.

Do regional methods really help reduce uncertainties in flood frequency analyses?

NASA Astrophysics Data System (ADS)

Cong Nguyen, Chi; Payrastre, Olivier; Gaume, Eric

2013-04-01

Flood frequency analyses are often based on continuous measured series at gauge sites. However, the length of the available data sets is usually too short to provide reliable estimates of extreme design floods. To reduce the estimation uncertainties, the analyzed data sets have to be extended either in time, making use of historical and paleoflood data, or in space, merging data sets considered as statistically homogeneous to build large regional data samples. Nevertheless, the advantage of the regional analyses, the important increase of the size of the studied data sets, may be counterbalanced by the possible heterogeneities of the merged sets. The application and comparison of four different flood frequency analysis methods to two regions affected by flash floods in the south of France (Ardèche and Var) illustrates how this balance between the number of records and possible heterogeneities plays in real-world applications. The four tested methods are: (1) a local statistical analysis based on the existing series of measured discharges, (2) a local analysis valuating the existing information on historical floods, (3) a standard regional flood frequency analysis based on existing measured series at gauged sites and (4) a modified regional analysis including estimated extreme peak discharges at ungauged sites. Monte Carlo simulations are conducted to simulate a large number of discharge series with characteristics similar to the observed ones (type of statistical distributions, number of sites and records) to evaluate to which extent the results obtained on these case studies can be generalized. These two case studies indicate that even small statistical heterogeneities, which are not detected by the standard homogeneity tests implemented in regional flood frequency studies, may drastically limit the usefulness of such approaches. On the other hand, these result show that the valuation of information on extreme events, either historical flood events at gauged sites or estimated extremes at ungauged sites in the considered region, is an efficient way to reduce uncertainties in flood frequency studies.

Advanced space-based InSAR risk analysis of planned and existing transportation infrastructure.

DOT National Transportation Integrated Search

2017-03-21

The purpose of this document is to summarize activities by Stanford University and : MDA Geospatial Services Inc. (MDA) to estimate surface deformation and associated : risk to transportation infrastructure using SAR Interferometric methods for the :...

Electrospray ionization time-of-flight mass spectrum analysis method of polyaluminum chloride flocculants.

PubMed

Feng, Chenghong; Bi, Zhe; Tang, Hongxiao

2015-01-06

Electrospray mass spectrometry has been reported as a novel technique for Al species identification, but to date, the working mechanism is not clear and no unanimous method exists for spectrum analysis of traditional Al salt flocculants, let alone for analysis of polyaluminum chloride (PAC) flocculants. Therefore, this paper introduces a novel theoretical calculation method to identify Al species from a mass spectrum, based on deducing changes in m/z (mass-to-charge ratio) and molecular formulas of oligomers in five typical PAC flocculants. The use of reference chemical species was specially proposed in the method to guarantee the uniqueness of the assigned species. The charge and mass reduction of the Al cluster was found to proceed by hydrolysis, gasification, and change of hydroxyl on the oxy bridge. The novel method was validated both qualitatively and quantitatively by comparing the results to those obtained with the (27)Al NMR spectrometry.

[Application of Stata software to test heterogeneity in meta-analysis method].

PubMed

Wang, Dan; Mou, Zhen-yun; Zhai, Jun-xia; Zong, Hong-xia; Zhao, Xiao-dong

2008-07-01

To introduce the application of Stata software to heterogeneity test in meta-analysis. A data set was set up according to the example in the study, and the corresponding commands of the methods in Stata 9 software were applied to test the example. The methods used were Q-test and I2 statistic attached to the fixed effect model forest plot, H statistic and Galbraith plot. The existence of the heterogeneity among studies could be detected by Q-test and H statistic and the degree of the heterogeneity could be detected by I2 statistic. The outliers which were the sources of the heterogeneity could be spotted from the Galbraith plot. Heterogeneity test in meta-analysis can be completed by the four methods in Stata software simply and quickly. H and I2 statistics are more robust, and the outliers of the heterogeneity can be clearly seen in the Galbraith plot among the four methods.

Dynamic Analysis With Stress Mode Animation by the Integrated Force Method

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Hopkins, Dale A.

1997-01-01

Dynamic animation of stresses and displacements, which complement each other, can be a useful tool in the analysis and design of structural components. At the present time only displacement-mode animation is available through the popular stiffness formulation. This paper attempts to complete this valuable visualization tool by augmenting the existing art with stress mode animation. The reformulated method of forces, which in the literature is known as the integrated force method (IFM), became the analyzer of choice for the development of stress mode animation because stresses are the primary unknowns of its dynamic analysis. Animation of stresses and displacements, which have been developed successfully through the IFM analyzers, is illustrated in several examples along with a brief introduction to IFM dynamic analysis. The usefulness of animation in design optimization is illustrated considering the spacer structure component of the International Space Station as an example. An overview of the integrated force method analysis code (IFM/ANALYZERS) is provided in the appendix.

The Flight Optimization System Weights Estimation Method

NASA Technical Reports Server (NTRS)

Wells, Douglas P.; Horvath, Bryce L.; McCullers, Linwood A.

2017-01-01

FLOPS has been the primary aircraft synthesis software used by the Aeronautics Systems Analysis Branch at NASA Langley Research Center. It was created for rapid conceptual aircraft design and advanced technology impact assessments. FLOPS is a single computer program that includes weights estimation, aerodynamics estimation, engine cycle analysis, propulsion data scaling and interpolation, detailed mission performance analysis, takeoff and landing performance analysis, noise footprint estimation, and cost analysis. It is well known as a baseline and common denominator for aircraft design studies. FLOPS is capable of calibrating a model to known aircraft data, making it useful for new aircraft and modifications to existing aircraft. The weight estimation method in FLOPS is known to be of high fidelity for conventional tube with wing aircraft and a substantial amount of effort went into its development. This report serves as a comprehensive documentation of the FLOPS weight estimation method. The development process is presented with the weight estimation process.

The Beck Depression Inventory, Second Edition (BDI-II): A Cross-Sample Structural Analysis

ERIC Educational Resources Information Center

Strunk, Kamden K.; Lane, Forrest C.

2017-01-01

A common concern about the Beck Depression Inventory, Second edition (BDI-II) among researchers in the area of depression has long been the single-factor scoring scheme. Methods exist for making cross-sample comparisons of latent structure but tend to rely on estimation methods that can be imprecise and unnecessarily complex. This study presents a…

Studying the Effectiveness of Physical Education in the Secondary School (by the Example of Kazakhstan)

ERIC Educational Resources Information Center

Botagariyev, ?ulegen A.; Kubiyeva, Svetlana S.; Baizakova, Venera E.; Mambetov, Nurolla; Tulegenov, Yerkin K.; Aralbayev, Alpysbay S.; Kairgozhin, Dulat U.

2016-01-01

The purpose of this study was to determine the effectiveness of the existing model of teaching physical training in secondary schools and the analysis of a game like method introduced to improve physical fitness of students. The authors substantiated the use of a game like method during physical training classes, which implementation should create…

Construction of Expert Knowledge Monitoring and Assessment System Based on Integral Method of Knowledge Evaluation

ERIC Educational Resources Information Center

Golovachyova, Viktoriya N.; Menlibekova, Gulbakhyt Zh.; Abayeva, Nella F.; Ten, Tatyana L.; Kogaya, Galina D.

2016-01-01

Using computer-based monitoring systems that rely on tests could be the most effective way of knowledge evaluation. The problem of objective knowledge assessment by means of testing takes on a new dimension in the context of new paradigms in education. The analysis of the existing test methods enabled us to conclude that tests with selected…

Evaluating phylogenetic congruence in the post-genomic era.

PubMed

Leigh, Jessica W; Lapointe, François-Joseph; Lopez, Philippe; Bapteste, Eric

2011-01-01

Congruence is a broadly applied notion in evolutionary biology used to justify multigene phylogeny or phylogenomics, as well as in studies of coevolution, lateral gene transfer, and as evidence for common descent. Existing methods for identifying incongruence or heterogeneity using character data were designed for data sets that are both small and expected to be rarely incongruent. At the same time, methods that assess incongruence using comparison of trees test a null hypothesis of uncorrelated tree structures, which may be inappropriate for phylogenomic studies. As such, they are ill-suited for the growing number of available genome sequences, most of which are from prokaryotes and viruses, either for phylogenomic analysis or for studies of the evolutionary forces and events that have shaped these genomes. Specifically, many existing methods scale poorly with large numbers of genes, cannot accommodate high levels of incongruence, and do not adequately model patterns of missing taxa for different markers. We propose the development of novel incongruence assessment methods suitable for the analysis of the molecular evolution of the vast majority of life and support the investigation of homogeneity of evolutionary process in cases where markers do not share identical tree structures.

Automated Detection of Electroencephalography Artifacts in Human, Rodent and Canine Subjects using Machine Learning.

PubMed

Levitt, Joshua; Nitenson, Adam; Koyama, Suguru; Heijmans, Lonne; Curry, James; Ross, Jason T; Kamerling, Steven; Saab, Carl Y

2018-06-23

Electroencephalography (EEG) invariably contains extra-cranial artifacts that are commonly dealt with based on qualitative and subjective criteria. Failure to account for EEG artifacts compromises data interpretation. We have developed a quantitative and automated support vector machine (SVM)-based algorithm to accurately classify artifactual EEG epochs in awake rodent, canine and humans subjects. An embodiment of this method also enables the determination of 'eyes open/closed' states in human subjects. The levels of SVM accuracy for artifact classification in humans, Sprague Dawley rats and beagle dogs were 94.17%, 83.68%, and 85.37%, respectively, whereas 'eyes open/closed' states in humans were labeled with 88.60% accuracy. Each of these results was significantly higher than chance. Comparison with Existing Methods: Other existing methods, like those dependent on Independent Component Analysis, have not been tested in non-human subjects, and require full EEG montages, instead of only single channels, as this method does. We conclude that our EEG artifact detection algorithm provides a valid and practical solution to a common problem in the quantitative analysis and assessment of EEG in pre-clinical research settings across evolutionary spectra. Copyright © 2018. Published by Elsevier B.V.

Evaluating Phylogenetic Congruence in the Post-Genomic Era

PubMed Central

Leigh, Jessica W.; Lapointe, François-Joseph; Lopez, Philippe; Bapteste, Eric

2011-01-01

Congruence is a broadly applied notion in evolutionary biology used to justify multigene phylogeny or phylogenomics, as well as in studies of coevolution, lateral gene transfer, and as evidence for common descent. Existing methods for identifying incongruence or heterogeneity using character data were designed for data sets that are both small and expected to be rarely incongruent. At the same time, methods that assess incongruence using comparison of trees test a null hypothesis of uncorrelated tree structures, which may be inappropriate for phylogenomic studies. As such, they are ill-suited for the growing number of available genome sequences, most of which are from prokaryotes and viruses, either for phylogenomic analysis or for studies of the evolutionary forces and events that have shaped these genomes. Specifically, many existing methods scale poorly with large numbers of genes, cannot accommodate high levels of incongruence, and do not adequately model patterns of missing taxa for different markers. We propose the development of novel incongruence assessment methods suitable for the analysis of the molecular evolution of the vast majority of life and support the investigation of homogeneity of evolutionary process in cases where markers do not share identical tree structures. PMID:21712432

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

A linear stability analysis for nonlinear, grey, thermal radiative transfer problems

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

Wollaber, Allan B., E-mail: wollaber@lanl.go; Larsen, Edward W., E-mail: edlarsen@umich.ed

2011-02-20

We present a new linear stability analysis of three time discretizations and Monte Carlo interpretations of the nonlinear, grey thermal radiative transfer (TRT) equations: the widely used 'Implicit Monte Carlo' (IMC) equations, the Carter Forest (CF) equations, and the Ahrens-Larsen or 'Semi-Analog Monte Carlo' (SMC) equations. Using a spatial Fourier analysis of the 1-D Implicit Monte Carlo (IMC) equations that are linearized about an equilibrium solution, we show that the IMC equations are unconditionally stable (undamped perturbations do not exist) if {alpha}, the IMC time-discretization parameter, satisfies 0.5 < {alpha} {<=} 1. This is consistent with conventional wisdom. However, wemore » also show that for sufficiently large time steps, unphysical damped oscillations can exist that correspond to the lowest-frequency Fourier modes. After numerically confirming this result, we develop a method to assess the stability of any time discretization of the 0-D, nonlinear, grey, thermal radiative transfer problem. Subsequent analyses of the CF and SMC methods then demonstrate that the CF method is unconditionally stable and monotonic, but the SMC method is conditionally stable and permits unphysical oscillatory solutions that can prevent it from reaching equilibrium. This stability theory provides new conditions on the time step to guarantee monotonicity of the IMC solution, although they are likely too conservative to be used in practice. Theoretical predictions are tested and confirmed with numerical experiments.« less

A linear stability analysis for nonlinear, grey, thermal radiative transfer problems

NASA Astrophysics Data System (ADS)

Wollaber, Allan B.; Larsen, Edward W.

2011-02-01

We present a new linear stability analysis of three time discretizations and Monte Carlo interpretations of the nonlinear, grey thermal radiative transfer (TRT) equations: the widely used “Implicit Monte Carlo” (IMC) equations, the Carter Forest (CF) equations, and the Ahrens-Larsen or “Semi-Analog Monte Carlo” (SMC) equations. Using a spatial Fourier analysis of the 1-D Implicit Monte Carlo (IMC) equations that are linearized about an equilibrium solution, we show that the IMC equations are unconditionally stable (undamped perturbations do not exist) if α, the IMC time-discretization parameter, satisfies 0.5 < α ⩽ 1. This is consistent with conventional wisdom. However, we also show that for sufficiently large time steps, unphysical damped oscillations can exist that correspond to the lowest-frequency Fourier modes. After numerically confirming this result, we develop a method to assess the stability of any time discretization of the 0-D, nonlinear, grey, thermal radiative transfer problem. Subsequent analyses of the CF and SMC methods then demonstrate that the CF method is unconditionally stable and monotonic, but the SMC method is conditionally stable and permits unphysical oscillatory solutions that can prevent it from reaching equilibrium. This stability theory provides new conditions on the time step to guarantee monotonicity of the IMC solution, although they are likely too conservative to be used in practice. Theoretical predictions are tested and confirmed with numerical experiments.

A critical methodological review of discourse and conversation analysis studies of family therapy.

PubMed

Tseliou, Eleftheria

2013-12-01

Discourse (DA) and conversation (CA) analysis, two qualitative research methods, have been recently suggested as potentially promising for the study of family therapy due to common epistemological adherences and their potential for an in situ study of therapeutic dialog. However, to date, there is no systematic methodological review of the few existing DA and CA studies of family therapy. This study aims at addressing this lack by critically reviewing published DA and CA studies of family therapy on methodological grounds. Twenty-eight articles in total are reviewed in relation to certain methodological axes identified in the relevant literature. These include choice of method, framing of research question(s), data/sampling, type of analysis, epistemological perspective, content/type of knowledge claims, and attendance to criteria for good quality practice. It is argued that the reviewed studies show "glimpses" of the methods' potential for family therapy research despite the identification of certain "shortcomings" regarding their methodological rigor. These include unclearly framed research questions and the predominance of case study designs. They also include inconsistencies between choice of method, stated or unstated epistemological orientations and knowledge claims, and limited attendance to criteria for good quality practice. In conclusion, it is argued that DA and CA can add to the existing quantitative and qualitative methods for family therapy research. They can both offer unique ways for a detailed study of the actual therapeutic dialog, provided that future attempts strive for a methodologically rigorous practice and against their uncritical deployment. © FPI, Inc.

Zero leakage separable and semipermanent ducting joints

NASA Technical Reports Server (NTRS)

Mischel, H. T.

1973-01-01

A study program has been conducted to explore new methods of achieving zero leakage, separable and semipermanent, ducting joints for space flight vehicles. The study consisted of a search of literature of existing zero leakage methods, the generation of concepts of new methods of achieving the desired zero leakage criteria and the development of detailed analysis and design of a selected concept. Other techniques of leak detection were explored with a view toward improving this area.

Estimating Logistics Support of Reusable Launch Vehicles During Conceptual Design

NASA Technical Reports Server (NTRS)

Morris, W. D.; White, N. H.; Davies, W. T.; Ebeling, C. E.

1997-01-01

Methods exist to define the logistics support requirements for new aircraft concepts but are not directly applicable to new launch vehicle concepts. In order to define the support requirements and to discriminate among new technologies and processing choices for these systems, NASA Langley Research Center (LaRC) is developing new analysis methods. This paper describes several methods under development, gives their current status, and discusses the benefits and limitations associated with their use.

Surface Area Analysis Using the Brunauer-Emmett-Teller (BET) Method: Standard Operating Procedure Series: SOP-C

DTIC Science & Technology

2016-09-01

Method Scientific Operating Procedure Series : SOP-C En vi ro nm en ta l L ab or at or y Jonathon Brame and Chris Griggs September 2016...BET) Method Scientific Operating Procedure Series : SOP-C Jonathon Brame and Chris Griggs Environmental Laboratory U.S. Army Engineer Research and...response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing

Frequency-dependent FDTD methods using Z transforms

NASA Technical Reports Server (NTRS)

Sullivan, Dennis M.

1992-01-01

While the frequency-dependent finite-difference time-domain, or (FD)2TD, method can correctly calculate EM propagation through media whose dielectric properties are frequency-dependent, more elaborate applications lead to greater (FD)2TD complexity. Z-transform theory is presently used to develop the mathematical bases of the (FD)2TD method, simultaneously obtaining a clearer formulation and allowing researchers to draw on the existing literature of systems analysis and signal-processing.

Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

PubMed

Chen, Gang; Song, Yongduan; Guan, Yanfeng

2018-03-01

This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Power flow as a complement to statistical energy analysis and finite element analysis

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1987-01-01

Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.

BinQuasi: a peak detection method for ChIP-sequencing data with biological replicates.

PubMed

Goren, Emily; Liu, Peng; Wang, Chao; Wang, Chong

2018-04-19

ChIP-seq experiments that are aimed at detecting DNA-protein interactions require biological replication to draw inferential conclusions, however there is no current consensus on how to analyze ChIP-seq data with biological replicates. Very few methodologies exist for the joint analysis of replicated ChIP-seq data, with approaches ranging from combining the results of analyzing replicates individually to joint modeling of all replicates. Combining the results of individual replicates analyzed separately can lead to reduced peak classification performance compared to joint modeling. Currently available methods for joint analysis may fail to control the false discovery rate at the nominal level. We propose BinQuasi, a peak caller for replicated ChIP-seq data, that jointly models biological replicates using a generalized linear model framework and employs a one-sided quasi-likelihood ratio test to detect peaks. When applied to simulated data and real datasets, BinQuasi performs favorably compared to existing methods, including better control of false discovery rate than existing joint modeling approaches. BinQuasi offers a flexible approach to joint modeling of replicated ChIP-seq data which is preferable to combining the results of replicates analyzed individually. Source code is freely available for download at https://cran.r-project.org/package=BinQuasi, implemented in R. pliu@iastate.edu or egoren@iastate.edu. Supplementary material is available at Bioinformatics online.

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

The Extraction of Terrace in the Loess Plateau Based on radial method

NASA Astrophysics Data System (ADS)

Liu, W.; Li, F.

2016-12-01

The terrace of Loess Plateau, as a typical kind of artificial landform and an important measure of soil and water conservation, its positioning and automatic extraction will simplify the work of land use investigation. The existing methods of terrace extraction mainly include visual interpretation and automatic extraction. The manual method is used in land use investigation, but it is time-consuming and laborious. Researchers put forward some automatic extraction methods. For example, Fourier transform method can recognize terrace and find accurate position from frequency domain image, but it is more affected by the linear objects in the same direction of terrace; Texture analysis method is simple and have a wide range application of image processing. The disadvantage of texture analysis method is unable to recognize terraces' edge; Object-oriented is a new method of image classification, but when introduce it to terrace extracting, fracture polygons will be the most serious problem and it is difficult to explain its geological meaning. In order to positioning the terraces, we use high- resolution remote sensing image to extract and analyze the gray value of the pixels which the radial went through. During the recognition process, we firstly use the DEM data analysis or by manual selecting, to roughly confirm the position of peak points; secondly, take each of the peak points as the center to make radials in all directions; finally, extracting the gray values of the pixels which the radials went through, and analyzing its changing characteristics to confirm whether the terrace exists. For the purpose of getting accurate position of terrace, terraces' discontinuity, extension direction, ridge width, image processing algorithm, remote sensing image illumination and other influence factors were fully considered when designing the algorithms.

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

Tuo, Rui; Wu, C. F. Jeff

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

Nondestructive equipment study

NASA Technical Reports Server (NTRS)

1985-01-01

Identification of existing nondestructive Evaluation (NDE) methods that could be used in a low Earth orbit environment; evaluation of each method with respect to the set of criteria called out in the statement of work; selection of the most promising NDE methods for further evaluation; use of selected NDE methods to test samples of pressure vessel materials in a vacuum; pressure testing of a complex monolythic pressure vessel with known flaws using acoustic emissions in a vacuum; and recommendations for further studies based on analysis and testing are covered.

[Applications of meta-analysis in multi-omics].

PubMed

Han, Mingfei; Zhu, Yunping

2014-07-01

As a statistical method integrating multi-features and multi-data, meta-analysis was introduced to the field of life science in the 1990s. With the rapid advances in high-throughput technologies, life omics, the core of which are genomics, transcriptomics and proteomics, is becoming the new hot spot of life science. Although the fast output of massive data has promoted the development of omics study, it results in excessive data that are difficult to integrate systematically. In this case, meta-analysis is frequently applied to analyze different types of data and is improved continuously. Here, we first summarize the representative meta-analysis methods systematically, and then study the current applications of meta-analysis in various omics fields, finally we discuss the still-existing problems and the future development of meta-analysis.

A Comparative Analysis of Child Welfare Services through the Eyes of African American, Caucasian, and Latino Parents

ERIC Educational Resources Information Center

Ayon, Cecilia; Lee, Cheryl D.

2005-01-01

Objective: The purpose of this study was to find if differences exist among 88 African American, Caucasian, and Latino families who received child welfare services. Method: A secondary data analysis of cross-sectional survey data employing standardized measures was used for this study. Family preservation (FP) services were received by 49…

A Semi-Parametric Bayesian Mixture Modeling Approach for the Analysis of Judge Mediated Data

ERIC Educational Resources Information Center

Muckle, Timothy Joseph

2010-01-01

Existing methods for the analysis of ordinal-level data arising from judge ratings, such as the Multi-Facet Rasch model (MFRM, or the so-called Facets model) have been widely used in assessment in order to render fair examinee ability estimates in situations where the judges vary in their behavior or severity. However, this model makes certain…

A Product Analysis Method and Its Staging to Develop Redesign Competences

ERIC Educational Resources Information Center

Hansen, Claus Thorp; Lenau, Torben Anker

2013-01-01

Most product development work in industrial practice is incremental, i.e., the company has had a product in production and on the market for some time, and now time has come to design an upgraded variant. This type of redesign project requires that the engineering designers have competences to carry through an analysis of the existing product…

An analysis method for two-dimensional transonic viscous flow

NASA Technical Reports Server (NTRS)

Bavitz, P. C.

1975-01-01

A method for the approximate calculation of transonic flow over airfoils, including shock waves and viscous effects, is described. Numerical solutions are obtained by use of a computer program which is discussed in the appendix. The importance of including the boundary layer in the analysis is clearly demonstrated, as well as the need to improve on existing procedures near the trailing edge. Comparisons between calculations and experimental data are presented for both conventional and supercritical airfoils, emphasis being on the surface pressure distribution, and good agreement is indicated.

Social construction of the patient through problems of safety, uninsurance, and unequal treatment.

PubMed

Trigg, Lisa J

2009-01-01

The purpose of this research was to study how the Institute of Medicine discourse promoting health information technology may reproduce existing social inequalities in healthcare. Social constructionist and critical discourse analysis combined with corpus linguistics methods have been used to study the subject positions constructed for receivers of healthcare across the executive summaries of 3 different Institute of Medicine reports. Data analysis revealed differences in the way receivers of healthcare are constructed through variations of social action through language use in the 3 texts selected for this method's testing.

Highly Efficient Design-of-Experiments Methods for Combining CFD Analysis and Experimental Data

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Haller, Harold S.

2009-01-01

It is the purpose of this study to examine the impact of "highly efficient" Design-of-Experiments (DOE) methods for combining sets of CFD generated analysis data with smaller sets of Experimental test data in order to accurately predict performance results where experimental test data were not obtained. The study examines the impact of micro-ramp flow control on the shock wave boundary layer (SWBL) interaction where a complete paired set of data exist from both CFD analysis and Experimental measurements By combining the complete set of CFD analysis data composed of fifteen (15) cases with a smaller subset of experimental test data containing four/five (4/5) cases, compound data sets (CFD/EXP) were generated which allows the prediction of the complete set of Experimental results No statistical difference were found to exist between the combined (CFD/EXP) generated data sets and the complete Experimental data set composed of fifteen (15) cases. The same optimal micro-ramp configuration was obtained using the (CFD/EXP) generated data as obtained with the complete set of Experimental data, and the DOE response surfaces generated by the two data sets were also not statistically different.

Dynamic Pressure Distribution due to Horizontal Acceleration in Spherical LNG Tank with Cylindrical Central Part

NASA Astrophysics Data System (ADS)

Ko, Dae-Eun; Shin, Sang-Hoon

2017-11-01

Spherical LNG tanks having many advantages such as structural safety are used as a cargo containment system of LNG carriers. However, it is practically difficult to fabricate perfectly spherical tanks of different sizes in the yard. The most effective method of manufacturing LNG tanks of various capacities is to insert a cylindrical part at the center of existing spherical tanks. While a simplified high-precision analysis method for the initial design of the spherical tanks has been developed for both static and dynamic loads, in the case of spherical tanks with a cylindrical central part, the analysis method available only considers static loads. The purpose of the present study is to derive the dynamic pressure distribution due to horizontal acceleration, which is essential for developing an analysis method that considers dynamic loads as well.

Probabilistic Structural Analysis Methods (PSAM) for Select Space Propulsion System Components

NASA Technical Reports Server (NTRS)

1999-01-01

Probabilistic Structural Analysis Methods (PSAM) are described for the probabilistic structural analysis of engine components for current and future space propulsion systems. Components for these systems are subjected to stochastic thermomechanical launch loads. Uncertainties or randomness also occurs in material properties, structural geometry, and boundary conditions. Material property stochasticity, such as in modulus of elasticity or yield strength, exists in every structure and is a consequence of variations in material composition and manufacturing processes. Procedures are outlined for computing the probabilistic structural response or reliability of the structural components. The response variables include static or dynamic deflections, strains, and stresses at one or several locations, natural frequencies, fatigue or creep life, etc. Sample cases illustrates how the PSAM methods and codes simulate input uncertainties and compute probabilistic response or reliability using a finite element model with probabilistic methods.

Methods of space radiation dose analysis with applications to manned space systems

NASA Technical Reports Server (NTRS)

Langley, R. W.; Billings, M. P.

1972-01-01

The full potential of state-of-the-art space radiation dose analysis for manned missions has not been exploited. Point doses have been overemphasized, and the critical dose to the bone marrow has been only crudely approximated, despite the existence of detailed man models and computer codes for dose integration in complex geometries. The method presented makes it practical to account for the geometrical detail of the astronaut as well as the vehicle. Discussed are the major assumptions involved and the concept of applying the results of detailed proton dose analysis to the real-time interpretation of on-board dosimetric measurements.

Recent Progresses in Nanobiosensing for Food Safety Analysis

PubMed Central

Yang, Tao; Huang, Huifen; Zhu, Fang; Lin, Qinlu; Zhang, Lin; Liu, Junwen

2016-01-01

With increasing adulteration, food safety analysis has become an important research field. Nanomaterials-based biosensing holds great potential in designing highly sensitive and selective detection strategies necessary for food safety analysis. This review summarizes various function types of nanomaterials, the methods of functionalization of nanomaterials, and recent (2014–present) progress in the design and development of nanobiosensing for the detection of food contaminants including pathogens, toxins, pesticides, antibiotics, metal contaminants, and other analytes, which are sub-classified according to various recognition methods of each analyte. The existing shortcomings and future perspectives of the rapidly growing field of nanobiosensing addressing food safety issues are also discussed briefly. PMID:27447636

Recent Progresses in Nanobiosensing for Food Safety Analysis.

PubMed

Yang, Tao; Huang, Huifen; Zhu, Fang; Lin, Qinlu; Zhang, Lin; Liu, Junwen

2016-07-19

With increasing adulteration, food safety analysis has become an important research field. Nanomaterials-based biosensing holds great potential in designing highly sensitive and selective detection strategies necessary for food safety analysis. This review summarizes various function types of nanomaterials, the methods of functionalization of nanomaterials, and recent (2014-present) progress in the design and development of nanobiosensing for the detection of food contaminants including pathogens, toxins, pesticides, antibiotics, metal contaminants, and other analytes, which are sub-classified according to various recognition methods of each analyte. The existing shortcomings and future perspectives of the rapidly growing field of nanobiosensing addressing food safety issues are also discussed briefly.

The choice of primary energy source including PV installation for providing electric energy to a public utility building - a case study

NASA Astrophysics Data System (ADS)

Radomski, Bartosz; Ćwiek, Barbara; Mróz, Tomasz M.

2017-11-01

The paper presents multicriteria decision aid analysis of the choice of PV installation providing electric energy to a public utility building. From the energy management point of view electricity obtained by solar radiation has become crucial renewable energy source. Application of PV installations may occur a profitable solution from energy, economic and ecologic point of view for both existing and newly erected buildings. Featured variants of PV installations have been assessed by multicriteria analysis based on ANP (Analytic Network Process) method. Technical, economical, energy and environmental criteria have been identified as main decision criteria. Defined set of decision criteria has an open character and can be modified in the dialog process between the decision-maker and the expert - in the present case, an expert in planning of development of energy supply systems. The proposed approach has been used to evaluate three variants of PV installation acceptable for existing educational building located in Poznań, Poland - the building of Faculty of Chemical Technology, Poznań University of Technology. Multi-criteria analysis based on ANP method and the calculation software Super Decisions has proven to be an effective tool for energy planning, leading to the indication of the recommended variant of PV installation in existing and newly erected public buildings. Achieved results show prospects and possibilities of rational renewable energy usage as complex solution to public utility buildings.

Analyzing Visibility Configurations.

PubMed

Dachsbacher, C

2011-04-01

Many algorithms, such as level of detail rendering and occlusion culling methods, make decisions based on the degree of visibility of an object, but do not analyze the distribution, or structure, of the visible and occluded regions across surfaces. We present an efficient method to classify different visibility configurations and show how this can be used on top of existing methods based on visibility determination. We adapt co-occurrence matrices for visibility analysis and generalize them to operate on clusters of triangular surfaces instead of pixels. We employ machine learning techniques to reliably classify the thus extracted feature vectors. Our method allows perceptually motivated level of detail methods for real-time rendering applications by detecting configurations with expected visual masking. We exemplify the versatility of our method with an analysis of area light visibility configurations in ray tracing and an area-to-area visibility analysis suitable for hierarchical radiosity refinement. Initial results demonstrate the robustness, simplicity, and performance of our method in synthetic scenes, as well as real applications.

RF transient analysis and stabilization of the phase and energy of the proposed PIP-II LINAC

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

Edelen, J. P.; Chase, B. E.

This paper describes a recent effort to develop and benchmark a simulation tool for the analysis of RF transients and their compensation in an H- linear accelerator. Existing tools in this area either focus on electron LINACs or lack fundamental details about the LLRF system that are necessary to provide realistic performance estimates. In our paper we begin with a discussion of our computational models followed by benchmarking with existing beam-dynamics codes and measured data. We then analyze the effect of RF transients and their compensation in the PIP-II LINAC, followed by an analysis of calibration errors and how amore » Newton’s Method based feedback scheme can be used to regulate the beam energy to within the specified limits.« less

Determination of N epsilon-(carboxymethyl)lysine in foods and related systems.

PubMed

Ames, Jennifer M

2008-04-01

The sensitive and specific determination of advanced glycation end products (AGEs) is of considerable interest because these compounds have been associated with pro-oxidative and proinflammatory effects in vivo. AGEs form when carbonyl compounds, such as glucose and its oxidation products, glyoxal and methylglyoxal, react with the epsilon-amino group of lysine and the guanidino group of arginine to give structures including N epsilon-(carboxymethyl)lysine (CML), N epsilon-(carboxyethyl)lysine, and hydroimidazolones. CML is frequently used as a marker for AGEs in general. It exists in both the free or peptide-bound forms. Analysis of CML involves its extraction from the food (including protein hydrolysis to release any peptide-bound adduct) and determination by immunochemical or instrumental means. Various factors must be considered at each step of the analysis. Extraction, hydrolysis, and sample clean-up are all less straight forward for food samples, compared to plasma and tissue. The immunochemical and instrumental methods all have their advantages and disadvantages, and no perfect method exists. Currently, different procedures are being used in different laboratories, and there is an urgent need to compare, improve, and validate methods.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review.

PubMed

Kamran, Muhammad A; Mannan, Malik M Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review

PubMed Central

Kamran, Muhammad A.; Mannan, Malik M. Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized. PMID:27375458

Building Energy Simulation Test for Existing Homes (BESTEST-EX) (Presentation)

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

Judkoff, R.; Neymark, J.; Polly, B.

2011-12-01

This presentation discusses the goals of NREL Analysis Accuracy R&D; BESTEST-EX goals; what BESTEST-EX is; how it works; 'Building Physics' cases; 'Building Physics' reference results; 'utility bill calibration' cases; limitations and potential future work. Goals of NREL Analysis Accuracy R&D are: (1) Provide industry with the tools and technical information needed to improve the accuracy and consistency of analysis methods; (2) Reduce the risks associated with purchasing, financing, and selling energy efficiency upgrades; and (3) Enhance software and input collection methods considering impacts on accuracy, cost, and time of energy assessments. BESTEST-EX Goals are: (1) Test software predictions of retrofitmore » energy savings in existing homes; (2) Ensure building physics calculations and utility bill calibration procedures perform up to a minimum standard; and (3) Quantify impact of uncertainties in input audit data and occupant behavior. BESTEST-EX is a repeatable procedure that tests how well audit software predictions compare to the current state of the art in building energy simulation. There is no direct truth standard. However, reference software have been subjected to validation testing, including comparisons with empirical data.« less

A Bayesian method for using simulator data to enhance human error probabilities assigned by existing HRA methods

DOE PAGES

Groth, Katrina M.; Smith, Curtis L.; Swiler, Laura P.

2014-04-05

In the past several years, several international agencies have begun to collect data on human performance in nuclear power plant simulators [1]. This data provides a valuable opportunity to improve human reliability analysis (HRA), but there improvements will not be realized without implementation of Bayesian methods. Bayesian methods are widely used in to incorporate sparse data into models in many parts of probabilistic risk assessment (PRA), but Bayesian methods have not been adopted by the HRA community. In this article, we provide a Bayesian methodology to formally use simulator data to refine the human error probabilities (HEPs) assigned by existingmore » HRA methods. We demonstrate the methodology with a case study, wherein we use simulator data from the Halden Reactor Project to update the probability assignments from the SPAR-H method. The case study demonstrates the ability to use performance data, even sparse data, to improve existing HRA methods. Furthermore, this paper also serves as a demonstration of the value of Bayesian methods to improve the technical basis of HRA.« less

Ultrafast and Wide Range Analysis of DNA Molecules Using Rigid Network Structure of Solid Nanowires

PubMed Central

Rahong, Sakon; Yasui, Takao; Yanagida, Takeshi; Nagashima, Kazuki; Kanai, Masaki; Klamchuen, Annop; Meng, Gang; He, Yong; Zhuge, Fuwei; Kaji, Noritada; Kawai, Tomoji; Baba, Yoshinobu

2014-01-01

Analyzing sizes of DNA via electrophoresis using a gel has played an important role in the recent, rapid progress of biology and biotechnology. Although analyzing DNA over a wide range of sizes in a short time is desired, no existing electrophoresis methods have been able to fully satisfy these two requirements. Here we propose a novel method using a rigid 3D network structure composed of solid nanowires within a microchannel. This rigid network structure enables analysis of DNA under applied DC electric fields for a large DNA size range (100 bp–166 kbp) within 13 s, which are much wider and faster conditions than those of any existing methods. The network density is readily varied for the targeted DNA size range by tailoring the number of cycles of the nanowire growth only at the desired spatial position within the microchannel. The rigid dense 3D network structure with spatial density control plays an important role in determining the capability for analyzing DNA. Since the present method allows the spatial location and density of the nanostructure within the microchannels to be defined, this unique controllability offers a new strategy to develop an analytical method not only for DNA but also for other biological molecules. PMID:24918865

Accuracy of Time Integration Approaches for Stiff Magnetohydrodynamics Problems

NASA Astrophysics Data System (ADS)

Knoll, D. A.; Chacon, L.

2003-10-01

The simulation of complex physical processes with multiple time scales presents a continuing challenge to the computational plasma physisist due to the co-existence of fast and slow time scales. Within computational plasma physics, practitioners have developed and used linearized methods, semi-implicit methods, and time splitting in an attempt to tackle such problems. All of these methods are understood to generate numerical error. We are currently developing algorithms which remove such error for MHD problems [1,2]. These methods do not rely on linearization or time splitting. We are also attempting to analyze the errors introduced by existing ``implicit'' methods using modified equation analysis (MEA) [3]. In this presentation we will briefly cover the major findings in [3]. We will then extend this work further into MHD. This analysis will be augmented with numerical experiments with the hope of gaining insight, particularly into how these errors accumulate over many time steps. [1] L. Chacon,. D.A. Knoll, J.M. Finn, J. Comput. Phys., vol. 178, pp. 15-36 (2002) [2] L. Chacon and D.A. Knoll, J. Comput. Phys., vol. 188, pp. 573-592 (2003) [3] D.A. Knoll , L. Chacon, L.G. Margolin, V.A. Mousseau, J. Comput. Phys., vol. 185, pp. 583-611 (2003)

Ultrafast and Wide Range Analysis of DNA Molecules Using Rigid Network Structure of Solid Nanowires

NASA Astrophysics Data System (ADS)

Rahong, Sakon; Yasui, Takao; Yanagida, Takeshi; Nagashima, Kazuki; Kanai, Masaki; Klamchuen, Annop; Meng, Gang; He, Yong; Zhuge, Fuwei; Kaji, Noritada; Kawai, Tomoji; Baba, Yoshinobu

2014-06-01

Analyzing sizes of DNA via electrophoresis using a gel has played an important role in the recent, rapid progress of biology and biotechnology. Although analyzing DNA over a wide range of sizes in a short time is desired, no existing electrophoresis methods have been able to fully satisfy these two requirements. Here we propose a novel method using a rigid 3D network structure composed of solid nanowires within a microchannel. This rigid network structure enables analysis of DNA under applied DC electric fields for a large DNA size range (100 bp-166 kbp) within 13 s, which are much wider and faster conditions than those of any existing methods. The network density is readily varied for the targeted DNA size range by tailoring the number of cycles of the nanowire growth only at the desired spatial position within the microchannel. The rigid dense 3D network structure with spatial density control plays an important role in determining the capability for analyzing DNA. Since the present method allows the spatial location and density of the nanostructure within the microchannels to be defined, this unique controllability offers a new strategy to develop an analytical method not only for DNA but also for other biological molecules.

International development of methods of analysis for the presence of products of modern biotechnology.

PubMed

Cantrill, Richard C

2008-01-01

Methods of analysis for products of modern biotechnology are required for national and international trade in seeds, grain and food in order to meet the labeling or import/export requirements of different nations and trading blocks. Although many methods were developed by the originators of transgenic events, governments, universities, and testing laboratories, trade is less complicated if there exists a set of international consensus-derived analytical standards. In any analytical situation, multiple methods may exist for testing for the same analyte. These methods may be supported by regional preferences and regulatory requirements. However, tests need to be sensitive enough to determine low levels of these traits in commodity grain for regulatory purposes and also to indicate purity of seeds containing these traits. The International Organization for Standardization (ISO) and its European counterpart have worked to produce a suite of standards through open, balanced and consensus-driven processes. Presently, these standards are approaching the time for their first review. In fact, ISO 21572, the "protein standard" has already been circulated for systematic review. In order to expedite the review and revision of the nucleic acid standards an ISO Technical Specification (ISO/TS 21098) was drafted to set the criteria for the inclusion of precision data from collaborative studies into the annexes of these standards.

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

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

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui

2014-03-15

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CBmore » alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.« less

Mechanistic-empirical asphalt overlay thickness design and analysis system.

DOT National Transportation Integrated Search

2009-10-01

The placement of an asphalt overlay is the most common method used by the Texas Department of Transportation (TxDOT) to rehabilitate : existing asphalt and concrete pavements. The type of overlay and its required thickness are important decisions tha...

Review of LMIs, Interior Point Methods, Complexity Theory, and Robustness Analysis

NASA Technical Reports Server (NTRS)

Mesbahi, M.

1996-01-01

From end of intro: ...We would like to show that for certain problems in systems and control theory, there exist algorithms for which corresponding (xi) can be viewed as a certain measure of robustness, e.g., stability margin.

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

PubMed

Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

2014-12-19

In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations.

A robust ridge regression approach in the presence of both multicollinearity and outliers in the data

NASA Astrophysics Data System (ADS)

Shariff, Nurul Sima Mohamad; Ferdaos, Nur Aqilah

2017-08-01

Multicollinearity often leads to inconsistent and unreliable parameter estimates in regression analysis. This situation will be more severe in the presence of outliers it will cause fatter tails in the error distributions than the normal distributions. The well-known procedure that is robust to multicollinearity problem is the ridge regression method. This method however is expected to be affected by the presence of outliers due to some assumptions imposed in the modeling procedure. Thus, the robust version of existing ridge method with some modification in the inverse matrix and the estimated response value is introduced. The performance of the proposed method is discussed and comparisons are made with several existing estimators namely, Ordinary Least Squares (OLS), ridge regression and robust ridge regression based on GM-estimates. The finding of this study is able to produce reliable parameter estimates in the presence of both multicollinearity and outliers in the data.

Timescale analysis of rule-based biochemical reaction networks

PubMed Central

Klinke, David J.; Finley, Stacey D.

2012-01-01

The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150

Application of Bayesian configural frequency analysis (BCFA) to determine characteristics user and non-user motor X

NASA Astrophysics Data System (ADS)

Mawardi, Muhamad Iqbal; Padmadisastra, Septiadi; Tantular, Bertho

2018-03-01

Configural Frequency Analysis is a method for cell-wise testing in contingency tables for exploratory search type and antitype, that can see the existence of discrepancy on the model by existence of a significant difference between the frequency of observation and frequency of expectation. This analysis focuses on whether or not the interaction among categories from different variables, and not the interaction among variables. One of the extensions of CFA method is Bayesian CFA, this alternative method pursue the same goal as frequentist version of CFA with the advantage that adjustment of the experiment-wise significance level α is not necessary and test whether groups of types and antitypes form composite types or composite antitypes. Hence, this research will present the concept of the Bayesian CFA and how it works for the real data. The data on this paper is based on case studies in a company about decrease Brand Awareness & Image motor X on Top Of Mind Unit indicator in Cirebon City for user 30.8% and non user 9.8%. From the result of B-CFA have four characteristics from deviation, one of the four characteristics above that is the configuration 2212 need more attention by company to determine promotion strategy to maintain and improve Top Of Mind Unit in Cirebon City.

Linear regression based on Minimum Covariance Determinant (MCD) and TELBS methods on the productivity of phytoplankton

NASA Astrophysics Data System (ADS)

Gusriani, N.; Firdaniza

2018-03-01

The existence of outliers on multiple linear regression analysis causes the Gaussian assumption to be unfulfilled. If the Least Square method is forcedly used on these data, it will produce a model that cannot represent most data. For that, we need a robust regression method against outliers. This paper will compare the Minimum Covariance Determinant (MCD) method and the TELBS method on secondary data on the productivity of phytoplankton, which contains outliers. Based on the robust determinant coefficient value, MCD method produces a better model compared to TELBS method.

A method to assess the allocation suitability of recreational activities: An economic approach

NASA Astrophysics Data System (ADS)

Wang, Hsiao-Lin

1996-03-01

Most existing methods of planning focus on development of a recreational area; less consideration is placed on the allocation of recreational activities within a recreational area. Most existing research emphasizes the economic benefits of developing a recreational area; few authors assessed the allocation suitability of recreational activities from an economic point of view. The purpose of this work was to develop a model to assess the allocation suitability of recreational activities according to the application of a concept of analysis of cost and benefit under a premise of ecological concern. The model was verified with a case study of Taiwan. We suggest that the proposed model should form a critical part of recreational planning.

A scoping review of spatial cluster analysis techniques for point-event data.

PubMed

Fritz, Charles E; Schuurman, Nadine; Robertson, Colin; Lear, Scott

2013-05-01

Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.

Current state of ethics literature synthesis: a systematic review of reviews.

PubMed

Mertz, Marcel; Kahrass, Hannes; Strech, Daniel

2016-10-03

Modern standards for evidence-based decision making in clinical care and public health still rely solely on eminence-based input when it comes to normative ethical considerations. Manuals for clinical guideline development or health technology assessment (HTA) do not explain how to search, analyze, and synthesize relevant normative information in a systematic and transparent manner. In the scientific literature, however, systematic or semi-systematic reviews of ethics literature already exist, and scholarly debate on their opportunities and limitations has recently bloomed. A systematic review was performed of all existing systematic or semi-systematic reviews for normative ethics literature on medical topics. The study further assessed how these reviews report on their methods for search, selection, analysis, and synthesis of ethics literature. We identified 84 reviews published between 1997 and 2015 in 65 different journals and demonstrated an increasing publication rate for this type of review. While most reviews reported on different aspects of search and selection methods, reporting was much less explicit for aspects of analysis and synthesis methods: 31 % did not fulfill any criteria related to the reporting of analysis methods; for example, only 25 % of the reviews reported the ethical approach needed to analyze and synthesize normative information. While reviews of ethics literature are increasingly published, their reporting quality for analysis and synthesis of normative information should be improved. Guiding questions are: What was the applied ethical approach and technical procedure for identifying and extracting the relevant normative information units? What method and procedure was employed for synthesizing normative information? Experts and stakeholders from bioethics, HTA, guideline development, health care professionals, and patient organizations should work together to further develop this area of evidence-based health care.

Hydration in advanced cancer: can bioelectrical impedance analysis improve the evidence base? A systematic review of the literature.

PubMed

Nwosu, Amara Callistus; Mayland, Catriona R; Mason, Stephen R; Khodabukus, Andrew F; Varro, Andrea; Ellershaw, John E

2013-09-01

Decisions surrounding the administration of clinically assisted hydration to patients dying of cancer can be challenging because of the limited understanding of hydration in advanced cancer and a lack of evidence to guide health care professionals. Bioelectrical impedance analysis (BIA) has been used to assess hydration in various patient groupings, but evidence for its use in advanced cancer is limited. To critically appraise existing methods of hydration status assessment in advanced cancer and review the potential for BIA to assess hydration in advanced cancer. Searches were carried out in four electronic databases. A hand search of selected peer-reviewed journals and conference abstracts also was conducted. Studies reporting (de)hydration assessment (physical examination, biochemical measures, symptom assessment, and BIA) in patients with advanced cancer were included. The results highlight how clinical examination and biochemical tests are standard methods of assessing hydration, but limitations exist with these methods in advanced cancer. Furthermore, there is disagreement over the evidence for some commonly associated symptoms with dehydration in cancer. Although there are limitations with using BIA alone to assess hydration in advanced cancer, analysis of BIA raw measurements through the method of bioelectrical impedance vector analysis may have a role in this population. The benefits and burdens of providing clinically assisted hydration to patients dying of cancer are unclear. Bioelectrical impedance vector analysis shows promise as a hydration assessment tool but requires further study in advanced cancer. Innovative methodologies for research are required to add to the evidence base and ultimately improve the care for the dying. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

75 FR 13 - Alternate Fracture Toughness Requirements for Protection Against Pressurized Thermal Shock Events

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-04

...The Nuclear Regulatory Commission (NRC) is amending its regulations to provide alternate fracture toughness requirements for protection against pressurized thermal shock (PTS) events for pressurized water reactor (PWR) pressure vessels. This final rule provides alternate PTS requirements based on updated analysis methods. This action is desirable because the existing requirements are based on unnecessarily conservative probabilistic fracture mechanics analyses. This action reduces regulatory burden for those PWR licensees who expect to exceed the existing requirements before the expiration of their licenses, while maintaining adequate safety, and may choose to comply with the final rule as an alternative to complying with the existing requirements.

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.

PubMed

Simovski, Boris; Kanduri, Chakravarthi; Gundersen, Sveinung; Titov, Dmytro; Domanska, Diana; Bock, Christoph; Bossini-Castillo, Lara; Chikina, Maria; Favorov, Alexander; Layer, Ryan M; Mironov, Andrey A; Quinlan, Aaron R; Sheffield, Nathan C; Trynka, Gosia; Sandve, Geir K

2018-06-05

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

Determining Semantically Related Significant Genes.

PubMed

Taha, Kamal

2014-01-01

GO relation embodies some aspects of existence dependency. If GO term xis existence-dependent on GO term y, the presence of y implies the presence of x. Therefore, the genes annotated with the function of the GO term y are usually functionally and semantically related to the genes annotated with the function of the GO term x. A large number of gene set enrichment analysis methods have been developed in recent years for analyzing gene sets enrichment. However, most of these methods overlook the structural dependencies between GO terms in GO graph by not considering the concept of existence dependency. We propose in this paper a biological search engine called RSGSearch that identifies enriched sets of genes annotated with different functions using the concept of existence dependency. We observe that GO term xcannot be existence-dependent on GO term y, if x- and y- have the same specificity (biological characteristics). After encoding into a numeric format the contributions of GO terms annotating target genes to the semantics of their lowest common ancestors (LCAs), RSGSearch uses microarray experiment to identify the most significant LCA that annotates the result genes. We evaluated RSGSearch experimentally and compared it with five gene set enrichment systems. Results showed marked improvement.

A Coarse-Grained Elastic Network Atom Contact Model and Its Use in the Simulation of Protein Dynamics and the Prediction of the Effect of Mutations

PubMed Central

Frappier, Vincent; Najmanovich, Rafael J.

2014-01-01

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cα−only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations. PMID:24762569

Double temporal sparsity based accelerated reconstruction of compressively sensed resting-state fMRI.

PubMed

Aggarwal, Priya; Gupta, Anubha

2017-12-01

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper addresses the issue of accelerating fMRI collection via undersampled k-space measurements combined with the proposed method based on l 1 -l 1 norm constraints, wherein we impose first l 1 -norm sparsity on the voxel time series (temporal data) in the transformed domain and the second l 1 -norm sparsity on the successive difference of the same temporal data. Hence, we name the proposed method as Double Temporal Sparsity based Reconstruction (DTSR) method. The robustness of the proposed DTSR method has been thoroughly evaluated both at the subject level and at the group level on real fMRI data. Results are presented at various acceleration factors. Quantitative analysis in terms of Peak Signal-to-Noise Ratio (PSNR) and other metrics, and qualitative analysis in terms of reproducibility of brain Resting State Networks (RSNs) demonstrate that the proposed method is accurate and robust. In addition, the proposed DTSR method preserves brain networks that are important for studying fMRI data. Compared to the existing methods, the DTSR method shows promising potential with an improvement of 10-12 dB in PSNR with acceleration factors upto 3.5 on resting state fMRI data. Simulation results on real data demonstrate that DTSR method can be used to acquire accelerated fMRI with accurate detection of RSNs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Contact stresses in gear teeth: A new method of analysis

NASA Technical Reports Server (NTRS)

Somprakit, Paisan; Huston, Ronald L.; Oswald, Fred B.

1991-01-01

A new, innovative procedure called point load superposition for determining the contact stresses in mating gear teeth. It is believed that this procedure will greatly extend both the range of applicability and the accuracy of gear contact stress analysis. Point load superposition is based upon fundamental solutions from the theory of elasticity. It is an iterative numerical procedure which has distinct advantages over the classical Hertz method, the finite element method, and over existing applications with the boundary element method. Specifically, friction and sliding effects, which are either excluded from or difficult to study with the classical methods, are routinely handled with the new procedure. Presented here are the basic theory and the algorithms. Several examples are given. Results are consistent with those of the classical theories. Applications to spur gears are discussed.

Nuclear States with Abnormally Large Radii (size Isomers)

NASA Astrophysics Data System (ADS)

Ogloblin, A. A.; Demyanova, A. S.; Danilov, A. N.; Belyaeva, T. L.; Goncharov, S. A.

2015-06-01

Application of the methods of measuring the radii of the short-lived excited states (Modified diffraction model MDM, Inelastic nuclear rainbow scattering method INRS, Asymptotic normalization coefficients method ANC) to the analysis of some nuclear reactions provide evidence of existing in 9Be, 11B, 12C, 13C the excited states whose radii exceed those of the corresponding ground states by ~ 30%. Two types of structure of these "size isomers" were identified: neutron halo an α-clusters.

Accuracy of p53 Codon 72 Polymorphism Status Determined by Multiple Laboratory Methods: A Latent Class Model Analysis

PubMed Central

Walter, Stephen D.; Riddell, Corinne A.; Rabachini, Tatiana; Villa, Luisa L.; Franco, Eduardo L.

2013-01-01

Introduction Studies on the association of a polymorphism in codon 72 of the p53 tumour suppressor gene (rs1042522) with cervical neoplasia have inconsistent results. While several methods for genotyping p53 exist, they vary in accuracy and are often discrepant. Methods We used latent class models (LCM) to examine the accuracy of six methods for p53 determination, all conducted by the same laboratory. We also examined the association of p53 with cytological cervical abnormalities, recognising potential test inaccuracy. Results Pairwise disagreement between laboratory methods occurred approximately 10% of the time. Given the estimated true p53 status of each woman, we found that each laboratory method is most likely to classify a woman to her correct status. Arg/Arg women had the highest risk of squamous intraepithelial lesions (SIL). Test accuracy was independent of cytology. There was no strong evidence for correlations of test errors. Discussion Empirical analyses ignore possible laboratory errors, and so are inherently biased, but test accuracy estimated by the LCM approach is unbiased when model assumptions are met. LCM analysis avoids ambiguities arising from empirical test discrepancies, obviating the need to regard any of the methods as a “gold” standard measurement. The methods we presented here to analyse the p53 data can be applied in many other situations where multiple tests exist, but where none of them is a gold standard. PMID:23441193

A LITERATURE REVIEW OF WIPE SAMPLING METHODS ...

EPA Pesticide Factsheets

Wipe sampling is an important technique for the estimation of contaminant deposition in buildings, homes, or outdoor surfaces as a source of possible human exposure. Numerousmethods of wipe sampling exist, and each method has its own specification for the type of wipe, wetting solvent, and determinative step to be used, depending upon the contaminant of concern. The objective of this report is to concisely summarize the findings of a literature review that was conducted to identify the state-of-the-art wipe sampling techniques for a target list of compounds. This report describes the methods used to perform the literature review; a brief review of wipe sampling techniques in general; an analysis of physical and chemical properties of each target analyte; an analysis of wipe sampling techniques for the target analyte list; and asummary of the wipe sampling techniques for the target analyte list, including existing data gaps. In general, no overwhelming consensus can be drawn from the current literature on how to collect a wipe sample for the chemical warfare agents, organophosphate pesticides, and other toxic industrial chemicals of interest to this study. Different methods, media, and wetting solvents have been recommended and used by various groups and different studies. For many of the compounds of interest, no specific wipe sampling methodology has been established for their collection. Before a wipe sampling method (or methods) can be established for the co

Avalanche correlations in the martensitic transition of a Cu-Zn-Al shape memory alloy: analysis of acoustic emission and calorimetry.

PubMed

Baró, Jordi; Martín-Olalla, José-María; Romero, Francisco Javier; Gallardo, María Carmen; Salje, Ekhard K H; Vives, Eduard; Planes, Antoni

2014-03-26

The existence of temporal correlations during the intermittent dynamics of a thermally driven structural phase transition is studied in a Cu-Zn-Al alloy. The sequence of avalanches is observed by means of two techniques: acoustic emission and high sensitivity calorimetry. Both methods reveal the existence of event clustering in a way that is equivalent to the Omori correlations between aftershocks in earthquakes as are commonly used in seismology.

Comprehensive Numerical Analysis of Finite Difference Time Domain Methods for Improving Optical Waveguide Sensor Accuracy

PubMed Central

Samak, M. Mosleh E. Abu; Bakar, A. Ashrif A.; Kashif, Muhammad; Zan, Mohd Saiful Dzulkifly

2016-01-01

This paper discusses numerical analysis methods for different geometrical features that have limited interval values for typically used sensor wavelengths. Compared with existing Finite Difference Time Domain (FDTD) methods, the alternating direction implicit (ADI)-FDTD method reduces the number of sub-steps by a factor of two to three, which represents a 33% time savings in each single run. The local one-dimensional (LOD)-FDTD method has similar numerical equation properties, which should be calculated as in the previous method. Generally, a small number of arithmetic processes, which result in a shorter simulation time, are desired. The alternating direction implicit technique can be considered a significant step forward for improving the efficiency of unconditionally stable FDTD schemes. This comparative study shows that the local one-dimensional method had minimum relative error ranges of less than 40% for analytical frequencies above 42.85 GHz, and the same accuracy was generated by both methods.

Non-destructive inspection of polymer composite products

NASA Astrophysics Data System (ADS)

Anoshkin, A. N.; Sal'nikov, A. F.; Osokin, V. M.; Tretyakov, A. A.; Luzin, G. S.; Potrakhov, N. N.; Bessonov, V. B.

2018-02-01

The paper considers the main types of defects encountered in products made of polymer composite materials for aviation use. The analysis of existing methods of nondestructive testing is carried out, features of their application are considered taking into account design features, geometrical parameters and internal structure of objects of inspection. The advantages and disadvantages of the considered methods of nondestructive testing used in industrial production are shown.

NASA software specification and evaluation system design, part 2

NASA Technical Reports Server (NTRS)

1976-01-01

A survey and analysis of the existing methods, tools and techniques employed in the development of software are presented along with recommendations for the construction of reliable software. Functional designs for software specification language, and the data base verifier are presented.

Looking at Fossils in New Ways

ERIC Educational Resources Information Center

Flannery, Maura C.

2005-01-01

Existing fossils could be studied from a different prospective with the use of new methods of analysis for gathering more information. The new techniques of studying fossils binds the new and the old techniques and information and provides another way to look at fossils.

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

R.I. Rudyka; Y.E. Zingerman; K.G. Lavrov

Up-to-date mathematical methods, such as correlation analysis and expert systems, are employed in creating a model of the coking process. Automatic coking-control systems developed by Giprokoks rule out human error. At an existing coke battery, after introducing automatic control, the heating-gas consumption is reduced by {>=}5%.

Mesopotamia, A Difficult but Interesting Topic.

ERIC Educational Resources Information Center

Kavett, Hyman

1979-01-01

Describes a method to help students become participants in historical analysis rather than observers of ancient history. Mesopotamia is used as a case study of a culture for which opportunities exist for conjecture, hypothesis formation, research, extrapolation, problem solving, and statements of causality. (Author/DB)

A comparison of optical gradation analysis devices to current test methods--phase 2.

DOT National Transportation Integrated Search

2012-04-01

Optical devices are being developed to deliver accurate size and shape of aggregate particles with, less labor, less consistency error, : and greater reliability. This study was initiated to review the existing technology, and generate basic data to ...

Scale Pretesting

ERIC Educational Resources Information Center

Howard, Matt C.

2018-01-01

Scale pretests analyze the suitability of individual scale items for further analysis, whether through judging their face validity, wording concerns, and/or other aspects. The current article reviews scale pretests, separated by qualitative and quantitative methods, in order to identify the differences, similarities, and even existence of the…

Comparing microscopic activity-based and traditional models of travel demand : an Austin area case study

DOT National Transportation Integrated Search

2007-09-01

Two competing approaches to travel demand modeling exist today. The more traditional 4-step travel demand models rely on aggregate demographic data at a traffic analysis zone (TAZ) level. Activity-based microsimulation methods employ more robus...

Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation.

PubMed

Xu, Zhe; Huang, Shaoli; Zhang, Ya; Tao, Dacheng

2018-05-01

Learning visual representations from web data has recently attracted attention for object recognition. Previous studies have mainly focused on overcoming label noise and data bias and have shown promising results by learning directly from web data. However, we argue that it might be better to transfer knowledge from existing human labeling resources to improve performance at nearly no additional cost. In this paper, we propose a new semi-supervised method for learning via web data. Our method has the unique design of exploiting strong supervision, i.e., in addition to standard image-level labels, our method also utilizes detailed annotations including object bounding boxes and part landmarks. By transferring as much knowledge as possible from existing strongly supervised datasets to weakly supervised web images, our method can benefit from sophisticated object recognition algorithms and overcome several typical problems found in webly-supervised learning. We consider the problem of fine-grained visual categorization, in which existing training resources are scarce, as our main research objective. Comprehensive experimentation and extensive analysis demonstrate encouraging performance of the proposed approach, which, at the same time, delivers a new pipeline for fine-grained visual categorization that is likely to be highly effective for real-world applications.

Analysis-Preserving Video Microscopy Compression via Correlation and Mathematical Morphology

PubMed Central

Shao, Chong; Zhong, Alfred; Cribb, Jeremy; Osborne, Lukas D.; O’Brien, E. Timothy; Superfine, Richard; Mayer-Patel, Ketan; Taylor, Russell M.

2015-01-01

The large amount video data produced by multi-channel, high-resolution microscopy system drives the need for a new high-performance domain-specific video compression technique. We describe a novel compression method for video microscopy data. The method is based on Pearson's correlation and mathematical morphology. The method makes use of the point-spread function (PSF) in the microscopy video acquisition phase. We compare our method to other lossless compression methods and to lossy JPEG, JPEG2000 and H.264 compression for various kinds of video microscopy data including fluorescence video and brightfield video. We find that for certain data sets, the new method compresses much better than lossless compression with no impact on analysis results. It achieved a best compressed size of 0.77% of the original size, 25× smaller than the best lossless technique (which yields 20% for the same video). The compressed size scales with the video's scientific data content. Further testing showed that existing lossy algorithms greatly impacted data analysis at similar compression sizes. PMID:26435032

Identification of varying time scales in sediment transport using the Hilbert-Huang Transform method

NASA Astrophysics Data System (ADS)

Kuai, Ken Z.; Tsai, Christina W.

2012-02-01

SummarySediment transport processes vary at a variety of time scales - from seconds, hours, days to months and years. Multiple time scales exist in the system of flow, sediment transport and bed elevation change processes. As such, identification and selection of appropriate time scales for flow and sediment processes can assist in formulating a system of flow and sediment governing equations representative of the dynamic interaction of flow and particles at the desired details. Recognizing the importance of different varying time scales in the fluvial processes of sediment transport, we introduce the Hilbert-Huang Transform method (HHT) to the field of sediment transport for the time scale analysis. The HHT uses the Empirical Mode Decomposition (EMD) method to decompose a time series into a collection of the Intrinsic Mode Functions (IMFs), and uses the Hilbert Spectral Analysis (HSA) to obtain instantaneous frequency data. The EMD extracts the variability of data with different time scales, and improves the analysis of data series. The HSA can display the succession of time varying time scales, which cannot be captured by the often-used Fast Fourier Transform (FFT) method. This study is one of the earlier attempts to introduce the state-of-the-art technique for the multiple time sales analysis of sediment transport processes. Three practical applications of the HHT method for data analysis of both suspended sediment and bedload transport time series are presented. The analysis results show the strong impact of flood waves on the variations of flow and sediment time scales at a large sampling time scale, as well as the impact of flow turbulence on those time scales at a smaller sampling time scale. Our analysis reveals that the existence of multiple time scales in sediment transport processes may be attributed to the fractal nature in sediment transport. It can be demonstrated by the HHT analysis that the bedload motion time scale is better represented by the ratio of the water depth to the settling velocity, h/ w. In the final part, HHT results are compared with an available time scale formula in literature.

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

PubMed

Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

2015-01-01

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

PubMed Central

2015-01-01

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works. PMID:26103634

BAYESIAN META-ANALYSIS ON MEDICAL DEVICES: APPLICATION TO IMPLANTABLE CARDIOVERTER DEFIBRILLATORS

PubMed Central

Youn, Ji-Hee; Lord, Joanne; Hemming, Karla; Girling, Alan; Buxton, Martin

2012-01-01

Objectives: The aim of this study is to describe and illustrate a method to obtain early estimates of the effectiveness of a new version of a medical device. Methods: In the absence of empirical data, expert opinion may be elicited on the expected difference between the conventional and modified devices. Bayesian Mixed Treatment Comparison (MTC) meta-analysis can then be used to combine this expert opinion with existing trial data on earlier versions of the device. We illustrate this approach for a new four-pole implantable cardioverter defibrillator (ICD) compared with conventional ICDs, Class III anti-arrhythmic drugs, and conventional drug therapy for the prevention of sudden cardiac death in high risk patients. Existing RCTs were identified from a published systematic review, and we elicited opinion on the difference between four-pole and conventional ICDs from experts recruited at a cardiology conference. Results: Twelve randomized controlled trials were identified. Seven experts provided valid probability distributions for the new ICDs compared with current devices. The MTC model resulted in estimated relative risks of mortality of 0.74 (0.60–0.89) (predictive relative risk [RR] = 0.77 [0.41–1.26]) and 0.83 (0.70–0.97) (predictive RR = 0.84 [0.55–1.22]) with the new ICD therapy compared to Class III anti-arrhythmic drug therapy and conventional drug therapy, respectively. These results showed negligible differences from the preliminary results for the existing ICDs. Conclusions: The proposed method incorporating expert opinion to adjust for a modification made to an existing device may play a useful role in assisting decision makers to make early informed judgments on the effectiveness of frequently modified healthcare technologies. PMID:22559753

A simple analytical procedure to replace HPLC for monitoring treatment concentrations of chloramine-T on fish culture facilities

USGS Publications Warehouse

Dawson, V.K.; Meinertz, J.R.; Schmidt, L.J.; Gingerich, W.H.

2003-01-01

Concentrations of chloramine-T must be monitored during experimental treatments of fish when studying the effectiveness of the drug for controlling bacterial gill disease. A surrogate analytical method for analysis of chloramine-T to replace the existing high-performance liquid chromatography (HPLC) method is described. A surrogate method was needed because the existing HPLC method is expensive, requires a specialist to use, and is not generally available at fish hatcheries. Criteria for selection of a replacement method included ease of use, analysis time, cost, safety, sensitivity, accuracy, and precision. The most promising approach was to use the determination of chlorine concentrations as an indicator of chloramine-T. Of the currently available methods for analysis of chlorine, the DPD (N,N-diethyl-p-phenylenediamine) colorimetric method best fit the established criteria. The surrogate method was evaluated under a variety of water quality conditions. Regression analysis of all DPD colorimetric analyses with the HPLC values produced a linear model (Y=0.9602 X+0.1259) with an r2 value of 0.9960. The average accuracy (percent recovery) of the DPD method relative to the HPLC method for the combined set of water quality data was 101.5%. The surrogate method was also evaluated with chloramine-T solutions that contained various concentrations of fish feed or selected densities of rainbow trout. When samples were analyzed within 2 h, the results of the surrogate method were consistent with those of the HPLC method. When samples with high concentrations of organic material were allowed to age more than 2 h before being analyzed, the DPD method seemed to be susceptible to interference, possibly from the development of other chloramine compounds. However, even after aging samples 6 h, the accuracy of the surrogate DPD method relative to the HPLC method was within the range of 80-120%. Based on the data comparing the two methods, the U.S. Food and Drug Administration has concluded that the DPD colorimetric method is appropriate to use to measure chloramine-T in water during pivotal efficacy trials designed to support the approval of chloramine-T for use in fish culture. ?? 2003 Elsevier Science B.V. All rights reserved.

Coupled CFD and Particle Vortex Transport Method: Wing Performance and Wake Validations

DTIC Science & Technology

2008-06-26

the PVTM analysis. The results obtained using the coupled RANS/PVTM analysis compare well with experimental data , in particular the pressure...searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments...is validated against wind tunnel test data . Comparisons with measured pressure distribution, loadings, and vortex parameters, and the corresponding

Is There a Sex Ratio Difference in the Familial Aggregation of Specific Language Impairment? A Meta-Analysis

ERIC Educational Resources Information Center

Whitehouse, Andrew J. O.

2010-01-01

Purpose: Specific language impairment (SLI) is known to aggregate in families. Debate exists on whether the male sex presents an additional risk for SLI. This meta-analysis examined whether there is a sex ratio difference in the risk for impairment among family members of an SLI proband and whether this is mediated by assessment method (direct…

Software Defined Network Monitoring Scheme Using Spectral Graph Theory and Phantom Nodes

DTIC Science & Technology

2014-09-01

networks is the emergence of software - defined networking ( SDN ) [1]. SDN has existed for the...Chapter III for network monitoring. A. SOFTWARE DEFINED NETWORKS SDNs provide a new and innovative method to simplify network hardware by logically...and R. Giladi, “Performance analysis of software - defined networking ( SDN ),” in Proc. of IEEE 21st International Symposium on Modeling, Analysis

A Study of Ideational Metafunction in Joseph Conrad's "Heart of Darkness": A Critical Discourse Analysis

ERIC Educational Resources Information Center

Alaei, Mahya; Ahangari, Saeideh

2016-01-01

The linguistic study of literature or critical analysis of literary discourse is no different from any other textual description; it is not a new branch or a new level or a new kind of linguistics but the application of existing theories and methods (Halliday, 2002). This study intends to determine how ideology or opinion is expressed in Joseph…

An Analysis of the Use and Policies Regarding Social Media Use as a Work Tool in Public Rehabilitation

ERIC Educational Resources Information Center

Garcia, Jorge; Zeglin, Robert J.; Matray, Shari; Froehlich, Robert; Marable, Ronica; McGuire-Kuletz, Maureen

2016-01-01

Purpose: The purpose of this article was to gather descriptive data on the professional use of social media in public rehabilitation settings and to analyze existing social media policies in those agencies through content analysis. Methods: The authors sent a survey to all state administrators or directors of these agencies (N = 50) in the United…

Power calculator for instrumental variable analysis in pharmacoepidemiology

PubMed Central

Walker, Venexia M; Davies, Neil M; Windmeijer, Frank; Burgess, Stephen; Martin, Richard M

2017-01-01

Abstract Background Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. Methods and Results The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. Conclusions The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. PMID:28575313

Statistical analysis of fNIRS data: a comprehensive review.

PubMed

Tak, Sungho; Ye, Jong Chul

2014-01-15

Functional near-infrared spectroscopy (fNIRS) is a non-invasive method to measure brain activities using the changes of optical absorption in the brain through the intact skull. fNIRS has many advantages over other neuroimaging modalities such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), or magnetoencephalography (MEG), since it can directly measure blood oxygenation level changes related to neural activation with high temporal resolution. However, fNIRS signals are highly corrupted by measurement noises and physiology-based systemic interference. Careful statistical analyses are therefore required to extract neuronal activity-related signals from fNIRS data. In this paper, we provide an extensive review of historical developments of statistical analyses of fNIRS signal, which include motion artifact correction, short source-detector separation correction, principal component analysis (PCA)/independent component analysis (ICA), false discovery rate (FDR), serially-correlated errors, as well as inference techniques such as the standard t-test, F-test, analysis of variance (ANOVA), and statistical parameter mapping (SPM) framework. In addition, to provide a unified view of various existing inference techniques, we explain a linear mixed effect model with restricted maximum likelihood (ReML) variance estimation, and show that most of the existing inference methods for fNIRS analysis can be derived as special cases. Some of the open issues in statistical analysis are also described. Copyright © 2013 Elsevier Inc. All rights reserved.

Research on the spatial analysis method of seismic hazard for island

NASA Astrophysics Data System (ADS)

Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

2017-05-01

Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform.

Pathway enrichment analysis approach based on topological structure and updated annotation of pathway.

PubMed

Yang, Qian; Wang, Shuyuan; Dai, Enyu; Zhou, Shunheng; Liu, Dianming; Liu, Haizhou; Meng, Qianqian; Jiang, Bin; Jiang, Wei

2017-08-16

Pathway enrichment analysis has been widely used to identify cancer risk pathways, and contributes to elucidating the mechanism of tumorigenesis. However, most of the existing approaches use the outdated pathway information and neglect the complex gene interactions in pathway. Here, we first reviewed the existing widely used pathway enrichment analysis approaches briefly, and then, we proposed a novel topology-based pathway enrichment analysis (TPEA) method, which integrated topological properties and global upstream/downstream positions of genes in pathways. We compared TPEA with four widely used pathway enrichment analysis tools, including database for annotation, visualization and integrated discovery (DAVID), gene set enrichment analysis (GSEA), centrality-based pathway enrichment (CePa) and signaling pathway impact analysis (SPIA), through analyzing six gene expression profiles of three tumor types (colorectal cancer, thyroid cancer and endometrial cancer). As a result, we identified several well-known cancer risk pathways that could not be obtained by the existing tools, and the results of TPEA were more stable than that of the other tools in analyzing different data sets of the same cancer. Ultimately, we developed an R package to implement TPEA, which could online update KEGG pathway information and is available at the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/TPEA/. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Improved Simplified Methods for Effective Seismic Analysis and Design of Isolated and Damped Bridges in Western and Eastern North America

NASA Astrophysics Data System (ADS)

Koval, Viacheslav

The seismic design provisions of the CSA-S6 Canadian Highway Bridge Design Code and the AASHTO LRFD Seismic Bridge Design Specifications have been developed primarily based on historical earthquake events that have occurred along the west coast of North America. For the design of seismic isolation systems, these codes include simplified analysis and design methods. The appropriateness and range of application of these methods are investigated through extensive parametric nonlinear time history analyses in this thesis. It was found that there is a need to adjust existing design guidelines to better capture the expected nonlinear response of isolated bridges. For isolated bridges located in eastern North America, new damping coefficients are proposed. The applicability limits of the code-based simplified methods have been redefined to ensure that the modified method will lead to conservative results and that a wider range of seismically isolated bridges can be covered by this method. The possibility of further improving current simplified code methods was also examined. By transforming the quantity of allocated energy into a displacement contribution, an idealized analytical solution is proposed as a new simplified design method. This method realistically reflects the effects of ground-motion and system design parameters, including the effects of a drifted oscillation center. The proposed method is therefore more appropriate than current existing simplified methods and can be applicable to isolation systems exhibiting a wider range of properties. A multi-level-hazard performance matrix has been adopted by different seismic provisions worldwide and will be incorporated into the new edition of the Canadian CSA-S6-14 Bridge Design code. However, the combined effect and optimal use of isolation and supplemental damping devices in bridges have not been fully exploited yet to achieve enhanced performance under different levels of seismic hazard. A novel Dual-Level Seismic Protection (DLSP) concept is proposed and developed in this thesis which permits to achieve optimum seismic performance with combined isolation and supplemental damping devices in bridges. This concept is shown to represent an attractive design approach for both the upgrade of existing seismically deficient bridges and the design of new isolated bridges.

Prioritizing Health: A Systematic Approach to Scoping Determinants in Health Impact Assessment.

PubMed

McCallum, Lindsay C; Ollson, Christopher A; Stefanovic, Ingrid L

2016-01-01

The determinants of health are those factors that have the potential to affect health, either positively or negatively, and include a range of personal, social, economic, and environmental factors. In the practice of health impact assessment (HIA), the stage at which the determinants of health are considered for inclusion is during the scoping step. The scoping step is intended to identify how the HIA will be carried out and to set the boundaries (e.g., temporal and geographical) for the assessment. There are several factors that can help to inform the scoping process, many of which are considered in existing HIA tools and guidance; however, a systematic method of prioritizing determinants was found to be lacking. In order to analyze existing HIA scoping tools that are available, a systematic literature review was conducted, including both primary and gray literature. A total of 10 HIA scoping tools met the inclusion/exclusion criteria and were carried forward for comparative analysis. The analysis focused on minimum elements and practice standards of HIA scoping that have been established in the field. The analysis determined that existing approaches lack a clear, systematic method of prioritization of health determinants for inclusion in HIA. This finding led to the development of a Systematic HIA Scoping tool that addressed this gap. The decision matrix tool uses factors, such as impact, public concern, and data availability, to prioritize health determinants. Additionally, the tool allows for identification of data gaps and provides a transparent method for budget allocation and assessment planning. In order to increase efficiency and improve utility, the tool was programed into Microsoft Excel. Future work in the area of HIA methodology development is vital to the ongoing success of the practice and utilization of HIA as a reliable decision-making tool.

Soliton solutions, stability analysis and conservation laws for the brusselator reaction diffusion model with time- and constant-dependent coefficients

NASA Astrophysics Data System (ADS)

Inc, Mustafa; Yusuf, Abdullahi; Isa Aliyu, Aliyu; Hashemi, M. S.

2018-05-01

This paper studies the brusselator reaction diffusion model (BRDM) with time- and constant-dependent coefficients. The soliton solutions for BRDM with time-dependent coefficients are obtained via first integral (FIM), ansatz, and sine-Gordon expansion (SGEM) methods. Moreover, it is well known that stability analysis (SA), symmetry analysis and conservation laws (CLs) give several information for modelling a system of differential equations (SDE). This is because they can be used for investigating the internal properties, existence, uniqueness and integrability of different SDE. For this reason, we investigate the SA via linear stability technique, symmetry analysis and CLs for BRDM with constant-dependent coefficients in order to extract more physics and information on the governing equation. The constraint conditions for the existence of the solutions are also examined. The new solutions obtained in this paper can be useful for describing the concentrations of diffusion problems of the BRDM. It is shown that the examined dependent coefficients are some of the factors that are affecting the diffusion rate. So, the present paper provides much motivational information in comparison to the existing results in the literature.

Cell-fusion method to visualize interphase nuclear pore formation.

PubMed

Maeshima, Kazuhiro; Funakoshi, Tomoko; Imamoto, Naoko

2014-01-01

In eukaryotic cells, the nucleus is a complex and sophisticated organelle that organizes genomic DNA to support essential cellular functions. The nuclear surface contains many nuclear pore complexes (NPCs), channels for macromolecular transport between the cytoplasm and nucleus. It is well known that the number of NPCs almost doubles during interphase in cycling cells. However, the mechanism of NPC formation is poorly understood, presumably because a practical system for analysis does not exist. The most difficult obstacle in the visualization of interphase NPC formation is that NPCs already exist after nuclear envelope formation, and these existing NPCs interfere with the observation of nascent NPCs. To overcome this obstacle, we developed a novel system using the cell-fusion technique (heterokaryon method), previously also used to analyze the shuttling of macromolecules between the cytoplasm and the nucleus, to visualize the newly synthesized interphase NPCs. In addition, we used a photobleaching approach that validated the cell-fusion method. We recently used these methods to demonstrate the role of cyclin-dependent protein kinases and of Pom121 in interphase NPC formation in cycling human cells. Here, we describe the details of the cell-fusion approach and compare the system with other NPC formation visualization methods. Copyright © 2014 Elsevier Inc. All rights reserved.

How Magnetic Disturbance Influences the Attitude and Heading in Magnetic and Inertial Sensor-Based Orientation Estimation.

PubMed

Fan, Bingfei; Li, Qingguo; Liu, Tao

2017-12-28

With the advancements in micro-electromechanical systems (MEMS) technologies, magnetic and inertial sensors are becoming more and more accurate, lightweight, smaller in size as well as low-cost, which in turn boosts their applications in human movement analysis. However, challenges still exist in the field of sensor orientation estimation, where magnetic disturbance represents one of the obstacles limiting their practical application. The objective of this paper is to systematically analyze exactly how magnetic disturbances affects the attitude and heading estimation for a magnetic and inertial sensor. First, we reviewed four major components dealing with magnetic disturbance, namely decoupling attitude estimation from magnetic reading, gyro bias estimation, adaptive strategies of compensating magnetic disturbance and sensor fusion algorithms. We review and analyze the features of existing methods of each component. Second, to understand each component in magnetic disturbance rejection, four representative sensor fusion methods were implemented, including gradient descent algorithms, improved explicit complementary filter, dual-linear Kalman filter and extended Kalman filter. Finally, a new standardized testing procedure has been developed to objectively assess the performance of each method against magnetic disturbance. Based upon the testing results, the strength and weakness of the existing sensor fusion methods were easily examined, and suggestions were presented for selecting a proper sensor fusion algorithm or developing new sensor fusion method.

On existence of the {sigma}(600) Its physical implications and related problems

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

Ishida, Shin

1998-05-29

We make a re-analysis of 1=0 {pi}{pi} scattering phase shift {delta}{sub 0}{sup 0} through a new method of S-matrix parametrization (IA; interfering amplitude method), and show a result suggesting strongly for the existence of {sigma}-particle-long-sought Chiral partner of {pi}-meson. Furthermore, through the phenomenological analyses of typical production processes of the 2{pi}-system, the pp-central collision and the J/{psi}{yields}{omega}{pi}{pi} decay, by applying an intuitive formula as sum of Breit-Wigner amplitudes, (VMW; variant mass and width method), the other evidences for the {sigma}-existence are given. The validity of the methods used in the above analyses is investigated, using a simple field theoretical model,more » from the general viewpoint of unitarity and the applicability of final state interaction (FSI-) theorem, especially in relation to the ''universality'' argument. It is shown that the IA and VMW are obtained as the physical state representations of scattering and production amplitudes, respectively. The VMW is shown to be an effective method to obtain the resonance properties from production processes, which generally have the unknown strong-phases. The conventional analyses based on the 'universality' seem to be powerless for this purpose.« less

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Mechanical modeling for magnetorheological elastomer isolators based on constitutive equations and electromagnetic analysis

NASA Astrophysics Data System (ADS)

Wang, Qi; Dong, Xufeng; Li, Luyu; Ou, Jinping

2018-06-01

As constitutive models are too complicated and existing mechanical models lack universality, these models are beyond satisfaction for magnetorheological elastomer (MRE) devices. In this article, a novel universal method is proposed to build concise mechanical models. Constitutive model and electromagnetic analysis were applied in this method to ensure universality, while a series of derivations and simplifications were carried out to obtain a concise formulation. To illustrate the proposed modeling method, a conical MRE isolator was introduced. Its basic mechanical equations were built based on equilibrium, deformation compatibility, constitutive equations and electromagnetic analysis. An iteration model and a highly efficient differential equation editor based model were then derived to solve the basic mechanical equations. The final simplified mechanical equations were obtained by re-fitting the simulations with a novel optimal algorithm. In the end, verification test of the isolator has proved the accuracy of the derived mechanical model and the modeling method.

Sizing up arthropod genomes: an evaluation of the impact of environmental variation on genome size estimates by flow cytometry and the use of qPCR as a method of estimation.

PubMed

Gregory, T Ryan; Nathwani, Paula; Bonnett, Tiffany R; Huber, Dezene P W

2013-09-01

A study was undertaken to evaluate both a pre-existing method and a newly proposed approach for the estimation of nuclear genome sizes in arthropods. First, concerns regarding the reliability of the well-established method of flow cytometry relating to impacts of rearing conditions on genome size estimates were examined. Contrary to previous reports, a more carefully controlled test found negligible environmental effects on genome size estimates in the fly Drosophila melanogaster. Second, a more recently touted method based on quantitative real-time PCR (qPCR) was examined in terms of ease of use, efficiency, and (most importantly) accuracy using four test species: the flies Drosophila melanogaster and Musca domestica and the beetles Tribolium castaneum and Dendroctonus ponderosa. The results of this analysis demonstrated that qPCR has the tendency to produce substantially different genome size estimates from other established techniques while also being far less efficient than existing methods.

Intensity non-uniformity correction in MRI: existing methods and their validation.

PubMed

Belaroussi, Boubakeur; Milles, Julien; Carme, Sabin; Zhu, Yue Min; Benoit-Cattin, Hugues

2006-04-01

Magnetic resonance imaging is a popular and powerful non-invasive imaging technique. Automated analysis has become mandatory to efficiently cope with the large amount of data generated using this modality. However, several artifacts, such as intensity non-uniformity, can degrade the quality of acquired data. Intensity non-uniformity consists in anatomically irrelevant intensity variation throughout data. It can be induced by the choice of the radio-frequency coil, the acquisition pulse sequence and by the nature and geometry of the sample itself. Numerous methods have been proposed to correct this artifact. In this paper, we propose an overview of existing methods. We first sort them according to their location in the acquisition/processing pipeline. Sorting is then refined based on the assumptions those methods rely on. Next, we present the validation protocols used to evaluate these different correction schemes both from a qualitative and a quantitative point of view. Finally, availability and usability of the presented methods is discussed.

An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.

PubMed

Kim, Junghi; Bai, Yun; Pan, Wei

2015-12-01

We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association study (GWAS) summary statistics without access to individual-level genotype and phenotype data. For most published GWASs, because obtaining summary data is substantially easier than accessing individual-level phenotype and genotype data, while often multiple correlated traits have been collected, the problem studied here has become increasingly important. We propose a powerful adaptive test and compare its performance with some existing tests. We illustrate its applications to analyses of a meta-analyzed GWAS dataset with three blood lipid traits and another with sex-stratified anthropometric traits, and further demonstrate its potential power gain over some existing methods through realistic simulation studies. We start from the situation with only one set of (possibly meta-analyzed) genome-wide summary statistics, then extend the method to meta-analysis of multiple sets of genome-wide summary statistics, each from one GWAS. We expect the proposed test to be useful in practice as more powerful than or complementary to existing methods. © 2015 WILEY PERIODICALS, INC.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Similitude design for the vibration problems of plates and shells: A review

NASA Astrophysics Data System (ADS)

Zhu, Yunpeng; Wang, You; Luo, Zhong; Han, Qingkai; Wang, Deyou

2017-06-01

Similitude design plays a vital role in the analysis of vibration and shock problems encountered in large engineering equipment. Similitude design, including dimensional analysis and governing equation method, is founded on the dynamic similitude theory. This study reviews the application of similitude design methods in engineering practice and summarizes the major achievements of the dynamic similitude theory in structural vibration and shock problems in different fields, including marine structures, civil engineering structures, and large power equipment. This study also reviews the dynamic similitude design methods for thin-walled and composite material plates and shells, including the most recent work published by the authors. Structure sensitivity analysis is used to evaluate the scaling factors to attain accurate distorted scaling laws. Finally, this study discusses the existing problems and the potential of the dynamic similitude theory for the analysis of vibration and shock problems of structures.

A complementation assay for in vivo protein structure/function analysis in Physcomitrella patens (Funariaceae)

DOE PAGES

Scavuzzo-Duggan, Tess R.; Chaves, Arielle M.; Roberts, Alison W.

2015-07-14

Here, a method for rapid in vivo functional analysis of engineered proteins was developed using Physcomitrella patens. A complementation assay was designed for testing structure/function relationships in cellulose synthase (CESA) proteins. The components of the assay include (1) construction of test vectors that drive expression of epitope-tagged PpCESA5 carrying engineered mutations, (2) transformation of a ppcesa5 knockout line that fails to produce gametophores with test and control vectors, (3) scoring the stable transformants for gametophore production, (4) statistical analysis comparing complementation rates for test vectors to positive and negative control vectors, and (5) analysis of transgenic protein expression by Westernmore » blotting. The assay distinguished mutations that generate fully functional, nonfunctional, and partially functional proteins. In conclusion, compared with existing methods for in vivo testing of protein function, this complementation assay provides a rapid method for investigating protein structure/function relationships in plants.« less

A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor.

PubMed

Kim, Ki Wan; Hong, Hyung Gil; Nam, Gi Pyo; Park, Kang Ryoung

2017-06-30

The necessity for the classification of open and closed eyes is increasing in various fields, including analysis of eye fatigue in 3D TVs, analysis of the psychological states of test subjects, and eye status tracking-based driver drowsiness detection. Previous studies have used various methods to distinguish between open and closed eyes, such as classifiers based on the features obtained from image binarization, edge operators, or texture analysis. However, when it comes to eye images with different lighting conditions and resolutions, it can be difficult to find an optimal threshold for image binarization or optimal filters for edge and texture extraction. In order to address this issue, we propose a method to classify open and closed eye images with different conditions, acquired by a visible light camera, using a deep residual convolutional neural network. After conducting performance analysis on both self-collected and open databases, we have determined that the classification accuracy of the proposed method is superior to that of existing methods.

Highly comparative time-series analysis: the empirical structure of time series and their methods.

PubMed

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

Highly comparative time-series analysis: the empirical structure of time series and their methods

PubMed Central

Fulcher, Ben D.; Little, Max A.; Jones, Nick S.

2013-01-01

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines. PMID:23554344

Assessing Species Diversity Using Metavirome Data: Methods and Challenges.

PubMed

Herath, Damayanthi; Jayasundara, Duleepa; Ackland, David; Saeed, Isaam; Tang, Sen-Lin; Halgamuge, Saman

2017-01-01

Assessing biodiversity is an important step in the study of microbial ecology associated with a given environment. Multiple indices have been used to quantify species diversity, which is a key biodiversity measure. Measuring species diversity of viruses in different environments remains a challenge relative to measuring the diversity of other microbial communities. Metagenomics has played an important role in elucidating viral diversity by conducting metavirome studies; however, metavirome data are of high complexity requiring robust data preprocessing and analysis methods. In this review, existing bioinformatics methods for measuring species diversity using metavirome data are categorised broadly as either sequence similarity-dependent methods or sequence similarity-independent methods. The former includes a comparison of DNA fragments or assemblies generated in the experiment against reference databases for quantifying species diversity, whereas estimates from the latter are independent of the knowledge of existing sequence data. Current methods and tools are discussed in detail, including their applications and limitations. Drawbacks of the state-of-the-art method are demonstrated through results from a simulation. In addition, alternative approaches are proposed to overcome the challenges in estimating species diversity measures using metavirome data.

A convenient spectrophotometric assay for the determination of l-ergothioneine in blood

PubMed Central

Carlsson, Jan; Kierstan, Marek P. J.; Brocklehurst, Keith

1974-01-01

1. A convenient spectrophotometric assay for the determination of l-ergothioneine in solution including deproteinized blood haemolysate was developed. 2. The method consists of deproteinization by heat precipitation and Cu2+-catalysed oxidation of thiols such as glutathione and of l-ascorbic acid, both in alkaline media, and titration of l-ergothioneine (which is not oxidized under these conditions) by its virtually instantaneous reaction with 2,2′-dipyridyl disulphide at pH1. 3. This method and the results obtained with it for the analysis of human, horse, sheep and pig blood are compared with existing methods of l-ergothioneine analysis and the results obtained thereby. PMID:4463946

Iris recognition based on robust principal component analysis

NASA Astrophysics Data System (ADS)

Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong

2014-11-01

Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

The Volatility of Data Space: Topology Oriented Sensitivity Analysis

PubMed Central

Du, Jing; Ligmann-Zielinska, Arika

2015-01-01

Despite the difference among specific methods, existing Sensitivity Analysis (SA) technologies are all value-based, that is, the uncertainties in the model input and output are quantified as changes of values. This paradigm provides only limited insight into the nature of models and the modeled systems. In addition to the value of data, a potentially richer information about the model lies in the topological difference between pre-model data space and post-model data space. This paper introduces an innovative SA method called Topology Oriented Sensitivity Analysis, which defines sensitivity as the volatility of data space. It extends SA into a deeper level that lies in the topology of data. PMID:26368929

Subsonic flutter analysis addition to NASTRAN. [for use with CDC 6000 series digital computers

NASA Technical Reports Server (NTRS)

Doggett, R. V., Jr.; Harder, R. L.

1973-01-01

A subsonic flutter analysis capability has been developed for NASTRAN, and a developmental version of the program has been installed on the CDC 6000 series digital computers at the Langley Research Center. The flutter analysis is of the modal type, uses doublet lattice unsteady aerodynamic forces, and solves the flutter equations by using the k-method. Surface and one-dimensional spline functions are used to transform from the aerodynamic degrees of freedom to the structural degrees of freedom. Some preliminary applications of the method to a beamlike wing, a platelike wing, and a platelike wing with a folded tip are compared with existing experimental and analytical results.

Good Laboratory Practices of Materials Testing at NASA White Sands Test Facility

NASA Technical Reports Server (NTRS)

Hirsch, David; Williams, James H.

2005-01-01

An approach to good laboratory practices of materials testing at NASA White Sands Test Facility is presented. The contents include: 1) Current approach; 2) Data analysis; and 3) Improvements sought by WSTF to enhance the diagnostic capability of existing methods.

RELIABLE COMPUTATION OF HOMOGENEOUS AZEOTROPES. (R824731)

EPA Science Inventory

Abstract

It is important to determine the existence and composition of homogeneous azeotropes in the analysis of phase behavior and in the synthesis and design of separation systems, from both theoretical and practical standpoints. A new method for reliably locating an...

Agent-based Training: Facilitating Knowledge and Skill Acquisition in a Modern Space Operations Team

DTIC Science & Technology

2002-04-01

face, and being careful to not add to existing problems such as limited display space. This required us to work closely with members of the SBIRS operational community and use research tools such as cognitive task analysis methods.

Military Support for Youth Development: An Exploratory Analysis

DTIC Science & Technology

1994-01-01

This report assesses existing evidence about the potential of military service and training as methods to prepare disadvantaged youth for productive...whether veterans in general receive a positive or negative return to military service; for disadvantaged veterans, it suggests little if any effect. Results

Empirical intrinsic geometry for nonlinear modeling and time series filtering.

PubMed

Talmon, Ronen; Coifman, Ronald R

2013-07-30

In this paper, we present a method for time series analysis based on empirical intrinsic geometry (EIG). EIG enables one to reveal the low-dimensional parametric manifold as well as to infer the underlying dynamics of high-dimensional time series. By incorporating concepts of information geometry, this method extends existing geometric analysis tools to support stochastic settings and parametrizes the geometry of empirical distributions. However, the statistical models are not required as priors; hence, EIG may be applied to a wide range of real signals without existing definitive models. We show that the inferred model is noise-resilient and invariant under different observation and instrumental modalities. In addition, we show that it can be extended efficiently to newly acquired measurements in a sequential manner. These two advantages enable us to revisit the Bayesian approach and incorporate empirical dynamics and intrinsic geometry into a nonlinear filtering framework. We show applications to nonlinear and non-Gaussian tracking problems as well as to acoustic signal localization.

Automatic Detection and Vulnerability Analysis of Areas Endangered by Heavy Rain

NASA Astrophysics Data System (ADS)

Krauß, Thomas; Fischer, Peter

2016-08-01

In this paper we present a new method for fully automatic detection and derivation of areas endangered by heavy rainfall based only on digital elevation models. Tracking news show that the majority of occuring natural hazards are flood events. So already many flood prediction systems were developed. But most of these existing systems for deriving areas endangered by flooding events are based only on horizontal and vertical distances to existing rivers and lakes. Typically such systems take not into account dangers arising directly from heavy rain events. In a study conducted by us together with a german insurance company a new approach for detection of areas endangered by heavy rain was proven to give a high correlation of the derived endangered areas and the losses claimed at the insurance company. Here we describe three methods for classification of digital terrain models and analyze their usability for automatic detection and vulnerability analysis for areas endangered by heavy rainfall and analyze the results using the available insurance data.

The presence of field geologists in Mars-like terrain

NASA Technical Reports Server (NTRS)

Mcgreevy, Michael W.

1992-01-01

Methods of ethnographic observation and analysis have been coupled with object-oriented analysis and design concepts to begin the development of a clear path from observations in the field to the design of virtual presence systems. The existence of redundancies in field geology and presence allowed for the application of methods for understanding complex systems. As a result of this study, some of these redundancies have been characterized. Those described are all classes of continuity relations, including the continuities of continuous existence, context-constituent continuities, and state-process continuities. The discussion of each includes statements of general relationships, logical consequences of these, and hypothetical situations in which the relationships would apply. These are meant to aid in the development of a theory of presence. The discussion also includes design considerations, providing guidance for the design of virtual planetary exploration systems and other virtual presence systems. Converging evidence regarding continuity in presence is found in the nature of psychological dissociation. Specific methodological refinements should enhance ecological validity in subsequent field studies, which are in progress.

Impact of diet on the design of waste processors in CELSS

NASA Technical Reports Server (NTRS)

Waleh, Ahmad; Kanevsky, Valery; Nguyen, Thoi K.; Upadhye, Ravi; Wydeven, Theodore

1991-01-01

The preliminary results of a design analysis for a waste processor which employs existing technologies and takes into account the constraints of human diet are presented. The impact of diet is determined by using a model and an algorithm developed for the control and management of diet in a Controlled Ecological Life Support System (CELSS). A material and energy balance model for thermal oxidation of waste is developed which is consistent with both physical/chemical methods of incineration and supercritical water oxidation. The two models yield quantitative analysis of the diet and waste streams and the specific design parameters for waste processors, respectively. The results demonstrate that existing technologies can meet the demands of waste processing, but the choice and design of the processors or processing methods will be sensitive to the constraints of diet. The numerical examples are chosen to display the nature and extent of the gap in the available experiment information about CELSS requirements.

Conducting Slug Tests in Mini-Piezometers.

PubMed

Fritz, Bradley G; Mackley, Rob D; Arntzen, Evan V

2016-03-01

Slug tests performed using mini-piezometers with internal diameters as small as 0.43 cm can provide a cost effective tool for hydraulic characterization. We evaluated the hydraulic properties of the apparatus in a laboratory environment and compared those results with field tests of mini-piezometers installed into locations with varying hydraulic properties. Based on our evaluation, slug tests conducted in mini-piezometers using the fabrication and installation approach described here are effective within formations where the hydraulic conductivity is less than 1 × 10(-3) cm/s. While these constraints limit the potential application of this method, the benefits to this approach are that the installation, measurement, and analysis is cost effective, and the installation can be completed in areas where other (larger diameter) methods might not be possible. Additionally, this methodology could be applied to existing mini-piezometers previously installed for other purposes. Such analysis of existing installations could be beneficial in interpreting previously collected data (e.g., water-quality data or hydraulic head data). © 2015, National Ground Water Association.

Time-series RNA-seq analysis package (TRAP) and its application to the analysis of rice, Oryza sativa L. ssp. Japonica, upon drought stress.

PubMed

Jo, Kyuri; Kwon, Hawk-Bin; Kim, Sun

2014-06-01

Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how organisms react to stress conditions over time. Thus many biologists routinely measure whole genome level gene expressions at multiple time points. However, there are several technical difficulties for analyzing such whole genome expression data. In addition, these days gene expression data is often measured by using RNA-sequencing rather than microarray technologies and then analysis of expression data is much more complicated since the analysis process should start with mapping short reads and produce differentially activated pathways and also possibly interactions among pathways. In addition, many useful tools for analyzing microarray gene expression data are not applicable for the RNA-seq data. Thus a comprehensive package for analyzing time series transcriptome data is much needed. In this article, we present a comprehensive package, Time-series RNA-seq Analysis Package (TRAP), integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment. In addition to implementing useful algorithms that are not available for RNA-seq data, we extended existing pathway analysis methods, ORA and SPIA, for time series analysis and estimates statistical values for combined dataset by an advanced metric. TRAP also produces visual summary of pathway interactions. Gene expression change labeling, a practical clustering method used in TRAP, enables more accurate interpretation of the data when combined with pathway analysis. We applied our methods on a real dataset for the analysis of rice (Oryza sativa L. Japonica nipponbare) upon drought stress. The result showed that TRAP was able to detect pathways more accurately than several existing methods. TRAP is available at http://biohealth.snu.ac.kr/software/TRAP/. Copyright © 2014 Elsevier Inc. All rights reserved.

ACCOUNTING FOR CALIBRATION UNCERTAINTIES IN X-RAY ANALYSIS: EFFECTIVE AREAS IN SPECTRAL FITTING

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

Lee, Hyunsook; Kashyap, Vinay L.; Drake, Jeremy J.

2011-04-20

While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a proper interpretation of analysis results because instrumental calibration uncertainty is a form of systematic uncertainty. Ignoring it can underestimate error bars and introduce bias into the fitted values of model parameters. Accounting for such uncertainties currently requires extensive case-specific simulations if using existing analysis packages. Here, we present general statistical methods that incorporate calibration uncertainties into spectral analysis of high-energy data. We first present a method based on multiple imputation that can bemore » applied with any fitting method, but is necessarily approximate. We then describe a more exact Bayesian approach that works in conjunction with a Markov chain Monte Carlo based fitting. We explore methods for improving computational efficiency, and in particular detail a method of summarizing calibration uncertainties with a principal component analysis of samples of plausible calibration files. This method is implemented using recently codified Chandra effective area uncertainties for low-resolution spectral analysis and is verified using both simulated and actual Chandra data. Our procedure for incorporating effective area uncertainty is easily generalized to other types of calibration uncertainties.« less

Improved methods to estimate the effective impervious area in urban catchments using rainfall-runoff data

NASA Astrophysics Data System (ADS)

Ebrahimian, Ali; Wilson, Bruce N.; Gulliver, John S.

2016-05-01

Impervious surfaces are useful indicators of the urbanization impacts on water resources. Effective impervious area (EIA), which is the portion of total impervious area (TIA) that is hydraulically connected to the drainage system, is a better catchment parameter in the determination of actual urban runoff. Development of reliable methods for quantifying EIA rather than TIA is currently one of the knowledge gaps in the rainfall-runoff modeling context. The objective of this study is to improve the rainfall-runoff data analysis method for estimating EIA fraction in urban catchments by eliminating the subjective part of the existing method and by reducing the uncertainty of EIA estimates. First, the theoretical framework is generalized using a general linear least square model and using a general criterion for categorizing runoff events. Issues with the existing method that reduce the precision of the EIA fraction estimates are then identified and discussed. Two improved methods, based on ordinary least square (OLS) and weighted least square (WLS) estimates, are proposed to address these issues. The proposed weighted least squares method is then applied to eleven urban catchments in Europe, Canada, and Australia. The results are compared to map measured directly connected impervious area (DCIA) and are shown to be consistent with DCIA values. In addition, both of the improved methods are applied to nine urban catchments in Minnesota, USA. Both methods were successful in removing the subjective component inherent in the analysis of rainfall-runoff data of the current method. The WLS method is more robust than the OLS method and generates results that are different and more precise than the OLS method in the presence of heteroscedastic residuals in our rainfall-runoff data.

Bridging Human Reliability Analysis and Psychology, Part 1: The Psychological Literature Review for the IDHEAS Method

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

April M. Whaley; Stacey M. L. Hendrickson; Ronald L. Boring

In response to Staff Requirements Memorandum (SRM) SRM-M061020, the U.S. Nuclear Regulatory Commission (NRC) is sponsoring work to update the technical basis underlying human reliability analysis (HRA) in an effort to improve the robustness of HRA. The ultimate goal of this work is to develop a hybrid of existing methods addressing limitations of current HRA models and in particular issues related to intra- and inter-method variabilities and results. This hybrid method is now known as the Integrated Decision-tree Human Event Analysis System (IDHEAS). Existing HRA methods have looked at elements of the psychological literature, but there has not previously beenmore » a systematic attempt to translate the complete span of cognition from perception to action into mechanisms that can inform HRA. Therefore, a first step of this effort was to perform a literature search of psychology, cognition, behavioral science, teamwork, and operating performance to incorporate current understanding of human performance in operating environments, thus affording an improved technical foundation for HRA. However, this literature review went one step further by mining the literature findings to establish causal relationships and explicit links between the different types of human failures, performance drivers and associated performance measures ultimately used for quantification. This is the first of two papers that detail the literature review (paper 1) and its product (paper 2). This paper describes the literature review and the high-level architecture used to organize the literature review, and the second paper (Whaley, Hendrickson, Boring, & Xing, these proceedings) describes the resultant cognitive framework.« less

Efficient calibration for imperfect computer models

DOE PAGES

Tuo, Rui; Wu, C. F. Jeff

2015-12-01

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

Interpolation Method Needed for Numerical Uncertainty Analysis of Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Groves, Curtis; Ilie, Marcel; Schallhorn, Paul

2014-01-01

Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact problem and uncertainties exist. There is a method to approximate the errors in CFD via Richardson's Extrapolation. This method is based off of progressive grid refinement. To estimate the errors in an unstructured grid, the analyst must interpolate between at least three grids. This paper describes a study to find an appropriate interpolation scheme that can be used in Richardson's extrapolation or other uncertainty method to approximate errors. Nomenclature

Analysis and design of three dimensional supersonic nozzles. Volume 1: Nozzle-exhaust flow field analysis by a reference plane characteristics technique

NASA Technical Reports Server (NTRS)

Dash, S.; Delguidice, P.

1972-01-01

A second order numerical method employing reference plane characteristics has been developed for the calculation of geometrically complex three dimensional nozzle-exhaust flow fields, heretofore uncalculable by existing methods. The nozzles may have irregular cross sections with swept throats and may be stacked in modules using the vehicle undersurface for additional expansion. The nozzles may have highly nonuniform entrance conditions, the medium considered being an equilibrium hydrogen-air mixture. The program calculates and carries along the underexpansion shock and contact as discrete discontinuity surfaces, for a nonuniform vehicle external flow.

Some comments on Hurst exponent and the long memory processes on capital markets

NASA Astrophysics Data System (ADS)

Sánchez Granero, M. A.; Trinidad Segovia, J. E.; García Pérez, J.

2008-09-01

The analysis of long memory processes in capital markets has been one of the topics in finance, since the existence of the market memory could implicate the rejection of an efficient market hypothesis. The study of these processes in finance is realized through Hurst exponent and the most classical method applied is R/S analysis. In this paper we will discuss the efficiency of this methodology as well as some of its more important modifications to detect the long memory. We also propose the application of a classical geometrical method with short modifications and we compare both approaches.

Quantifying construction and demolition waste: an analytical review.

PubMed

Wu, Zezhou; Yu, Ann T W; Shen, Liyin; Liu, Guiwen

2014-09-01

Quantifying construction and demolition (C&D) waste generation is regarded as a prerequisite for the implementation of successful waste management. In literature, various methods have been employed to quantify the C&D waste generation at both regional and project levels. However, an integrated review that systemically describes and analyses all the existing methods has yet to be conducted. To bridge this research gap, an analytical review is conducted. Fifty-seven papers are retrieved based on a set of rigorous procedures. The characteristics of the selected papers are classified according to the following criteria - waste generation activity, estimation level and quantification methodology. Six categories of existing C&D waste quantification methodologies are identified, including site visit method, waste generation rate method, lifetime analysis method, classification system accumulation method, variables modelling method and other particular methods. A critical comparison of the identified methods is given according to their characteristics and implementation constraints. Moreover, a decision tree is proposed for aiding the selection of the most appropriate quantification method in different scenarios. Based on the analytical review, limitations of previous studies and recommendations of potential future research directions are further suggested. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime.

PubMed

Fitterer, Jessica L; Nelson, Trisalyn A

2015-01-01

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks).

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime

PubMed Central

Fitterer, Jessica L.; Nelson, Trisalyn A.

2015-01-01

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks). PMID:26418016

Measuring the Return on Information Technology: A Knowledge-Based Approach for Revenue Allocation at the Process and Firm Level

DTIC Science & Technology

2005-07-01

approach for measuring the return on Information Technology (IT) investments. A review of existing methods suggests the difficulty in adequately...measuring the returns of IT at various levels of analysis (e.g., firm or process level). To address this issue, this study aims to develop a method for...view (KBV), this paper proposes an analytic method for measuring the historical revenue and cost of IT investments by estimating the amount of

Computer tomography of flows external to test models

NASA Technical Reports Server (NTRS)

Prikryl, I.; Vest, C. M.

1982-01-01

Computer tomographic techniques for reconstruction of three-dimensional aerodynamic density fields, from interferograms recorded from several different viewing directions were studied. Emphasis is on the case in which an opaque object such as a test model in a wind tunnel obscures significant regions of the interferograms (projection data). A method called the Iterative Convolution Method (ICM), existing methods in which the field is represented by a series expansions, and analysis of real experimental data in the form of aerodynamic interferograms are discussed.

Vision-based building energy diagnostics and retrofit analysis using 3D thermography and building information modeling

NASA Astrophysics Data System (ADS)

Ham, Youngjib

The emerging energy crisis in the building sector and the legislative measures on improving energy efficiency are steering the construction industry towards adopting new energy efficient design concepts and construction methods that decrease the overall energy loads. However, the problems of energy efficiency are not only limited to the design and construction of new buildings. Today, a significant amount of input energy in existing buildings is still being wasted during the operational phase. One primary source of the energy waste is attributed to unnecessary heat flows through building envelopes during hot and cold seasons. This inefficiency increases the operational frequency of heating and cooling systems to keep the desired thermal comfort of building occupants, and ultimately results in excessive energy use. Improving thermal performance of building envelopes can reduce the energy consumption required for space conditioning and in turn provide building occupants with an optimal thermal comfort at a lower energy cost. In this sense, energy diagnostics and retrofit analysis for existing building envelopes are key enablers for improving energy efficiency. Since proper retrofit decisions of existing buildings directly translate into energy cost saving in the future, building practitioners are increasingly interested in methods for reliable identification of potential performance problems so that they can take timely corrective actions. However, sensing what and where energy problems are emerging or are likely to emerge and then analyzing how the problems influence the energy consumption are not trivial tasks. The overarching goal of this dissertation focuses on understanding the gaps in knowledge in methods for building energy diagnostics and retrofit analysis, and filling these gaps by devising a new method for multi-modal visual sensing and analytics using thermography and Building Information Modeling (BIM). First, to address the challenges in scaling and localization issues of 2D thermal image-based inspection, a new computer vision-based method is presented for automated 3D spatio-thermal modeling of building environments from images and localizing the thermal images into the 3D reconstructed scenes, which helps better characterize the as-is condition of existing buildings in 3D. By using these models, auditors can conduct virtual walk-through in buildings and explore the as-is condition of building geometry and the associated thermal conditions in 3D. Second, to address the challenges in qualitative and subjective interpretation of visual data, a new model-based method is presented to convert the 3D thermal profiles of building environments into their associated energy performance metrics. More specifically, the Energy Performance Augmented Reality (EPAR) models are formed which integrate the actual 3D spatio-thermal models ('as-is') with energy performance benchmarks ('as-designed') in 3D. In the EPAR models, the presence and location of potential energy problems in building environments are inferred based on performance deviations. The as-is thermal resistances of the building assemblies are also calculated at the level of mesh vertex in 3D. Then, based on the historical weather data reflecting energy load for space conditioning, the amount of heat transfer that can be saved by improving the as-is thermal resistances of the defective areas to the recommended level is calculated, and the equivalent energy cost for this saving is estimated. The outcome provides building practitioners with unique information that can facilitate energy efficient retrofit decision-makings. This is a major departure from offhand calculations that are based on historical cost data of industry best practices. Finally, to improve the reliability of BIM-based energy performance modeling and analysis for existing buildings, a new model-based automated method is presented to map actual thermal resistance measurements at the level of 3D vertexes to the associated BIM elements and update their corresponding thermal properties in the gbXML schema. By reflecting the as-is building condition in the BIM-based energy modeling process, this method bridges over the gap between the architectural information in the as-designed BIM and the as-is building condition for accurate energy performance analysis. The performance of each method was validated on ten case studies from interiors and exteriors of existing residential and instructional buildings in IL and VA. The extensive experimental results show the promise of the proposed methods in addressing the fundamental challenges of (1) visual sensing : scaling 2D visual assessments to real-world building environments and localizing energy problems; (2) analytics: subjective and qualitative assessments; and (3) BIM-based building energy analysis : a lack of procedures for reflecting the as-is building condition in the energy modeling process. Beyond the technical contributions, the domain expert surveys conducted in this dissertation show that the proposed methods have potential to improve the quality of thermographic inspection processes and complement the current building energy analysis tools.

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

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

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

PubMed Central

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE PAGES

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-11-21

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks.

PubMed

Haraldsdóttir, Hulda S; Fleming, Ronan M T

2016-11-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

PubMed

Ma, Chuang; Wang, Xiangfeng

2012-09-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

PubMed Central

Ma, Chuang; Wang, Xiangfeng

2012-01-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655

A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram

PubMed Central

Chu, Catherine. J.; Chan, Arthur; Song, Dan; Staley, Kevin J.; Stufflebeam, Steven M.; Kramer, Mark A.

2017-01-01

Summary Background High frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. New Method The new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. Results We evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. Comparison with Existing Method The proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. Conclusions Accurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable. PMID:27988323

Design, Generation and Tooth Contact Analysis (TCA) of Asymmetric Face Gear Drive With Modified Geometry

NASA Technical Reports Server (NTRS)

Litvin, Faydor L.; Fuentes, Alfonso; Hawkins, J. M.; Handschuh, Robert F.

2001-01-01

A new type of face gear drive for application in transmissions, particularly in helicopters, has been developed. The new geometry differs from the existing geometry by application of asymmetric profiles and double-crowned pinion of the face gear mesh. The paper describes the computerized design, simulation of meshing and contact, and stress analysis by finite element method. Special purpose computer codes have been developed to conduct the analysis. The analysis of this new type of face gear is illustrated with a numerical example.

Performance Improvement of Power Analysis Attacks on AES with Encryption-Related Signals

NASA Astrophysics Data System (ADS)

Lee, You-Seok; Lee, Young-Jun; Han, Dong-Guk; Kim, Ho-Won; Kim, Hyoung-Nam

A power analysis attack is a well-known side-channel attack but the efficiency of the attack is frequently degraded by the existence of power components, irrelative to the encryption included in signals used for the attack. To enhance the performance of the power analysis attack, we propose a preprocessing method based on extracting encryption-related parts from the measured power signals. Experimental results show that the attacks with the preprocessed signals detect correct keys with much fewer signals, compared to the conventional power analysis attacks.

A single extraction and HPLC procedure for simultaneous analysis of phytosterols, tocopherols and lutein in soybeans.

PubMed

Slavin, Margaret; Yu, Liangli Lucy

2012-12-15

A saponification/extraction procedure and high performance liquid chromatography (HPLC) analysis method were developed and validated for simultaneous analysis of phytosterols, tocopherols and lutein (a carotenoid) in soybeans. Separation was achieved on a phenyl column with a ternary, isocratic solvent system of acetonitrile, methanol and water (48:22.5:29.5, v/v/v). Evaporative light scattering detection (ELSD) was used to quantify β-sitosterol, stigmasterol, campesterol, and α-, δ- and γ-tocopherols, while lutein was quantified with visible light absorption at 450 nm. Peak identification was verified by retention times and spikes with external standards. Standard curves were constructed (R(2)>0.99) to allow for sample quantification. Recovery of the saponification and extraction was demonstrated via analysis of spiked samples. Also, the accuracy of results of four soybeans using the described saponification and HPLC analytical method was validated against existing methods. This method offers a more efficient alternative to individual methods for quantifying lutein, tocopherols and sterols in soybeans. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes.

PubMed

Binns, Michael; de Atauri, Pedro; Vlysidis, Anestis; Cascante, Marta; Theodoropoulos, Constantinos

2015-02-18

Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value. In this work, we have modified the applied linear objective of flux balance analysis to include a poling penalty function, which pushes each new set of reaction fluxes away from previous solutions generated. Repeated poling-based flux balance analysis generates a sample of different solutions (a characteristic set), which represents all the possible functionality of the reaction network. Compared to existing sampling methods, for the purpose of generating a relatively "small" characteristic set, our new method is shown to obtain a higher coverage than competing methods under most conditions. The influence of the linear objective function on the sampling (the linear bias) constrains optimisation results to a subspace of optimal solutions all producing the same maximal fluxes. Visualisation of reaction fluxes plotted against each other in 2 dimensions with and without the linear bias indicates the existence of correlations between fluxes. This method of sampling is applied to the organism Actinobacillus succinogenes for the production of succinic acid from glycerol. A new method of sampling for the generation of different flux distributions (sets of individual fluxes satisfying constraints on the steady-state mass balances of intermediates) has been developed using a relatively simple modification of flux balance analysis to include a poling penalty function inside the resulting optimisation objective function. This new methodology can achieve a high coverage of the possible flux space and can be used with and without linear bias to show optimal versus sub-optimal solution spaces. Basic analysis of the Actinobacillus succinogenes system using sampling shows that in order to achieve the maximal succinic acid production CO₂ must be taken into the system. Solutions involving release of CO₂ all give sub-optimal succinic acid production.

Validation of protein carbonyl measurement: A multi-centre study

PubMed Central

Augustyniak, Edyta; Adam, Aisha; Wojdyla, Katarzyna; Rogowska-Wrzesinska, Adelina; Willetts, Rachel; Korkmaz, Ayhan; Atalay, Mustafa; Weber, Daniela; Grune, Tilman; Borsa, Claudia; Gradinaru, Daniela; Chand Bollineni, Ravi; Fedorova, Maria; Griffiths, Helen R.

2014-01-01

Protein carbonyls are widely analysed as a measure of protein oxidation. Several different methods exist for their determination. A previous study had described orders of magnitude variance that existed when protein carbonyls were analysed in a single laboratory by ELISA using different commercial kits. We have further explored the potential causes of variance in carbonyl analysis in a ring study. A soluble protein fraction was prepared from rat liver and exposed to 0, 5 and 15 min of UV irradiation. Lyophilised preparations were distributed to six different laboratories that routinely undertook protein carbonyl analysis across Europe. ELISA and Western blotting techniques detected an increase in protein carbonyl formation between 0 and 5 min of UV irradiation irrespective of method used. After irradiation for 15 min, less oxidation was detected by half of the laboratories than after 5 min irradiation. Three of the four ELISA carbonyl results fell within 95% confidence intervals. Likely errors in calculating absolute carbonyl values may be attributed to differences in standardisation. Out of up to 88 proteins identified as containing carbonyl groups after tryptic cleavage of irradiated and control liver proteins, only seven were common in all three liver preparations. Lysine and arginine residues modified by carbonyls are likely to be resistant to tryptic proteolysis. Use of a cocktail of proteases may increase the recovery of oxidised peptides. In conclusion, standardisation is critical for carbonyl analysis and heavily oxidised proteins may not be effectively analysed by any existing technique. PMID:25560243

Hypercuboidal renormalization in spin foam quantum gravity

NASA Astrophysics Data System (ADS)

Bahr, Benjamin; Steinhaus, Sebastian

2017-06-01

In this article, we apply background-independent renormalization group methods to spin foam quantum gravity. It is aimed at extending and elucidating the analysis of a companion paper, in which the existence of a fixed point in the truncated renormalization group flow for the model was reported. Here, we repeat the analysis with various modifications and find that both qualitative and quantitative features of the fixed point are robust in this setting. We also go into details about the various approximation schemes employed in the analysis.

Analytical concepts for health management systems of liquid rocket engines

NASA Technical Reports Server (NTRS)

Williams, Richard; Tulpule, Sharayu; Hawman, Michael

1990-01-01

Substantial improvement in health management systems performance can be realized by implementing advanced analytical methods of processing existing liquid rocket engine sensor data. In this paper, such techniques ranging from time series analysis to multisensor pattern recognition to expert systems to fault isolation models are examined and contrasted. The performance of several of these methods is evaluated using data from test firings of the Space Shuttle main engines.

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

PubMed

Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

2013-05-01

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process

PubMed Central

Chen, Yang; Zhang, Michael Q.

2018-01-01

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. PMID:29440282

TMA Vessel Segmentation Based on Color and Morphological Features: Application to Angiogenesis Research

PubMed Central

Fernández-Carrobles, M. Milagro; Tadeo, Irene; Bueno, Gloria; Noguera, Rosa; Déniz, Oscar; Salido, Jesús; García-Rojo, Marcial

2013-01-01

Given that angiogenesis and lymphangiogenesis are strongly related to prognosis in neoplastic and other pathologies and that many methods exist that provide different results, we aim to construct a morphometric tool allowing us to measure different aspects of the shape and size of vascular vessels in a complete and accurate way. The developed tool presented is based on vessel closing which is an essential property to properly characterize the size and the shape of vascular and lymphatic vessels. The method is fast and accurate improving existing tools for angiogenesis analysis. The tool also improves the accuracy of vascular density measurements, since the set of endothelial cells forming a vessel is considered as a single object. PMID:24489494

Application of multi-agent coordination methods to the design of space debris mitigation tours

NASA Astrophysics Data System (ADS)

Stuart, Jeffrey; Howell, Kathleen; Wilson, Roby

2016-04-01

The growth in the number of defunct and fragmented objects near to the Earth poses a growing hazard to launch operations as well as existing on-orbit assets. Numerous studies have demonstrated the positive impact of active debris mitigation campaigns upon the growth of debris populations, but comparatively fewer investigations incorporate specific mission scenarios. Furthermore, while many active mitigation methods have been proposed, certain classes of debris objects are amenable to mitigation campaigns employing chaser spacecraft with existing chemical and low-thrust propulsive technologies. This investigation incorporates an ant colony optimization routing algorithm and multi-agent coordination via auctions into a debris mitigation tour scheme suitable for preliminary mission design and analysis as well as spacecraft flight operations.

Leakage detection in galvanized iron pipelines using ensemble empirical mode decomposition analysis

NASA Astrophysics Data System (ADS)

Amin, Makeen; Ghazali, M. Fairusham

2015-05-01

There are many numbers of possible approaches to detect leaks. Some leaks are simply noticeable when the liquids or water appears on the surface. However many leaks do not find their way to the surface and the existence has to be check by analysis of fluid flow in the pipeline. The first step is to determine the approximate position of leak. This can be done by isolate the sections of the mains in turn and noting which section causes a drop in the flow. Next approach is by using sensor to locate leaks. This approach are involves strain gauge pressure transducers and piezoelectric sensor. the occurrence of leaks and know its exact location in the pipeline by using specific method which are Acoustic leak detection method and transient method. The objective is to utilize the signal processing technique in order to analyse leaking in the pipeline. With this, an EEMD method will be applied as the analysis method to collect and analyse the data.

Development and application of dynamic hybrid multi-region inventory analysis for macro-level environmental policy analysis: a case study on climate policy in Taiwan.

PubMed

Chao, Chia-Wei; Heijungs, Reinout; Ma, Hwong-wen

2013-03-19

We develop a novel inventory method called Dynamic Hybrid Multi-Region Inventory analysis (DHMRI), which integrates the EEMRIOA and Integrated Hybrid LCA and applies time-dependent environmental intervention information for inventory analysis. Consequently, DHMRI is able to quantify the change in the environmental footprint caused by a specific policy while taking structural changes and technological dynamics into consideration. DHMRI is applied to assess the change in the total CO2 emissions associated with the total final demand caused by the climate policy in Taiwan to demonstrate the practicality of this novel method. The evaluation reveals that the implementation of mitigation measures included in the existing climate policy, such as an enhancement in energy efficiency, promotion of renewable energy, and limitation of the growth of energy-intensive industries, will lead to a 28% increase in the total CO2 emissions and that the main driver is the export-oriented electronics industry. Moreover, a major increase in the total emissions is predicted to occur in Southeast Asia and China. The observations from the case study reveal that DHMRI is capable of overcoming the limitations of existing assessment tools at macro-level evaluation of environmental policies.

Probability Density Functions of Observed Rainfall in Montana

NASA Technical Reports Server (NTRS)

Larsen, Scott D.; Johnson, L. Ronald; Smith, Paul L.

1995-01-01

The question of whether a rain rate probability density function (PDF) can vary uniformly between precipitation events is examined. Image analysis on large samples of radar echoes is possible because of advances in technology. The data provided by such an analysis easily allow development of radar reflectivity factors (and by extension rain rate) distribution. Finding a PDF becomes a matter of finding a function that describes the curve approximating the resulting distributions. Ideally, one PDF would exist for all cases; or many PDF's that have the same functional form with only systematic variations in parameters (such as size or shape) exist. Satisfying either of theses cases will, validate the theoretical basis of the Area Time Integral (ATI). Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89 percent of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit. Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89% of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit.

Software phantom with realistic speckle modeling for validation of image analysis methods in echocardiography

NASA Astrophysics Data System (ADS)

Law, Yuen C.; Tenbrinck, Daniel; Jiang, Xiaoyi; Kuhlen, Torsten

2014-03-01

Computer-assisted processing and interpretation of medical ultrasound images is one of the most challenging tasks within image analysis. Physical phenomena in ultrasonographic images, e.g., the characteristic speckle noise and shadowing effects, make the majority of standard methods from image analysis non optimal. Furthermore, validation of adapted computer vision methods proves to be difficult due to missing ground truth information. There is no widely accepted software phantom in the community and existing software phantoms are not exible enough to support the use of specific speckle models for different tissue types, e.g., muscle and fat tissue. In this work we propose an anatomical software phantom with a realistic speckle pattern simulation to _ll this gap and provide a exible tool for validation purposes in medical ultrasound image analysis. We discuss the generation of speckle patterns and perform statistical analysis of the simulated textures to obtain quantitative measures of the realism and accuracy regarding the resulting textures.

Using Economic Evaluation to Illustrate Value of Care for Improving Patient Safety and Quality: Choosing the Right Method.

PubMed

Padula, William V; Lee, Ken K H; Pronovost, Peter J

2017-08-03

To scale and sustain successful quality improvement (QI) interventions, it is recommended for health system leaders to calculate the economic and financial sustainability of the intervention. Many methods of economic evaluation exist, and the type of method depends on the audience: providers, researchers, and hospital executives. This is a primer to introduce cost-effectiveness analysis, budget impact analysis, and return on investment calculation as 3 distinct methods for each stakeholder needing a measurement of the value of QI at the health system level. Using cases for the QI of hospital-acquired condition rates (e.g., pressure injuries), this primer proceeds stepwise through each method beginning from the same starting point of constructing a model so that the repetition of steps is minimized and thereby capturing the attention of all intended audiences.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, George

1993-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, Stanislav

1992-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

Exploring the Concept of HIV-Related Stigma

PubMed Central

Florom-Smith, Aubrey L.; De Santis, Joseph P.

2013-01-01

BACKGROUND HIV infection is a chronic, manageable illness. Despite advances in the care and treatment of people living with HIV infection, HIV-related stigma remains a challenge to HIV testing, care, and prevention. Numerous studies have documented the impact of HIV-related stigma among various groups of people living with HIV infection, but the concept of HIV-related stigma remains unclear. PURPOSE Concept exploration of HIV-related stigma via an integrative literature review was conducted in order to examine the existing knowledge base of this concept. METHODS Search engines were employed to review the existing knowledge base of this concept. CONCLUSION After the integrative literature review, an analysis of HIV-related stigma emerged. Implications for future concept analysis, research, and practice are included. PMID:22861652

Application of Key Events and Analysis to Chemical Carcinogens and Noncarcinogens

EPA Science Inventory

The existence of thresholds for toxicants is a matter of debate in chemical rsk assessment and regulation. Current risk assessment methods are based on the assumption that, in the basense of sufficient data, carcinogenesis does not have a threshold, while non-carcinogenic endpoi...

Management and analysis of Michigan intelligent transportation systems center data with application to the Detroit area I-75 corridor.

DOT National Transportation Integrated Search

2011-02-01

An understanding of traffic flow in time and space is fundamental to the development of : strategies for the efficient use of the existing transportation infrastructure in large : metropolitan areas. Thus, this project involved developing the methods...

An Analysis of Item Identification for Additive Manufacturing (3-D Printing) Within the Naval Supply Chain

DTIC Science & Technology

2014-12-01

manufacturing BPA blanket purchase agreement BMW Bavarian Motor Works CAD computer-aided design CASREP casualty report CDSA Combat Direction...agreements ( BPA ), and through existing indefinite delivery and indefinite quantity (IDIQ) contracts. These types of procurement methods have less visibility

A Practical Approach to Vocabulary Reinforcement.

ERIC Educational Resources Information Center

Stieglitz, Ezra L.

1983-01-01

Techniques of semantic feature analysis are applied to exploration and reinforcement of vocabulary. Students are presented with categories of familiar items and asked to describe their characteristics. The method can be used to elicit sentences, reinforce existing vocabulary, and begin discussion. Sample exercises for several difficulty levels are…

A possible additional body in eclipsing binary system HS 2231+2441

NASA Astrophysics Data System (ADS)

Vidmachenko, A. P.; Shliakhetska, Ya. O.; Romanyuk, Ya. O.

2016-12-01

Analysis of the light curves of eclipsing binary systems HS 2231+2441, obtained with the 36-cm telescope, is made. In processing the photometric data on eclipses by method of timing, obtained evidence for the existence of a third body in the system.

Correlation of rapid hydrometer analysis for select material to existing procedure LDH-TR-407-66 : final report.

DOT National Transportation Integrated Search

1968-05-01

Conditions arise during construction of bases with Portland cement stabilized soils which require close programming of work. Therefore, time is of significant importance. : That is the objective of this report; to evaluate a method by which considera...

An extended GS method for dense linear systems

NASA Astrophysics Data System (ADS)

Niki, Hiroshi; Kohno, Toshiyuki; Abe, Kuniyoshi

2009-09-01

Davey and Rosindale [K. Davey, I. Rosindale, An iterative solution scheme for systems of boundary element equations, Internat. J. Numer. Methods Engrg. 37 (1994) 1399-1411] derived the GSOR method, which uses an upper triangular matrix [Omega] in order to solve dense linear systems. By applying functional analysis, the authors presented an expression for the optimum [Omega]. Moreover, Davey and Bounds [K. Davey, S. Bounds, A generalized SOR method for dense linear systems of boundary element equations, SIAM J. Comput. 19 (1998) 953-967] also introduced further interesting results. In this note, we employ a matrix analysis approach to investigate these schemes, and derive theorems that compare these schemes with existing preconditioners for dense linear systems. We show that the convergence rate of the Gauss-Seidel method with preconditioner PG is superior to that of the GSOR method. Moreover, we define some splittings associated with the iterative schemes. Some numerical examples are reported to confirm the theoretical analysis. We show that the EGS method with preconditioner produces an extremely small spectral radius in comparison with the other schemes considered.

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

Stability analysis for a multi-camera photogrammetric system.

PubMed

Habib, Ayman; Detchev, Ivan; Kwak, Eunju

2014-08-18

Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction.

Stability Analysis for a Multi-Camera Photogrammetric System

PubMed Central

Habib, Ayman; Detchev, Ivan; Kwak, Eunju

2014-01-01

Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction. PMID:25196012

Rapid preparation of nuclei-depleted detergent-resistant membrane fractions suitable for proteomics analysis.

PubMed

Adam, Rosalyn M; Yang, Wei; Di Vizio, Dolores; Mukhopadhyay, Nishit K; Steen, Hanno

2008-06-05

Cholesterol-rich membrane microdomains known as lipid rafts have been implicated in diverse physiologic processes including lipid transport and signal transduction. Lipid rafts were originally defined as detergent-resistant membranes (DRMs) due to their relative insolubility in cold non-ionic detergents. Recent findings suggest that, although DRMs are not equivalent to lipid rafts, the presence of a given protein within DRMs strongly suggests its potential for raft association in vivo. Therefore, isolation of DRMs represents a useful starting point for biochemical analysis of lipid rafts. The physicochemical properties of DRMs present unique challenges to analysis of their protein composition. Existing methods of isolating DRM-enriched fractions involve flotation of cell extracts in a sucrose density gradient, which, although successful, can be labor intensive, time consuming and results in dilute sucrose-containing fractions with limited utility for direct proteomic analysis. In addition, several studies describing the proteomic characterization of DRMs using this and other approaches have reported the presence of nuclear proteins in such fractions. It is unclear whether these results reflect trafficking of nuclear proteins to DRMs or whether they arise from nuclear contamination during isolation. To address these issues, we have modified a published differential detergent extraction method to enable rapid DRM isolation that minimizes nuclear contamination and yields fractions compatible with mass spectrometry. DRM-enriched fractions isolated using the conventional or modified extraction methods displayed comparable profiles of known DRM-associated proteins, including flotillins, GPI-anchored proteins and heterotrimeric G-protein subunits. Thus, the modified procedure yielded fractions consistent with those isolated by existing methods. However, we observed a marked reduction in the percentage of nuclear proteins identified in DRM fractions isolated with the modified method (15%) compared to DRMs isolated by conventional means (36%). Furthermore, of the 21 nuclear proteins identified exclusively in modified DRM fractions, 16 have been reported to exist in other subcellular sites, with evidence to suggest shuttling of these species between the nucleus and other organelles. We describe a modified DRM isolation procedure that generates DRMs that are largely free of nuclear contamination and that is compatible with downstream proteomic analyses with minimal additional processing. Our findings also imply that identification of nuclear proteins in DRMs is likely to reflect legitimate movement of proteins between compartments, and is not a result of contamination during extraction.

Evaluation of the marginal fit of single-unit, complete-coverage ceramic restorations fabricated after digital and conventional impressions: A systematic review and meta-analysis.

PubMed

Tsirogiannis, Panagiotis; Reissmann, Daniel R; Heydecke, Guido

2016-09-01

In existing published reports, some studies indicate the superiority of digital impression systems in terms of the marginal accuracy of ceramic restorations, whereas others show that the conventional method provides restorations with better marginal fit than fully digital fabrication. Which impression method provides the lowest mean values for marginal adaptation is inconclusive. The findings from those studies cannot be easily generalized, and in vivo studies that could provide valid and meaningful information are limited in the existing publications. The purpose of this study was to systematically review existing reports and evaluate the marginal fit of ceramic single-tooth restorations after either digital or conventional impression methods by combining the available evidence in a meta-analysis. The search strategy for this systematic review of the publications was based on a Population, Intervention, Comparison, and Outcome (PICO) framework. For the statistical analysis, the mean marginal fit values of each study were extracted and categorized according to the impression method to calculate the mean value, together with the 95% confidence intervals (CI) of each category, and to evaluate the impact of each impression method on the marginal adaptation by comparing digital and conventional techniques separately for in vitro and in vivo studies. Twelve studies were included in the meta-analysis from the 63 identified records after database searching. For the in vitro studies, where ceramic restorations were fabricated after conventional impressions, the mean value of the marginal fit was 58.9 μm (95% CI: 41.1-76.7 μm), whereas after digital impressions, it was 63.3 μm (95% CI: 50.5-76.0 μm). In the in vivo studies, the mean marginal discrepancy of the restorations after digital impressions was 56.1 μm (95% CI: 46.3-65.8 μm), whereas after conventional impressions, it was 79.2 μm (95% CI: 59.6-98.9 μm) No significant difference was observed regarding the marginal discrepancy of single-unit ceramic restorations fabricated after digital or conventional impressions. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

Novel Method For Low-Rate Ddos Attack Detection

NASA Astrophysics Data System (ADS)

Chistokhodova, A. A.; Sidorov, I. D.

2018-05-01

The relevance of the work is associated with an increasing number of advanced types of DDoS attacks, in particular, low-rate HTTP-flood. Last year, the power and complexity of such attacks increased significantly. The article is devoted to the analysis of DDoS attacks detecting methods and their modifications with the purpose of increasing the accuracy of DDoS attack detection. The article details low-rate attacks features in comparison with conventional DDoS attacks. During the analysis, significant shortcomings of the available method for detecting low-rate DDoS attacks were found. Thus, the result of the study is an informal description of a new method for detecting low-rate denial-of-service attacks. The architecture of the stand for approbation of the method is developed. At the current stage of the study, it is possible to improve the efficiency of an already existing method by using a classifier with memory, as well as additional information.

Extracting insights from the shape of complex data using topology

PubMed Central

Lum, P. Y.; Singh, G.; Lehman, A.; Ishkanov, T.; Vejdemo-Johansson, M.; Alagappan, M.; Carlsson, J.; Carlsson, G.

2013-01-01

This paper applies topological methods to study complex high dimensional data sets by extracting shapes (patterns) and obtaining insights about them. Our method combines the best features of existing standard methodologies such as principal component and cluster analyses to provide a geometric representation of complex data sets. Through this hybrid method, we often find subgroups in data sets that traditional methodologies fail to find. Our method also permits the analysis of individual data sets as well as the analysis of relationships between related data sets. We illustrate the use of our method by applying it to three very different kinds of data, namely gene expression from breast tumors, voting data from the United States House of Representatives and player performance data from the NBA, in each case finding stratifications of the data which are more refined than those produced by standard methods. PMID:23393618

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Extracting insights from the shape of complex data using topology.

PubMed

Lum, P Y; Singh, G; Lehman, A; Ishkanov, T; Vejdemo-Johansson, M; Alagappan, M; Carlsson, J; Carlsson, G

2013-01-01

This paper applies topological methods to study complex high dimensional data sets by extracting shapes (patterns) and obtaining insights about them. Our method combines the best features of existing standard methodologies such as principal component and cluster analyses to provide a geometric representation of complex data sets. Through this hybrid method, we often find subgroups in data sets that traditional methodologies fail to find. Our method also permits the analysis of individual data sets as well as the analysis of relationships between related data sets. We illustrate the use of our method by applying it to three very different kinds of data, namely gene expression from breast tumors, voting data from the United States House of Representatives and player performance data from the NBA, in each case finding stratifications of the data which are more refined than those produced by standard methods.

A study of best practices in promoting sustainable urbanization in China.

PubMed

Tan, Yongtao; Xu, Hui; Jiao, Liudan; Ochoa, J Jorge; Shen, Liyin

2017-05-15

In the past twenty years, various sustainable urban development policies and methods had been implemented within China, such that sustainable urbanization is now more widely accepted. Some of these policies and methods have been found to be successful in improving the sustainability of cities in China. Those practices can be defined as the best practices of sustainable urbanization, which can provide useful references for future urban developments. However, few existing studies examine how to learn from these best practices. Combining the methods of content analysis and social network analysis, this paper conducts a comprehensive study on 150 best practices of sustainable urbanization in China. The methods and outcomes of the 150 best practices are identified. The research findings demonstrate the statistics of categories, methods and outcomes of the 150 best practices and the main adopted methods. The achieved outcomes in different regions of China are also presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Radar signal analysis of ballistic missile with micro-motion based on time-frequency distribution

NASA Astrophysics Data System (ADS)

Wang, Jianming; Liu, Lihua; Yu, Hua

2015-12-01

The micro-motion of ballistic missile targets induces micro-Doppler modulation on the radar return signal, which is a unique feature for the warhead discrimination during flight. In order to extract the micro-Doppler feature of ballistic missile targets, time-frequency analysis is employed to process the micro-Doppler modulated time-varying radar signal. The images of time-frequency distribution (TFD) reveal the micro-Doppler modulation characteristic very well. However, there are many existing time-frequency analysis methods to generate the time-frequency distribution images, including the short-time Fourier transform (STFT), Wigner distribution (WD) and Cohen class distribution, etc. Under the background of ballistic missile defence, the paper aims at working out an effective time-frequency analysis method for ballistic missile warhead discrimination from the decoys.

Conceptual designs for in situ analysis of Mars soil

NASA Technical Reports Server (NTRS)

Mckay, C. P.; Zent, A. P.; Hartman, H.

1991-01-01

A goal of this research is to develop conceptual designs for instrumentation to perform in situ measurements of the Martian soil in order to determine the existence and nature of any reactive chemicals. Our approach involves assessment and critical review of the Viking biology results which indicated the presence of a soil oxidant, an investigation of the possible application of standard soil science techniques to the analysis of Martian soil, and a preliminary consideration of non-standard methods that may be necessary for use in the highly oxidizing Martian soil. Based on our preliminary analysis, we have developed strawman concepts for standard soil analysis on Mars, including pH, suitable for use on a Mars rover mission. In addition, we have devised a method for the determination of the possible strong oxidants on Mars.

Cue-based assertion classification for Swedish clinical text – developing a lexicon for pyConTextSwe

PubMed Central

Velupillai, Sumithra; Skeppstedt, Maria; Kvist, Maria; Mowery, Danielle; Chapman, Brian E.; Dalianis, Hercules; Chapman, Wendy W.

2014-01-01

Objective The ability of a cue-based system to accurately assert whether a disorder is affirmed, negated, or uncertain is dependent, in part, on its cue lexicon. In this paper, we continue our study of porting an assertion system (pyConTextNLP) from English to Swedish (pyConTextSwe) by creating an optimized assertion lexicon for clinical Swedish. Methods and material We integrated cues from four external lexicons, along with generated inflections and combinations. We used subsets of a clinical corpus in Swedish. We applied four assertion classes (definite existence, probable existence, probable negated existence and definite negated existence) and two binary classes (existence yes/no and uncertainty yes/no) to pyConTextSwe. We compared pyConTextSwe’s performance with and without the added cues on a development set, and improved the lexicon further after an error analysis. On a separate evaluation set, we calculated the system’s final performance. Results Following integration steps, we added 454 cues to pyConTextSwe. The optimized lexicon developed after an error analysis resulted in statistically significant improvements on the development set (83% F-score, overall). The system’s final F-scores on an evaluation set were 81% (overall). For the individual assertion classes, F-score results were 88% (definite existence), 81% (probable existence), 55% (probable negated existence), and 63% (definite negated existence). For the binary classifications existence yes/no and uncertainty yes/no, final system performance was 97%/87% and 78%/86% F-score, respectively. Conclusions We have successfully ported pyConTextNLP to Swedish (pyConTextSwe). We have created an extensive and useful assertion lexicon for Swedish clinical text, which could form a valuable resource for similar studies, and which is publicly available. PMID:24556644

A novel measure of effect size for mediation analysis.

PubMed

Lachowicz, Mark J; Preacher, Kristopher J; Kelley, Ken

2018-06-01

Mediation analysis has become one of the most popular statistical methods in the social sciences. However, many currently available effect size measures for mediation have limitations that restrict their use to specific mediation models. In this article, we develop a measure of effect size that addresses these limitations. We show how modification of a currently existing effect size measure results in a novel effect size measure with many desirable properties. We also derive an expression for the bias of the sample estimator for the proposed effect size measure and propose an adjusted version of the estimator. We present a Monte Carlo simulation study conducted to examine the finite sampling properties of the adjusted and unadjusted estimators, which shows that the adjusted estimator is effective at recovering the true value it estimates. Finally, we demonstrate the use of the effect size measure with an empirical example. We provide freely available software so that researchers can immediately implement the methods we discuss. Our developments here extend the existing literature on effect sizes and mediation by developing a potentially useful method of communicating the magnitude of mediation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Derivation of groundwater flow-paths based on semi-automatic extraction of lineaments from remote sensing data

NASA Astrophysics Data System (ADS)

Mallast, U.; Gloaguen, R.; Geyer, S.; Rödiger, T.; Siebert, C.

2011-08-01

In this paper we present a semi-automatic method to infer groundwater flow-paths based on the extraction of lineaments from digital elevation models. This method is especially adequate in remote and inaccessible areas where in-situ data are scarce. The combined method of linear filtering and object-based classification provides a lineament map with a high degree of accuracy. Subsequently, lineaments are differentiated into geological and morphological lineaments using auxiliary information and finally evaluated in terms of hydro-geological significance. Using the example of the western catchment of the Dead Sea (Israel/Palestine), the orientation and location of the differentiated lineaments are compared to characteristics of known structural features. We demonstrate that a strong correlation between lineaments and structural features exists. Using Euclidean distances between lineaments and wells provides an assessment criterion to evaluate the hydraulic significance of detected lineaments. Based on this analysis, we suggest that the statistical analysis of lineaments allows a delineation of flow-paths and thus significant information on groundwater movements. To validate the flow-paths we compare them to existing results of groundwater models that are based on well data.

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

PubMed

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Poly(ethylene oxide) Chains Are Not ``Hydrophilic'' When They Exist As Polymer Brush Chains

NASA Astrophysics Data System (ADS)

Lee, Hoyoung; Kim, Dae Hwan; Witte, Kevin N.; Ohn, Kimberly; Choi, Je; Kim, Kyungil; Meron, Mati; Lin, Binhua; Akgun, Bulent; Satija, Sushil; Won, You-Yeon

2012-02-01

By using a combined experimental and theoretical approach, a model poly(ethylene oxide) (PEO) brush system, prepared by spreading a poly(ethylene oxide)-poly(n-butyl acrylate) (PEO-PnBA) amphiphilic diblock copolymer onto an air-water interface, was investigated. The polymer segment density profiles of the PEO brush in the direction normal to the air-water interface under various grafting density conditions were determined from combined X-ray and neutron reflectivity data. In order to achieve a theoretically sound analysis of the reflectivity data, we developed a new data analysis method that uses the self-consistent field theoretical modeling as a tool for predicting expected reflectivity results for comparison with the experimental data. Using this new data analysis method, we discovered that the effective Flory-Huggins interaction parameter of the PEO brush chains is significantly greater than that corresponding to the theta condition, suggesting that contrary to what is more commonly observed for PEO in normal situations, the PEO chains are actually not ``hydrophilic'' when they exist as polymer brush chains, because of the many body interactions forced to be effective in the brush situation.

Speed of Sound and Ultrasound Absorption in Ionic Liquids.

PubMed

Dzida, Marzena; Zorębski, Edward; Zorębski, Michał; Żarska, Monika; Geppert-Rybczyńska, Monika; Chorążewski, Mirosław; Jacquemin, Johan; Cibulka, Ivan

2017-03-08

A complete review of the literature data on the speed of sound and ultrasound absorption in pure ionic liquids (ILs) is presented. Apart of the analysis of data published to date, the significance of the speed of sound in ILs is regarded. An analysis of experimental methods described in the literature to determine the speed of sound in ILs as a function of temperature and pressure is reported, and the relevance of ultrasound absorption in acoustic investigations is discussed. Careful attention was paid to highlight possible artifacts, and side phenomena related to the absorption and relaxation present in such measurements. Then, an overview of existing data is depicted to describe the temperature and pressure dependences on the speed of sound in ILs, as well as the impact of impurities in ILs on this property. A relation between ions structure and speeds of sound is presented by highlighting existing correlation and evaluative methods described in the literature. Importantly, a critical analysis of speeds of sound in ILs vs those in classical molecular solvents is presented to compare these two classes of compounds. The last part presents the importance of acoustic investigations for chemical engineering design and possible industrial applications of ILs.

Structural dynamic analysis of turbine blade

NASA Astrophysics Data System (ADS)

Antony, A. Daniel; Gopalsamy, M.; Viswanadh, Chaparala B. V.; Krishnaraj, R.

2017-10-01

In any gas turbine design cycle, blade design is a crucial element which needs maximum attention to meet the aerodynamic performance, structural safety margins, manufacturing feasibility, material availability etc. In present day gas turbine engines, most of the failures occur during engine development test and in-service, in rotor and stator blades due to fatigue and resonance failures. To address this issue, an extensive structural dynamic analysis is carried out to predict the natural frequencies and mode shapes using FE methods. Using the dynamics characteristics, the Campbell diagram is constructed to study the possibility of resonance at various operating speeds. In this work, the feasibility of using composite material in place of titanium alloy from the structural dynamics point of view. This is being attempted in a Low-pressure compressor where the temperatures are relatively low and fixed with the casings. The analysis will be carried out using FE method for different composite material with different lamina orientations chosen through the survey. This study will focus on the sensitivity of blade mode shapes to different laminae orientations, which will be used to alter the natural frequency and tailor the mode shapes. Campbell diagrams of existing titanium alloy are compared with the composite materials with different laminae at all critical operating conditions. The existing manufacturing methods and the proven techniques for blade profiles will also be discussed in this report.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

A novel finite element analysis of three-dimensional circular crack

NASA Astrophysics Data System (ADS)

Ping, X. C.; Wang, C. G.; Cheng, L. P.

2018-06-01

A novel singular element containing a part of the circular crack front is established to solve the singular stress fields of circular cracks by using the numerical series eigensolutions of singular stress fields. The element is derived from the Hellinger-Reissner variational principle and can be directly incorporated into existing 3D brick elements. The singular stress fields are determined as the system unknowns appearing as displacement nodal values. The numerical studies are conducted to demonstrate the simplicity of the proposed technique in handling fracture problems of circular cracks. The usage of the novel singular element can avoid mesh refinement near the crack front domain without loss of calculation accuracy and velocity of convergence. Compared with the conventional finite element methods and existing analytical methods, the present method is more suitable for dealing with complicated structures with a large number of elements.

Analysis of Classes of Singular Steady State Reaction Diffusion Equations

NASA Astrophysics Data System (ADS)

Son, Byungjae

We study positive radial solutions to classes of steady state reaction diffusion problems on the exterior of a ball with both Dirichlet and nonlinear boundary conditions. We study both Laplacian as well as p-Laplacian problems with reaction terms that are p-sublinear at infinity. We consider both positone and semipositone reaction terms and establish existence, multiplicity and uniqueness results. Our existence and multiplicity results are achieved by a method of sub-supersolutions and uniqueness results via a combination of maximum principles, comparison principles, energy arguments and a-priori estimates. Our results significantly enhance the literature on p-sublinear positone and semipositone problems. Finally, we provide exact bifurcation curves for several one-dimensional problems. In the autonomous case, we extend and analyze a quadrature method, and in the nonautonomous case, we employ shooting methods. We use numerical solvers in Mathematica to generate the bifurcation curves.

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

PubMed

Haghverdi, Laleh; Lun, Aaron T L; Morgan, Michael D; Marioni, John C

2018-06-01

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in different laboratories and at different times contain batch effects that may compromise the integration and interpretation of the data. Existing scRNA-seq analysis methods incorrectly assume that the composition of cell populations is either known or identical across batches. We present a strategy for batch correction based on the detection of mutual nearest neighbors (MNNs) in the high-dimensional expression space. Our approach does not rely on predefined or equal population compositions across batches; instead, it requires only that a subset of the population be shared between batches. We demonstrate the superiority of our approach compared with existing methods by using both simulated and real scRNA-seq data sets. Using multiple droplet-based scRNA-seq data sets, we demonstrate that our MNN batch-effect-correction method can be scaled to large numbers of cells.

Analysis of modal behavior at frequency cross-over

NASA Astrophysics Data System (ADS)

Costa, Robert N., Jr.

1994-11-01

The existence of the mode crossing condition is detected and analyzed in the Active Control of Space Structures Model 4 (ACOSS4). The condition is studied for its contribution to the inability of previous algorithms to successfully optimize the structure and converge to a feasible solution. A new algorithm is developed to detect and correct for mode crossings. The existence of the mode crossing condition is verified in ACOSS4 and found not to have appreciably affected the solution. The structure is then successfully optimized using new analytic methods based on modal expansion. An unrelated error in the optimization algorithm previously used is verified and corrected, thereby equipping the optimization algorithm with a second analytic method for eigenvector differentiation based on Nelson's Method. The second structure is the Control of Flexible Structures (COFS). The COFS structure is successfully reproduced and an initial eigenanalysis completed.

Comprehensive Structural Dynamic Analysis of the SSME/AT Fuel Pump First-Stage Turbine Blade

NASA Technical Reports Server (NTRS)

Brown, A. M.

1998-01-01

A detailed structural dynamic analysis of the Pratt & Whitney high-pressure fuel pump first-stage turbine blades has been performed to identify the cause of the tip cracking found in the turbomachinery in November 1997. The analysis was also used to help evaluate potential fixes for the problem. Many of the methods available in structural dynamics were applied, including modal displacement and stress analysis, frequency and transient response to tip loading from the first-stage Blade Outer Gas Seals (BOGS), fourier analysis, and shock spectra analysis of the transient response. The primary findings were that the BOGS tip loading is impulsive in nature, thereby exciting many modes of the blade that exhibit high stress at the tip cracking location. Therefore, a proposed BOGS count change would not help the situation because a clearly identifiable resonance situation does not exist. The recommendations for the resolution of the problem are to maintain the existing BOGS count, eliminate the stress concentration in the blade due to its geometric design, and reduce the applied load on the blade by adding shiplaps in the BOGS.

Two phase modeling of nanofluid flow in existence of melting heat transfer by means of HAM

NASA Astrophysics Data System (ADS)

Sheikholeslami, M.; Jafaryar, M.; Bateni, K.; Ganji, D. D.

2018-02-01

In this article, Buongiorno Model is applied for investigation of nanofluid flow over a stretching plate in existence of magnetic field. Radiation and Melting heat transfer are taken into account. Homotopy analysis method (HAM) is selected to solve ODEs which are obtained from similarity transformation. Roles of Brownian motion, thermophoretic parameter, Hartmann number, porosity parameter, Melting parameter and Eckert number are presented graphically. Results indicate that nanofluid velocity and concentration enhance with rise of melting parameter. Nusselt number reduces with increase of porosity and melting parameters.

The potential of genetic algorithms for conceptual design of rotor systems

NASA Technical Reports Server (NTRS)

Crossley, William A.; Wells, Valana L.; Laananen, David H.

1993-01-01

The capabilities of genetic algorithms as a non-calculus based, global search method make them potentially useful in the conceptual design of rotor systems. Coupling reasonably simple analysis tools to the genetic algorithm was accomplished, and the resulting program was used to generate designs for rotor systems to match requirements similar to those of both an existing helicopter and a proposed helicopter design. This provides a comparison with the existing design and also provides insight into the potential of genetic algorithms in design of new rotors.

Non-contact method of search and analysis of pulsating vessels

NASA Astrophysics Data System (ADS)

Avtomonov, Yuri N.; Tsoy, Maria O.; Postnov, Dmitry E.

2018-04-01

Despite the variety of existing methods of recording the human pulse and a solid history of their development, there is still considerable interest in this topic. The development of new non-contact methods, based on advanced image processing, caused a new wave of interest in this issue. We present a simple but quite effective method for analyzing the mechanical pulsations of blood vessels lying close to the surface of the skin. Our technique is a modification of imaging (or remote) photoplethysmography (i-PPG). We supplemented this method with the addition of a laser light source, which made it possible to use other methods of searching for the proposed pulsation zone. During the testing of the method, several series of experiments were carried out with both artificial oscillating objects as well as with the target signal source (human wrist). The obtained results show that our method allows correct interpretation of complex data. To summarize, we proposed and tested an alternative method for the search and analysis of pulsating vessels.

A Multi Directional Perfect Reconstruction Filter Bank Designed with 2-D Eigenfilter Approach: Application to Ultrasound Speckle Reduction.

PubMed

Nagare, Mukund B; Patil, Bhushan D; Holambe, Raghunath S

2017-02-01

B-Mode ultrasound images are degraded by inherent noise called Speckle, which creates a considerable impact on image quality. This noise reduces the accuracy of image analysis and interpretation. Therefore, reduction of speckle noise is an essential task which improves the accuracy of the clinical diagnostics. In this paper, a Multi-directional perfect-reconstruction (PR) filter bank is proposed based on 2-D eigenfilter approach. The proposed method used for the design of two-dimensional (2-D) two-channel linear-phase FIR perfect-reconstruction filter bank. In this method, the fan shaped, diamond shaped and checkerboard shaped filters are designed. The quadratic measure of the error function between the passband and stopband of the filter has been used an objective function. First, the low-pass analysis filter is designed and then the PR condition has been expressed as a set of linear constraints on the corresponding synthesis low-pass filter. Subsequently, the corresponding synthesis filter is designed using the eigenfilter design method with linear constraints. The newly designed 2-D filters are used in translation invariant pyramidal directional filter bank (TIPDFB) for reduction of speckle noise in ultrasound images. The proposed 2-D filters give better symmetry, regularity and frequency selectivity of the filters in comparison to existing design methods. The proposed method is validated on synthetic and real ultrasound data which ensures improvement in the quality of ultrasound images and efficiently suppresses the speckle noise compared to existing methods.

Solving phase appearance/disappearance two-phase flow problems with high resolution staggered grid and fully implicit schemes by the Jacobian-free Newton–Krylov Method

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

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

2016-04-01

The phase appearance/disappearance issue presents serious numerical challenges in two-phase flow simulations. Many existing reactor safety analysis codes use different kinds of treatments for the phase appearance/disappearance problem. However, to our best knowledge, there are no fully satisfactory solutions. Additionally, the majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many situations, it is desirable to use high-resolution spatial discretization and fully implicit time integration schemes to reduce numerical errors. In this work, we adapted a high-resolution spatial discretization scheme on staggered grid mesh and fully implicit time integrationmore » methods (such as BDF1 and BDF2) to solve the two-phase flow problems. The discretized nonlinear system was solved by the Jacobian-free Newton Krylov (JFNK) method, which does not require the derivation and implementation of analytical Jacobian matrix. These methods were tested with a few two-phase flow problems with phase appearance/disappearance phenomena considered, such as a linear advection problem, an oscillating manometer problem, and a sedimentation problem. The JFNK method demonstrated extremely robust and stable behaviors in solving the two-phase flow problems with phase appearance/disappearance. No special treatments such as water level tracking or void fraction limiting were used. High-resolution spatial discretization and second- order fully implicit method also demonstrated their capabilities in significantly reducing numerical errors.« less

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

Bradonjic, Milan; Hagberg, Aric; Hengartner, Nick

We analyze component evolution in general random intersection graphs (RIGs) and give conditions on existence and uniqueness of the giant component. Our techniques generalize the existing methods for analysis on component evolution in RIGs. That is, we analyze survival and extinction properties of a dependent, inhomogeneous Galton-Watson branching process on general RIGs. Our analysis relies on bounding the branching processes and inherits the fundamental concepts from the study on component evolution in Erdos-Renyi graphs. The main challenge becomes from the underlying structure of RIGs, when the number of offsprings follows a binomial distribution with a different number of nodes andmore » different rate at each step during the evolution. RIGs can be interpreted as a model for large randomly formed non-metric data sets. Besides the mathematical analysis on component evolution, which we provide in this work, we perceive RIGs as an important random structure which has already found applications in social networks, epidemic networks, blog readership, or wireless sensor networks.« less

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning

NASA Astrophysics Data System (ADS)

Zhou, Huan; Wang, Jian-qiang; Zhang, Hong-yu; Chen, Xiao-hong

2016-01-01

Linguistic hesitant fuzzy sets (LHFSs), which can be used to represent decision-makers' qualitative preferences as well as reflect their hesitancy and inconsistency, have attracted a great deal of attention due to their flexibility and efficiency. This paper focuses on a multi-criteria decision-making approach that combines LHFSs with the evidential reasoning (ER) method. After reviewing existing studies of LHFSs, a new order relationship and Hamming distance between LHFSs are introduced and some linguistic scale functions are applied. Then, the ER algorithm is used to aggregate the distributed assessment of each alternative. Subsequently, the set of aggregated alternatives on criteria are further aggregated to get the overall value of each alternative. Furthermore, a nonlinear programming model is developed and genetic algorithms are used to obtain the optimal weights of the criteria. Finally, two illustrative examples are provided to show the feasibility and usability of the method, and comparison analysis with the existing method is made.

Covariance analysis for evaluating head trackers

NASA Astrophysics Data System (ADS)

Kang, Donghoon

2017-10-01

Existing methods for evaluating the performance of head trackers usually rely on publicly available face databases, which contain facial images and the ground truths of their corresponding head orientations. However, most of the existing publicly available face databases are constructed by assuming that a frontal head orientation can be determined by compelling the person under examination to look straight ahead at the camera on the first video frame. Since nobody can accurately direct one's head toward the camera, this assumption may be unrealistic. Rather than obtaining estimation errors, we present a method for computing the covariance of estimation error rotations to evaluate the reliability of head trackers. As an uncertainty measure of estimators, the Schatten 2-norm of a square root of error covariance (or the algebraic average of relative error angles) can be used. The merit of the proposed method is that it does not disturb the person under examination by asking him to direct his head toward certain directions. Experimental results using real data validate the usefulness of our method.

A New Approach for Mining Order-Preserving Submatrices Based on All Common Subsequences.

PubMed

Xue, Yun; Liao, Zhengling; Li, Meihang; Luo, Jie; Kuang, Qiuhua; Hu, Xiaohui; Li, Tiechen

2015-01-01

Order-preserving submatrices (OPSMs) have been applied in many fields, such as DNA microarray data analysis, automatic recommendation systems, and target marketing systems, as an important unsupervised learning model. Unfortunately, most existing methods are heuristic algorithms which are unable to reveal OPSMs entirely in NP-complete problem. In particular, deep OPSMs, corresponding to long patterns with few supporting sequences, incur explosive computational costs and are completely pruned by most popular methods. In this paper, we propose an exact method to discover all OPSMs based on frequent sequential pattern mining. First, an existing algorithm was adjusted to disclose all common subsequence (ACS) between every two row sequences, and therefore all deep OPSMs will not be missed. Then, an improved data structure for prefix tree was used to store and traverse ACS, and Apriori principle was employed to efficiently mine the frequent sequential pattern. Finally, experiments were implemented on gene and synthetic datasets. Results demonstrated the effectiveness and efficiency of this method.

CS_TOTR: A new vertex centrality method for directed signed networks based on status theory

NASA Astrophysics Data System (ADS)

Ma, Yue; Liu, Min; Zhang, Peng; Qi, Xingqin

Measuring the importance (or centrality) of vertices in a network is a significant topic in complex network analysis, which has significant applications in diverse domains, for example, disease control, spread of rumors, viral marketing and so on. Existing studies mainly focus on social networks with only positive (or friendship) relations, while signed networks with also negative (or enemy) relations are seldom studied. Various signed networks commonly exist in real world, e.g. a network indicating friendship/enmity, love/hate or trust/mistrust relationships. In this paper, we propose a new centrality method named CS_TOTR to give a ranking of vertices in directed signed networks. To design this new method, we use the “status theory” for signed networks, and also adopt the vertex ranking algorithm for a tournament and the topological sorting algorithm for a general directed graph. We apply this new centrality method on the famous Sampson Monastery dataset and obtain a convincing result which shows its validity.

Individual Factors Predicting Mental Health Court Diversion Outcome

ERIC Educational Resources Information Center

Verhaaff, Ashley; Scott, Hannah

2015-01-01

Objective: This study examined which individual factors predict mental health court diversion outcome among a sample of persons with mental illness participating in a postcharge diversion program. Method: The study employed secondary analysis of existing program records for 419 persons with mental illness in a court diversion program. Results:…

In situ cell-by-cell imaging and analysis of small cell populations by mass spectrometry

USDA-ARS?s Scientific Manuscript database

Molecular imaging by mass spectrometry (MS) is emerging as a tool to determine the distribution of proteins, lipids and metabolites in tissues. The existing imaging methods, however, rely on predefined typically rectangular grids for sampling that ignore the natural cellular organization of the tiss...

An Analysis of Costs in Institutions of Higher Education in England

ERIC Educational Resources Information Center

Johnes, Geraint; Johnes, Jill; Thanassoulis, Emmanuel

2008-01-01

Cost functions are estimated, using random effects and stochastic frontier methods, for English higher education institutions. The article advances on existing literature by employing finer disaggregation by subject, institution type and location, and by introducing consideration of quality effects. Estimates are provided of average incremental…

Local Influence and Robust Procedures for Mediation Analysis

ERIC Educational Resources Information Center

Zu, Jiyun; Yuan, Ke-Hai

2010-01-01

Existing studies of mediation models have been limited to normal-theory maximum likelihood (ML). Because real data in the social and behavioral sciences are seldom normally distributed and often contain outliers, classical methods generally lead to inefficient or biased parameter estimates. Consequently, the conclusions from a mediation analysis…

Novel and efficient tag SNPs selection algorithms.

PubMed

Chen, Wen-Pei; Hung, Che-Lun; Tsai, Suh-Jen Jane; Lin, Yaw-Ling

2014-01-01

SNPs are the most abundant forms of genetic variations amongst species; the association studies between complex diseases and SNPs or haplotypes have received great attention. However, these studies are restricted by the cost of genotyping all SNPs; thus, it is necessary to find smaller subsets, or tag SNPs, representing the rest of the SNPs. In fact, the existing tag SNP selection algorithms are notoriously time-consuming. An efficient algorithm for tag SNP selection was presented, which was applied to analyze the HapMap YRI data. The experimental results show that the proposed algorithm can achieve better performance than the existing tag SNP selection algorithms; in most cases, this proposed algorithm is at least ten times faster than the existing methods. In many cases, when the redundant ratio of the block is high, the proposed algorithm can even be thousands times faster than the previously known methods. Tools and web services for haplotype block analysis integrated by hadoop MapReduce framework are also developed using the proposed algorithm as computation kernels.

CRITICA: coding region identification tool invoking comparative analysis

NASA Technical Reports Server (NTRS)

Badger, J. H.; Olsen, G. J.; Woese, C. R. (Principal Investigator)

1999-01-01

Gene recognition is essential to understanding existing and future DNA sequence data. CRITICA (Coding Region Identification Tool Invoking Comparative Analysis) is a suite of programs for identifying likely protein-coding sequences in DNA by combining comparative analysis of DNA sequences with more common noncomparative methods. In the comparative component of the analysis, regions of DNA are aligned with related sequences from the DNA databases; if the translation of the aligned sequences has greater amino acid identity than expected for the observed percentage nucleotide identity, this is interpreted as evidence for coding. CRITICA also incorporates noncomparative information derived from the relative frequencies of hexanucleotides in coding frames versus other contexts (i.e., dicodon bias). The dicodon usage information is derived by iterative analysis of the data, such that CRITICA is not dependent on the existence or accuracy of coding sequence annotations in the databases. This independence makes the method particularly well suited for the analysis of novel genomes. CRITICA was tested by analyzing the available Salmonella typhimurium DNA sequences. Its predictions were compared with the DNA sequence annotations and with the predictions of GenMark. CRITICA proved to be more accurate than GenMark, and moreover, many of its predictions that would seem to be errors instead reflect problems in the sequence databases. The source code of CRITICA is freely available by anonymous FTP (rdp.life.uiuc.edu in/pub/critica) and on the World Wide Web (http:/(/)rdpwww.life.uiuc.edu).

A comparative analysis of spectral exponent estimation techniques for 1/fβ processes with applications to the analysis of stride interval time series

PubMed Central

Schaefer, Alexander; Brach, Jennifer S.; Perera, Subashan; Sejdić, Ervin

2013-01-01

Background The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f) = 1/fβ. The scaling exponent β is thus often interpreted as a “biomarker” of relative health and decline. New Method This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. Results The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Comparison with Existing Methods: Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. Conclusions The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. PMID:24200509

Heuristic decomposition for non-hierarchic systems

NASA Technical Reports Server (NTRS)

Bloebaum, Christina L.; Hajela, P.

1991-01-01

Design and optimization is substantially more complex in multidisciplinary and large-scale engineering applications due to the existing inherently coupled interactions. The paper introduces a quasi-procedural methodology for multidisciplinary optimization that is applicable for nonhierarchic systems. The necessary decision-making support for the design process is provided by means of an embedded expert systems capability. The method employs a decomposition approach whose modularity allows for implementation of specialized methods for analysis and optimization within disciplines.

The Generation of Novel MR Imaging Techniques to Visualize Inflammatory/Degenerative Mechanisms and the Correlation of MR Data with 3D Microscopic Changes

DTIC Science & Technology

2013-09-01

existing MR scanning systems providing the ability to visualize structures that are impossible with current methods . Using techniques to concurrently...and unique system for analysis of affected brain regions and coupled with other imaging techniques and molecular measurements holds significant...scanning systems providing the ability to visualize structures that are impossible with current methods . Using techniques to concurrently stain

Application of Non-destructive Methods of Stress-strain State at Hazardous Production Facilities

NASA Astrophysics Data System (ADS)

Shram, V.; Kravtsova, Ye; Selsky, A.; Bezborodov, Yu; Lysyannikova, N.; Lysyannikov, A.

2016-06-01

The paper deals with the sources of accidents in distillation columns, on the basis of which the most dangerous defects are detected. The analysis of the currently existing methods of non-destructive testing of the stress-strain state is performed. It is proposed to apply strain and acoustic emission techniques to continuously monitor dangerous objects, which helps prevent the possibility of accidents, as well as reduce the work.

Sexual Dimorphism Analysis and Gender Classification in 3D Human Face

NASA Astrophysics Data System (ADS)

Hu, Yuan; Lu, Li; Yan, Jingqi; Liu, Zhi; Shi, Pengfei

In this paper, we present the sexual dimorphism analysis in 3D human face and perform gender classification based on the result of sexual dimorphism analysis. Four types of features are extracted from a 3D human-face image. By using statistical methods, the existence of sexual dimorphism is demonstrated in 3D human face based on these features. The contributions of each feature to sexual dimorphism are quantified according to a novel criterion. The best gender classification rate is 94% by using SVMs and Matcher Weighting fusion method.This research adds to the knowledge of 3D faces in sexual dimorphism and affords a foundation that could be used to distinguish between male and female in 3D faces.

Stratospheric and mesospheric pressure-temperature profiles from rotational analysis of CO2 lines in atmospheric trace molecule spectroscopy/ATLAS 1 infrared solar occultation spectra

NASA Technical Reports Server (NTRS)

Stiller, G. P.; Gunson, M. R.; Lowes, L. L.; Abrams, M. C.; Raper, O. F.; Farmer, C. B.; Zander, R.; Rinsland, C. P.

1995-01-01

A simple, classical, and expedient method for the retrieval of atmospheric pressure-temperature profiles has been applied to the high-resolution infrared solar absorption spectra obtained with the atmospheric trace molecule spectroscopy (ATMOS) instrument. The basis for this method is a rotational analysis of retrieved apparent abundances from CO2 rovibrational absorption lines, employing existing constituent concentration retrieval software used in the analysis of data returned by ATMOS. Pressure-temperature profiles derived from spectra acquired during the ATLAS 1 space shuttle mission of March-April 1992 are quantitatively evaluated and compared with climatological and meteorological data as a means of assessing the validity of this approach.

Visualizing the Heterogeneity of Effects in the Analysis of Associations of Multiple Myeloma with Glyphosate Use. Comments on Sorahan, T. Multiple Myeloma and Glyphosate Use: A Re-Analysis of US Agricultural Health Study (AHS) Data. Int. J. Environ. Res. Public Health 2015, 12, 1548-1559.

PubMed

Burstyn, Igor; De Roos, Anneclaire J

2016-12-22

We address a methodological issue of the evaluation of the difference in effects in epidemiological studies that may arise, for example, from stratum-specific analyses or differences in analytical decisions during data analysis. We propose a new simulation-based method to quantify the plausible extent of such heterogeneity, rather than testing a hypothesis about its existence. We examine the contribution of the method to the debate surrounding risk of multiple myeloma and glyphosate use and propose that its application contributes to a more balanced weighting of evidence.

Visualizing the Heterogeneity of Effects in the Analysis of Associations of Multiple Myeloma with Glyphosate Use. Comments on Sorahan, T. Multiple Myeloma and Glyphosate Use: A Re-Analysis of US Agricultural Health Study (AHS) Data. Int. J. Environ. Res. Public Health 2015, 12, 1548–1559

PubMed Central

Burstyn, Igor; De Roos, Anneclaire J.

2016-01-01

We address a methodological issue of the evaluation of the difference in effects in epidemiological studies that may arise, for example, from stratum-specific analyses or differences in analytical decisions during data analysis. We propose a new simulation-based method to quantify the plausible extent of such heterogeneity, rather than testing a hypothesis about its existence. We examine the contribution of the method to the debate surrounding risk of multiple myeloma and glyphosate use and propose that its application contributes to a more balanced weighting of evidence. PMID:28025514

Inhomogeneous scaling behaviors in Malaysian foreign currency exchange rates

NASA Astrophysics Data System (ADS)

Muniandy, S. V.; Lim, S. C.; Murugan, R.

2001-12-01

In this paper, we investigate the fractal scaling behaviors of foreign currency exchange rates with respect to Malaysian currency, Ringgit Malaysia. These time series are examined piecewise before and after the currency control imposed in 1st September 1998 using the monofractal model based on fractional Brownian motion. The global Hurst exponents are determined using the R/ S analysis, the detrended fluctuation analysis and the method of second moment using the correlation coefficients. The limitation of these monofractal analyses is discussed. The usual multifractal analysis reveals that there exists a wide range of Hurst exponents in each of the time series. A new method of modelling the multifractal time series based on multifractional Brownian motion with time-varying Hurst exponents is studied.

How Magnetic Disturbance Influences the Attitude and Heading in Magnetic and Inertial Sensor-Based Orientation Estimation

PubMed Central

Li, Qingguo

2017-01-01

With the advancements in micro-electromechanical systems (MEMS) technologies, magnetic and inertial sensors are becoming more and more accurate, lightweight, smaller in size as well as low-cost, which in turn boosts their applications in human movement analysis. However, challenges still exist in the field of sensor orientation estimation, where magnetic disturbance represents one of the obstacles limiting their practical application. The objective of this paper is to systematically analyze exactly how magnetic disturbances affects the attitude and heading estimation for a magnetic and inertial sensor. First, we reviewed four major components dealing with magnetic disturbance, namely decoupling attitude estimation from magnetic reading, gyro bias estimation, adaptive strategies of compensating magnetic disturbance and sensor fusion algorithms. We review and analyze the features of existing methods of each component. Second, to understand each component in magnetic disturbance rejection, four representative sensor fusion methods were implemented, including gradient descent algorithms, improved explicit complementary filter, dual-linear Kalman filter and extended Kalman filter. Finally, a new standardized testing procedure has been developed to objectively assess the performance of each method against magnetic disturbance. Based upon the testing results, the strength and weakness of the existing sensor fusion methods were easily examined, and suggestions were presented for selecting a proper sensor fusion algorithm or developing new sensor fusion method. PMID:29283432

Controlling the Display of Capsule Endoscopy Video for Diagnostic Assistance

NASA Astrophysics Data System (ADS)

Vu, Hai; Echigo, Tomio; Sagawa, Ryusuke; Yagi, Keiko; Shiba, Masatsugu; Higuchi, Kazuhide; Arakawa, Tetsuo; Yagi, Yasushi

Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5 ± minutes per full sequence while the number of abnormalities found was similar. As well, physicians needed less effort because of the systems efficient operability. The results of the evaluations should convince physicians that they can safely use this method and obtain reduced diagnostic times.

Pooling Data from Multiple Longitudinal Studies: The Role of Item Response Theory in Integrative Data Analysis

PubMed Central

Curran, Patrick J.; Hussong, Andrea M.; Cai, Li; Huang, Wenjing; Chassin, Laurie; Sher, Kenneth J.; Zucker, Robert A.

2010-01-01

There are a number of significant challenges encountered when studying development over an extended period of time including subject attrition, changing measurement structures across group and developmental period, and the need to invest substantial time and money. Integrative data analysis is an emerging set of methodologies that overcomes many of the challenges of single sample designs through the pooling of data drawn from multiple existing developmental studies. This approach is characterized by a host of advantages, but this also introduces several new complexities that must be addressed prior to broad adoption by developmental researchers. In this paper we focus on methods for fitting measurement models and creating scale scores using data drawn from multiple longitudinal studies. We present findings from the analysis of repeated measures of internalizing symptomatology that were pooled from three existing developmental studies. We describe and demonstrate each step in the analysis and we conclude with a discussion of potential limitations and directions for future research. PMID:18331129

Redefining the Practice of Peer Review Through Intelligent Automation-Part 3: Automated Report Analysis and Data Reconciliation.

PubMed

Reiner, Bruce I

2018-02-01

One method for addressing existing peer review limitations is the assignment of peer review cases on a completely blinded basis, in which the peer reviewer would create an independent report which can then be cross-referenced with the primary reader report of record. By leveraging existing computerized data mining techniques, one could in theory automate and objectify the process of report data extraction, classification, and analysis, while reducing time and resource requirements intrinsic to manual peer review report analysis. Once inter-report analysis has been performed, resulting inter-report discrepancies can be presented to the radiologist of record for review, along with the option to directly communicate with the peer reviewer through an electronic data reconciliation tool aimed at collaboratively resolving inter-report discrepancies and improving report accuracy. All associated report and reconciled data could in turn be recorded in a referenceable peer review database, which provides opportunity for context and user-specific education and decision support.

Manufacturing Methods for High Speed Machining of Aluminum

DTIC Science & Technology

1978-02-01

Tests 53 4.4.3 Intergrmnular Corrosion Tests. ........... 53 4.4.4 Cost Analysis . .. ............... . .. .... 60 4.5 Conclusions...Corporat~ion and Others to equuip an existing Uwidstvahd, five-axes, Modal as-i, oidail with a 20,000 rVIL 20 hOW~pse spindle, Based anresults obtained...economic analysis for high-speed machining wan also conducted by Metout, and the results are given in Section 11.0. Xn Section 12.0, conclusions and

Force analysis of magnetic bearings with power-saving controls

NASA Technical Reports Server (NTRS)

Johnson, Dexter; Brown, Gerald V.; Inman, Daniel J.

1992-01-01

Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. For most operating conditions, the existence of the bias current requires more power than alternative methods that do not use conventional bias. Two such methods are examined which diminish or eliminate bias current. In the typical bias control scheme it is found that for a harmonic control force command into a voltage limited transconductance amplifier, the desired force output is obtained only up to certain combinations of force amplitude and frequency. Above these values, the force amplitude is reduced and a phase lag occurs. The power saving alternative control schemes typically exhibit such deficiencies at even lower command frequencies and amplitudes. To assess the severity of these effects, a time history analysis of the force output is performed for the bias method and the alternative methods. Results of the analysis show that the alternative approaches may be viable. The various control methods examined were mathematically modeled using nondimensionalized variables to facilitate comparison of the various methods.

Prediction and analysis of protein solubility using a novel scoring card method with dipeptide composition

PubMed Central

2012-01-01

Background Existing methods for predicting protein solubility on overexpression in Escherichia coli advance performance by using ensemble classifiers such as two-stage support vector machine (SVM) based classifiers and a number of feature types such as physicochemical properties, amino acid and dipeptide composition, accompanied with feature selection. It is desirable to develop a simple and easily interpretable method for predicting protein solubility, compared to existing complex SVM-based methods. Results This study proposes a novel scoring card method (SCM) by using dipeptide composition only to estimate solubility scores of sequences for predicting protein solubility. SCM calculates the propensities of 400 individual dipeptides to be soluble using statistic discrimination between soluble and insoluble proteins of a training data set. Consequently, the propensity scores of all dipeptides are further optimized using an intelligent genetic algorithm. The solubility score of a sequence is determined by the weighted sum of all propensity scores and dipeptide composition. To evaluate SCM by performance comparisons, four data sets with different sizes and variation degrees of experimental conditions were used. The results show that the simple method SCM with interpretable propensities of dipeptides has promising performance, compared with existing SVM-based ensemble methods with a number of feature types. Furthermore, the propensities of dipeptides and solubility scores of sequences can provide insights to protein solubility. For example, the analysis of dipeptide scores shows high propensity of α-helix structure and thermophilic proteins to be soluble. Conclusions The propensities of individual dipeptides to be soluble are varied for proteins under altered experimental conditions. For accurately predicting protein solubility using SCM, it is better to customize the score card of dipeptide propensities by using a training data set under the same specified experimental conditions. The proposed method SCM with solubility scores and dipeptide propensities can be easily applied to the protein function prediction problems that dipeptide composition features play an important role. Availability The used datasets, source codes of SCM, and supplementary files are available at http://iclab.life.nctu.edu.tw/SCM/. PMID:23282103

CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations.

PubMed

Johnson, Quentin R; Lindsay, Richard J; Shen, Tongye

2018-02-21

A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Pattern Activity Clustering and Evaluation (PACE)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Banas, Christopher; Paul, Michael; Bussjager, Becky; Seetharaman, Guna

2012-06-01

With the vast amount of network information available on activities of people (i.e. motions, transportation routes, and site visits) there is a need to explore the salient properties of data that detect and discriminate the behavior of individuals. Recent machine learning approaches include methods of data mining, statistical analysis, clustering, and estimation that support activity-based intelligence. We seek to explore contemporary methods in activity analysis using machine learning techniques that discover and characterize behaviors that enable grouping, anomaly detection, and adversarial intent prediction. To evaluate these methods, we describe the mathematics and potential information theory metrics to characterize behavior. A scenario is presented to demonstrate the concept and metrics that could be useful for layered sensing behavior pattern learning and analysis. We leverage work on group tracking, learning and clustering approaches; as well as utilize information theoretical metrics for classification, behavioral and event pattern recognition, and activity and entity analysis. The performance evaluation of activity analysis supports high-level information fusion of user alerts, data queries and sensor management for data extraction, relations discovery, and situation analysis of existing data.

A Rapid Method for Measuring Strontium-90 Activity in Crops in China

NASA Astrophysics Data System (ADS)

Pan, Lingjing Pan; Yu, Guobing; Wen, Deyun; Chen, Zhi; Sheng, Liusi; Liu, Chung-King; Xu, X. George

2017-09-01

A rapid method for measuring Sr-90 activity in crop ashes is presented. Liquid scintillation counting, combined with ion exchange columns 4`, 4"(5")-di-t-butylcyclohexane-18-crown-6, is used to determine the activity of Sr-90 in crops. The yields of chemical procedure are quantified using gravimetric analysis. The conventional method that uses ion-exchange resin with HDEHP could not completely remove all the bismuth when comparatively large lead and bismuth exist in the samples. This is overcome by the rapid method. The chemical yield of this method is about 60% and the MDA for Sr-90 is found to be 2:32 Bq/kg. The whole procedure together with using spectrum analysis to determine the activity only takes about one day, which is really a large improvement compared with the conventional method. A modified conventional method is also described here to verify the value of the rapid one. These two methods can meet di_erent needs of daily monitoring and emergency situation.

Mimvec: a deep learning approach for analyzing the human phenome.

PubMed

Gan, Mingxin; Li, Wenran; Zeng, Wanwen; Wang, Xiaojian; Jiang, Rui

2017-09-21

The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation. This framework, though intuitive, not only ignores semantic relationships between words but also tends to produce high-dimensional vectors, and hence lacks the ability to precisely capture intrinsic semantic characteristics of biomedical documents. To overcome these limitations, we propose a framework called mimvec to analyze the human phenome by making use of the state-of-the-art deep learning technique in natural language processing. We converted 24,061 records in the Online Mendelian Inheritance in Man (OMIM) database to low-dimensional vectors using our method. We demonstrated that the vector presentation not only effectively enabled classification of phenotype records against gene ones, but also succeeded in discriminating diseases of different inheritance styles and different mechanisms. We further derived pairwise phenotype similarities between 7988 human inherited diseases using their vector presentations. With a joint analysis of this phenome with multiple genomic data, we showed that phenotype overlap indeed implied genotype overlap. We finally used the derived phenotype similarities with genomic data to prioritize candidate genes and demonstrated advantages of this method over existing ones. Our method is capable of not only capturing semantic relationships between words in biomedical records but also alleviating the dimensional disaster accompanying the traditional TF-IDF framework. With the approaching of precision medicine, there will be abundant electronic records of medicine and health awaiting for deep analysis, and we expect to see a wide spectrum of applications borrowing the idea of our method in the near future.

Mal-Xtract: Hidden Code Extraction using Memory Analysis

NASA Astrophysics Data System (ADS)

Lim, Charles; Syailendra Kotualubun, Yohanes; Suryadi; Ramli, Kalamullah

2017-01-01

Software packer has been used effectively to hide the original code inside a binary executable, making it more difficult for existing signature based anti malware software to detect malicious code inside the executable. A new method of written and rewritten memory section is introduced to to detect the exact end time of unpacking routine and extract original code from packed binary executable using Memory Analysis running in an software emulated environment. Our experiment results show that at least 97% of the original code from the various binary executable packed with different software packers could be extracted. The proposed method has also been successfully extracted hidden code from recent malware family samples.

Experimental design and quantitative analysis of microbial community multiomics.

PubMed

Mallick, Himel; Ma, Siyuan; Franzosa, Eric A; Vatanen, Tommi; Morgan, Xochitl C; Huttenhower, Curtis

2017-11-30

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

Characterization of fiber diameter using image analysis

NASA Astrophysics Data System (ADS)

Baheti, S.; Tunak, M.

2017-10-01

Due to high surface area and porosity, the applications of nanofibers have increased in recent years. In the production process, determination of average fiber diameter and fiber orientation is crucial for quality assessment. The objective of present study was to compare the relative performance of different methods discussed in literature for estimation of fiber diameter. In this work, the existing automated fiber diameter analysis software packages available in literature were developed and validated based on simulated images of known fiber diameter. Finally, all methods were compared for their reliable and accurate estimation of fiber diameter in electro spun nanofiber membranes based on obtained mean and standard deviation.

Neuronal and network computation in the brain

NASA Astrophysics Data System (ADS)

Babloyantz, A.

1999-03-01

The concepts and methods of non-linear dynamics have been a powerful tool for studying some gamow aspects of brain dynamics. In this paper we show how, from time series analysis of electroencepholograms in sick and healthy subjects, chaotic nature of brain activity could be unveiled. This finding gave rise to the concept of spatiotemporal cortical chaotic networks which in turn was the foundation for a simple brain-like device which is able to become attentive, perform pattern recognition and motion detection. A new method of time series analysis is also proposed which demonstrates for the first time the existence of neuronal code in interspike intervals of coclear cells.

Search automation of the generalized method of device operational characteristics improvement

NASA Astrophysics Data System (ADS)

Petrova, I. Yu; Puchkova, A. A.; Zaripova, V. M.

2017-01-01

The article presents brief results of analysis of existing search methods of the closest patents, which can be applied to determine generalized methods of device operational characteristics improvement. There were observed the most widespread clustering algorithms and metrics for determining the proximity degree between two documents. The article proposes the technique of generalized methods determination; it has two implementation variants and consists of 7 steps. This technique has been implemented in the “Patents search” subsystem of the “Intellect” system. Also the article gives an example of the use of the proposed technique.

How High is that Dune? A Comparison of Methods Used to Constrain the Morphometry of Aeolian Bedforms on Mars

NASA Technical Reports Server (NTRS)

Bourke, M.; Balme, M.; Beyer, R. A.; Williams, K. K.

2004-01-01

Methods traditionally used to estimate the relative height of surface features on Mars include: photoclinometry, shadow length and stereography. The MOLA data set enables a more accurate assessment of the surface topography of Mars. However, many small-scale aeolian bedforms remain below the sample resolution of the MOLA data set. In response to this a number of research teams have adopted and refined existing methods and applied them to high resolution (2-6 m/pixel) narrow angle MOC satellite images. Collectively, the methods provide data on a range of morphometric parameters (many not previously available for dunes on Mars). These include dune height, width, length, surface area, volume, longitudinal and cross profiles). This data will facilitate a more accurate analysis of aeolian bedforms on Mars. In this paper we undertake a comparative analysis of methods used to determine the height of aeolian dunes and ripples.

Analyzing the Structure and Content of Public Health Messages

PubMed Central

Morrison, Frances P.; Kukafka, Rita; Johnson, Stephen B.

2005-01-01

Background Health messages are crucial to the field of public health in effecting behavior change, but little research is available to assist writers in composing the overall structure of a message. In order to develop software to assist individuals in constructing effective messages, the structure of existing health messages must be understood, and an appropriate method for analyzing health message structure developed. Methods 72 messages from expert sources were used for development of the method, which was then tested for reproducibility using ten randomly selected health messages. Four raters analyzed the messages and inter-coder agreement was calculated. Results A method for analyzing the structure of the messages was developed using sublanguage analysis and discourse analysis. Overall kappa between four coders was 0.69. Conclusion A novel framework for characterizing health message structure and a method for analyzing messages appears to be reproducible and potentially useful for creating an authoring tool. PMID:16779098

Trans-dimensional MCMC methods for fully automatic motion analysis in tagged MRI.

PubMed

Smal, Ihor; Carranza-Herrezuelo, Noemí; Klein, Stefan; Niessen, Wiro; Meijering, Erik

2011-01-01

Tagged magnetic resonance imaging (tMRI) is a well-known noninvasive method allowing quantitative analysis of regional heart dynamics. Its clinical use has so far been limited, in part due to the lack of robustness and accuracy of existing tag tracking algorithms in dealing with low (and intrinsically time-varying) image quality. In this paper, we propose a novel probabilistic method for tag tracking, implemented by means of Bayesian particle filtering and a trans-dimensional Markov chain Monte Carlo (MCMC) approach, which efficiently combines information about the imaging process and tag appearance with prior knowledge about the heart dynamics obtained by means of non-rigid image registration. Experiments using synthetic image data (with ground truth) and real data (with expert manual annotation) from preclinical (small animal) and clinical (human) studies confirm that the proposed method yields higher consistency, accuracy, and intrinsic tag reliability assessment in comparison with other frequently used tag tracking methods.

Gait Analysis Methods for Rodent Models of Osteoarthritis

PubMed Central

Jacobs, Brittany Y.; Kloefkorn, Heidi E.; Allen, Kyle D.

2014-01-01

Patients with osteoarthritis (OA) primarily seek treatment due to pain and disability, yet the primary endpoints for rodent OA models tend to be histological measures of joint destruction. The discrepancy between clinical and preclinical evaluations is problematic, given that radiographic evidence of OA in humans does not always correlate to the severity of patient-reported symptoms. Recent advances in behavioral analyses have provided new methods to evaluate disease sequelae in rodents. Of particular relevance to rodent OA models are methods to assess rodent gait. While obvious differences exist between quadrupedal and bipedal gait sequences, the gait abnormalities seen in humans and in rodent OA models reflect similar compensatory behaviors that protect an injured limb from loading. The purpose of this review is to describe these compensations and current methods used to assess rodent gait characteristics, while detailing important considerations for the selection of gait analysis methods in rodent OA models. PMID:25160712

Exploiting salient semantic analysis for information retrieval

NASA Astrophysics Data System (ADS)

Luo, Jing; Meng, Bo; Quan, Changqin; Tu, Xinhui

2016-11-01

Recently, many Wikipedia-based methods have been proposed to improve the performance of different natural language processing (NLP) tasks, such as semantic relatedness computation, text classification and information retrieval. Among these methods, salient semantic analysis (SSA) has been proven to be an effective way to generate conceptual representation for words or documents. However, its feasibility and effectiveness in information retrieval is mostly unknown. In this paper, we study how to efficiently use SSA to improve the information retrieval performance, and propose a SSA-based retrieval method under the language model framework. First, SSA model is adopted to build conceptual representations for documents and queries. Then, these conceptual representations and the bag-of-words (BOW) representations can be used in combination to estimate the language models of queries and documents. The proposed method is evaluated on several standard text retrieval conference (TREC) collections. Experiment results on standard TREC collections show the proposed models consistently outperform the existing Wikipedia-based retrieval methods.

Structural design using equilibrium programming formulations

NASA Technical Reports Server (NTRS)

Scotti, Stephen J.

1995-01-01

Solutions to increasingly larger structural optimization problems are desired. However, computational resources are strained to meet this need. New methods will be required to solve increasingly larger problems. The present approaches to solving large-scale problems involve approximations for the constraints of structural optimization problems and/or decomposition of the problem into multiple subproblems that can be solved in parallel. An area of game theory, equilibrium programming (also known as noncooperative game theory), can be used to unify these existing approaches from a theoretical point of view (considering the existence and optimality of solutions), and be used as a framework for the development of new methods for solving large-scale optimization problems. Equilibrium programming theory is described, and existing design techniques such as fully stressed design and constraint approximations are shown to fit within its framework. Two new structural design formulations are also derived. The first new formulation is another approximation technique which is a general updating scheme for the sensitivity derivatives of design constraints. The second new formulation uses a substructure-based decomposition of the structure for analysis and sensitivity calculations. Significant computational benefits of the new formulations compared with a conventional method are demonstrated.

Multiscale analysis and computation for flows in heterogeneous media

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

Efendiev, Yalchin; Hou, T. Y.; Durlofsky, L. J.

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.« less

Bruise chromophore concentrations over time

NASA Astrophysics Data System (ADS)

Duckworth, Mark G.; Caspall, Jayme J.; Mappus, Rudolph L., IV; Kong, Linghua; Yi, Dingrong; Sprigle, Stephen H.

2008-03-01

During investigations of potential child and elder abuse, clinicians and forensic practitioners are often asked to offer opinions about the age of a bruise. A commonality between existing methods of bruise aging is analysis of bruise color or estimation of chromophore concentration. Relative chromophore concentration is an underlying factor that determines bruise color. We investigate a method of chromophore concentration estimation that can be employed in a handheld imaging spectrometer with a small number of wavelengths. The method, based on absorbance properties defined by Beer-Lambert's law, allows estimation of differential chromophore concentration between bruised and normal skin. Absorption coefficient data for each chromophore are required to make the estimation. Two different sources of this data are used in the analysis- generated using Independent Component Analysis and taken from published values. Differential concentration values over time, generated using both sources, show correlation to published models of bruise color change over time and total chromophore concentration over time.