Harmonic analysis of electrified railway based on improved HHT

NASA Astrophysics Data System (ADS)

Wang, Feng

2018-04-01

In this paper, the causes and harms of the current electric locomotive electrical system harmonics are firstly studied and analyzed. Based on the characteristics of the harmonics in the electrical system, the Hilbert-Huang transform method is introduced. Based on the in-depth analysis of the empirical mode decomposition method and the Hilbert transform method, the reasons and solutions to the endpoint effect and modal aliasing problem in the HHT method are explored. For the endpoint effect of HHT, this paper uses point-symmetric extension method to extend the collected data; In allusion to the modal aliasing problem, this paper uses the high frequency harmonic assistant method to preprocess the signal and gives the empirical formula of high frequency auxiliary harmonic. Finally, combining the suppression of HHT endpoint effect and modal aliasing problem, an improved HHT method is proposed and simulated by matlab. The simulation results show that the improved HHT is effective for the electric locomotive power supply system.

Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization

NASA Astrophysics Data System (ADS)

Li, Li

2018-03-01

In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.

Discovering Synergistic Drug Combination from a Computational Perspective.

PubMed

Ding, Pingjian; Luo, Jiawei; Liang, Cheng; Xiao, Qiu; Cao, Buwen; Li, Guanghui

2018-03-30

Synergistic drug combinations play an important role in the treatment of complex diseases. The identification of effective drug combination is vital to further reduce the side effects and improve therapeutic efficiency. In previous years, in vitro method has been the main route to discover synergistic drug combinations. However, many limitations of time and resource consumption lie within the in vitro method. Therefore, with the rapid development of computational models and the explosive growth of large and phenotypic data, computational methods for discovering synergistic drug combinations are an efficient and promising tool and contribute to precision medicine. It is the key of computational methods how to construct the computational model. Different computational strategies generate different performance. In this review, the recent advancements in computational methods for predicting effective drug combination are concluded from multiple aspects. First, various datasets utilized to discover synergistic drug combinations are summarized. Second, we discussed feature-based approaches and partitioned these methods into two classes including feature-based methods in terms of similarity measure, and feature-based methods in terms of machine learning. Third, we discussed network-based approaches for uncovering synergistic drug combinations. Finally, we analyzed and prospected computational methods for predicting effective drug combinations. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Web-Based Versus Conventional Training for Medical Students on Infant Gross Motor Screening.

PubMed

Pusponegoro, Hardiono D; Soebadi, Amanda; Surya, Raymond

2015-12-01

Early detection of developmental abnormalities is important for early intervention. A simple screening method is needed for use by general practitioners, as is an effective and efficient training method. This study aims to evaluate the effectiveness, acceptability, and usability of Web-based training for medical students on a simple gross motor screening method in infants. Fifth-year medical students at University of Indonesia in Jakarta were randomized into two groups. A Web-based training group received online video modules, discussions, and assessments (at www.schoology.com ). A conventional training group received a 1-day live training using the same module. Both groups completed identical pre- and posttests and the User Satisfaction Questionnaire (USQ). The Web-based group also completed the System Usability Scale (SUS). The module was based on a gross motor screening method used in the World Health Organization Multicentre Growth Reference Study. There were 39 and 32 subjects in the Web-based and conventional groups, respectively. Mean pretest versus posttest scores (correct answers out of 20) were 9.05 versus 16.95 (p=0.0001) in the Web-based group and 9.31 versus 16.88 (p=0.0001) in the conventional group. Mean difference between pre- and posttest scores did not differ significantly between the Web-based and conventional groups (mean [standard deviation], 7.56 [3.252] versus 7.90 [5.170]; p=0.741]. Both training methods were acceptable based on USQ scores. Based on SUS scores, the Web-based training had good usability. Web-based training is an effective, efficient, and acceptable training method for medical students on simple infant gross motor screening and is as effective as conventional training.

Improved patch-based learning for image deblurring

NASA Astrophysics Data System (ADS)

Dong, Bo; Jiang, Zhiguo; Zhang, Haopeng

2015-05-01

Most recent image deblurring methods only use valid information found in input image as the clue to fill the deblurring region. These methods usually have the defects of insufficient prior information and relatively poor adaptiveness. Patch-based method not only uses the valid information of the input image itself, but also utilizes the prior information of the sample images to improve the adaptiveness. However the cost function of this method is quite time-consuming and the method may also produce ringing artifacts. In this paper, we propose an improved non-blind deblurring algorithm based on learning patch likelihoods. On one hand, we consider the effect of the Gaussian mixture model with different weights and normalize the weight values, which can optimize the cost function and reduce running time. On the other hand, a post processing method is proposed to solve the ringing artifacts produced by traditional patch-based method. Extensive experiments are performed. Experimental results verify that our method can effectively reduce the execution time, suppress the ringing artifacts effectively, and keep the quality of deblurred image.

Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders.

PubMed

Kim, Dongchul; Kang, Mingon; Biswas, Ashis; Liu, Chunyu; Gao, Jean

2016-08-10

Inferring gene regulatory networks is one of the most interesting research areas in the systems biology. Many inference methods have been developed by using a variety of computational models and approaches. However, there are two issues to solve. First, depending on the structural or computational model of inference method, the results tend to be inconsistent due to innately different advantages and limitations of the methods. Therefore the combination of dissimilar approaches is demanded as an alternative way in order to overcome the limitations of standalone methods through complementary integration. Second, sparse linear regression that is penalized by the regularization parameter (lasso) and bootstrapping-based sparse linear regression methods were suggested in state of the art methods for network inference but they are not effective for a small sample size data and also a true regulator could be missed if the target gene is strongly affected by an indirect regulator with high correlation or another true regulator. We present two novel network inference methods based on the integration of three different criteria, (i) z-score to measure the variation of gene expression from knockout data, (ii) mutual information for the dependency between two genes, and (iii) linear regression-based feature selection. Based on these criterion, we propose a lasso-based random feature selection algorithm (LARF) to achieve better performance overcoming the limitations of bootstrapping as mentioned above. In this work, there are three main contributions. First, our z score-based method to measure gene expression variations from knockout data is more effective than similar criteria of related works. Second, we confirmed that the true regulator selection can be effectively improved by LARF. Lastly, we verified that an integrative approach can clearly outperform a single method when two different methods are effectively jointed. In the experiments, our methods were validated by outperforming the state of the art methods on DREAM challenge data, and then LARF was applied to inferences of gene regulatory network associated with psychiatric disorders.

Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery.

PubMed

Fu, Szu-Wei; Li, Pei-Chun; Lai, Ying-Hui; Yang, Cheng-Chien; Hsieh, Li-Chun; Tsao, Yu

2017-11-01

Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients. Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients.

The performance of different propensity score methods for estimating absolute effects of treatments on survival outcomes: A simulation study.

PubMed

Austin, Peter C; Schuster, Tibor

2016-10-01

Observational studies are increasingly being used to estimate the effect of treatments, interventions and exposures on outcomes that can occur over time. Historically, the hazard ratio, which is a relative measure of effect, has been reported. However, medical decision making is best informed when both relative and absolute measures of effect are reported. When outcomes are time-to-event in nature, the effect of treatment can also be quantified as the change in mean or median survival time due to treatment and the absolute reduction in the probability of the occurrence of an event within a specified duration of follow-up. We describe how three different propensity score methods, propensity score matching, stratification on the propensity score and inverse probability of treatment weighting using the propensity score, can be used to estimate absolute measures of treatment effect on survival outcomes. These methods are all based on estimating marginal survival functions under treatment and lack of treatment. We then conducted an extensive series of Monte Carlo simulations to compare the relative performance of these methods for estimating the absolute effects of treatment on survival outcomes. We found that stratification on the propensity score resulted in the greatest bias. Caliper matching on the propensity score and a method based on earlier work by Cole and Hernán tended to have the best performance for estimating absolute effects of treatment on survival outcomes. When the prevalence of treatment was less extreme, then inverse probability of treatment weighting-based methods tended to perform better than matching-based methods. © The Author(s) 2014.

Positive Psychology in the Class: The Effectiveness of a Teaching Method Based on Subjective Well-Being and Engagement Increasing Activities

ERIC Educational Resources Information Center

Eryilmaz, Ali

2015-01-01

The aim of the present study is investigate that the effectiveness of a teaching method which is based on subjective well-being increasing activities and engagement increasing activities, has been developed for university students in the present study. The method of the present study is a mixed method. Thus, the most important feature of it has…

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Identifying Effective Methods of Instruction for Adult Emergent Readers through Community-Based Research

ERIC Educational Resources Information Center

Blackmer, Rachel; Hayes-Harb, Rachel

2016-01-01

We present a community-based research project aimed at identifying effective methods and materials for teaching English literacy skills to adult English as a second language emergent readers. We conducted a quasi-experimental study whereby we evaluated the efficacy of two approaches, one based on current practices at the English Skills Learning…

Effectiveness of Variable-Gain Kalman Filter Based on Angle Error Calculated from Acceleration Signals in Lower Limb Angle Measurement with Inertial Sensors

PubMed Central

Watanabe, Takashi

2013-01-01

The wearable sensor system developed by our group, which measured lower limb angles using Kalman-filtering-based method, was suggested to be useful in evaluation of gait function for rehabilitation support. However, it was expected to reduce variations of measurement errors. In this paper, a variable-Kalman-gain method based on angle error that was calculated from acceleration signals was proposed to improve measurement accuracy. The proposed method was tested comparing to fixed-gain Kalman filter and a variable-Kalman-gain method that was based on acceleration magnitude used in previous studies. First, in angle measurement in treadmill walking, the proposed method measured lower limb angles with the highest measurement accuracy and improved significantly foot inclination angle measurement, while it improved slightly shank and thigh inclination angles. The variable-gain method based on acceleration magnitude was not effective for our Kalman filter system. Then, in angle measurement of a rigid body model, it was shown that the proposed method had measurement accuracy similar to or higher than results seen in other studies that used markers of camera-based motion measurement system fixing on a rigid plate together with a sensor or on the sensor directly. The proposed method was found to be effective in angle measurement with inertial sensors. PMID:24282442

Variable-intercept panel model for deformation zoning of a super-high arch dam.

PubMed

Shi, Zhongwen; Gu, Chongshi; Qin, Dong

2016-01-01

This study determines dam deformation similarity indexes based on an analysis of deformation zoning features and panel data clustering theory, with comprehensive consideration to the actual deformation law of super-high arch dams and the spatial-temporal features of dam deformation. Measurement methods of these indexes are studied. Based on the established deformation similarity criteria, the principle used to determine the number of dam deformation zones is constructed through entropy weight method. This study proposes the deformation zoning method for super-high arch dams and the implementation steps, analyzes the effect of special influencing factors of different dam zones on the deformation, introduces dummy variables that represent the special effect of dam deformation, and establishes a variable-intercept panel model for deformation zoning of super-high arch dams. Based on different patterns of the special effect in the variable-intercept panel model, two panel analysis models were established to monitor fixed and random effects of dam deformation. Hausman test method of model selection and model effectiveness assessment method are discussed. Finally, the effectiveness of established models is verified through a case study.

Incorporating external evidence in trial-based cost-effectiveness analyses: the use of resampling methods

PubMed Central

2014-01-01

Background Cost-effectiveness analyses (CEAs) that use patient-specific data from a randomized controlled trial (RCT) are popular, yet such CEAs are criticized because they neglect to incorporate evidence external to the trial. A popular method for quantifying uncertainty in a RCT-based CEA is the bootstrap. The objective of the present study was to further expand the bootstrap method of RCT-based CEA for the incorporation of external evidence. Methods We utilize the Bayesian interpretation of the bootstrap and derive the distribution for the cost and effectiveness outcomes after observing the current RCT data and the external evidence. We propose simple modifications of the bootstrap for sampling from such posterior distributions. Results In a proof-of-concept case study, we use data from a clinical trial and incorporate external evidence on the effect size of treatments to illustrate the method in action. Compared to the parametric models of evidence synthesis, the proposed approach requires fewer distributional assumptions, does not require explicit modeling of the relation between external evidence and outcomes of interest, and is generally easier to implement. A drawback of this approach is potential computational inefficiency compared to the parametric Bayesian methods. Conclusions The bootstrap method of RCT-based CEA can be extended to incorporate external evidence, while preserving its appealing features such as no requirement for parametric modeling of cost and effectiveness outcomes. PMID:24888356

Methods to estimate effective population size using pedigree data: Examples in dog, sheep, cattle and horse

PubMed Central

2013-01-01

Background Effective population sizes of 140 populations (including 60 dog breeds, 40 sheep breeds, 20 cattle breeds and 20 horse breeds) were computed using pedigree information and six different computation methods. Simple demographical information (number of breeding males and females), variance of progeny size, or evolution of identity by descent probabilities based on coancestry or inbreeding were used as well as identity by descent rate between two successive generations or individual identity by descent rate. Results Depending on breed and method, effective population sizes ranged from 15 to 133 056, computation method and interaction between computation method and species showing a significant effect on effective population size (P < 0.0001). On average, methods based on number of breeding males and females and variance of progeny size produced larger values (4425 and 356, respectively), than those based on identity by descent probabilities (average values between 93 and 203). Since breeding practices and genetic substructure within dog breeds increased inbreeding, methods taking into account the evolution of inbreeding produced lower effective population sizes than those taking into account evolution of coancestry. The correlation level between the simplest method (number of breeding males and females, requiring no genealogical information) and the most sophisticated one ranged from 0.44 to 0.60 according to species. Conclusions When choosing a method to compute effective population size, particular attention should be paid to the species and the specific genetic structure of the population studied. PMID:23281913

The Effect of Inquiry-Based Learning Method on Students' Academic Achievement in Science Course

ERIC Educational Resources Information Center

Abdi, Ali

2014-01-01

The purpose of this study was to investigate the effects of inquiry-based learning method on students' academic achievement in sciences lesson. A total of 40 fifth grade students from two different classes were involved in the study. They were selected through purposive sampling method. The group which was assigned as experimental group was…

Comparing effects of fire modeling methods on simulated fire patterns and succession: a case study in the Missouri Ozarks

Treesearch

Jian Yang; Hong S. He; Brian R. Sturtevant; Brian R. Miranda; Eric J. Gustafson

2008-01-01

We compared four fire spread simulation methods (completely random, dynamic percolation. size-based minimum travel time algorithm. and duration-based minimum travel time algorithm) and two fire occurrence simulation methods (Poisson fire frequency model and hierarchical fire frequency model) using a two-way factorial design. We examined these treatment effects on...

Effective Practices in the Delivery of Research Ethics Education: A Qualitative Review of Instructional Methods.

PubMed

Todd, E Michelle; Torrence, Brett S; Watts, Logan L; Mulhearn, Tyler J; Connelly, Shane; Mumford, Michael D

2017-01-01

In order to delineate best practices for courses on research ethics, the goal of the present effort was to identify themes related to instructional methods reflected in effective research ethics and responsible conduct of research (RCR) courses. By utilizing a qualitative review, four themes relevant to instructional methods were identified in effective research ethics courses: active participation, case-based activities, a combination of individual and group approaches, and a small number of instructional methods. Three instructional method themes associated with less effective courses were also identified: passive learning, a group-based approach, and a large number of instructional methods. Key characteristics of each theme, along with example courses relative to each theme, are described. Additionally, implications regarding these instructional method themes and recommendations for best practices in research ethics courses are discussed.

Effectiveness of pharmacovigilance training of general practitioners: a retrospective cohort study in the Netherlands comparing two methods.

PubMed

Gerritsen, Roald; Faddegon, Hans; Dijkers, Fred; van Grootheest, Kees; van Puijenbroek, Eugène

2011-09-01

Spontaneous reporting is a cornerstone of pharmacovigilance. Unfamiliarity with the reporting of suspected adverse drug reactions (ADRs) is a major factor leading to not reporting these events. Medical education may promote more effective reporting. Numerous changes have been implemented in medical education over the last decade, with a shift in training methods from those aimed predominantly at the transfer of knowledge towards those that are more practice based and skill oriented. It is conceivable that these changes have an impact on pharmacovigilance training in vocational training programmes. Therefore, this study compares the effectiveness of a skill-oriented, practice-based pharmacovigilance training method, with a traditional, lecture-based pharmacovigilance training method in the vocational training of general practitioners (GPs). The traditional, lecture-based method is common practice in the Netherlands. The purpose of this study was to establish whether the use of a practice-based, skill-oriented method in pharmacovigilance training during GP traineeship leads to an increase of reported ADRs after completion of this traineeship, compared with a lecture-based method. We also investigated whether the applied training method has an impact on the documentation level of the reports and on the number of unlabelled events reported. A retrospective cohort study. The number of ADR reports submitted to the Netherlands Pharmacovigilance Centre Lareb (between January 2006 and October 2010) after completion of GP vocational training was compared between the two groups. Documentation level of the reports and the number of labelled/unlabelled events reported were also compared. The practice-based cohort reported 32 times after completion of training (124 subjects, 6.8 reports per 1000 months of follow-up; total follow-up of 4704 months). The lecture-based cohort reported 12 times after training (135 subjects, 2.1 reports per 1000 months of follow-up; total follow-up of 5824 months) [odds ratio 2.9; 95% CI 1.4, 6.1]. Reports from GPs with practice-based training had a better documentation grade than those from GPs with lecture-based training, and more often concerned unlabelled events. The practice-based method resulted in significantly more and better-documented reports and more often concerned unlabelled events than the lecture-based method. This effect persisted and did not appear to diminish over time.

Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology

PubMed Central

Marshall, Brandon D. L.; Galea, Sandro

2015-01-01

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. PMID:25480821

Information recovery in propagation-based imaging with decoherence effects

NASA Astrophysics Data System (ADS)

Froese, Heinrich; Lötgering, Lars; Wilhein, Thomas

2017-05-01

During the past decades the optical imaging community witnessed a rapid emergence of novel imaging modalities such as coherent diffraction imaging (CDI), propagation-based imaging and ptychography. These methods have been demonstrated to recover complex-valued scalar wave fields from redundant data without the need for refractive or diffractive optical elements. This renders these techniques suitable for imaging experiments with EUV and x-ray radiation, where the use of lenses is complicated by fabrication, photon efficiency and cost. However, decoherence effects can have detrimental effects on the reconstruction quality of the numerical algorithms involved. Here we demonstrate propagation-based optical phase retrieval from multiple near-field intensities with decoherence effects such as partially coherent illumination, detector point spread, binning and position uncertainties of the detector. Methods for overcoming these systematic experimental errors - based on the decomposition of the data into mutually incoherent modes - are proposed and numerically tested. We believe that the results presented here open up novel algorithmic methods to accelerate detector readout rates and enable subpixel resolution in propagation-based phase retrieval. Further the techniques are straightforward to be extended to methods such as CDI, ptychography and holography.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

LEAKAGE CHARACTERISTICS OF BASE OF RIVERBANK BY SELF POTENTIAL METHOD AND EXAMINATION OF EFFECTIVENESS OF SELF POTENTIAL METHOD TO HEALTH MONITORING OF BASE OF RIVERBANK

NASA Astrophysics Data System (ADS)

Matsumoto, Kensaku; Okada, Takashi; Takeuchi, Atsuo; Yazawa, Masato; Uchibori, Sumio; Shimizu, Yoshihiko

Field Measurement of Self Potential Method using Copper Sulfate Electrode was performed in base of riverbank in WATARASE River, where has leakage problem to examine leakage characteristics. Measurement results showed typical S-shape what indicates existence of flow groundwater. The results agreed with measurement results by Ministry of Land, Infrastructure and Transport with good accuracy. Results of 1m depth ground temperature detection and Chain-Array detection showed good agreement with results of the Self Potential Method. Correlation between Self Potential value and groundwater velocity was examined model experiment. The result showed apparent correlation. These results indicate that the Self Potential Method was effective method to examine the characteristics of ground water of base of riverbank in leakage problem.

Characterizing Task-Based OpenMP Programs

PubMed Central

Muddukrishna, Ananya; Jonsson, Peter A.; Brorsson, Mats

2015-01-01

Programmers struggle to understand performance of task-based OpenMP programs since profiling tools only report thread-based performance. Performance tuning also requires task-based performance in order to balance per-task memory hierarchy utilization against exposed task parallelism. We provide a cost-effective method to extract detailed task-based performance information from OpenMP programs. We demonstrate the utility of our method by quickly diagnosing performance problems and characterizing exposed task parallelism and per-task instruction profiles of benchmarks in the widely-used Barcelona OpenMP Tasks Suite. Programmers can tune performance faster and understand performance tradeoffs more effectively than existing tools by using our method to characterize task-based performance. PMID:25860023

The Effect of Teaching Methods and Learning Style on Learning Program Design in Web-Based Education Systems

ERIC Educational Resources Information Center

Hung, Yen-Chu

2012-01-01

The instructional value of web-based education systems has been an important area of research in information systems education. This study investigates the effect of various teaching methods on program design learning for students with specific learning styles in web-based education systems. The study takes first-year Computer Science and…

Evaluation method based on the image correlation for laser jamming image

NASA Astrophysics Data System (ADS)

Che, Jinxi; Li, Zhongmin; Gao, Bo

2013-09-01

The jamming effectiveness evaluation of infrared imaging system is an important part of electro-optical countermeasure. The infrared imaging devices in the military are widely used in the searching, tracking and guidance and so many other fields. At the same time, with the continuous development of laser technology, research of laser interference and damage effect developed continuously, laser has been used to disturbing the infrared imaging device. Therefore, the effect evaluation of the infrared imaging system by laser has become a meaningful problem to be solved. The information that the infrared imaging system ultimately present to the user is an image, so the evaluation on jamming effect can be made from the point of assessment of image quality. The image contains two aspects of the information, the light amplitude and light phase, so the image correlation can accurately perform the difference between the original image and disturbed image. In the paper, the evaluation method of digital image correlation, the assessment method of image quality based on Fourier transform, the estimate method of image quality based on error statistic and the evaluation method of based on peak signal noise ratio are analysed. In addition, the advantages and disadvantages of these methods are analysed. Moreover, the infrared disturbing images of the experiment result, in which the thermal infrared imager was interfered by laser, were analysed by using these methods. The results show that the methods can better reflect the jamming effects of the infrared imaging system by laser. Furthermore, there is good consistence between evaluation results by using the methods and the results of subjective visual evaluation. And it also provides well repeatability and convenient quantitative analysis. The feasibility of the methods to evaluate the jamming effect was proved. It has some extent reference value for the studying and developing on electro-optical countermeasures equipments and effectiveness evaluation.

An improved method for predicting the effects of flight on jet mixing noise

NASA Technical Reports Server (NTRS)

Stone, J. R.

1979-01-01

The NASA method (1976) for predicting the effects of flight on jet mixing noise was improved. The earlier method agreed reasonably well with experimental flight data for jet velocities up to about 520 m/sec (approximately 1700 ft/sec). The poorer agreement at high jet velocities appeared to be due primarily to the manner in which supersonic convection effects were formulated. The purely empirical supersonic convection formulation of the earlier method was replaced by one based on theoretical considerations. Other improvements of an empirical nature included were based on model-jet/free-jet simulated flight tests. The revised prediction method is presented and compared with experimental data obtained from the Bertin Aerotrain with a J85 engine, the DC-10 airplane with JT9D engines, and the DC-9 airplane with refanned JT8D engines. It is shown that the new method agrees better with the data base than a recently proposed SAE method.

Adaptive Set-Based Methods for Association Testing

PubMed Central

Su, Yu-Chen; Gauderman, W. James; Kiros, Berhane; Lewinger, Juan Pablo

2017-01-01

With a typical sample size of a few thousand subjects, a single genomewide association study (GWAS) using traditional one-SNP-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. While self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly ‘adapt’ to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a LASSO based test. PMID:26707371

Instruction via Web-Based Modules in Early Childhood Personnel Preparation: A Mixed-Methods Study of Effectiveness and Learner Perspectives

ERIC Educational Resources Information Center

Hollingsworth, Heidi L.; Lim, Chih-Ing

2015-01-01

Effective personnel preparation is critical to the development of a high quality early childhood workforce that provides optimal care and education for young children. This mixed-methods study examined the effectiveness of, and learner perspectives on, instruction via web-based modules within face-to-face early childhood personnel preparation…

Verification of Emergent Behaviors in Swarm-based Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy; Hinchey, Mike; Truszkowski, Walt; Rash, James

2004-01-01

The emergent properties of swarms make swarm-based missions powerful, but at the same time more difficult to design and to assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of swarm-based missions. The Autonomous Nano-Technology Swarm (ANTS) mission is being used as an example and case study for swarm-based missions to experiment and test current formal methods with intelligent swarms. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior. This paper introduces how intelligent swarm technology is being proposed for NASA missions, and gives the results of a comparison of several formal methods and approaches for specifying intelligent swarm-based systems and their effectiveness for predicting emergent behavior.

The effect of using genealogy-based haplotypes for genomic prediction

PubMed Central

2013-01-01

Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy. PMID:23496971

VORSTAB: A computer program for calculating lateral-directional stability derivatives with vortex flow effect

NASA Technical Reports Server (NTRS)

Lan, C. Edward

1985-01-01

A computer program based on the Quasi-Vortex-Lattice Method of Lan is presented for calculating longitudinal and lateral-directional aerodynamic characteristics of nonplanar wing-body combination. The method is based on the assumption of inviscid subsonic flow. Both attached and vortex-separated flows are treated. For the vortex-separated flow, the calculation is based on the method of suction analogy. The effect of vortex breakdown is accounted for by an empirical method. A summary of the theoretical method, program capabilities, input format, output variables and program job control set-up are described. Three test cases are presented as guides for potential users of the code.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Community-based human–elephant conflict mitigation: The value of an evidence-based approach in promoting the uptake of effective methods

PubMed Central

Gunaryadi, Donny; Sugiyo

2017-01-01

Human–elephant conflict (HEC) is a serious threat to elephants and can cause major economic losses. It is widely accepted that reduction of HEC will often require community-based methods for repelling elephants but there are few tests of such methods. We tested community-based crop-guarding methods with and without novel chili-based elephant deterrents and describe changes in farmers’ willingness to adopt these methods following our demonstration of their relative effectiveness. In three separate field-trials that took place over almost two years (October 2005 –May 2007) in two villages adjacent to Way Kambas National Park (WKNP) in Indonesia, we found that community-based crop-guarding was effective at keeping Asian elephants (Elephas maximus) out of crop fields in 91.2% (52 out of 57), 87.6% (156 out of 178), and 80.0% (16 out of 20) of attempted raids. Once the method had been shown to be effective at demonstration sites, farmers in 16 villages around WKNP voluntarily adopted it during the July 2008 to March 2009 period and were able to repel elephants in 73.9% (150 out of 203) of attempted raids, with seven villages repelling 100% of attempted raids. These 16 villages had all experienced high levels of HEC in the preceding years; e.g. they accounted for >97% of the 742 HEC incidents recorded for the entire park in 2006. Our work shows, therefore, that a simple evidence-based approach can facilitate significant reductions in HEC at the protected area scale. PMID:28510590

Near-Infrared Spectrum Detection of Wheat Gluten Protein Content Based on a Combined Filtering Method.

PubMed

Cai, Jian-Hua

2017-09-01

To eliminate the random error of the derivative near-IR (NIR) spectrum and to improve model stability and the prediction accuracy of the gluten protein content, a combined method is proposed for pretreatment of the NIR spectrum based on both empirical mode decomposition and the wavelet soft-threshold method. The principle and the steps of the method are introduced and the denoising effect is evaluated. The wheat gluten protein content is calculated based on the denoised spectrum, and the results are compared with those of the nine-point smoothing method and the wavelet soft-threshold method. Experimental results show that the proposed combined method is effective in completing pretreatment of the NIR spectrum, and the proposed method improves the accuracy of detection of wheat gluten protein content from the NIR spectrum.

An Evaluation of Attitude-Independent Magnetometer-Bias Determination Methods

NASA Technical Reports Server (NTRS)

Hashmall, J. A.; Deutschmann, Julie

1996-01-01

Although several algorithms now exist for determining three-axis magnetometer (TAM) biases without the use of attitude data, there are few studies on the effectiveness of these methods, especially in comparison with attitude dependent methods. This paper presents the results of a comparison of three attitude independent methods and an attitude dependent method for computing TAM biases. The comparisons are based on in-flight data from the Extreme Ultraviolet Explorer (EUVE), the Upper Atmosphere Research Satellite (UARS), and the Compton Gamma Ray Observatory (GRO). The effectiveness of an algorithm is measured by the accuracy of attitudes computed using biases determined with that algorithm. The attitude accuracies are determined by comparison with known, extremely accurate, star-tracker-based attitudes. In addition, the effect of knowledge of calibration parameters other than the biases on the effectiveness of all bias determination methods is examined.

Mapping Urban Environmental Noise Using Smartphones.

PubMed

Zuo, Jinbo; Xia, Hao; Liu, Shuo; Qiao, Yanyou

2016-10-13

Noise mapping is an effective method of visualizing and accessing noise pollution. In this paper, a noise-mapping method based on smartphones to effectively and easily measure environmental noise is proposed. By using this method, a noise map of an entire area can be created using limited measurement data. To achieve the measurement with certain precision, a set of methods was designed to calibrate the smartphones. Measuring noise with mobile phones is different from the traditional static observations. The users may be moving at any time. Therefore, a method of attaching an additional microphone with a windscreen is proposed to reduce the wind effect. However, covering an entire area is impossible. Therefore, an interpolation method is needed to achieve full coverage of the area. To reduce the influence of spatial heterogeneity and improve the precision of noise mapping, a region-based noise-mapping method is proposed in this paper, which is based on the distribution of noise in different region types tagged by volunteers, to interpolate and combine them to create a noise map. To validate the effect of the method, a comparison of the interpolation results was made to analyse our method and the ordinary Kriging method. The result shows that our method is more accurate in reflecting the local distribution of noise and has better interpolation precision. We believe that the proposed noise-mapping method is a feasible and low-cost noise-mapping solution.

Mapping Urban Environmental Noise Using Smartphones

PubMed Central

Zuo, Jinbo; Xia, Hao; Liu, Shuo; Qiao, Yanyou

2016-01-01

Noise mapping is an effective method of visualizing and accessing noise pollution. In this paper, a noise-mapping method based on smartphones to effectively and easily measure environmental noise is proposed. By using this method, a noise map of an entire area can be created using limited measurement data. To achieve the measurement with certain precision, a set of methods was designed to calibrate the smartphones. Measuring noise with mobile phones is different from the traditional static observations. The users may be moving at any time. Therefore, a method of attaching an additional microphone with a windscreen is proposed to reduce the wind effect. However, covering an entire area is impossible. Therefore, an interpolation method is needed to achieve full coverage of the area. To reduce the influence of spatial heterogeneity and improve the precision of noise mapping, a region-based noise-mapping method is proposed in this paper, which is based on the distribution of noise in different region types tagged by volunteers, to interpolate and combine them to create a noise map. To validate the effect of the method, a comparison of the interpolation results was made to analyse our method and the ordinary Kriging method. The result shows that our method is more accurate in reflecting the local distribution of noise and has better interpolation precision. We believe that the proposed noise-mapping method is a feasible and low-cost noise-mapping solution. PMID:27754359

Incorporating external evidence in trial-based cost-effectiveness analyses: the use of resampling methods.

PubMed

Sadatsafavi, Mohsen; Marra, Carlo; Aaron, Shawn; Bryan, Stirling

2014-06-03

Cost-effectiveness analyses (CEAs) that use patient-specific data from a randomized controlled trial (RCT) are popular, yet such CEAs are criticized because they neglect to incorporate evidence external to the trial. A popular method for quantifying uncertainty in a RCT-based CEA is the bootstrap. The objective of the present study was to further expand the bootstrap method of RCT-based CEA for the incorporation of external evidence. We utilize the Bayesian interpretation of the bootstrap and derive the distribution for the cost and effectiveness outcomes after observing the current RCT data and the external evidence. We propose simple modifications of the bootstrap for sampling from such posterior distributions. In a proof-of-concept case study, we use data from a clinical trial and incorporate external evidence on the effect size of treatments to illustrate the method in action. Compared to the parametric models of evidence synthesis, the proposed approach requires fewer distributional assumptions, does not require explicit modeling of the relation between external evidence and outcomes of interest, and is generally easier to implement. A drawback of this approach is potential computational inefficiency compared to the parametric Bayesian methods. The bootstrap method of RCT-based CEA can be extended to incorporate external evidence, while preserving its appealing features such as no requirement for parametric modeling of cost and effectiveness outcomes.

Multi person detection and tracking based on hierarchical level-set method

NASA Astrophysics Data System (ADS)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

The Effects of Web-Based Interactive Virtual Tours on the Development of Prospective Mathematics Teachers' Spatial Skills

ERIC Educational Resources Information Center

Kurtulus, Aytac

2013-01-01

The aim of this study was to investigate the effects of web-based interactive virtual tours on the development of prospective mathematics teachers' spatial skills. The study was designed based on experimental method. The "one-group pre-test post-test design" of this method was taken as the research model. The study was conducted with 3rd year…

Modeling of Bulk Evaporation and Condensation

NASA Technical Reports Server (NTRS)

Anghaie, S.; Ding, Z.

1996-01-01

This report describes the modeling and mathematical formulation of the bulk evaporation and condensation involved in liquid-vapor phase change processes. An internal energy formulation, for these phase change processes that occur under the constraint of constant volume, was studied. Compared to the enthalpy formulation, the internal energy formulation has a more concise and compact form. The velocity and time scales of the interface movement were obtained through scaling analysis and verified by performing detailed numerical experiments. The convection effect induced by the density change was analyzed and found to be negligible compared to the conduction effect. Two iterative methods for updating the value of the vapor phase fraction, the energy based (E-based) and temperature based (T-based) methods, were investigated. Numerical experiments revealed that for the evaporation and condensation problems the E-based method is superior to the T-based method in terms of computational efficiency. The internal energy formulation and the E-based method were used to compute the bulk evaporation and condensation processes under different conditions. The evolution of the phase change processes was investigated. This work provided a basis for the modeling of thermal performance of multi-phase nuclear fuel elements under variable gravity conditions, in which the buoyancy convection due to gravity effects and internal heating are involved.

An eco-friendly, quick and cost-effective method for the quantification of acrylamide in cereal-based baby foods.

PubMed

Cengiz, Mehmet Fatih; Gündüz, Cennet Pelin Boyacı

2014-09-01

The presence of acrylamide in cereal-based baby foods is a matter of great concern owing to its possible health effects. Derivatization followed by gas chromatography/mass spectrometry (GC/MS) is one of the most common methods to quantify acrylamide. However, it requires the use of toxic chemicals and is time-consuming. The aim of this study was to develop an eco-friendly, rapid and inexpensive method for the determination of acrylamide in cereal-based baby foods. The method involves defatting with n-hexane, extraction into water, precipitation of proteins, bromination, extraction into ethyl acetate and injection into a GC/MS system. The effects of defatting, precipitation, treatment with triethylamine, addition of internal standard and column selection were reviewed. A flow chart for acrylamide analysis was prepared. To evaluate the applicability of the method, 62 different cereal-based baby foods were analyzed. The levels of acrylamide ranged from not detected (below the limit of detection) to 660 µg kg(-1). The method is more eco-friendly and less expensive because it consumes very little solvent relative to other methods using bromine solutions and ethyl acetate. In addition, sample pre-treatment requires no solid phase extraction or concentration steps. The method is recommended for the determination of trace acrylamide in complex cereal-based baby food products. © 2014 Society of Chemical Industry.

A unified frame of predicting side effects of drugs by using linear neighborhood similarity.

PubMed

Zhang, Wen; Yue, Xiang; Liu, Feng; Chen, Yanlin; Tu, Shikui; Zhang, Xining

2017-12-14

Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame.

Research and Implementation of Tibetan Word Segmentation Based on Syllable Methods

NASA Astrophysics Data System (ADS)

Jiang, Jing; Li, Yachao; Jiang, Tao; Yu, Hongzhi

2018-03-01

Tibetan word segmentation (TWS) is an important problem in Tibetan information processing, while abbreviated word recognition is one of the key and most difficult problems in TWS. Most of the existing methods of Tibetan abbreviated word recognition are rule-based approaches, which need vocabulary support. In this paper, we propose a method based on sequence tagging model for abbreviated word recognition, and then implement in TWS systems with sequence labeling models. The experimental results show that our abbreviated word recognition method is fast and effective and can be combined easily with the segmentation model. This significantly increases the effect of the Tibetan word segmentation.

A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

DTIC Science & Technology

1980-07-08

to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...the weight assigned to each variable whenever a new one is added. Jennrich, R. I. (1977). Stepwise discriminant analysis , in Statistical Methods for

Context-sensitive trace inlining for Java.

PubMed

Häubl, Christian; Wimmer, Christian; Mössenböck, Hanspeter

2013-12-01

Method inlining is one of the most important optimizations in method-based just-in-time (JIT) compilers. It widens the compilation scope and therefore allows optimizing multiple methods as a whole, which increases the performance. However, if method inlining is used too frequently, the compilation time increases and too much machine code is generated. This has negative effects on the performance. Trace-based JIT compilers only compile frequently executed paths, so-called traces, instead of whole methods. This may result in faster compilation, less generated machine code, and better optimized machine code. In the previous work, we implemented a trace recording infrastructure and a trace-based compiler for [Formula: see text], by modifying the Java HotSpot VM. Based on this work, we evaluate the effect of trace inlining on the performance and the amount of generated machine code. Trace inlining has several major advantages when compared to method inlining. First, trace inlining is more selective than method inlining, because only frequently executed paths are inlined. Second, the recorded traces may capture information about virtual calls, which simplify inlining. A third advantage is that trace information is context sensitive so that different method parts can be inlined depending on the specific call site. These advantages allow more aggressive inlining while the amount of generated machine code is still reasonable. We evaluate several inlining heuristics on the benchmark suites DaCapo 9.12 Bach, SPECjbb2005, and SPECjvm2008 and show that our trace-based compiler achieves an up to 51% higher peak performance than the method-based Java HotSpot client compiler. Furthermore, we show that the large compilation scope of our trace-based compiler has a positive effect on other compiler optimizations such as constant folding or null check elimination.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Overcoming Recruitment Challenges of Web-based Interventions for Tobacco Use: The Case of Web-based Acceptance and Commitment Therapy for Smoking Cessation

PubMed Central

Heffner, Jaimee L; Wyszynski, Christopher M; Comstock, Bryan; Mercer, Laina D.; Bricker, Jonathan

2013-01-01

Web-based behavioral interventions for substance use are being developed at a rapid pace, yet there is a dearth of information regarding the most effective methods for recruiting participants into web-based intervention trials. In this paper, we describe our successful recruitment of participants into a pilot trial of web-based Acceptance and Commitment Therapy (ACT) for smoking cessation and compare traditional and web-based methods of recruitment in terms of their effects on baseline participant characteristics, association with study retention and treatment outcome, yield, and cost-effectiveness. Over a 10-week period starting June 15, 2010, we recruited 222 smokers for a web-based smoking cessation study using a variety of recruitment methods. The largest portion of randomized participants were recruited through Google AdWords (36%), followed by medical Internet media (23%), standard media (14%), word of mouth (12%), broadcast emails (11%), and social media (6%). Recruitment source was not related to baseline participant characteristics, 3-month data retention, or 30-day point prevalence smoking abstinence at the 3-month outcome assessment. Cost per randomized participant ranged from $5.27/participant for word of mouth to $172.76/participant for social media, with a mean cost of $42.48/participant. Our diversified approach to recruitment, including both traditional and web-based methods, enabled timely enrollment of participants into the study. Because there was no evidence of a substantive difference in baseline characteristics, retention, or outcomes based on recruitment channel, the yield and cost-effectiveness of recruitment methods may be the more critical considerations in developing a feasible recruitment plan for a web-based smoking cessation intervention study. PMID:23770645

Overcoming recruitment challenges of web-based interventions for tobacco use: the case of web-based acceptance and commitment therapy for smoking cessation.

PubMed

Heffner, Jaimee L; Wyszynski, Christopher M; Comstock, Bryan; Mercer, Laina D; Bricker, Jonathan

2013-10-01

Web-based behavioral interventions for substance use are being developed at a rapid pace, yet there is a dearth of information regarding the most effective methods for recruiting participants into web-based intervention trials. In this paper, we describe our successful recruitment of participants into a pilot trial of web-based Acceptance and Commitment Therapy (ACT) for smoking cessation and compare traditional and web-based methods of recruitment in terms of their effects on baseline participant characteristics, association with study retention and treatment outcome, yield, and cost-effectiveness. Over a 10-week period starting June 15, 2010, we recruited 222 smokers for a web-based smoking cessation study using a variety of recruitment methods. The largest portion of randomized participants were recruited through Google AdWords (36%), followed by medical Internet media (23%), standard media (14%), word of mouth (12%), broadcast emails (11%), and social media (6%). Recruitment source was not related to baseline participant characteristics, 3-month data retention, or 30-day point prevalence smoking abstinence at the 3-month outcome assessment. Cost per randomized participant ranged from $5.27/participant for word of mouth to $172.76/participant for social media, with a mean cost of $42.48/participant. Our diversified approach to recruitment, including both traditional and web-based methods, enabled timely enrollment of participants into the study. Because there was no evidence of a substantive difference in baseline characteristics, retention, or outcomes based on recruitment channel, the yield and cost-effectiveness of recruitment methods may be the more critical considerations in developing a feasible recruitment plan for a web-based smoking cessation intervention study. Copyright © 2013 Elsevier Ltd. All rights reserved.

Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification.

PubMed

Caumes, Géraldine; Borrel, Alexandre; Abi Hussein, Hiba; Camproux, Anne-Claude; Regad, Leslie

2017-09-01

Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket-based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket-estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket-estimation methods on the results of pocket-based approaches. We focused on the effect of three pocket-estimation methods on a pocket-ligand (PL) classification. This pocket-based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket-estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket-estimation method choice in pocket-based approaches. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Game-Based E-Learning Is More Effective than a Conventional Instructional Method: A Randomized Controlled Trial with Third-Year Medical Students

PubMed Central

Boeker, Martin; Andel, Peter; Vach, Werner; Frankenschmidt, Alexander

2013-01-01

Background When compared with more traditional instructional methods, Game-based e-learning (GbEl) promises a higher motivation of learners by presenting contents in an interactive, rule-based and competitive way. Most recent systematic reviews and meta-analysis of studies on Game-based learning and GbEl in the medical professions have shown limited effects of these instructional methods. Objectives To compare the effectiveness on the learning outcome of a Game-based e-learning (GbEl) instruction with a conventional script-based instruction in the teaching of phase contrast microscopy urinalysis under routine training conditions of undergraduate medical students. Methods A randomized controlled trial was conducted with 145 medical students in their third year of training in the Department of Urology at the University Medical Center Freiburg, Germany. 82 subjects where allocated for training with an educational adventure-game (GbEl group) and 69 subjects for conventional training with a written script-based approach (script group). Learning outcome was measured with a 34 item single choice test. Students' attitudes were collected by a questionnaire regarding fun with the training, motivation to continue the training and self-assessment of acquired knowledge. Results The students in the GbEl group achieved significantly better results in the cognitive knowledge test than the students in the script group: the mean score was 28.6 for the GbEl group and 26.0 for the script group of a total of 34.0 points with a Cohen's d effect size of 0.71 (ITT analysis). Attitudes towards the recent learning experience were significantly more positive with GbEl. Students reported to have more fun while learning with the game when compared to the script-based approach. Conclusions Game-based e-learning is more effective than a script-based approach for the training of urinalysis in regard to cognitive learning outcome and has a high positive motivational impact on learning. Game-based e-learning can be used as an effective teaching method for self-instruction. PMID:24349257

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

Properties of a Formal Method for Prediction of Emergent Behaviors in Swarm-based Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy; Hinchey, Mike; Truszkowski, Walt; Rash, James

2004-01-01

Autonomous intelligent swarms of satellites are being proposed for NASA missions that have complex behaviors and interactions. The emergent properties of swarms make these missions powerful, but at the same time more difficult to design and assure that proper behaviors will emerge. This paper gives the results of research into formal methods techniques for verification and validation of NASA swarm-based missions. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft. The NASA ANTS mission was used as an example of swarm intelligence for which to apply the formal methods. This paper will give the evaluation of these formal methods and give partial specifications of the ANTS mission using four selected methods. We then give an evaluation of the methods and the needed properties of a formal method for effective specification and prediction of emergent behavior in swarm-based systems.

Prediction of ground effects on aircraft noise

NASA Technical Reports Server (NTRS)

Pao, S. P.; Wenzel, A. R.; Oncley, P. B.

1978-01-01

A unified method is recommended for predicting ground effects on noise. This method may be used in flyover noise predictions and in correcting static test-stand data to free-field conditions. The recommendation is based on a review of recent progress in the theory of ground effects and of the experimental evidence which supports this theory. It is shown that a surface wave must be included sometimes in the prediction method. Prediction equations are collected conveniently in a single section of the paper. Methods of measuring ground impedance and the resulting ground-impedance data are also reviewed because the recommended method is based on a locally reactive impedance boundary model. Current practice of estimating ground effects are reviewed and consideration is given to practical problems in applying the recommended method. These problems include finite frequency-band filters, finite source dimension, wind and temperature gradients, and signal incoherence.

A temperature match based optimization method for daily load prediction considering DLC effect

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

Yu, Z.

This paper presents a unique optimization method for short term load forecasting. The new method is based on the optimal template temperature match between the future and past temperatures. The optimal error reduction technique is a new concept introduced in this paper. Two case studies show that for hourly load forecasting, this method can yield results as good as the rather complicated Box-Jenkins Transfer Function method, and better than the Box-Jenkins method; for peak load prediction, this method is comparable in accuracy to the neural network method with back propagation, and can produce more accurate results than the multi-linear regressionmore » method. The DLC effect on system load is also considered in this method.« less

Evaluation of Vacuum Blasting and Heat Guns as Methods for Abating Lead- Based Paint on Buildings

DTIC Science & Technology

1993-09-01

INCOMPATIBILITY - Contact with powerful oxidizing agents such as FLUORINE, CHLORINE TRIFLUORIDE , MANGANESE TRIOXIDE, OXYGEN DIFLUORIDE, MANGANESE...investigating new technologies for lead-based paint abatement. This research evaluates the effectiveness , safety, LEC1L•.T• and cost of vacuum abrasive...paint abatement. This research evaluates the effectiveness , safety, and cost of vacuum abrasive units and heat guns as methods of removing lead-based

Adaptive Set-Based Methods for Association Testing.

PubMed

Su, Yu-Chen; Gauderman, William James; Berhane, Kiros; Lewinger, Juan Pablo

2016-02-01

With a typical sample size of a few thousand subjects, a single genome-wide association study (GWAS) using traditional one single nucleotide polymorphism (SNP)-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. Although self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly "adapt" to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a least absolute shrinkage and selection operator (LASSO)-based test. © 2015 WILEY PERIODICALS, INC.

Measurement correction method for force sensor used in dynamic pressure calibration based on artificial neural network optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Gu, Tingwei; Kong, Deren; Shang, Fei; Chen, Jing

2017-12-01

We present an optimization algorithm to obtain low-uncertainty dynamic pressure measurements from a force-transducer-based device. In this paper, the advantages and disadvantages of the methods that are commonly used to measure the propellant powder gas pressure, the applicable scope of dynamic pressure calibration devices, and the shortcomings of the traditional comparison calibration method based on the drop-weight device are firstly analysed in detail. Then, a dynamic calibration method for measuring pressure using a force sensor based on a drop-weight device is introduced. This method can effectively save time when many pressure sensors are calibrated simultaneously and extend the life of expensive reference sensors. However, the force sensor is installed between the drop-weight and the hammerhead by transition pieces through the connection mode of bolt fastening, which causes adverse effects such as additional pretightening and inertia forces. To solve these effects, the influence mechanisms of the pretightening force, the inertia force and other influence factors on the force measurement are theoretically analysed. Then a measurement correction method for the force measurement is proposed based on an artificial neural network optimized by a genetic algorithm. The training and testing data sets are obtained from calibration tests, and the selection criteria for the key parameters of the correction model is discussed. The evaluation results for the test data show that the correction model can effectively improve the force measurement accuracy of the force sensor. Compared with the traditional high-accuracy comparison calibration method, the percentage difference of the impact-force-based measurement is less than 0.6% and the relative uncertainty of the corrected force value is 1.95%, which can meet the requirements of engineering applications.

Effectiveness of Project Based Learning in Statistics for Lower Secondary Schools

ERIC Educational Resources Information Center

Siswono, Tatag Yuli Eko; Hartono, Sugi; Kohar, Ahmad Wachidul

2018-01-01

Purpose: This study aimed at investigating the effectiveness of implementing Project Based Learning (PBL) on the topic of statistics at a lower secondary school in Surabaya city, Indonesia, indicated by examining student learning outcomes, student responses, and student activity. Research Methods: A quasi experimental method was conducted over two…

Selecting Faculty with Behavioral-Based Interviewing

ERIC Educational Resources Information Center

Hammons, James O.; Gansz, Joey L.

2005-01-01

In the corporate world, more and more companies have begun to use a more effective method of evaluating prospective employees. It is estimated that by 1996, approximately 20 to 30 percent of the nation's large companies had begun to use this more effective method known as behavioral-based interviewing (BI). This article explains what BI is and…

Effective Teaching Methods--Project-based Learning in Physics

ERIC Educational Resources Information Center

Holubova, Renata

2008-01-01

The paper presents results of the research of new effective teaching methods in physics and science. It is found out that it is necessary to educate pre-service teachers in approaches stressing the importance of the own activity of students, in competences how to create an interdisciplinary project. Project-based physics teaching and learning…

Meta-analysis in evidence-based healthcare: a paradigm shift away from random effects is overdue.

PubMed

Doi, Suhail A R; Furuya-Kanamori, Luis; Thalib, Lukman; Barendregt, Jan J

2017-12-01

Each year up to 20 000 systematic reviews and meta-analyses are published whose results influence healthcare decisions, thus making the robustness and reliability of meta-analytic methods one of the world's top clinical and public health priorities. The evidence synthesis makes use of either fixed-effect or random-effects statistical methods. The fixed-effect method has largely been replaced by the random-effects method as heterogeneity of study effects led to poor error estimation. However, despite the widespread use and acceptance of the random-effects method to correct this, it too remains unsatisfactory and continues to suffer from defective error estimation, posing a serious threat to decision-making in evidence-based clinical and public health practice. We discuss here the problem with the random-effects approach and demonstrate that there exist better estimators under the fixed-effect model framework that can achieve optimal error estimation. We argue for an urgent return to the earlier framework with updates that address these problems and conclude that doing so can markedly improve the reliability of meta-analytical findings and thus decision-making in healthcare.

Antipsychotic drug poisoning monitoring of clozapine in urine by using coffee ring effect based surface-enhanced Raman spectroscopy.

PubMed

Zhu, Qingxia; Yu, Xiaoyan; Wu, Zebing; Lu, Feng; Yuan, Yongfang

2018-07-19

Antipsychotics are the drugs most often involved in drug poisoning cases, and therefore, therapeutic drug monitoring (TDM) is necessary for safe and effective medication administration of these drugs. In this study, a coffee ring effect-based surface-enhanced Raman spectroscopy (CRE-SERS) method was developed and successfully used to monitor antipsychotic poisoning by using urine samples for the first time. The established method exhibited excellent SERS performance since more hot spots were obtained in the "coffee ring". Using the optimized CRE-SERS method, the sensitivity was improved one order more than that of the conventional method with reasonable reproducibility. The antipsychotic drug clozapine (CLO) spiked into urine samples at 0.5-50 μg mL -1 was quantitatively detected, at concentrations above the thresholds for toxicity. The CRE-SERS method allowed CLO and its metabolites to be ultimately distinguished from real poisoning urine samples. The coffee-ring effect would provide more opportunities for practical applications of the SERS-based method. The frequent occurrence of drug poisoning may have created a new area for the application of the CRE-SERS method. It is anticipated that the developed method will also have great potential for other drug poisoning monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of empty bins on image upscaling in capsule endoscopy

NASA Astrophysics Data System (ADS)

Rukundo, Olivier

2017-07-01

This paper presents a preliminary study of the effect of empty bins on image upscaling in capsule endoscopy. The presented study was conducted based on results of existing contrast enhancement and interpolation methods. A low contrast enhancement method based on pixels consecutiveness and modified bilinear weighting scheme has been developed to distinguish between necessary empty bins and unnecessary empty bins in the effort to minimize the number of empty bins in the input image, before further processing. Linear interpolation methods have been used for upscaling input images with stretched histograms. Upscaling error differences and similarity indices between pairs of interpolation methods have been quantified using the mean squared error and feature similarity index techniques. Simulation results demonstrated more promising effects using the developed method than other contrast enhancement methods mentioned.

Linear Elastic and Cohesive Fracture Analysis to Model Hydraulic Fracture in Brittle and Ductile Rocks

NASA Astrophysics Data System (ADS)

Yao, Yao

2012-05-01

Hydraulic fracturing technology is being widely used within the oil and gas industry for both waste injection and unconventional gas production wells. It is essential to predict the behavior of hydraulic fractures accurately based on understanding the fundamental mechanism(s). The prevailing approach for hydraulic fracture modeling continues to rely on computational methods based on Linear Elastic Fracture Mechanics (LEFM). Generally, these methods give reasonable predictions for hard rock hydraulic fracture processes, but still have inherent limitations, especially when fluid injection is performed in soft rock/sand or other non-conventional formations. These methods typically give very conservative predictions on fracture geometry and inaccurate estimation of required fracture pressure. One of the reasons the LEFM-based methods fail to give accurate predictions for these materials is that the fracture process zone ahead of the crack tip and softening effect should not be neglected in ductile rock fracture analysis. A 3D pore pressure cohesive zone model has been developed and applied to predict hydraulic fracturing under fluid injection. The cohesive zone method is a numerical tool developed to model crack initiation and growth in quasi-brittle materials considering the material softening effect. The pore pressure cohesive zone model has been applied to investigate the hydraulic fracture with different rock properties. The hydraulic fracture predictions of a three-layer water injection case have been compared using the pore pressure cohesive zone model with revised parameters, LEFM-based pseudo 3D model, a Perkins-Kern-Nordgren (PKN) model, and an analytical solution. Based on the size of the fracture process zone and its effect on crack extension in ductile rock, the fundamental mechanical difference of LEFM and cohesive fracture mechanics-based methods is discussed. An effective fracture toughness method has been proposed to consider the fracture process zone effect on the ductile rock fracture.

Atmospheric Effects on InSAR Measurements and Their Mitigation

PubMed Central

Ding, Xiao-li; Li, Zhi-wei; Zhu, Jian-jun; Feng, Guang-cai; Long, Jiang-ping

2008-01-01

Interferometric Synthetic Aperture Radar (InSAR) is a powerful technology for observing the Earth surface, especially for mapping the Earth's topography and deformations. InSAR measurements are however often significantly affected by the atmosphere as the radar signals propagate through the atmosphere whose state varies both in space and in time. Great efforts have been made in recent years to better understand the properties of the atmospheric effects and to develop methods for mitigating the effects. This paper provides a systematic review of the work carried out in this area. The basic principles of atmospheric effects on repeat-pass InSAR are first introduced. The studies on the properties of the atmospheric effects, including the magnitudes of the effects determined in the various parts of the world, the spectra of the atmospheric effects, the isotropic properties and the statistical distributions of the effects, are then discussed. The various methods developed for mitigating the atmospheric effects are then reviewed, including the methods that are based on PSInSAR processing, the methods that are based on interferogram modeling, and those that are based on external data such as GPS observations, ground meteorological data, and satellite data including those from the MODIS and MERIS. Two examples that use MODIS and MERIS data respectively to calibrate atmospheric effects on InSAR are also given. PMID:27873822

Atmospheric Effects on InSAR Measurements and Their Mitigation.

PubMed

Ding, Xiao-Li; Li, Zhi-Wei; Zhu, Jian-Jun; Feng, Guang-Cai; Long, Jiang-Ping

2008-09-03

Interferometric Synthetic Aperture Radar (InSAR) is a powerful technology for observing the Earth surface, especially for mapping the Earth's topography and deformations. InSAR measurements are however often significantly affected by the atmosphere as the radar signals propagate through the atmosphere whose state varies both in space and in time. Great efforts have been made in recent years to better understand the properties of the atmospheric effects and to develop methods for mitigating the effects. This paper provides a systematic review of the work carried out in this area. The basic principles of atmospheric effects on repeat-pass InSAR are first introduced. The studies on the properties of the atmospheric effects, including the magnitudes of the effects determined in the various parts of the world, the spectra of the atmospheric effects, the isotropic properties and the statistical distributions of the effects, are then discussed. The various methods developed for mitigating the atmospheric effects are then reviewed, including the methods that are based on PSInSAR processing, the methods that are based on interferogram modeling, and those that are based on external data such as GPS observations, ground meteorological data, and satellite data including those from the MODIS and MERIS. Two examples that use MODIS and MERIS data respectively to calibrate atmospheric effects on InSAR are also given.

Application of a Dense Gas Technique for Sterilizing Soft Biomaterials

PubMed Central

Karajanagi, Sandeep S.; Yoganathan, Roshan; Mammucari, Raffaella; Park, Hyoungshin; Cox, Julian; Zeitels, Steven M.; Langer, Robert; Foster, Neil R.

2017-01-01

Sterilization of soft biomaterials such as hydrogels is challenging because existing methods such as gamma irradiation, steam sterilization, or ethylene oxide sterilization, while effective at achieving high sterility assurance levels (SAL), may compromise their physicochemical properties and biocompatibility. New methods that effectively sterilize soft biomaterials without compromising their properties are therefore required. In this report, a dense-carbon dioxide (CO2)-based technique was used to sterilize soft polyethylene glycol (PEG)-based hydrogels while retaining their structure and physicochemical properties. Conventional sterilization methods such as gamma irradiation and steam sterilization severely compromised the structure of the hydrogels. PEG hydrogels with high water content and low elastic shear modulus (a measure of stiffness) were deliberately inoculated with bacteria and spores and then subjected to dense CO2. The dense CO2-based methods effectively sterilized the hydrogels achieving a SAL of 10−7 without compromising the viscoelastic properties, pH, water-content, and structure of the gels. Furthermore, dense CO2-treated gels were biocompatible and non-toxic when implanted subcutaneously in ferrets. The application of novel dense CO2-based methods to sterilize soft biomaterials has implications in developing safe sterilization methods for soft biomedical implants such as dermal fillers and viscosupplements. PMID:21337339

Abstract: Inference and Interval Estimation for Indirect Effects With Latent Variable Models.

PubMed

Falk, Carl F; Biesanz, Jeremy C

2011-11-30

Models specifying indirect effects (or mediation) and structural equation modeling are both popular in the social sciences. Yet relatively little research has compared methods that test for indirect effects among latent variables and provided precise estimates of the effectiveness of different methods. This simulation study provides an extensive comparison of methods for constructing confidence intervals and for making inferences about indirect effects with latent variables. We compared the percentile (PC) bootstrap, bias-corrected (BC) bootstrap, bias-corrected accelerated (BC a ) bootstrap, likelihood-based confidence intervals (Neale & Miller, 1997), partial posterior predictive (Biesanz, Falk, and Savalei, 2010), and joint significance tests based on Wald tests or likelihood ratio tests. All models included three reflective latent variables representing the independent, dependent, and mediating variables. The design included the following fully crossed conditions: (a) sample size: 100, 200, and 500; (b) number of indicators per latent variable: 3 versus 5; (c) reliability per set of indicators: .7 versus .9; (d) and 16 different path combinations for the indirect effect (α = 0, .14, .39, or .59; and β = 0, .14, .39, or .59). Simulations were performed using a WestGrid cluster of 1680 3.06GHz Intel Xeon processors running R and OpenMx. Results based on 1,000 replications per cell and 2,000 resamples per bootstrap method indicated that the BC and BC a bootstrap methods have inflated Type I error rates. Likelihood-based confidence intervals and the PC bootstrap emerged as methods that adequately control Type I error and have good coverage rates.

Cellular Metabolomics for Exposure and Toxicity Assessment

EPA Science Inventory

We have developed NMR automation and cell quench methods for cell culture-based metabolomics to study chemical exposure and toxicity. Our flow automation method is robust and free of cross contamination. The direct cell quench method is rapid and effective. Cell culture-based met...

Tracking rural-to-urban migration in China: Lessons from the 2005 inter-census population survey.

PubMed

Ebenstein, Avraham; Zhao, Yaohui

2015-01-01

We examined migration in China using the 2005 inter-census population survey, in which migrants were registered at both their place of original (hukou) residence and at their destination. We find evidence that the estimated number of internal migrants in China is extremely sensitive to the enumeration method. We estimate that the traditional destination-based survey method fails to account for more than a third of migrants found using comparable origin-based methods. The 'missing' migrants are disproportionately young, male, and holders of rural hukou. We find that origin-based methods are more effective at capturing migrants who travel short distances for short periods, whereas destination-based methods are more effective when entire households have migrated and no remaining family members are located at the hukou location. We conclude with a set of policy recommendations for the design of population surveys in countries with large migrant populations.

n-Gram-Based Indexing for Korean Text Retrieval.

ERIC Educational Resources Information Center

Lee, Joon Ho; Cho, Hyun Yang; Park, Hyouk Ro

1999-01-01

Discusses indexing methods in Korean text retrieval and proposes a new indexing method based on n-grams which can handle compound nouns effectively without dictionaries and complex linguistic knowledge. Experimental results show that n-gram-based indexing is considerably faster than morpheme-based indexing, and also provides better retrieval…

Unit asking: a method to boost donations and beyond.

PubMed

Hsee, Christopher K; Zhang, Jiao; Lu, Zoe Y; Xu, Fei

2013-09-01

The solicitation of charitable donations costs billions of dollars annually. Here, we introduce a virtually costless method for boosting charitable donations to a group of needy persons: merely asking donors to indicate a hypothetical amount for helping one of the needy persons before asking donors to decide how much to donate for all of the needy persons. We demonstrated, in both real fund-raisers and scenario-based research, that this simple unit-asking method greatly increases donations for the group of needy persons. Different from phenomena such as the foot-in-the-door and identifiable-victim effects, the unit-asking effect arises because donors are initially scope insensitive and subsequently scope consistent. The method applies to both traditional paper-based fund-raisers and increasingly popular Web-based fund-raisers and has implications for domains other than fund-raisers, such as auctions and budget proposals. Our research suggests that a subtle manipulation based on psychological science can generate a substantial effect in real life.

An orientation measurement method based on Hall-effect sensors for permanent magnet spherical actuators with 3D magnet array.

PubMed

Yan, Liang; Zhu, Bo; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-10-24

An orientation measurement method based on Hall-effect sensors is proposed for permanent magnet (PM) spherical actuators with three-dimensional (3D) magnet array. As there is no contact between the measurement system and the rotor, this method could effectively avoid friction torque and additional inertial moment existing in conventional approaches. Curved surface fitting method based on exponential approximation is proposed to formulate the magnetic field distribution in 3D space. The comparison with conventional modeling method shows that it helps to improve the model accuracy. The Hall-effect sensors are distributed around the rotor with PM poles to detect the flux density at different points, and thus the rotor orientation can be computed from the measured results and analytical models. Experiments have been conducted on the developed research prototype of the spherical actuator to validate the accuracy of the analytical equations relating the rotor orientation and the value of magnetic flux density. The experimental results show that the proposed method can measure the rotor orientation precisely, and the measurement accuracy could be improved by the novel 3D magnet array. The study result could be used for real-time motion control of PM spherical actuators.

Likelihood-Based Random-Effect Meta-Analysis of Binary Events.

PubMed

Amatya, Anup; Bhaumik, Dulal K; Normand, Sharon-Lise; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D

2015-01-01

Meta-analysis has been used extensively for evaluation of efficacy and safety of medical interventions. Its advantages and utilities are well known. However, recent studies have raised questions about the accuracy of the commonly used moment-based meta-analytic methods in general and for rare binary outcomes in particular. The issue is further complicated for studies with heterogeneous effect sizes. Likelihood-based mixed-effects modeling provides an alternative to moment-based methods such as inverse-variance weighted fixed- and random-effects estimators. In this article, we compare and contrast different mixed-effect modeling strategies in the context of meta-analysis. Their performance in estimation and testing of overall effect and heterogeneity are evaluated when combining results from studies with a binary outcome. Models that allow heterogeneity in both baseline rate and treatment effect across studies have low type I and type II error rates, and their estimates are the least biased among the models considered.

Base Pressure at Supersonic Speeds on Two-dimensional Airfoils and on Bodies of Revolution with and Without Fins Having Turbulent Boundary Layers

NASA Technical Reports Server (NTRS)

LOVE EUGENE S

1957-01-01

An analysis has been made of available experimental data to show the effects of most of the variables that are more predominant in determining base pressure at supersonic speeds. The analysis covers base pressures for two-dimensional airfoils and for bodies of revolution with and without stabilizing fins and is restricted to turbulent boundary layers. The present status of available experimental information is summarized as are the existing methods for predicting base pressure. A simple semiempirical method is presented for estimating base pressure. For two-dimensional bases, this method stems from an analogy established between the base-pressure phenomena and the peak pressure rise associated with the separation of the boundary layer. An analysis made for axially symmetric flow indicates that the base pressure for bodies of revolution is subject to the same analogy. Based upon the methods presented, estimations are made of such effects as Mach number, angle of attack, boattailing, fineness ratio, and fins. These estimations give fair predictions of experimental results. (author)

Survival analysis using inverse probability of treatment weighted methods based on the generalized propensity score.

PubMed

Sugihara, Masahiro

2010-01-01

In survival analysis, treatment effects are commonly evaluated based on survival curves and hazard ratios as causal treatment effects. In observational studies, these estimates may be biased due to confounding factors. The inverse probability of treatment weighted (IPTW) method based on the propensity score is one of the approaches utilized to adjust for confounding factors between binary treatment groups. As a generalization of this methodology, we developed an exact formula for an IPTW log-rank test based on the generalized propensity score for survival data. This makes it possible to compare the group differences of IPTW Kaplan-Meier estimators of survival curves using an IPTW log-rank test for multi-valued treatments. As causal treatment effects, the hazard ratio can be estimated using the IPTW approach. If the treatments correspond to ordered levels of a treatment, the proposed method can be easily extended to the analysis of treatment effect patterns with contrast statistics. In this paper, the proposed method is illustrated with data from the Kyushu Lipid Intervention Study (KLIS), which investigated the primary preventive effects of pravastatin on coronary heart disease (CHD). The results of the proposed method suggested that pravastatin treatment reduces the risk of CHD and that compliance to pravastatin treatment is important for the prevention of CHD. (c) 2009 John Wiley & Sons, Ltd.

Modeling of heat flow and effective thermal conductivity of fractured media: Analytical and numerical methods

NASA Astrophysics Data System (ADS)

Nguyen, S. T.; Vu, M.-H.; Vu, M. N.; Tang, A. M.

2017-05-01

The present work aims to modeling the thermal conductivity of fractured materials using homogenization-based analytical and pattern-based numerical methods. These materials are considered as a network of cracks distributed inside a solid matrix. Heat flow through such media is perturbed by the crack system. The problem of heat flow across a single crack is firstly investigated. The classical Eshelby's solution, extended to the thermal conduction problem of an ellipsoidal inclusion embedding in an infinite homogeneous matrix, gives an analytical solution of temperature discontinuity across a non-conducting penny-shaped crack. This solution is then validated by the numerical simulation based on the finite elements method. The numerical simulation allows analyzing the effect of crack conductivity. The problem of a single crack is then extended to a medium containing multiple cracks. Analytical estimations for effective thermal conductivity, that take into account the interaction between cracks and their spatial distribution, are developed for the case of non-conducting cracks. Pattern-based numerical method is then employed for both cases non-conducting and conducting cracks. In the case of non-conducting cracks, numerical and analytical methods, both account for the spatial distribution of the cracks, fit perfectly. In the case of conducting cracks, the numerical analyzing of crack conductivity effect shows that highly conducting cracks weakly affect heat flow and the effective thermal conductivity of fractured media.

The Effects of Jigsaw Technique Based on Cooperative Learning on Prospective Science Teachers' Science Process Skill

ERIC Educational Resources Information Center

Karacop, Ataman; Diken, Emine Hatun

2017-01-01

The purpose of this study is to investigate the effects of laboratory approach based on jigsaw method with cooperative learning and confirmatory laboratory approach on university students' cognitive process development in Science teaching laboratory applications, and to determine the opinions of the students on applied laboratory methods. The…

Project-Based Method as an Effective Means of Interdisciplinary Interaction While Teaching a Foreign Language

ERIC Educational Resources Information Center

Bondar, Irina Alekseevna; Kulbakova, Renata Ivanovna; Svintorzhitskaja, Irina Andreevna; Pilat, Larisa Pavlovna; Zavrumov, Zaur Aslanovich

2016-01-01

The article explains how to use a project-based method as an effective means of interdisciplinary interaction when teaching a foreign language on the example of The Institute of service, tourism and design (branch) of the North Caucasus Federal University (Pyatigorsk, Stavropol Territory Russia). The article holds the main objectives of the…

Internet-Based Distance Learning in Higher Education.

ERIC Educational Resources Information Center

Hofmann, Donald W.

2002-01-01

Suggests that the effectiveness of Internet-based distance learning has increased with its increased popularity. Looks at the differences between the effectiveness of Internet-based distance learning and traditional methods. Indicates that distance learning is more effective because of the necessity for students to become active learners.…

Assessment of spatial discordance of primary and effective seed dispersal of European beech (Fagus sylvatica L.) by ecological and genetic methods.

PubMed

Millerón, M; López de Heredia, U; Lorenzo, Z; Alonso, J; Dounavi, A; Gil, L; Nanos, N

2013-03-01

Spatial discordance between primary and effective dispersal in plant populations indicates that postdispersal processes erase the seed rain signal in recruitment patterns. Five different models were used to test the spatial concordance of the primary and effective dispersal patterns in a European beech (Fagus sylvatica) population from central Spain. An ecological method was based on classical inverse modelling (SSS), using the number of seed/seedlings as input data. Genetic models were based on direct kernel fitting of mother-to-offspring distances estimated by a parentage analysis or were spatially explicit models based on the genotype frequencies of offspring (competing sources model and Moran-Clark's Model). A fully integrated mixed model was based on inverse modelling, but used the number of genotypes as input data (gene shadow model). The potential sources of error and limitations of each seed dispersal estimation method are discussed. The mean dispersal distances for seeds and saplings estimated with these five methods were higher than those obtained by previous estimations for European beech forests. All the methods show strong discordance between primary and effective dispersal kernel parameters, and for dispersal directionality. While seed rain was released mostly under the canopy, saplings were established far from mother trees. This discordant pattern may be the result of the action of secondary dispersal by animals or density-dependent effects; that is, the Janzen-Connell effect. © 2013 Blackwell Publishing Ltd.

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion

PubMed Central

Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

2016-01-01

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13. Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract PMID:27504009

Image dehazing based on non-local saturation

NASA Astrophysics Data System (ADS)

Wang, Linlin; Zhang, Qian; Yang, Deyun; Hou, Yingkun; He, Xiaoting

2018-04-01

In this paper, a method based on non-local saturation algorithm is proposed to avoid block and halo effect for single image dehazing with dark channel prior. First we convert original image from RGB color space into HSV color space with the idea of non-local method. Image saturation is weighted equally by the size of fixed window according to image resolution. Second we utilize the saturation to estimate the atmospheric light value and transmission rate. Then through the function of saturation and transmission, the haze-free image is obtained based on the atmospheric scattering model. Comparing the results of existing methods, our method can restore image color and enhance contrast. We guarantee the proposed method with quantitative and qualitative evaluation respectively. Experiments show the better visual effect with high efficiency.

Evaluation of Alternative Altitude Scaling Methods for Thermal Ice Protection System in NASA Icing Research Tunnel

NASA Technical Reports Server (NTRS)

Lee, Sam; Addy, Harold; Broeren, Andy P.; Orchard, David M.

2017-01-01

A test was conducted at NASA Icing Research Tunnel to evaluate altitude scaling methods for thermal ice protection system. Two scaling methods based on Weber number were compared against a method based on the Reynolds number. The results generally agreed with the previous set of tests conducted in NRCC Altitude Icing Wind Tunnel. The Weber number based scaling methods resulted in smaller runback ice mass than the Reynolds number based scaling method. The ice accretions from the Weber number based scaling method also formed farther upstream. However there were large differences in the accreted ice mass between the two Weber number based scaling methods. The difference became greater when the speed was increased. This indicated that there may be some Reynolds number effects that isnt fully accounted for and warrants further study.

The effect of using genealogy-based haplotypes for genomic prediction.

PubMed

Edriss, Vahid; Fernando, Rohan L; Su, Guosheng; Lund, Mogens S; Guldbrandtsen, Bernt

2013-03-06

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.

Use of focused ultrasonication in activity-based profiling of deubiquitinating enzymes in tissue.

PubMed

Nanduri, Bindu; Shack, Leslie A; Rai, Aswathy N; Epperson, William B; Baumgartner, Wes; Schmidt, Ty B; Edelmann, Mariola J

2016-12-15

To develop a reproducible tissue lysis method that retains enzyme function for activity-based protein profiling, we compared four different methods to obtain protein extracts from bovine lung tissue: focused ultrasonication, standard sonication, mortar & pestle method, and homogenization combined with standard sonication. Focused ultrasonication and mortar & pestle methods were sufficiently effective for activity-based profiling of deubiquitinases in tissue, and focused ultrasonication also had the fastest processing time. We used focused-ultrasonicator for subsequent activity-based proteomic analysis of deubiquitinases to test the compatibility of this method in sample preparation for activity-based chemical proteomics. Copyright © 2016 Elsevier Inc. All rights reserved.

Effectiveness of Jigsaw learning compared to lecture-based learning in dental education.

PubMed

Sagsoz, O; Karatas, O; Turel, V; Yildiz, M; Kaya, E

2017-02-01

The objective of this study was to evaluate the success levels of students using the Jigsaw learning method in dental education. Fifty students with similar grade point average (GPA) scores were selected and randomly assigned into one of two groups (n = 25). A pretest concerning 'adhesion and bonding agents in dentistry' was administered to all students before classes. The Jigsaw learning method was applied to the experimental group for 3 weeks. At the same time, the control group was taking classes using the lecture-based learning method. At the end of the 3 weeks, all students were retested (post-test) on the subject. A retention test was administered 3 weeks after the post-test. Mean scores were calculated for each test for the experimental and control groups, and the data obtained were analysed using the independent samples t-test. No significant difference was determined between the Jigsaw and lecture-based methods at pretest or post-test. The highest mean test score was observed in the post-test with the Jigsaw method. In the retention test, success with the Jigsaw method was significantly higher than that with the lecture-based method. The Jigsaw method is as effective as the lecture-based method. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Single underwater image enhancement based on color cast removal and visibility restoration

NASA Astrophysics Data System (ADS)

Li, Chongyi; Guo, Jichang; Wang, Bo; Cong, Runmin; Zhang, Yan; Wang, Jian

2016-05-01

Images taken under underwater condition usually have color cast and serious loss of contrast and visibility. Degraded underwater images are inconvenient for observation and analysis. In order to address these problems, an underwater image-enhancement method is proposed. A simple yet effective underwater image color cast removal algorithm is first presented based on the optimization theory. Then, based on the minimum information loss principle and inherent relationship of medium transmission maps of three color channels in an underwater image, an effective visibility restoration algorithm is proposed to recover visibility, contrast, and natural appearance of degraded underwater images. To evaluate the performance of the proposed method, qualitative comparison, quantitative comparison, and color accuracy test are conducted. Experimental results demonstrate that the proposed method can effectively remove color cast, improve contrast and visibility, and recover natural appearance of degraded underwater images. Additionally, the proposed method is comparable to and even better than several state-of-the-art methods.

Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Formalizing the role of agent-based modeling in causal inference and epidemiology.

PubMed

Marshall, Brandon D L; Galea, Sandro

2015-01-15

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluating the effectiveness of Behavior-Based Safety education methods for commercial vehicle drivers.

PubMed

Wang, Xuesong; Xing, Yilun; Luo, Lian; Yu, Rongjie

2018-08-01

Risky driving behavior is one of the main causes of commercial vehicle related crashes. In order to achieve safer vehicle operation, safety education for drivers is often provided. However, the education programs vary in quality and may not always be successful in reducing crash rates. Behavior-Based Safety (BBS) education is a popular approach found effective by numerous studies, but even this approach varies as to the combination of frequency, mode and content used by different education providers. This study therefore evaluates and compares the effectiveness of BBS education methods. Thirty-five drivers in Shanghai, China, were coached with one of three different BBS education methods for 13 weeks following a 13-week baseline phase with no education. A random-effects negative binomial (NB) model was built and calibrated to investigate the relationship between BBS education and the driver at-fault safety-related event rate. Based on the results of the random-effects NB model, event modification factors (EMF) were calculated to evaluate and compare the effectiveness of the methods. Results show that (1) BBS education was confirmed to be effective in safety-related event reduction; (2) the most effective method among the three applied monthly face-to-face coaching, including feedback with video and statistical data, and training on strategies to avoid driver-specific unsafe behaviors; (3) weekly telephone coaching using statistics and strategies was rated by drivers as the most convenient delivery mode, and was also significantly effective. Copyright © 2018 Elsevier Ltd. All rights reserved.

On the estimation of jet-induced fountain lift and additional suckdown in hover for two-jet configurations

NASA Technical Reports Server (NTRS)

Kuhn, Richard E.; Bellavia, David C.; Corsiglia, Victor R.; Wardwell, Douglas A.

1991-01-01

Currently available methods for estimating the net suckdown induced on jet V/STOL aircraft hovering in ground effect are based on a correlation of available force data and are, therefore, limited to configurations similar to those in the data base. Experience with some of these configurations has shown that both the fountain lift and additional suckdown are overestimated but these effects cancel each other for configurations within the data base. For other configurations, these effects may not cancel and the net suckdown could be grossly overestimated or underestimated. Also, present methods do not include the prediction of the pitching moments associated with the suckdown induced in ground effect. An attempt to develop a more logically based method for estimating the fountain lift and suckdown based on the jet-induced pressures is initiated. The analysis is based primarily on the data from a related family of three two-jet configurations (all using the same jet spacing) and limited data from two other two-jet configurations. The current status of the method, which includes expressions for estimating the maximum pressure induced in the fountain regions, and the sizes of the fountain and suckdown regions is presented. Correlating factors are developed to be used with these areas and pressures to estimate the fountain lift, the suckdown, and the related pitching moment increments.

Dynamic updating atlas for heart segmentation with a nonlinear field-based model.

PubMed

Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng

2017-09-01

Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.

IT: An Effective Pedagogic Tool in the Teaching of Quantitative Methods in Management.

ERIC Educational Resources Information Center

Nadkami, Sanjay M.

1998-01-01

Examines the possibility of supplementing conventional pedagogic methods with information technology-based teaching aids in the instruction of quantitative methods to undergraduate students. Considers the case for a problem-based learning approach, and discusses the role of information technology. (Author/LRW)

Words, concepts, or both: optimal indexing units for automated information retrieval.

PubMed Central

Hersh, W. R.; Hickam, D. H.; Leone, T. J.

1992-01-01

What is the best way to represent the content of documents in an information retrieval system? This study compares the retrieval effectiveness of five different methods for automated (machine-assigned) indexing using three test collections. The consistently best methods are those that use indexing based on the words that occur in the available text of each document. Methods used to map text into concepts from a controlled vocabulary showed no advantage over the word-based methods. This study also looked at an approach to relevance feedback which showed benefit for both word-based and concept-based methods. PMID:1482951

Practice and effectiveness of web-based problem-based learning approach in a large class-size system: A comparative study.

PubMed

Ding, Yongxia; Zhang, Peili

2018-06-12

Problem-based learning (PBL) is an effective and highly efficient teaching approach that is extensively applied in education systems across a variety of countries. This study aimed to investigate the effectiveness of web-based PBL teaching pedagogies in large classes. The cluster sampling method was used to separate two college-level nursing student classes (graduating class of 2013) into two groups. The experimental group (n = 162) was taught using a web-based PBL teaching approach, while the control group (n = 166) was taught using conventional teaching methods. We subsequently assessed the satisfaction of the experimental group in relation to the web-based PBL teaching mode. This assessment was performed following comparison of teaching activity outcomes pertaining to exams and self-learning capacity between the two groups. When compared with the control group, the examination scores and self-learning capabilities were significantly higher in the experimental group (P < 0.01) compared with the control group. In addition, 92.6% of students in the experimental group expressed satisfaction with the new web-based PBL teaching approach. In a large class-size teaching environment, the web-based PBL teaching approach appears to be more optimal than traditional teaching methods. These results demonstrate the effectiveness of web-based teaching technologies in problem-based learning. Copyright © 2018. Published by Elsevier Ltd.

Dereverberation and denoising based on generalized spectral subtraction by multi-channel LMS algorithm using a small-scale microphone array

NASA Astrophysics Data System (ADS)

Wang, Longbiao; Odani, Kyohei; Kai, Atsuhiko

2012-12-01

A blind dereverberation method based on power spectral subtraction (SS) using a multi-channel least mean squares algorithm was previously proposed to suppress the reverberant speech without additive noise. The results of isolated word speech recognition experiments showed that this method achieved significant improvements over conventional cepstral mean normalization (CMN) in a reverberant environment. In this paper, we propose a blind dereverberation method based on generalized spectral subtraction (GSS), which has been shown to be effective for noise reduction, instead of power SS. Furthermore, we extend the missing feature theory (MFT), which was initially proposed to enhance the robustness of additive noise, to dereverberation. A one-stage dereverberation and denoising method based on GSS is presented to simultaneously suppress both the additive noise and nonstationary multiplicative noise (reverberation). The proposed dereverberation method based on GSS with MFT is evaluated on a large vocabulary continuous speech recognition task. When the additive noise was absent, the dereverberation method based on GSS with MFT using only 2 microphones achieves a relative word error reduction rate of 11.4 and 32.6% compared to the dereverberation method based on power SS and the conventional CMN, respectively. For the reverberant and noisy speech, the dereverberation and denoising method based on GSS achieves a relative word error reduction rate of 12.8% compared to the conventional CMN with GSS-based additive noise reduction method. We also analyze the effective factors of the compensation parameter estimation for the dereverberation method based on SS, such as the number of channels (the number of microphones), the length of reverberation to be suppressed, and the length of the utterance used for parameter estimation. The experimental results showed that the SS-based method is robust in a variety of reverberant environments for both isolated and continuous speech recognition and under various parameter estimation conditions.

Three Methods of Estimating a Model of Group Effects: A Comparison with Reference to School Effect Studies.

ERIC Educational Resources Information Center

Igra, Amnon

1980-01-01

Three methods of estimating a model of school effects are compared: ordinary least squares; an approach based on the analysis of covariance; and, a residualized input-output approach. Results are presented using a matrix algebra formulation, and advantages of the first two methods are considered. (Author/GK)

Evaluating the Good Ontology Design Guideline (GoodOD) with the Ontology Quality Requirements and Evaluation Method and Metrics (OQuaRE)

PubMed Central

Duque-Ramos, Astrid; Boeker, Martin; Jansen, Ludger; Schulz, Stefan; Iniesta, Miguela; Fernández-Breis, Jesualdo Tomás

2014-01-01

Objective To (1) evaluate the GoodOD guideline for ontology development by applying the OQuaRE evaluation method and metrics to the ontology artefacts that were produced by students in a randomized controlled trial, and (2) informally compare the OQuaRE evaluation method with gold standard and competency questions based evaluation methods, respectively. Background In the last decades many methods for ontology construction and ontology evaluation have been proposed. However, none of them has become a standard and there is no empirical evidence of comparative evaluation of such methods. This paper brings together GoodOD and OQuaRE. GoodOD is a guideline for developing robust ontologies. It was previously evaluated in a randomized controlled trial employing metrics based on gold standard ontologies and competency questions as outcome parameters. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies and has been successfully used for evaluating the quality of ontologies. Methods In this paper, we evaluate the effect of training in ontology construction based on the GoodOD guideline within the OQuaRE quality evaluation framework and compare the results with those obtained for the previous studies based on the same data. Results Our results show a significant effect of the GoodOD training over developed ontologies by topics: (a) a highly significant effect was detected in three topics from the analysis of the ontologies of untrained and trained students; (b) both positive and negative training effects with respect to the gold standard were found for five topics. Conclusion The GoodOD guideline had a significant effect over the quality of the ontologies developed. Our results show that GoodOD ontologies can be effectively evaluated using OQuaRE and that OQuaRE is able to provide additional useful information about the quality of the GoodOD ontologies. PMID:25148262

A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation

NASA Astrophysics Data System (ADS)

Zhou, Xiran; Liu, Jun; Liu, Shuguang; Cao, Lei; Zhou, Qiming; Huang, Huawen

2014-02-01

High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity-hue-saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.

Estimation of effective refractive index of birefringent particles using a combination of the immersion liquid method and light scattering.

PubMed

Niskanen, Ilpo; Räty, Jukka; Peiponen, Kai-Erik

2008-04-01

A method to detect the effective refractive index and concentration of birefringent pigments is suggested. The method is based on the utilization of the immersion liquid method and a multifunction spectrophotometer for the measurement of back scattered light. The method has applications in the measurement of the effective refractive index of pigments that are used, e.g., in the paper industry to improve the opacity of paper products.

Exploring the Effects of Online Team-Based Learning and Co-Regulated Learning on Students' Development of Computing Skills

ERIC Educational Resources Information Center

Tsai, Chia-Wen

2016-01-01

As more and more educational institutions are providing online courses, it is necessary to design effective teaching methods integrated with technologies to benefit both teachers and students. The researcher in this study designed innovative online teaching methods of team-based learning (TBL) and co-regulated learning (CRL) to improve students'…

Comparison of "E-Rater"[R] Automated Essay Scoring Model Calibration Methods Based on Distributional Targets

ERIC Educational Resources Information Center

Zhang, Mo; Williamson, David M.; Breyer, F. Jay; Trapani, Catherine

2012-01-01

This article describes two separate, related studies that provide insight into the effectiveness of "e-rater" score calibration methods based on different distributional targets. In the first study, we developed and evaluated a new type of "e-rater" scoring model that was cost-effective and applicable under conditions of absent human rating and…

Introduction and Evaluation of Case-Based Learning in the First Foundational Course of an Undergraduate Medical Curriculum

ERIC Educational Resources Information Center

Fortun, Jenny; Morales, Ana Cecilia; Tempest, Helen Ghislaine

2017-01-01

Case-based learning (CBL) has been proposed as an effective method to promote student knowledge and motivation. The timing and methods for implementation have varied among schools, and data regarding the effectiveness of this pedagogy compared to other learning modalities are inconclusive. We introduced five different cases in the first course of…

Estimation of Standard Error of Regression Effects in Latent Regression Models Using Binder's Linearization. Research Report. ETS RR-07-09

ERIC Educational Resources Information Center

Li, Deping; Oranje, Andreas

2007-01-01

Two versions of a general method for approximating standard error of regression effect estimates within an IRT-based latent regression model are compared. The general method is based on Binder's (1983) approach, accounting for complex samples and finite populations by Taylor series linearization. In contrast, the current National Assessment of…

Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization

PubMed Central

Chiu, Chung-Cheng; Ting, Chih-Chung

2016-01-01

Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE) is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE) is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA), which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods. PMID:27338412

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

NASA Astrophysics Data System (ADS)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.

Effect of Surveillance Method on Reported Characteristics of Lyme Disease, Connecticut, 1996–2007

PubMed Central

Nelson, Randall S.; Cartter, Matthew L.

2012-01-01

To determine the effect of changing public health surveillance methods on the reported epidemiology of Lyme disease, we analyzed Connecticut data for 1996–2007. Data were stratified by 4 surveillance methods and compared. A total of 87,174 reports were received that included 79,896 potential cases. Variations based on surveillance methods were seen. Cases reported through physician-based surveillance were significantly more likely to be classified as confirmed; such case-patients were significantly more likely to have symptoms of erythema migrans only and to have illness onset during summer months. Case-patients reported through laboratory-based surveillance were significantly more likely to have late manifestations only and to be older. Use of multiple surveillance methods provided a more complete clinical and demographic description of cases but lacked efficiency. When interpreting data, changes in surveillance method must be considered. PMID:22304873

The effectiveness of module based on guided inquiry method to improve students’ logical thinking ability

NASA Astrophysics Data System (ADS)

Ash-Shiddieqy, M. H.; Suparmi, A.; Sunarno, W.

2018-04-01

The purpose of this research is to understand the effectiveness of module based on guided inquiry method to improve students’ logical thinking ability. This research only evaluate the students’ logical ability after follows the learning activities that used developed physics module based on guided inquiry method. After the learning activities, students This research method uses a test instrument that adapts TOLT instrument. There are samples of 68 students of grade XI taken from SMA Negeri 4 Surakarta.Based on the results of the research can be seen that in the experimental class and control class, the posttest value aspect of probabilistic reasoning has the highest value than other aspects, whereas the posttest value of the proportional reasoning aspect has the lowest value. The average value of N-gain in the experimental class is 0.39, while in the control class is 0.30. Nevertheless, the N-gain values obtained in the experimental class are larger than the control class, so the guided inquiry-based module is considered more effective for improving students’ logical thinking. Based on the data obtained from the research shows the modules available to help teachers and students in learning activities. The developed Physics module is integrated with every syntax present in guided inquiry method, so it can be used to improve students’ logical thinking ability.

Cervical motion assessment using virtual reality.

PubMed

Sarig-Bahat, Hilla; Weiss, Patrice L; Laufer, Yocheved

2009-05-01

Repeated measures of cervical motion in asymptomatic subjects. To introduce a virtual reality (VR)-based assessment of cervical range of motion (ROM); to establish inter and intratester reliability of the VR-based assessment in comparison with conventional assessment in asymptomatic individuals; and to evaluate the effect of a single VR session on cervical ROM. Cervical ROM and clinical issues related to neck pain is frequently studied. A wide variety of methods is available for evaluation of cervical motion. To date, most methods rely on voluntary responses to an assessor's instructions. However, in day-to-day life, head movement is generally an involuntary response to multiple stimuli. Therefore, there is a need for a more functional assessment method, using sensory stimuli to elicit spontaneous neck motion. VR attributes may provide a methodology for achieving this goal. A novel method was developed for cervical motion assessment utilizing an electromagnetic tracking system and a VR game scenario displayed via a head mounted device. Thirty asymptomatic participants were assessed by both conventional and VR-based methods. Inter and intratester repeatability analyses were performed. The effect of a single VR session on ROM was evaluated. Both assessments showed non-biased results between tests and between testers (P > 0.1). Full-cycle repeatability coefficients ranged between 15.0 degrees and 29.2 degrees with smaller values for rotation and for the VR assessment. A single VR session significantly increased ROM, with largest effect found in the rotation direction. Inter and intratester reliability was supported for both the VR-based and the conventional methods. Results suggest better repeatability for the VR method, with rotation being more precise than flexion/extension. A single VR session was found to be effective in increasing cervical motion, possibly due to its motivating effect.

A Hybrid Key Management Scheme for WSNs Based on PPBR and a Tree-Based Path Key Establishment Method

PubMed Central

Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei

2016-01-01

With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes. PMID:27070624

Evaluation of the repeatability and reproducibility of a suite of qPCR based microbial source tracking methods

EPA Science Inventory

Many PCR-based methods for microbial source tracking (MST) have been developed and validated within individual research laboratories. Inter-laboratory validation of these methods, however, has been minimal, and the effects of protocol standardization regimes have not been thor...

Delta Clipper-Experimental In-Ground Effect on Base-Heating Environment

NASA Technical Reports Server (NTRS)

Wang, Ten-See

1998-01-01

A quasitransient in-ground effect method is developed to study the effect of vertical landing on a launch vehicle base-heating environment. This computational methodology is based on a three-dimensional, pressure-based, viscous flow, chemically reacting, computational fluid dynamics formulation. Important in-ground base-flow physics such as the fountain-jet formation, plume growth, air entrainment, and plume afterburning are captured with the present methodology. Convective and radiative base-heat fluxes are computed for comparison with those of a flight test. The influence of the laminar Prandtl number on the convective heat flux is included in this study. A radiative direction-dependency test is conducted using both the discrete ordinate and finite volume methods. Treatment of the plume afterburning is found to be very important for accurate prediction of the base-heat fluxes. Convective and radiative base-heat fluxes predicted by the model using a finite rate chemistry option compared reasonably well with flight-test data.

A Real-Time Thermal Self-Elimination Method for Static Mode Operated Freestanding Piezoresistive Microcantilever-Based Biosensors.

PubMed

Ku, Yu-Fu; Huang, Long-Sun; Yen, Yi-Kuang

2018-02-28

Here, we provide a method and apparatus for real-time compensation of the thermal effect of single free-standing piezoresistive microcantilever-based biosensors. The sensor chip contained an on-chip fixed piezoresistor that served as a temperature sensor, and a multilayer microcantilever with an embedded piezoresistor served as a biomolecular sensor. This method employed the calibrated relationship between the resistance and the temperature of piezoresistors to eliminate the thermal effect on the sensor, including the temperature coefficient of resistance (TCR) and bimorph effect. From experimental results, the method was verified to reduce the signal of thermal effect from 25.6 μV/°C to 0.3 μV/°C, which was approximately two orders of magnitude less than that before the processing of the thermal elimination method. Furthermore, the proposed approach and system successfully demonstrated its effective real-time thermal self-elimination on biomolecular detection without any thermostat device to control the environmental temperature. This method realizes the miniaturization of an overall measurement system of the sensor, which can be used to develop portable medical devices and microarray analysis platforms.

An adaptive block-based fusion method with LUE-SSIM for multi-focus images

NASA Astrophysics Data System (ADS)

Zheng, Jianing; Guo, Yongcai; Huang, Yukun

2016-09-01

Because of the lenses' limited depth of field, digital cameras are incapable of acquiring an all-in-focus image of objects at varying distances in a scene. Multi-focus image fusion technique can effectively solve this problem. Aiming at the block-based multi-focus image fusion methods, the problem that blocking-artifacts often occurs. An Adaptive block-based fusion method based on lifting undistorted-edge structural similarity (LUE-SSIM) is put forward. In this method, image quality metrics LUE-SSIM is firstly proposed, which utilizes the characteristics of human visual system (HVS) and structural similarity (SSIM) to make the metrics consistent with the human visual perception. Particle swarm optimization(PSO) algorithm which selects LUE-SSIM as the object function is used for optimizing the block size to construct the fused image. Experimental results on LIVE image database shows that LUE-SSIM outperform SSIM on Gaussian defocus blur images quality assessment. Besides, multi-focus image fusion experiment is carried out to verify our proposed image fusion method in terms of visual and quantitative evaluation. The results show that the proposed method performs better than some other block-based methods, especially in reducing the blocking-artifact of the fused image. And our method can effectively preserve the undistorted-edge details in focus region of the source images.

Comparison of Knowledge and Attitudes Using Computer-Based and Face-to-Face Personal Hygiene Training Methods in Food Processing Facilities

ERIC Educational Resources Information Center

Fenton, Ginger D.; LaBorde, Luke F.; Radhakrishna, Rama B.; Brown, J. Lynne; Cutter, Catherine N.

2006-01-01

Computer-based training is increasingly favored by food companies for training workers due to convenience, self-pacing ability, and ease of use. The objectives of this study were to determine if personal hygiene training, offered through a computer-based method, is as effective as a face-to-face method in knowledge acquisition and improved…

Examining the Effectiveness of Problem-Based Learning in the Teaching of Information Technology: A Comparison with Lectured-Based Learning

ERIC Educational Resources Information Center

Liu, YuFing

2013-01-01

This paper applies a quasi-experimental research method to compare the difference in students' approaches to learning and their learning achievements between the group that follows the problem based learning (PBL) teaching method with computer support and the group that follows the non-PBL teaching methods. The study sample consisted of 68 junior…

Viscous fingering and channeling in chemical enhanced oil recovery

NASA Astrophysics Data System (ADS)

Daripa, Prabir; Dutta, Sourav

2017-11-01

We have developed a hybrid numerical method based on discontinuous finite element method and modified method of characteristics to compute the multiphase multicomponent fluid flow in porous media in the context of chemical enhanced oil recovery. We use this method to study the effect of various chemical components on the viscous fingering and channeling in rectilinear and radial flow configurations. We will also discuss about the efficiency of various flooding schemes based on these understandings. Time permitting, we will discuss about the effect of variable injection rates in these practical setting. U.S. National Science Foundation Grant DMS-1522782.

Quantifying the interplay effect in prostate IMRT delivery using a convolution-based method.

PubMed

Li, Haisen S; Chetty, Indrin J; Solberg, Timothy D

2008-05-01

The authors present a segment-based convolution method to account for the interplay effect between intrafraction organ motion and the multileaf collimator position for each particular segment in intensity modulated radiation therapy (IMRT) delivered in a step-and-shoot manner. In this method, the static dose distribution attributed to each segment is convolved with the probability density function (PDF) of motion during delivery of the segment, whereas in the conventional convolution method ("average-based convolution"), the static dose distribution is convolved with the PDF averaged over an entire fraction, an entire treatment course, or even an entire patient population. In the case of IMRT delivered in a step-and-shoot manner, the average-based convolution method assumes that in each segment the target volume experiences the same motion pattern (PDF) as that of population. In the segment-based convolution method, the dose during each segment is calculated by convolving the static dose with the motion PDF specific to that segment, allowing both intrafraction motion and the interplay effect to be accounted for in the dose calculation. Intrafraction prostate motion data from a population of 35 patients tracked using the Calypso system (Calypso Medical Technologies, Inc., Seattle, WA) was used to generate motion PDFs. These were then convolved with dose distributions from clinical prostate IMRT plans. For a single segment with a small number of monitor units, the interplay effect introduced errors of up to 25.9% in the mean CTV dose compared against the planned dose evaluated by using the PDF of the entire fraction. In contrast, the interplay effect reduced the minimum CTV dose by 4.4%, and the CTV generalized equivalent uniform dose by 1.3%, in single fraction plans. For entire treatment courses delivered in either a hypofractionated (five fractions) or conventional (> 30 fractions) regimen, the discrepancy in total dose due to interplay effect was negligible.

Restoration of solar and star images with phase diversity-based blind deconvolution

NASA Astrophysics Data System (ADS)

Li, Qiang; Liao, Sheng; Wei, Honggang; Shen, Mangzuo

2007-04-01

The images recorded by a ground-based telescope are often degraded by atmospheric turbulence and the aberration of the optical system. Phase diversity-based blind deconvolution is an effective post-processing method that can be used to overcome the turbulence-induced degradation. The method uses an ensemble of short-exposure images obtained simultaneously from multiple cameras to jointly estimate the object and the wavefront distribution on pupil. Based on signal estimation theory and optimization theory, we derive the cost function and solve the large-scale optimization problem using a limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method. We apply the method to the turbulence-degraded images generated with computer, the solar images acquired with the swedish vacuum solar telescope (SVST, 0.475 m) in La Palma and the star images collected with 1.2-m telescope in Yunnan Observatory. In order to avoid edge effect in the restoration of the solar images, a modified Hanning apodized window is adopted. The star image still can be restored when the defocus distance is measured inaccurately. The restored results demonstrate that the method is efficient for removing the effect of turbulence and reconstructing the point-like or extended objects.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

Wavelength selection for portable noninvasive blood component measurement system based on spectral difference coefficient and dynamic spectrum

NASA Astrophysics Data System (ADS)

Feng, Ximeng; Li, Gang; Yu, Haixia; Wang, Shaohui; Yi, Xiaoqing; Lin, Ling

2018-03-01

Noninvasive blood component analysis by spectroscopy has been a hotspot in biomedical engineering in recent years. Dynamic spectrum provides an excellent idea for noninvasive blood component measurement, but studies have been limited to the application of broadband light sources and high-resolution spectroscopy instruments. In order to remove redundant information, a more effective wavelength selection method has been presented in this paper. In contrast to many common wavelength selection methods, this method is based on sensing mechanism which has a clear mechanism and can effectively avoid the noise from acquisition system. The spectral difference coefficient was theoretically proved to have a guiding significance for wavelength selection. After theoretical analysis, the multi-band spectral difference coefficient-wavelength selection method combining with the dynamic spectrum was proposed. An experimental analysis based on clinical trial data from 200 volunteers has been conducted to illustrate the effectiveness of this method. The extreme learning machine was used to develop the calibration models between the dynamic spectrum data and hemoglobin concentration. The experiment result shows that the prediction precision of hemoglobin concentration using multi-band spectral difference coefficient-wavelength selection method is higher compared with other methods.

Comparative evaluation of tensile bond strength of a polyvinyl acetate-based resilient liner following various denture base surface pre-treatment methods and immersion in artificial salivary medium: An in vitro study.

PubMed

Philip, Jacob M; Ganapathy, Dhanraj M; Ariga, Padma

2012-07-01

This study was formulated to evaluate and estimate the influence of various denture base resin surface pre-treatments (chemical and mechanical and combinations) upon tensile bond strength between a poly vinyl acetate-based denture liner and a denture base resin. A universal testing machine was used for determining the bond strength of the liner to surface pre-treated acrylic resin blocks. The data was analyzed by one-way analysis of variance and the t-test (α =.05). This study infers that denture base surface pre-treatment can improve the adhesive tensile bond strength between the liner and denture base specimens. The results of this study infer that chemical, mechanical, and mechano-chemical pre-treatments will have different effects on the bond strength of the acrylic soft resilient liner to the denture base. Among the various methods of pre-treatment of denture base resins, it was inferred that the mechano-chemical pre-treatment method with air-borne particle abrasion followed by monomer application exhibited superior bond strength than other methods with the resilient liner. Hence, this method could be effectively used to improve bond strength between liner and denture base and thus could minimize delamination of liner from the denture base during function.

Study on combat effectiveness of air defense missile weapon system based on queuing theory

NASA Astrophysics Data System (ADS)

Zhao, Z. Q.; Hao, J. X.; Li, L. J.

2017-01-01

Queuing Theory is a method to analyze the combat effectiveness of air defense missile weapon system. The model of service probability based on the queuing theory was constructed, and applied to analyzing the combat effectiveness of "Sidewinder" and "Tor-M1" air defense missile weapon system. Finally aimed at different targets densities, the combat effectiveness of different combat units of two types' defense missile weapon system is calculated. This method can be used to analyze the usefulness of air defense missile weapon system.

Design and fabrication of multimode interference couplers based on digital micro-mirror system

NASA Astrophysics Data System (ADS)

Wu, Sumei; He, Xingdao; Shen, Chenbo

2008-03-01

Multimode interference (MMI) couplers, based on the self-imaging effect (SIE), are accepted popularly in integrated optics. According to the importance of MMI devices, in this paper, we present a novel method to design and fabricate MMI couplers. A technology of maskless lithography to make MMI couplers based on a smart digital micro-mirror device (DMD) system is proposed. A 1×4 MMI device is designed as an example, which shows the present method is efficient and cost-effective.

Total Variation with Overlapping Group Sparsity for Image Deblurring under Impulse Noise

PubMed Central

Liu, Gang; Huang, Ting-Zhu; Liu, Jun; Lv, Xiao-Guang

2015-01-01

The total variation (TV) regularization method is an effective method for image deblurring in preserving edges. However, the TV based solutions usually have some staircase effects. In order to alleviate the staircase effects, we propose a new model for restoring blurred images under impulse noise. The model consists of an ℓ1-fidelity term and a TV with overlapping group sparsity (OGS) regularization term. Moreover, we impose a box constraint to the proposed model for getting more accurate solutions. The solving algorithm for our model is under the framework of the alternating direction method of multipliers (ADMM). We use an inner loop which is nested inside the majorization minimization (MM) iteration for the subproblem of the proposed method. Compared with other TV-based methods, numerical results illustrate that the proposed method can significantly improve the restoration quality, both in terms of peak signal-to-noise ratio (PSNR) and relative error (ReE). PMID:25874860

Comparison of Methods for Evaluating Urban Transportation Alternatives

DOT National Transportation Integrated Search

1975-02-01

The objective of the report was to compare five alternative methods for evaluating urban transportation improvement options: unaided judgmental evaluation cost-benefit analysis, cost-effectiveness analysis based on a single measure of effectiveness, ...

Developing an evidence-based Guide to Community Preventive Services--methods. The Task Force on Community Preventive Services.

PubMed

Briss, P A; Zaza, S; Pappaioanou, M; Fielding, J; Wright-De Agüero, L; Truman, B I; Hopkins, D P; Mullen, P D; Thompson, R S; Woolf, S H; Carande-Kulis, V G; Anderson, L; Hinman, A R; McQueen, D V; Teutsch, S M; Harris, J R

2000-01-01

Systematic reviews and evidence-based recommendations are increasingly important for decision making in health and medicine. Over the past 20 years, information on the science of synthesizing research results has exploded. However, some approaches to systematic reviews of the effectiveness of clinical preventive services and medical care may be less appropriate for evaluating population-based interventions. Furthermore, methods for linking evidence to recommendations are less well developed than methods for synthesizing evidence. The Guide to Community Preventive Services: Systematic Reviews and Evidence-Based Recommendations (the Guide) will evaluate and make recommendations on population-based and public health interventions. This paper provides an overview of the Guide's process to systematically review evidence and translate that evidence into recommendations. The Guide reviews evidence on effectiveness, the applicability of effectiveness data, (i.e., the extent to which available effectiveness data is thought to apply to additional populations and settings), the intervention's other effects (i.e., important side effects), economic impact, and barriers to implementation of interventions. The steps for obtaining and evaluating evidence into recommendations involve: (1) forming multidisciplinary chapter development teams, (2) developing a conceptual approach to organizing, grouping, selecting and evaluating the interventions in each chapter; (3) selecting interventions to be evaluated; (4) searching for and retrieving evidence; (5) assessing the quality of and summarizing the body of evidence of effectiveness; (6) translating the body of evidence of effectiveness into recommendations; (7) considering information on evidence other than effectiveness; and (8) identifying and summarizing research gaps. Systematic reviews of and evidence-based recommendations for population-health interventions are challenging and methods will continue to evolve. However, using an evidence-based approach to identify and recommend effective interventions directed at specific public health goals may reduce errors in how information is collected and interpreted, identify important gaps in current knowledge thus guiding further research, and enhance the Guide users' ability to assess whether recommendations are valid and prudent from their own perspectives. Over time, all of these advantages could help to increase agreement regarding appropriate community health strategies and help to increase their implementation.

High correlations between MRI brain volume measurements based on NeuroQuant® and FreeSurfer.

PubMed

Ross, David E; Ochs, Alfred L; Tate, David F; Tokac, Umit; Seabaugh, John; Abildskov, Tracy J; Bigler, Erin D

2018-05-30

NeuroQuant ® (NQ) and FreeSurfer (FS) are commonly used computer-automated programs for measuring MRI brain volume. Previously they were reported to have high intermethod reliabilities but often large intermethod effect size differences. We hypothesized that linear transformations could be used to reduce the large effect sizes. This study was an extension of our previously reported study. We performed NQ and FS brain volume measurements on 60 subjects (including normal controls, patients with traumatic brain injury, and patients with Alzheimer's disease). We used two statistical approaches in parallel to develop methods for transforming FS volumes into NQ volumes: traditional linear regression, and Bayesian linear regression. For both methods, we used regression analyses to develop linear transformations of the FS volumes to make them more similar to the NQ volumes. The FS-to-NQ transformations based on traditional linear regression resulted in effect sizes which were small to moderate. The transformations based on Bayesian linear regression resulted in all effect sizes being trivially small. To our knowledge, this is the first report describing a method for transforming FS to NQ data so as to achieve high reliability and low effect size differences. Machine learning methods like Bayesian regression may be more useful than traditional methods. Copyright © 2018 Elsevier B.V. All rights reserved.

Meta-Analysis of Rare Binary Adverse Event Data

PubMed Central

Bhaumik, Dulal K.; Amatya, Anup; Normand, Sharon-Lise; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D.

2013-01-01

We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse event data. Special attention is paid to the case of rare adverse events which are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We derive three new methods, simple (unweighted) average treatment effect estimator, a new heterogeneity estimator, and a parametric bootstrapping test for heterogeneity. We then study the statistical properties of both the traditional and new methods via simulation. We find that in general, moment-based estimators of combined treatment effects and heterogeneity are biased and the degree of bias is proportional to the rarity of the event under study. The new methods eliminate much, but not all of this bias. The various estimators and hypothesis testing methods are then compared and contrasted using an example dataset on treatment of stable coronary artery disease. PMID:23734068

Web-Based Instruction on Preservice Teachers' Knowledge of Fraction Operations

ERIC Educational Resources Information Center

Lin, Cheng-Yao

2010-01-01

This study determines whether web-based instruction (WBI) represents an improved method for helping preservice teachers learn procedural and conceptual knowledge of fractions.. The purpose was to compare the effectiveness of web-based instruction (WBI) with the traditional lecture in mathematics content and methods for the elementary school…

Effect of tensile mean stress on fatigue behavior of single-crystal and directionally solidified superalloys

NASA Technical Reports Server (NTRS)

Kalluri, Sreeramesh; Mcgaw, Michael A.

1992-01-01

Two nickel base superalloys, single crystal PWA 1480 and directionally solidified MAR-M 246 + Hf, were studied in view of the potential usage of the former and usage of the latter as blade materials for the turbomachinery of the Space Shuttle main engine. The baseline zero mean stress (ZMS) fatigue life (FL) behavior of these superalloys was established, and then the effect of tensile mean stress (TMS) on their FL behavior was characterized. A stress range based FL prediction approach was used to characterize both the ZMS and TMS fatigue data. In the past, several researchers have developed methods to account for the detrimental effect of tensile mean stress on the FL for polycrystalline engineering alloys. These methods were applied to characterize the TMS fatigue data of single crystal PWA 1480 and directionally solidified MAR-M 246 + Hf and were found to be unsatisfactory. Therefore, a method of accounting for the TMS effect on FL, that is based on a technique proposed by Heidmann and Manson was developed to characterize the TMS fatigue data of these superalloys. Details of this method and its relationship to the conventionally used mean stress methods in FL prediction are discussed.

DRAINWAT--Based Methods For Estimating Nitrogen Transport in Poorly Drained Watersheds

Treesearch

Devendra M. Amatya; George M. Chescheir; Glenn P. Fernandez; R. Wayne Skaggs; J.W. Gilliam

2004-01-01

Methods are needed to quantify effects of land use and management practices on nutrient and sediment loads at the watershed scale. Two methods were used to apply a DRAINMOD-based watershed-scale model (DRAINWAT) to estimate total nitrogen (N) transport from a poorly drained, forested watershed. In both methods, in-stream retention or losses of N were calculated with a...

Comparison of Standard Culture-Based Method to Culture-Independent Method for Evaluation of Hygiene Effects on the Hand Microbiome.

PubMed

Zapka, C; Leff, J; Henley, J; Tittl, J; De Nardo, E; Butler, M; Griggs, R; Fierer, N; Edmonds-Wilson, S

2017-03-28

Hands play a critical role in the transmission of microbiota on one's own body, between individuals, and on environmental surfaces. Effectively measuring the composition of the hand microbiome is important to hand hygiene science, which has implications for human health. Hand hygiene products are evaluated using standard culture-based methods, but standard test methods for culture-independent microbiome characterization are lacking. We sampled the hands of 50 participants using swab-based and glove-based methods prior to and following four hand hygiene treatments (using a nonantimicrobial hand wash, alcohol-based hand sanitizer [ABHS], a 70% ethanol solution, or tap water). We compared results among culture plate counts, 16S rRNA gene sequencing of DNA extracted directly from hands, and sequencing of DNA extracted from culture plates. Glove-based sampling yielded higher numbers of unique operational taxonomic units (OTUs) but had less diversity in bacterial community composition than swab-based sampling. We detected treatment-induced changes in diversity only by using swab-based samples ( P < 0.001); we were unable to detect changes with glove-based samples. Bacterial cell counts significantly decreased with use of the ABHS ( P < 0.05) and ethanol control ( P < 0.05). Skin hydration at baseline correlated with bacterial abundances, bacterial community composition, pH, and redness across subjects. The importance of the method choice was substantial. These findings are important to ensure improvement of hand hygiene industry methods and for future hand microbiome studies. On the basis of our results and previously published studies, we propose recommendations for best practices in hand microbiome research. IMPORTANCE The hand microbiome is a critical area of research for diverse fields, such as public health and forensics. The suitability of culture-independent methods for assessing effects of hygiene products on microbiota has not been demonstrated. This is the first controlled laboratory clinical hand study to have compared traditional hand hygiene test methods with newer culture-independent characterization methods typically used by skin microbiologists. This study resulted in recommendations for hand hygiene product testing, development of methods, and future hand skin microbiome research. It also demonstrated the importance of inclusion of skin physiological metadata in skin microbiome research, which is atypical for skin microbiome studies. Copyright © 2017 Zapka et al.

An Orientation Measurement Method Based on Hall-effect Sensors for Permanent Magnet Spherical Actuators with 3D Magnet Array

PubMed Central

Yan, Liang; Zhu, Bo; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-01-01

An orientation measurement method based on Hall-effect sensors is proposed for permanent magnet (PM) spherical actuators with three-dimensional (3D) magnet array. As there is no contact between the measurement system and the rotor, this method could effectively avoid friction torque and additional inertial moment existing in conventional approaches. Curved surface fitting method based on exponential approximation is proposed to formulate the magnetic field distribution in 3D space. The comparison with conventional modeling method shows that it helps to improve the model accuracy. The Hall-effect sensors are distributed around the rotor with PM poles to detect the flux density at different points, and thus the rotor orientation can be computed from the measured results and analytical models. Experiments have been conducted on the developed research prototype of the spherical actuator to validate the accuracy of the analytical equations relating the rotor orientation and the value of magnetic flux density. The experimental results show that the proposed method can measure the rotor orientation precisely, and the measurement accuracy could be improved by the novel 3D magnet array. The study result could be used for real-time motion control of PM spherical actuators. PMID:25342000

The Effectiveness of Teaching Methods Used in Graphic Design Pedagogy in Both Analogue and Digital Education Systems

ERIC Educational Resources Information Center

Alhajri, Salman

2016-01-01

Purpose: this paper investigates the effectiveness of teaching methods used in graphic design pedagogy in both analogue and digital education systems. Methodology and approach: the paper is based on theoretical study using a qualitative, case study approach. Comparison between the digital teaching methods and traditional teaching methods was…

Correction for FDG PET dose extravasations: Monte Carlo validation and quantitative evaluation of patient studies

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

Silva-Rodríguez, Jesús, E-mail: jesus.silva.rodriguez@sergas.es; Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es; Servicio de Medicina Nuclear, Complexo Hospitalario Universidade de Santiago de Compostela

Purpose: Current procedure guidelines for whole body [18F]fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET) state that studies with visible dose extravasations should be rejected for quantification protocols. Our work is focused on the development and validation of methods for estimating extravasated doses in order to correct standard uptake value (SUV) values for this effect in clinical routine. Methods: One thousand three hundred sixty-seven consecutive whole body FDG-PET studies were visually inspected looking for extravasation cases. Two methods for estimating the extravasated dose were proposed and validated in different scenarios using Monte Carlo simulations. All visible extravasations were retrospectively evaluated using a manualmore » ROI based method. In addition, the 50 patients with higher extravasated doses were also evaluated using a threshold-based method. Results: Simulation studies showed that the proposed methods for estimating extravasated doses allow us to compensate the impact of extravasations on SUV values with an error below 5%. The quantitative evaluation of patient studies revealed that paravenous injection is a relatively frequent effect (18%) with a small fraction of patients presenting considerable extravasations ranging from 1% to a maximum of 22% of the injected dose. A criterion based on the extravasated volume and maximum concentration was established in order to identify this fraction of patients that might be corrected for paravenous injection effect. Conclusions: The authors propose the use of a manual ROI based method for estimating the effectively administered FDG dose and then correct SUV quantification in those patients fulfilling the proposed criterion.« less

Efficient Online Learning Algorithms Based on LSTM Neural Networks.

PubMed

Ergen, Tolga; Kozat, Suleyman Serdar

2017-09-13

We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

A comparison of interteaching and lecture in the college classroom.

PubMed

Saville, Bryan K; Zinn, Tracy E; Neef, Nancy A; Van Norman, Renee; Ferreri, Summer J

2006-01-01

Interteaching is a new method of classroom instruction that is based on behavioral principles but offers more flexibility than other behaviorally based methods. We examined the effectiveness of interteaching relative to a traditional form of classroom instruction-the lecture. In Study 1, participants in a graduate course in special education took short quizzes after alternating conditions of interteaching and lecture. Quiz scores following interteaching were higher than quiz scores following lecture, although both methods improved performance relative to pretest measures. In Study 2, we also alternated interteaching and lecture but counterbalanced the conditions across two sections of an undergraduate research methods class. After each unit of information, participants from both sections took the same test. Again, test scores following interteaching were higher than test scores following lecture. In addition, students correctly answered more interteaching-based questions than lecture-based questions on a cumulative final test. In both studies, the majority of students reported a preference for interteaching relative to traditional lecture. In sum, the results suggest that interteaching may be an effective alternative to traditional lecture-based methods of instruction.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

PubMed

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

Uncertainty in simulated groundwater-quality trends in transient flow

USGS Publications Warehouse

Starn, J. Jeffrey; Bagtzoglou, Amvrossios; Robbins, Gary A.

2013-01-01

In numerical modeling of groundwater flow, the result of a given solution method is affected by the way in which transient flow conditions and geologic heterogeneity are simulated. An algorithm is demonstrated that simulates breakthrough curves at a pumping well by convolution-based particle tracking in a transient flow field for several synthetic basin-scale aquifers. In comparison to grid-based (Eulerian) methods, the particle (Lagrangian) method is better able to capture multimodal breakthrough caused by changes in pumping at the well, although the particle method may be apparently nonlinear because of the discrete nature of particle arrival times. Trial-and-error choice of number of particles and release times can perhaps overcome the apparent nonlinearity. Heterogeneous aquifer properties tend to smooth the effects of transient pumping, making it difficult to separate their effects in parameter estimation. Porosity, a new parameter added for advective transport, can be accurately estimated using both grid-based and particle-based methods, but predictions can be highly uncertain, even in the simple, nonreactive case.

Stiffness Parameter Design of Suspension Element of Under-Chassis-Equipment for A Rail Vehicle

NASA Astrophysics Data System (ADS)

Ma, Menglin; Wang, Chengqiang; Deng, Hai

2017-06-01

According to the frequency configuration requirements of the vibration of railway under-chassis-equipment, the three- dimension stiffness of the suspension elements of under-chassis-equipment is designed based on the static principle and dynamics principle. The design results of the concrete engineering case show that, compared with the design method based on the static principle, the three- dimension stiffness of the suspension elements designed by the dynamic principle design method is more uniform. The frequency and decoupling degree analysis show that the calculation frequency of under-chassis-equipment under the two design methods is basically the same as the predetermined frequency. Compared with the design method based on the static principle, the design method based on the dynamic principle is adopted. The decoupling degree can be kept high, and the coupling vibration of the corresponding vibration mode can be reduced effectively, which can effectively reduce the fatigue damage of the key parts of the hanging element.

Summary of water body extraction methods based on ZY-3 satellite

NASA Astrophysics Data System (ADS)

Zhu, Yu; Sun, Li Jian; Zhang, Chuan Yin

2017-12-01

Extracting from remote sensing images is one of the main means of water information extraction. Affected by spectral characteristics, many methods can be not applied to the satellite image of ZY-3. To solve this problem, we summarize the extraction methods for ZY-3 and analyze the extraction results of existing methods. According to the characteristics of extraction results, the method of WI& single band threshold and the method of texture filtering based on probability statistics are explored. In addition, the advantages and disadvantages of all methods are compared, which provides some reference for the research of water extraction from images. The obtained conclusions are as follows. 1) NIR has higher water sensitivity, consequently when the surface reflectance in the study area is less similar to water, using single band threshold method or multi band operation can obtain the ideal effect. 2) Compared with the water index and HIS optimal index method, object extraction method based on rules, which takes into account not only the spectral information of the water, but also space and texture feature constraints, can obtain better extraction effect, yet the image segmentation process is time consuming and the definition of the rules requires a certain knowledge. 3) The combination of the spectral relationship and water index can eliminate the interference of the shadow to a certain extent. When there is less small water or small water is not considered in further study, texture filtering based on probability statistics can effectively reduce the noises in result and avoid mixing shadows or paddy field with water in a certain extent.

Development and Evaluation of the Method with an Affective Interface for Promoting Employees' Morale

NASA Astrophysics Data System (ADS)

Fujino, Hidenori; Ishii, Hirotake; Shimoda, Hiroshi; Yoshikawa, Hidekazu

For the sustainable society, organization management not based on the mass production and mass consumption but having the flexibility to meet to various social needs precisely is required. For realizing such management, the emploees' work morale is required. Recently, however, the emploees' work morale is tend to decrease. Therefore, in this study, the authors developed the model of the method for promoting and keeping employees' work morale effectively and efficiently. Especially the authors thought “work morale” of “attitude to the work”. Based on this idea, it could be considered that the theory of the persuasion psychology and various persuasion techniques. Therefore, the model of the method applying the character agent was developed based on the forced compliance which is one of persuasion techniques based on the theory of the cognitive dissonance. By the evaluation experiment using human subjects, it was confirmed that developed method could improve workers' work morle effectively.

On the value of nonremovable reminders for behavior modification: an application to nail-biting (onychophagia).

PubMed

Koritzky, Gilly; Yechiam, Eldad

2011-11-01

The authors examined the effectiveness of a novel behavior modification method for dysfunctional and impulsive habits, based on nonremovable reminders (NrRs). NrRs were implemented by having participants wear nonremovable wristbands designated to constantly remind them of their resolution to quit the targeted habit (nail-biting). Participants were 80 nail-biters who resolved to quit. The NrR approach was contrasted with an aversion-based behavioral modification technique. Recovery was assessed after 3 and 6 weeks of treatment and in a 5-month follow-up. The NrR method was associated with lower drop-out rate and was as successful as the aversion-based method altogether. When considering only non-dropouts, the aversion-based method was more effective. This suggests that the use of constantly present reminders broadens the target population that can benefit from reminders in the course of behavior modification.

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

PubMed Central

Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

2017-01-01

The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

The effect of isoflurane anesthesia on the electroencephalogram assessed by harmonic wavelet bicoherence-based indices

NASA Astrophysics Data System (ADS)

Li, Duan; Li, Xiaoli; Hagihira, Satoshi; Sleigh, Jamie W.

2011-10-01

Bicoherence quantifies the degree of quadratic phase coupling among different frequency components within a signal. Previous studies, using Fourier-based methods of bicoherence calculation (FBIC), have demonstrated that electroencephalographic bicoherence can be related to the end-tidal concentration of inhaled anesthetic drugs. However, FBIC methods require excessively long sections of the encephalogram. This problem might be overcome by the use of wavelet-based methods. In this study, we compare FBIC and a recently developed wavelet bicoherence (WBIC) method as a tool to quantify the effect of isoflurane on the electroencephalogram. We analyzed a set of previously published electroencephalographic data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. Nine potential indices of the electroencephalographic anesthetic effect were obtained from the WBIC and FBIC techniques. The relationship between each index and end-tidal concentrations of isoflurane was evaluated using correlation coefficients (r), the inter-individual variations (CV) of index values, the coefficient of determination (R2) of the PKPD models and the prediction probability (PK). The WBIC-based indices tracked anesthetic effects better than the traditional FBIC-based ones. The DiagBic_En index (derived from the Shannon entropy of the diagonal bicoherence values) performed best [r = 0.79 (0.66-0.92), CV = 0.08 (0.05-0.12), R2 = 0.80 (0.75-0.85), PK = 0.79 (0.75-0.83)]. Short data segments of ~10-30 s were sufficient to reliably calculate the indices of WBIC. The wavelet-based bicoherence has advantages over the traditional Fourier-based bicoherence in analyzing volatile anesthetic effects on the electroencephalogram.

A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways

PubMed Central

Han, Junwei; Li, Chunquan; Yang, Haixiu; Xu, Yanjun; Zhang, Chunlong; Ma, Jiquan; Shi, Xinrui; Liu, Wei; Shang, Desi; Yao, Qianlan; Zhang, Yunpeng; Su, Fei; Feng, Li; Li, Xia

2015-01-01

Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI). PMID:25551156

Game-based e-learning is more effective than a conventional instructional method: a randomized controlled trial with third-year medical students.

PubMed

Boeker, Martin; Andel, Peter; Vach, Werner; Frankenschmidt, Alexander

2013-01-01

When compared with more traditional instructional methods, Game-based e-learning (GbEl) promises a higher motivation of learners by presenting contents in an interactive, rule-based and competitive way. Most recent systematic reviews and meta-analysis of studies on Game-based learning and GbEl in the medical professions have shown limited effects of these instructional methods. To compare the effectiveness on the learning outcome of a Game-based e-learning (GbEl) instruction with a conventional script-based instruction in the teaching of phase contrast microscopy urinalysis under routine training conditions of undergraduate medical students. A randomized controlled trial was conducted with 145 medical students in their third year of training in the Department of Urology at the University Medical Center Freiburg, Germany. 82 subjects where allocated for training with an educational adventure-game (GbEl group) and 69 subjects for conventional training with a written script-based approach (script group). Learning outcome was measured with a 34 item single choice test. Students' attitudes were collected by a questionnaire regarding fun with the training, motivation to continue the training and self-assessment of acquired knowledge. The students in the GbEl group achieved significantly better results in the cognitive knowledge test than the students in the script group: the mean score was 28.6 for the GbEl group and 26.0 for the script group of a total of 34.0 points with a Cohen's d effect size of 0.71 (ITT analysis). Attitudes towards the recent learning experience were significantly more positive with GbEl. Students reported to have more fun while learning with the game when compared to the script-based approach. Game-based e-learning is more effective than a script-based approach for the training of urinalysis in regard to cognitive learning outcome and has a high positive motivational impact on learning. Game-based e-learning can be used as an effective teaching method for self-instruction.

Development of a Moodle Course for Schoolchildren's Table Tennis Learning Based on Competence Motivation Theory: Its Effectiveness in Comparison to Traditional Training Method

ERIC Educational Resources Information Center

Zou, Junhua; Liu, Qingtang; Yang, Zongkai

2012-01-01

Based on Competence Motivation Theory (CMT), a Moodle course for schoolchildren's table tennis learning was developed (The URL is http://www.bssepp.com, and this course allows guest access). The effects of the course on students' knowledge, perceived competence and interest were evaluated through quantitative methods. The sample of the study…

The Effect of Computer Assisted and Computer Based Teaching Methods on Computer Course Success and Computer Using Attitudes of Students

ERIC Educational Resources Information Center

Tosun, Nilgün; Suçsuz, Nursen; Yigit, Birol

2006-01-01

The purpose of this research was to investigate the effects of the computer-assisted and computer-based instructional methods on students achievement at computer classes and on their attitudes towards using computers. The study, which was completed in 6 weeks, were carried out with 94 sophomores studying in formal education program of Primary…

A Safety Program that Integrated Behavior-Based Safety and Traditional Safety Methods and Its Effects on Injury Rates of Manufacturing Workers

ERIC Educational Resources Information Center

Hermann, Jaime A.; Ibarra, Guillermo V.; Hopkins, B. L.

2010-01-01

The present research examines the effects of a complex safety program that combined Behavior-Based Safety (BBS) and traditional safety methods. The study was conducted in an automobile parts plant in Mexico. Two sister plants served as comparison. Some of the components of the safety programs addressed behaviors of managers and included methods…

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

NASA Astrophysics Data System (ADS)

Zhao, Feng; Huang, Qingming; Wang, Hao; Gao, Wen

2010-12-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion.

PubMed

Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

2016-01-01

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13.Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract. © The Author(s) 2016. Published by Oxford University Press.

Method of production of pure hydrogen near room temperature from aluminum-based hydride materials

DOEpatents

Pecharsky, Vitalij K.; Balema, Viktor P.

2004-08-10

The present invention provides a cost-effective method of producing pure hydrogen gas from hydride-based solid materials. The hydride-based solid material is mechanically processed in the presence of a catalyst to obtain pure gaseous hydrogen. Unlike previous methods, hydrogen may be obtained from the solid material without heating, and without the addition of a solvent during processing. The described method of hydrogen production is useful for energy conversion and production technologies that consume pure gaseous hydrogen as a fuel.

A Computer Simulation of Community Pharmacy Practice for Educational Use.

PubMed

Bindoff, Ivan; Ling, Tristan; Bereznicki, Luke; Westbury, Juanita; Chalmers, Leanne; Peterson, Gregory; Ollington, Robert

2014-11-15

To provide a computer-based learning method for pharmacy practice that is as effective as paper-based scenarios, but more engaging and less labor-intensive. We developed a flexible and customizable computer simulation of community pharmacy. Using it, the students would be able to work through scenarios which encapsulate the entirety of a patient presentation. We compared the traditional paper-based teaching method to our computer-based approach using equivalent scenarios. The paper-based group had 2 tutors while the computer group had none. Both groups were given a prescenario and postscenario clinical knowledge quiz and survey. Students in the computer-based group had generally greater improvements in their clinical knowledge score, and third-year students using the computer-based method also showed more improvements in history taking and counseling competencies. Third-year students also found the simulation fun and engaging. Our simulation of community pharmacy provided an educational experience as effective as the paper-based alternative, despite the lack of a human tutor.

[Application of case-based method in genetics and eugenics teaching].

PubMed

Li, Ya-Xuan; Zhao, Xin; Zhang, Fei-Xiong; Hu, Ying-Kao; Yan, Yue-Ming; Cai, Min-Hua; Li, Xiao-Hui

2012-05-01

Genetics and Eugenics is a cross-discipline between genetics and eugenics. It is a common curriculum in many Chinese universities. In order to increase the learning interest, we introduced case teaching method and got a better teaching effect. Based on our teaching practices, we summarized some experiences about this subject. In this article, the main problem of case-based method applied in Genetics and Eugenics teaching was discussed.

Method variation in the impact of missing data on response shift detection.

PubMed

Schwartz, Carolyn E; Sajobi, Tolulope T; Verdam, Mathilde G E; Sebille, Veronique; Lix, Lisa M; Guilleux, Alice; Sprangers, Mirjam A G

2015-03-01

Missing data due to attrition or item non-response can result in biased estimates and loss of power in longitudinal quality-of-life (QOL) research. The impact of missing data on response shift (RS) detection is relatively unknown. This overview article synthesizes the findings of three methods tested in this special section regarding the impact of missing data patterns on RS detection in incomplete longitudinal data. The RS detection methods investigated include: (1) Relative importance analysis to detect reprioritization RS in stroke caregivers; (2) Oort's structural equation modeling (SEM) to detect recalibration, reprioritization, and reconceptualization RS in cancer patients; and (3) Rasch-based item-response theory-based (IRT) models as compared to SEM models to detect recalibration and reprioritization RS in hospitalized chronic disease patients. Each method dealt with missing data differently, either with imputation (1), attrition-based multi-group analysis (2), or probabilistic analysis that is robust to missingness due to the specific objectivity property (3). Relative importance analyses were sensitive to the type and amount of missing data and imputation method, with multiple imputation showing the largest RS effects. The attrition-based multi-group SEM revealed differential effects of both the changes in health-related QOL and the occurrence of response shift by attrition stratum, and enabled a more complete interpretation of findings. The IRT RS algorithm found evidence of small recalibration and reprioritization effects in General Health, whereas SEM mostly evidenced small recalibration effects. These differences may be due to differences between the two methods in handling of missing data. Missing data imputation techniques result in different conclusions about the presence of reprioritization RS using the relative importance method, while the attrition-based SEM approach highlighted different recalibration and reprioritization RS effects by attrition group. The IRT analyses detected more recalibration and reprioritization RS effects than SEM, presumably due to IRT's robustness to missing data. Future research should apply simulation techniques in order to make conclusive statements about the impacts of missing data according to the type and amount of RS.

Usability Evaluation of a Web-Based Learning System

ERIC Educational Resources Information Center

Nguyen, Thao

2012-01-01

The paper proposes a contingent, learner-centred usability evaluation method and a prototype tool of such systems. This is a new usability evaluation method for web-based learning systems using a set of empirically-supported usability factors and can be done effectively with limited resources. During the evaluation process, the method allows for…

Teaching Research Methods in Communication Disorders: "A Problem-Based Learning Approach"

ERIC Educational Resources Information Center

Greenwald, Margaret L.

2006-01-01

A critical professional issue in speech-language pathology and audiology is the current shortage of researchers. In this context, the most effective methods for training graduate students in research must be identified and implemented. This article describes a problem-based approach to teaching research methods. In this approach, the instructor…

Collaborating to Improve Inquiry-Based Teaching in Elementary Science and Mathematics Methods Courses

ERIC Educational Resources Information Center

Magee, Paula A.; Flessner, Ryan

2012-01-01

This study examines the effect of promoting inquiry-based teaching (IBT) through collaboration between a science methods course and mathematics methods course in an elementary teacher education program. During the collaboration, preservice elementary teacher (PST) candidates experienced 3 different types of inquiry as a way to foster increased…

Enhanced learning through design problems - teaching a components-based course through design

NASA Astrophysics Data System (ADS)

Jensen, Bogi Bech; Högberg, Stig; Fløtum Jensen, Frida av; Mijatovic, Nenad

2012-08-01

This paper describes a teaching method used in an electrical machines course, where the students learn about electrical machines by designing them. The aim of the course is not to teach design, albeit this is a side product, but rather to teach the fundamentals and the function of electrical machines through design. The teaching method is evaluated by a student questionnaire, designed to measure the quality and effectiveness of the teaching method. The results of the questionnaire conclusively show that this method labelled 'learning through design' is a very effective way of teaching a components-based course. This teaching method can easily be generalised and used in other courses.

Influence of inner circular sealing area impression method on the retention of complete dentures.

PubMed

Wang, Cun-Wei; Shao, Qi; Sun, Hui-Qiang; Mao, Meng-Yun; Zhang, Xin-Wei; Gong, Qi; Xiao, Guo-Ning

2015-01-01

The aims of the present study were to describe an impression method of "inner circular sealing area" and to evaluate the effect of the method on retention, aesthetics and comfort of complete dentures, which lack labial base for patients with maxillary protrusions. Three patients were subjected to the experiment, and two sets of complete maxillary dentures were made for each patient; the first set was made without labial base via an inner circular sealing area method (experimental group) and the second had an intact base that was made with conventional methods (control group). Retention force tests were implemented with a tensile strength assessment device to assess the retention and a visual analogue scale (VAS) was used to evaluate the comfort between the two groups. Results showed larger retention force, better aesthetics and more comfort in the experimental group. The improved two-step impression method formed an inner circular sealing area that prevented damage to the peripheral border seal effect of the denture caused by incomplete bases and obtained better denture retention.

Evaluating the Good Ontology Design Guideline (GoodOD) with the ontology quality requirements and evaluation method and metrics (OQuaRE).

PubMed

Duque-Ramos, Astrid; Boeker, Martin; Jansen, Ludger; Schulz, Stefan; Iniesta, Miguela; Fernández-Breis, Jesualdo Tomás

2014-01-01

To (1) evaluate the GoodOD guideline for ontology development by applying the OQuaRE evaluation method and metrics to the ontology artefacts that were produced by students in a randomized controlled trial, and (2) informally compare the OQuaRE evaluation method with gold standard and competency questions based evaluation methods, respectively. In the last decades many methods for ontology construction and ontology evaluation have been proposed. However, none of them has become a standard and there is no empirical evidence of comparative evaluation of such methods. This paper brings together GoodOD and OQuaRE. GoodOD is a guideline for developing robust ontologies. It was previously evaluated in a randomized controlled trial employing metrics based on gold standard ontologies and competency questions as outcome parameters. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies and has been successfully used for evaluating the quality of ontologies. In this paper, we evaluate the effect of training in ontology construction based on the GoodOD guideline within the OQuaRE quality evaluation framework and compare the results with those obtained for the previous studies based on the same data. Our results show a significant effect of the GoodOD training over developed ontologies by topics: (a) a highly significant effect was detected in three topics from the analysis of the ontologies of untrained and trained students; (b) both positive and negative training effects with respect to the gold standard were found for five topics. The GoodOD guideline had a significant effect over the quality of the ontologies developed. Our results show that GoodOD ontologies can be effectively evaluated using OQuaRE and that OQuaRE is able to provide additional useful information about the quality of the GoodOD ontologies.

[Nonpharmacological correction of low back pain by single or integrated means of medical rehabilitation and the evaluation of their effectiveness].

PubMed

Sakalauskiene, Giedre

2009-01-01

Low back pain is a global worldwide problem. A great attention is given to correction of this health status by a wide range of rehabilitation specialists. Some single or integrated physical factors, physiotherapy, specific and nonspecific physical exercises, alternative methods of treatment, also the complex of multidisciplinary rehabilitation means are applied in the management of low back pain. The evidence-based data are analyzed in order to identify which nonpharmacological means are effective in pain correction; in addition, the effectiveness of various methods and models of low back pain management are compared in this article. Research data evaluating the impact effectiveness of single or integrated means of rehabilitation are very controversial. There are no evidence-based specific recommendations for the correction of this health status objectively assessing advantages of physiotherapy or physical factors and referring the definite indications of their prescription. It is thought that multidisciplinary rehabilitation is most effective in management of chronic low back pain. The positive results depend on the experience of a physician and other rehabilitation specialists. A patient's motivation to participate in the process of pain control is very important. It is recommended to inform a patient about the effectiveness of administered methods. There is a lack of evidence-based trials evaluating the effectiveness of nonpharmacological methods of pain control in Lithuania. Therefore, the greater attention of researchers and administrative structures of health care should be given to this problem in order to develop the evidence-based guidelines for an effective correction of low back pain.

Position Accuracy Analysis of a Robust Vision-Based Navigation

NASA Astrophysics Data System (ADS)

Gaglione, S.; Del Pizzo, S.; Troisi, S.; Angrisano, A.

2018-05-01

Using images to determine camera position and attitude is a consolidated method, very widespread for application like UAV navigation. In harsh environment, where GNSS could be degraded or denied, image-based positioning could represent a possible candidate for an integrated or alternative system. In this paper, such method is investigated using a system based on single camera and 3D maps. A robust estimation method is proposed in order to limit the effect of blunders or noisy measurements on position solution. The proposed approach is tested using images collected in an urban canyon, where GNSS positioning is very unaccurate. A previous photogrammetry survey has been performed to build the 3D model of tested area. The position accuracy analysis is performed and the effect of the robust method proposed is validated.

Robust estimation of the proportion of treatment effect explained by surrogate marker information.

PubMed

Parast, Layla; McDermott, Mary M; Tian, Lu

2016-05-10

In randomized treatment studies where the primary outcome requires long follow-up of patients and/or expensive or invasive obtainment procedures, the availability of a surrogate marker that could be used to estimate the treatment effect and could potentially be observed earlier than the primary outcome would allow researchers to make conclusions regarding the treatment effect with less required follow-up time and resources. The Prentice criterion for a valid surrogate marker requires that a test for treatment effect on the surrogate marker also be a valid test for treatment effect on the primary outcome of interest. Based on this criterion, methods have been developed to define and estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker. These methods aim to identify useful statistical surrogates that capture a large proportion of the treatment effect. However, current methods to estimate this proportion usually require restrictive model assumptions that may not hold in practice and thus may lead to biased estimates of this quantity. In this paper, we propose a nonparametric procedure to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on a potential surrogate marker and extend this procedure to a setting with multiple surrogate markers. We compare our approach with previously proposed model-based approaches and propose a variance estimation procedure based on a perturbation-resampling method. Simulation studies demonstrate that the procedure performs well in finite samples and outperforms model-based procedures when the specified models are not correct. We illustrate our proposed procedure using a data set from a randomized study investigating a group-mediated cognitive behavioral intervention for peripheral artery disease participants. Copyright © 2015 John Wiley & Sons, Ltd.

Modelling cost-effectiveness of different vasectomy methods in India, Kenya, and Mexico

PubMed Central

Seamans, Yancy; Harner-Jay, Claudia M

2007-01-01

Background Vasectomy is generally considered a safe and effective method of permanent contraception. The historical effectiveness of vasectomy has been questioned by recent research results indicating that the most commonly used method of vasectomy – simple ligation and excision (L and E) – appears to have a relatively high failure rate, with reported pregnancy rates as high as 4%. Updated methods such as fascial interposition (FI) and thermal cautery can lower the rate of failure but may require additional financial investments and may not be appropriate for low-resource clinics. In order to better compare the cost-effectiveness of these different vasectomy methods, we modelled the costs of different vasectomy methods using cost data collected in India, Kenya, and Mexico and effectiveness data from the latest published research. Methods The costs associated with providing vasectomies were determined in each country through interviews with clinic staff. Costs collected were economic, direct, programme costs of fixed vasectomy services but did not include large capital expenses or general recurrent costs for the health care facility. Estimates of the time required to provide service were gained through interviews and training costs were based on the total costs of vasectomy training programmes in each country. Effectiveness data were obtained from recent published studies and comparative cost-effectiveness was determined using cost per couple years of protection (CYP). Results In each country, the labour to provide the vasectomy and follow-up services accounts for the greatest portion of the overall cost. Because each country almost exclusively used one vasectomy method at all of the clinics included in the study, we modelled costs based on the additional material, labour, and training costs required in each country. Using a model of a robust vasectomy program, more effective methods such as FI and thermal cautery reduce the cost per CYP of a vasectomy by $0.08 – $0.55. Conclusion Based on the results presented, more effective methods of vasectomy – including FI, thermal cautery, and thermal cautery combined with FI – are more cost-effective than L and E alone. Analysis shows that for a programme in which a minimum of 20 clients undergo vasectomies per month, the cost per CYP is reduced in all three countries by updated vasectomy methods. PMID:17629921

Study on Hybrid Image Search Technology Based on Texts and Contents

NASA Astrophysics Data System (ADS)

Wang, H. T.; Ma, F. L.; Yan, C.; Pan, H.

2018-05-01

Image search was studied first here based on texts and contents, respectively. The text-based image feature extraction was put forward by integrating the statistical and topic features in view of the limitation of extraction of keywords only by means of statistical features of words. On the other hand, a search-by-image method was put forward based on multi-feature fusion in view of the imprecision of the content-based image search by means of a single feature. The layered-searching method depended on primarily the text-based image search method and additionally the content-based image search was then put forward in view of differences between the text-based and content-based methods and their difficult direct fusion. The feasibility and effectiveness of the hybrid search algorithm were experimentally verified.

Comparing the Effects of Simulation-Based and Traditional Teaching Methods on the Critical Thinking Abilities and Self-Confidence of Nursing Students.

PubMed

Alamrani, Mashael Hasan; Alammar, Kamila Ahmad; Alqahtani, Sarah Saad; Salem, Olfat A

2018-06-01

Critical thinking and self-confidence are imperative to success in clinical practice. Educators should use teaching strategies that will help students enhance their critical thinking and self-confidence in complex content such as electrocardiogram interpretation. Therefore, teaching electrocardiogram interpretation to students is important for nurse educators. This study compares the effect of simulation-based and traditional teaching methods on the critical thinking and self-confidence of students during electrocardiogram interpretation sessions. Thirty undergraduate nursing students volunteered to participate in this study. The participants were divided into intervention and control groups, which were taught respectively using the simulation-based and traditional teaching programs. All of the participants were asked to complete the study instrumentpretest and posttest to measure their critical thinking and self-confidence. Improvement was observed in the control and experimental groups with respect to critical thinking and self-confidence, as evidenced by the results of the paired samples t test and the Wilcoxon signed-rank test (p < .05). However, the independent t test and Mann-Whitney U test indicate that the difference between the two groups was not significant (p > .05). This study evaluated an innovative simulation-based teaching method for nurses. No significant differences in outcomes were identified between the simulator-based and traditional teaching methods, indicating that well-implemented educational programs that use either teaching method effectively promote critical thinking and self-confidence in nursing students. Nurse educators are encouraged to design educational plans with clear objectives to improve the critical thinking and self-confidence of their students. Future research should compare the effects of several teaching sessions using each method in a larger sample.

Advanced Cardiac Life Support Training by Problem-Based Method: Effect on the Trainee's Skills, Knowledge and Evaluation of Trainers.

PubMed

Hosseini, Seyed Kianoosh; Ghalamkari, Marziyeh; Yousefshahi, Fardin; Mireskandari, Seyed Mohammad; Rezaei Hamami, Mohsen

2013-10-28

Cardiopulmonary-cerebral resuscitation (CPCR) training is essential for all hospital workers, especially junior residents who might become the manager of the resuscitation team. In our center, the traditional CPCR knowledge training curriculum for junior residents up to 5 years ago was lecture-based and had some faults. This study aimed to evaluate the effect of a problem-based method on residents' CPCR knowledge and skills as well as their evaluation of their CPCR trainers. This study, conducted at Tehran University of Medical Sciences, included 290 first-year residents in 2009-2010 - who were trained via a problem-based method (the problem-based group) - and 160 first-year residents in 2003-2004 - who were trained via a lecture-based method (the lecture-based group). Other educational techniques and facilities were similar. The participants self-evaluated their own CPCR knowledge and skills pre and post workshop and also assessed their trainers' efficacy post workshop by completing special questionnaires. The problem-based group, trained via the problem-based method, had higher self-assessment scores of CPCR knowledge and skills post workshop: the difference as regards the mean scores between the problem-based and lecture-based groups was 32.36 ± 19.23 vs. 22.33 ± 20.35 for knowledge (p value = 0.003) and 10.13 ± 7.17 vs. 8.19 ± 8.45 for skills (p value = 0.043). The residents' evaluation of their trainers was similar between the two study groups (p value = 0.193), with the mean scores being 15.90 ± 2.59 and 15.46 ± 2.90 in the problem-based and lecture-based groups - respectively. The problem-based method increased our residents' self-evaluation score of their own CPCR knowledge and skills.

Comparison of CTT and Rasch-based approaches for the analysis of longitudinal Patient Reported Outcomes.

PubMed

Blanchin, Myriam; Hardouin, Jean-Benoit; Le Neel, Tanguy; Kubis, Gildas; Blanchard, Claire; Mirallié, Eric; Sébille, Véronique

2011-04-15

Health sciences frequently deal with Patient Reported Outcomes (PRO) data for the evaluation of concepts, in particular health-related quality of life, which cannot be directly measured and are often called latent variables. Two approaches are commonly used for the analysis of such data: Classical Test Theory (CTT) and Item Response Theory (IRT). Longitudinal data are often collected to analyze the evolution of an outcome over time. The most adequate strategy to analyze longitudinal latent variables, which can be either based on CTT or IRT models, remains to be identified. This strategy must take into account the latent characteristic of what PROs are intended to measure as well as the specificity of longitudinal designs. A simple and widely used IRT model is the Rasch model. The purpose of our study was to compare CTT and Rasch-based approaches to analyze longitudinal PRO data regarding type I error, power, and time effect estimation bias. Four methods were compared: the Score and Mixed models (SM) method based on the CTT approach, the Rasch and Mixed models (RM), the Plausible Values (PV), and the Longitudinal Rasch model (LRM) methods all based on the Rasch model. All methods have shown comparable results in terms of type I error, all close to 5 per cent. LRM and SM methods presented comparable power and unbiased time effect estimations, whereas RM and PV methods showed low power and biased time effect estimations. This suggests that RM and PV methods should be avoided to analyze longitudinal latent variables. Copyright © 2010 John Wiley & Sons, Ltd.

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.

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.

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

PubMed

Niu, Bing; Yuan, Xiao-Cheng; Roeper, Preston; Su, Qiang; Peng, Chun-Rong; Yin, Jing-Yuan; Ding, Juan; Li, HaiPeng; Lu, Wen-Cong

2013-03-01

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.

Study of effects of injector geometry on fuel-air mixing and combustion

NASA Technical Reports Server (NTRS)

Bangert, L. H.; Roach, R. L.

1977-01-01

An implicit finite-difference method has been developed for computing the flow in the near field of a fuel injector as part of a broader study of the effects of fuel injector geometry on fuel-air mixing and combustion. Detailed numerical results have been obtained for cases of laminar and turbulent flow without base injection, corresponding to the supersonic base flow problem. These numerical results indicated that the method is stable and convergent, and that significant savings in computer time can be achieved, compared with explicit methods.

Quick, easy, cheap, effective, rugged, and safe sample preparation approach for pesticide residue analysis using traditional detectors in chromatography: A review.

PubMed

Rahman, Md Musfiqur; Abd El-Aty, A M; Kim, Sung-Woo; Shin, Sung Chul; Shin, Ho-Chul; Shim, Jae-Han

2017-01-01

In pesticide residue analysis, relatively low-sensitivity traditional detectors, such as UV, diode array, electron-capture, flame photometric, and nitrogen-phosphorus detectors, have been used following classical sample preparation (liquid-liquid extraction and open glass column cleanup); however, the extraction method is laborious, time-consuming, and requires large volumes of toxic organic solvents. A quick, easy, cheap, effective, rugged, and safe method was introduced in 2003 and coupled with selective and sensitive mass detectors to overcome the aforementioned drawbacks. Compared to traditional detectors, mass spectrometers are still far more expensive and not available in most modestly equipped laboratories, owing to maintenance and cost-related issues. Even available, traditional detectors are still being used for analysis of residues in agricultural commodities. It is widely known that the quick, easy, cheap, effective, rugged, and safe method is incompatible with conventional detectors owing to matrix complexity and low sensitivity. Therefore, modifications using column/cartridge-based solid-phase extraction instead of dispersive solid-phase extraction for cleanup have been applied in most cases to compensate and enable the adaptation of the extraction method to conventional detectors. In gas chromatography, the matrix enhancement effect of some analytes has been observed, which lowers the limit of detection and, therefore, enables gas chromatography to be compatible with the quick, easy, cheap, effective, rugged, and safe extraction method. For liquid chromatography with a UV detector, a combination of column/cartridge-based solid-phase extraction and dispersive solid-phase extraction was found to reduce the matrix interference and increase the sensitivity. A suitable double-layer column/cartridge-based solid-phase extraction might be the perfect solution, instead of a time-consuming combination of column/cartridge-based solid-phase extraction and dispersive solid-phase extraction. Therefore, replacing dispersive solid-phase extraction with column/cartridge-based solid-phase extraction in the cleanup step can make the quick, easy, cheap, effective, rugged, and safe extraction method compatible with traditional detectors for more sensitive, effective, and green analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

NASA Astrophysics Data System (ADS)

Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

2017-12-01

We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.

The Robustness of IRT-Based Vertical Scaling Methods to Violation of Unidimensionality

ERIC Educational Resources Information Center

Yin, Liqun

2013-01-01

In recent years, many states have adopted Item Response Theory (IRT) based vertically scaled tests due to their compelling features in a growth-based accountability context. However, selection of a practical and effective calibration/scaling method and proper understanding of issues with possible multidimensionality in the test data is critical to…

Discovery of Boolean metabolic networks: integer linear programming based approach.

PubMed

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

An image mosaic method based on corner

NASA Astrophysics Data System (ADS)

Jiang, Zetao; Nie, Heting

2015-08-01

In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.

Research on a Method of Geographical Information Service Load Balancing

NASA Astrophysics Data System (ADS)

Li, Heyuan; Li, Yongxing; Xue, Zhiyong; Feng, Tao

2018-05-01

With the development of geographical information service technologies, how to achieve the intelligent scheduling and high concurrent access of geographical information service resources based on load balancing is a focal point of current study. This paper presents an algorithm of dynamic load balancing. In the algorithm, types of geographical information service are matched with the corresponding server group, then the RED algorithm is combined with the method of double threshold effectively to judge the load state of serve node, finally the service is scheduled based on weighted probabilistic in a certain period. At the last, an experiment system is built based on cluster server, which proves the effectiveness of the method presented in this paper.

Comparing Effectiveness of Active and Passive Client Follow-Up Approaches in Sustaining the Continued Use of Long Acting Reversible Contraceptives (LARC) in Rural Punjab: A Multicentre, Non-Inferiority Trial

PubMed Central

Hameed, Waqas; Azmat, Syed Khurram; Ali, Moazzam; Ishaque, Muhammad; Abbas, Ghazunfer; Munroe, Erik; Harrison, Rebecca; Shamsi, Wajahat Hussain; Mustafa, Ghulam; Khan, Omar Farooq; Ali, Safdar; Ahmed, Aftab

2016-01-01

Background The use of long-acting reversible contraceptive (LARC) methods is very low in Pakistan with high discontinuation rates mainly attributed to method-related side effects. Mixed evidence is available on the effectiveness of different client follow-up approaches used to ensure method continuation. We compared the effectiveness of active and passive follow-up approaches in sustaining the use of LARC—and within ‘active’ follow-up, we further compared a telephone versus home-based approach in rural Punjab, Pakistan. Methods This was a 12-month multicentre non-inferiority trial conducted in twenty-two (16 rural- and 6 urban-based) franchised reproductive healthcare facilities in district Chakwal of Punjab province, between November 2013 and December 2014. The study comprised of three groups of LARC clients: a) home-based follow-up, b) telephone-based follow-up, and c) passive or needs-based follow-up. Participants in the first two study groups received counselling on scheduled follow-up from the field workers at 1, 3, 6, 9, and 12 month post-insertion whereas participants in the third group were asked to contact the health facility if in need of medical assistance relating to LARC method use. Study participants were recruited with equal allocation to each study group, but participants were not randomized. The analyses are based on 1,246 LARC (intra-uterine contraceptive device and implant) users that completed approximately 12-months of follow-up. The non-inferiority margin was kept at five percentage points for the comparison of active and passive follow-up and six percentage points for telephone and home-based approach. The primary outcome was cumulative probability of method continuation at 12-month among LARC users. Results Women recruited in home-based, telephone-based, and passive groups were 400, 419 and 427, respectively. The cumulative probability of LARC continuation at 12 month was 87.6% (95% CI 83.8 to 90.6) among women who received home-based follow-up; 89.1% (95% CI 85.7, 91.8) who received telephone-based follow-up; and 83.8% (95% CI 79.8 to 87.1) who were in the passive or needs-based follow-up group. The probability of continuation among women who were actively followed-up by field health educators—either through home-based visit or telephone-based follow-up was, 88.3% (95% CI 85.9 to 90.0). An adjusted risk difference of -4.1 (95% CI -7.8 to -0.28; p-value = 0.035) was estimated between active and passive follow-up. Whereas, within the active client follow-up, the telephone-based follow-up was found to be as effective as the home-based follow-up with an adjusted risk difference of 1.8 (95% CI -2.7 to 6.4; p-value = 0.431). Conclusion A passive follow-up approach was 5% inferior to an active follow-up approach; whereas telephone-based follow-up was as effective as the home-based visits in sustaining the use of LARC, and was far more resource efficient. Therefore, active follow-up could improve method continuation especially in the critical post-insertion period. PMID:27584088

Testing Differential Effects of Computer-Based, Web-Based and Paper-Based Administration of Questionnaire Research Instruments

ERIC Educational Resources Information Center

Hardre, Patricia L.; Crowson, H. Michael; Xie, Kui; Ly, Cong

2007-01-01

Translation of questionnaire instruments to digital administration systems, both self-contained and web-based, is widespread and increasing daily. However, the literature is lean on controlled empirical studies investigating the potential for differential effects of administrative methods. In this study, two university student samples were…

Determination of the starting dose in the first-in-human clinical trials with monoclonal antibodies: a systematic review of papers published between 1990 and 2013.

PubMed

Suh, Hoon Young; Peck, Carl C; Yu, Kyung-Sang; Lee, Howard

2016-01-01

A systematic review was performed to evaluate how the maximum recommended starting dose (MRSD) was determined in first-in-human (FIH) studies with monoclonal antibodies (mAbs). Factors associated with the choice of each MRSD determination method were also identified. PubMed was searched for FIH studies with mAbs published in English between January 1, 1990 and December 31, 2013, and the following information was extracted: MRSD determination method, publication year, therapeutic area, antibody type, safety factor, safety assessment results after the first dose, and number of dose escalation steps. Seventy-nine FIH studies with mAbs were identified, 49 of which clearly reported the MRSD determination method. The no observed adverse effects level (NOAEL)-based approach was the most frequently used method, whereas the model-based approach was the least commonly used method (34.7% vs 16.3%). The minimal anticipated biological effect level (MABEL)- or minimum effective dose (MED)-based approach was used more frequently in 2011-2013 than in 1990-2007 (31.6% vs 6.3%, P =0.036), reflecting a slow, but steady acceptance of the European Medicines Agency's guidance on mitigating risks for FIH clinical trials (2007). The median safety factor was much lower for the MABEL- or MED-based approach than for the other MRSD determination methods (10 vs 32.2-53). The number of dose escalation steps was not significantly different among the different MRSD determination methods. The MABEL-based approach appears to be safer and as efficient as the other MRSD determination methods for achieving the objectives of FIH studies with mAbs faster.

Effectiveness of E-Learning for Students Vocational High School Building Engineering Program

NASA Astrophysics Data System (ADS)

Soeparno; Muslim, Supari

2018-04-01

Implementation of vocational learning in accordance with the 2013 curriculum must meet the criteria, one of which is learning to be consistent with advances in technology and information. Technology-based learning in vocational commonly referred to as E-Learning, online (in the network) and WBL (Web-Based Learning). Facts on the ground indicate that based learning technology and information on Vocational High School of Building Engineering is still not going well. The purpose of this research is to know: advantages and disadvantages of learning with E-Learning, conformity of learning with E-Learning with characteristics of students on Vocational High School of Building Engineering and effective learning method based on E-Learning for students on Vocational High School of Building Engineering. Research done by literature method, get the following conclusion as follow: the advantages of E-Learning is learning can be done anywhere and anytime, efficient in accessing materials and tasks, ease of communication and discussion; while the shortage is the need for additional costs for good internet access and lack of social interaction between teachers and students. E-learning is appropriate to basic knowledge competencies, and not appropriate at the level of advanced competencies and skills. Effective E-Learning Based Learning Method on Vocational High School of Building Engineering is a Blended method that is a mix between conventional method and e-learning.

The effects of bridge exercise on an unstable base of support on lumbar stability and the thickness of the transversus abdominis.

PubMed

Cho, Misuk; Jeon, Hyewon

2013-06-01

[Purpose] We examined the effects of an abdominal drawing-in bridge exercise using a pressure biofeedback unit on different bases on the thickness of trunk and abdominal muscles, and lumbar stability. [Subjects] Thirty healthy young adults (2 males, 28 females) took part in this study. The subjects were randomly and equally assigned to a stable bridge exercise group and an unstable bridge exercise group. [Methods] The subjects performed bridge exercises using an abdominal drawing-in method on a stable base and on an unstable base, and changes in their abdominal muscle thickness and on the stable and on unstable bases lumbar stability were evaluated. [Results] After the intervention, the stable bridge exercise group showed a statistically significantly increased muscle thickness in the transversus abdominis, and the unstable bridge exercise group showed significantly increased muscle thicknesses of the transversus abdominis and internal obliques in static and dynamic lumbar stability. The unstable bridge exercise group showed significant increase after performing the exercise. [Conclusion] Lumbar stability exercise, with the compensation of the lumbar spine minimized, using an abdominal drawing-in method on an unstable support of base is effective and efforts to prevent the compensation may induce a greater exercise effect.

A New Method for Setting Calculation Sequence of Directional Relay Protection in Multi-Loop Networks

NASA Astrophysics Data System (ADS)

Haijun, Xiong; Qi, Zhang

2016-08-01

Workload of relay protection setting calculation in multi-loop networks may be reduced effectively by optimization setting calculation sequences. A new method of setting calculation sequences of directional distance relay protection in multi-loop networks based on minimum broken nodes cost vector (MBNCV) was proposed to solve the problem experienced in current methods. Existing methods based on minimum breakpoint set (MBPS) lead to more break edges when untying the loops in dependent relationships of relays leading to possibly more iterative calculation workloads in setting calculations. A model driven approach based on behavior trees (BT) was presented to improve adaptability of similar problems. After extending the BT model by adding real-time system characters, timed BT was derived and the dependency relationship in multi-loop networks was then modeled. The model was translated into communication sequence process (CSP) models and an optimization setting calculation sequence in multi-loop networks was finally calculated by tools. A 5-nodes multi-loop network was applied as an example to demonstrate effectiveness of the modeling and calculation method. Several examples were then calculated with results indicating the method effectively reduces the number of forced broken edges for protection setting calculation in multi-loop networks.

An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS

NASA Astrophysics Data System (ADS)

Zhang, Xin; Cui, Yiming; Wang, Yan; Sun, Mingjian; Hu, Hengshan

2018-01-01

In order to ensure the safety and reliability of railway system, Acoustic Emission (AE) method is employed to investigate rail defect detection. However, little attention has been paid to the defect detection at high speed, especially for noise interference suppression. Based on AE technology, this paper presents an improved rail defect detection method by multi-level ANC with VSS-LMS. Multi-level noise cancellation based on SANC and ANC is utilized to eliminate complex noises at high speed, and tongue-shaped curve with index adjustment factor is proposed to enhance the performance of variable step-size algorithm. Defect signals and reference signals are acquired by the rail-wheel test rig. The features of noise signals and defect signals are analyzed for effective detection. The effectiveness of the proposed method is demonstrated by comparing with the previous study, and different filter lengths are investigated to obtain a better noise suppression performance. Meanwhile, the detection ability of the proposed method is verified at the top speed of the test rig. The results clearly illustrate that the proposed method is effective in detecting rail defects at high speed, especially for noise interference suppression.

[A retrieval method of drug molecules based on graph collapsing].

PubMed

Qu, J W; Lv, X Q; Liu, Z M; Liao, Y; Sun, P H; Wang, B; Tang, Z

2018-04-18

To establish a compact and efficient hypergraph representation and a graph-similarity-based retrieval method of molecules to achieve effective and efficient medicine information retrieval. Chemical structural formula (CSF) was a primary search target as a unique and precise identifier for each compound at the molecular level in the research field of medicine information retrieval. To retrieve medicine information effectively and efficiently, a complete workflow of the graph-based CSF retrieval system was introduced. This system accepted the photos taken from smartphones and the sketches drawn on tablet personal computers as CSF inputs, and formalized the CSFs with the corresponding graphs. Then this paper proposed a compact and efficient hypergraph representation for molecules on the basis of analyzing factors that directly affected the efficiency of graph matching. According to the characteristics of CSFs, a hierarchical collapsing method combining graph isomorphism and frequent subgraph mining was adopted. There was yet a fundamental challenge, subgraph overlapping during the collapsing procedure, which hindered the method from establishing the correct compact hypergraph of an original CSF graph. Therefore, a graph-isomorphism-based algorithm was proposed to select dominant acyclic subgraphs on the basis of overlapping analysis. Finally, the spatial similarity among graphical CSFs was evaluated by multi-dimensional measures of similarity. To evaluate the performance of the proposed method, the proposed system was firstly compared with Wikipedia Chemical Structure Explorer (WCSE), the state-of-the-art system that allowed CSF similarity searching within Wikipedia molecules dataset, on retrieval accuracy. The system achieved higher values on mean average precision, discounted cumulative gain, rank-biased precision, and expected reciprocal rank than WCSE from the top-2 to the top-10 retrieved results. Specifically, the system achieved 10%, 1.41, 6.42%, and 1.32% higher than WCSE on these metrics for top-10 retrieval results, respectively. Moreover, several retrieval cases were presented to intuitively compare with WCSE. The results of the above comparative study demonstrated that the proposed method outperformed the existing method with regard to accuracy and effectiveness. This paper proposes a graph-similarity-based retrieval approach for medicine information. To obtain satisfactory retrieval results, an isomorphism-based algorithm is proposed for dominant subgraph selection based on the subgraph overlapping analysis, as well as an effective and efficient hypergraph representation of molecules. Experiment results demonstrate the effectiveness of the proposed approach.

Comparison of sample preparation methods combined with fast gas chromatography-mass spectrometry for ultratrace analysis of pesticide residues in baby food.

PubMed

Hercegová, Andrea; Dömötörová, Milena; Kruzlicová, Dása; Matisová, Eva

2006-05-01

Four sample preparation techniques were compared for the ultratrace analysis of pesticide residues in baby food: (a) modified Schenck's method based on ACN extraction with SPE cleaning; (b) quick, easy, cheap, effective, rugged, and safe (QuEChERS) method based on ACN extraction and dispersive SPE; (c) modified QuEChERS method which utilizes column-based SPE instead of dispersive SPE; and (d) matrix solid phase dispersion (MSPD). The methods were combined with fast gas chromatographic-mass spectrometric analysis. The effectiveness of clean-up of the final extract was determined by comparison of the chromatograms obtained. Time consumption, laboriousness, demands on glassware and working place, and consumption of chemicals, especially solvents, increase in the following order QuEChERS < modified QuEChERS < MSPD < modified Schenck's method. All methods offer satisfactory analytical characteristics at the concentration levels of 5, 10, and 100 microg/kg in terms of recoveries and repeatability. Recoveries obtained for the modified QuEChERS method were lower than for the original QuEChERS. In general the best LOQs were obtained for the modified Schenck's method. Modified QuEChERS method provides 21-72% better LOQs than the original method.

Embedded System Implementation of Sound Localization in Proximal Region

NASA Astrophysics Data System (ADS)

Iwanaga, Nobuyuki; Matsumura, Tomoya; Yoshida, Akihiro; Kobayashi, Wataru; Onoye, Takao

A sound localization method in the proximal region is proposed, which is based on a low-cost 3D sound localization algorithm with the use of head-related transfer functions (HRTFs). The auditory parallax model is applied to the current algorithm so that more accurate HRTFs can be used for sound localization in the proximal region. In addition, head-shadowing effects based on rigid-sphere model are reproduced in the proximal region by means of a second-order IIR filter. A subjective listening test demonstrates the effectiveness of the proposed method. Embedded system implementation of the proposed method is also described claiming that the proposed method improves sound effects in the proximal region only with 5.1% increase of memory capacity and 8.3% of computational costs.

A powerful score-based test statistic for detecting gene-gene co-association.

PubMed

Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun

2016-01-29

The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Effectiveness evaluation of objective and subjective weighting methods for aquifer vulnerability assessment in urban context

NASA Astrophysics Data System (ADS)

Sahoo, Madhumita; Sahoo, Satiprasad; Dhar, Anirban; Pradhan, Biswajeet

2016-10-01

Groundwater vulnerability assessment has been an accepted practice to identify the zones with relatively increased potential for groundwater contamination. DRASTIC is the most popular secondary information-based vulnerability assessment approach. Original DRASTIC approach considers relative importance of features/sub-features based on subjective weighting/rating values. However variability of features at a smaller scale is not reflected in this subjective vulnerability assessment process. In contrast to the subjective approach, the objective weighting-based methods provide flexibility in weight assignment depending on the variation of the local system. However experts' opinion is not directly considered in the objective weighting-based methods. Thus effectiveness of both subjective and objective weighting-based approaches needs to be evaluated. In the present study, three methods - Entropy information method (E-DRASTIC), Fuzzy pattern recognition method (F-DRASTIC) and Single parameter sensitivity analysis (SA-DRASTIC), were used to modify the weights of the original DRASTIC features to include local variability. Moreover, a grey incidence analysis was used to evaluate the relative performance of subjective (DRASTIC and SA-DRASTIC) and objective (E-DRASTIC and F-DRASTIC) weighting-based methods. The performance of the developed methodology was tested in an urban area of Kanpur City, India. Relative performance of the subjective and objective methods varies with the choice of water quality parameters. This methodology can be applied without/with suitable modification. These evaluations establish the potential applicability of the methodology for general vulnerability assessment in urban context.

The Effect of Blackboard Collaborate-Based Instruction on Pre-Service Teachers' Achievement in the EFL Teaching Methods Course at Faculties of Education for Girls

ERIC Educational Resources Information Center

Hussein, Hussein El-ghamry Mohammad

2016-01-01

This study investigated the effect of Blackboard-based instruction on pre-service teachers' achievement in the teaching methods course at The Faculty of Education for Girls, in Bisha, KSA. Forty seventh-level English Department students were randomly assigned into either the experimental group (N = 20) or the control group (N = 20). While studying…

Examining the Implementation of a Problem-Based Learning and Traditional Hybrid Model of Instruction in Remedial Mathematics Classes Designed for State Testing Preparation of Eleventh Grade Students

ERIC Educational Resources Information Center

Rodgers, Lindsay D.

2011-01-01

The following paper examined the effects of a new method of teaching for remedial mathematics, named the hybrid model of instruction. Due to increasing importance of high stakes testing, the study sought to determine if this method of instruction, that blends traditional teaching and problem-based learning, had different learning effects on…

Prognostic score–based balance measures for propensity score methods in comparative effectiveness research

PubMed Central

Stuart, Elizabeth A.; Lee, Brian K.; Leacy, Finbarr P.

2013-01-01

Objective Examining covariate balance is the prescribed method for determining when propensity score methods are successful at reducing bias. This study assessed the performance of various balance measures, including a proposed balance measure based on the prognostic score (also known as the disease-risk score), to determine which balance measures best correlate with bias in the treatment effect estimate. Study Design and Setting The correlations of multiple common balance measures with bias in the treatment effect estimate produced by weighting by the odds, subclassification on the propensity score, and full matching on the propensity score were calculated. Simulated data were used, based on realistic data settings. Settings included both continuous and binary covariates and continuous covariates only. Results The standardized mean difference in prognostic scores, the mean standardized mean difference, and the mean t-statistic all had high correlations with bias in the effect estimate. Overall, prognostic scores displayed the highest correlations of all the balance measures considered. Prognostic score measure performance was generally not affected by model misspecification and performed well under a variety of scenarios. Conclusion Researchers should consider using prognostic score–based balance measures for assessing the performance of propensity score methods for reducing bias in non-experimental studies. PMID:23849158

Effect of three decellularisation protocols on the mechanical behaviour and structural properties of sheep aortic valve conduits.

PubMed

Khorramirouz, Reza; Sabetkish, Shabnam; Akbarzadeh, Aram; Muhammadnejad, Ahad; Heidari, Reza; Kajbafzadeh, Abdol-Mohammad

2014-09-01

To determine the best method for decellularisation of aortic valve conduits (AVCs) that efficiently removes the cells while preserving the extracellular matrix (ECM) by examining the valvular and conduit sections separately. Sheep AVCs were decellularised by using three different protocols: detergent-based (1% SDS+1% SDC), detergent and enzyme-based (Triton+EDTA+RNase and DNase), and enzyme-based (Trypsin+RNase and DNase) methods. The efficacy of the decellularisation methods to completely remove the cells while preserving the ECM was evaluated by histological evaluation, scanning electron microscopy (SEM), hydroxyproline analysis, tensile test, and DAPI staining. The detergent-based method completely removed the cells and left the ECM and collagen content in the valve and conduit sections relatively well preserved. The detergent and enzyme-based protocol did not completely remove the cells, but left the collagen content in both sections well preserved. ECM deterioration was observed in the aortic valves (AVs), but the ultrastructure of the conduits was well preserved, with no media distortion. The enzyme-based protocol removed the cells relatively well; however, mild structural distortion and poor collagen content was observed in the AVs. Incomplete cell removal (better than that observed with the detergent and enzyme-based protocol), poor collagen preservation, and mild structural distortion were observed in conduits treated with the enzyme-based method. The results suggested that the detergent-based methods are the most effective protocols for cell removal and ECM preservation of AVCs. The AVCs treated with this detergent-based method may be excellent scaffolds for recellularisation. Copyright © 2014 Medical University of Bialystok. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

PubMed

Zhang, Xiaohua Douglas; Yang, Xiting Cindy; Chung, Namjin; Gates, Adam; Stec, Erica; Kunapuli, Priya; Holder, Dan J; Ferrer, Marc; Espeseth, Amy S

2006-04-01

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.

a New Improved Threshold Segmentation Method for Scanning Images of Reservoir Rocks Considering Pore Fractal Characteristics

NASA Astrophysics Data System (ADS)

Lin, Wei; Li, Xizhe; Yang, Zhengming; Lin, Lijun; Xiong, Shengchun; Wang, Zhiyuan; Wang, Xiangyang; Xiao, Qianhua

Based on the basic principle of the porosity method in image segmentation, considering the relationship between the porosity of the rocks and the fractal characteristics of the pore structures, a new improved image segmentation method was proposed, which uses the calculated porosity of the core images as a constraint to obtain the best threshold. The results of comparative analysis show that the porosity method can best segment images theoretically, but the actual segmentation effect is deviated from the real situation. Due to the existence of heterogeneity and isolated pores of cores, the porosity method that takes the experimental porosity of the whole core as the criterion cannot achieve the desired segmentation effect. On the contrary, the new improved method overcomes the shortcomings of the porosity method, and makes a more reasonable binary segmentation for the core grayscale images, which segments images based on the actual porosity of each image by calculated. Moreover, the image segmentation method based on the calculated porosity rather than the measured porosity also greatly saves manpower and material resources, especially for tight rocks.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

Effect of costing methods on unit cost of hospital medical services.

PubMed

Riewpaiboon, Arthorn; Malaroje, Saranya; Kongsawatt, Sukalaya

2007-04-01

To explore the variance of unit costs of hospital medical services due to different costing methods employed in the analysis. Retrospective and descriptive study at Kaengkhoi District Hospital, Saraburi Province, Thailand, in the fiscal year 2002. The process started with a calculation of unit costs of medical services as a base case. After that, the unit costs were re-calculated based on various methods. Finally, the variations of the results obtained from various methods and the base case were computed and compared. The total annualized capital cost of buildings and capital items calculated by the accounting-based approach (averaging the capital purchase prices throughout their useful life) was 13.02% lower than that calculated by the economic-based approach (combination of depreciation cost and interest on undepreciated portion over the useful life). A change of discount rate from 3% to 6% results in a 4.76% increase of the hospital's total annualized capital cost. When the useful life of durable goods was changed from 5 to 10 years, the total annualized capital cost of the hospital decreased by 17.28% from that of the base case. Regarding alternative criteria of indirect cost allocation, unit cost of medical services changed by a range of -6.99% to +4.05%. We explored the effect on unit cost of medical services in one department. Various costing methods, including departmental allocation methods, ranged between -85% and +32% against those of the base case. Based on the variation analysis, the economic-based approach was suitable for capital cost calculation. For the useful life of capital items, appropriate duration should be studied and standardized. Regarding allocation criteria, single-output criteria might be more efficient than the combined-output and complicated ones. For the departmental allocation methods, micro-costing method was the most suitable method at the time of study. These different costing methods should be standardized and developed as guidelines since they could affect implementation of the national health insurance scheme and health financing management.

Accuracy and the Effect of Possible Subject-Based Confounders of Magnitude-Based MRI for Estimating Hepatic Proton Density Fat Fraction in Adults, Using MR Spectroscopy as Reference

PubMed Central

Heba, Elhamy R.; Desai, Ajinkya; Zand, Kevin A.; Hamilton, Gavin; Wolfson, Tanya; Schlein, Alexandra N.; Gamst, Anthony; Loomba, Rohit; Sirlin, Claude B.; Middleton, Michael S.

2016-01-01

Purpose To determine the accuracy and the effect of possible subject-based confounders of magnitude-based magnetic resonance imaging (MRI) for estimating hepatic proton density fat fraction (PDFF) for different numbers of echoes in adults with known or suspected nonalcoholic fatty liver disease, using MR spectroscopy (MRS) as a reference. Materials and Methods In this retrospective analysis of 506 adults, hepatic PDFF was estimated by unenhanced 3.0T MRI, using right-lobe MRS as reference. Regions of interest placed on source images and on six-echo parametric PDFF maps were colocalized to MRS voxel location. Accuracy using different numbers of echoes was assessed by regression and Bland–Altman analysis; slope, intercept, average bias, and R2 were calculated. The effect of age, sex, and body mass index (BMI) on hepatic PDFF accuracy was investigated using multivariate linear regression analyses. Results MRI closely agreed with MRS for all tested methods. For three- to six-echo methods, slope, regression intercept, average bias, and R2 were 1.01–0.99, 0.11–0.62%, 0.24–0.56%, and 0.981–0.982, respectively. Slope was closest to unity for the five-echo method. The two-echo method was least accurate, underestimating PDFF by an average of 2.93%, compared to an average of 0.23–0.69% for the other methods. Statistically significant but clinically nonmeaningful effects on PDFF error were found for subject BMI (P range: 0.0016 to 0.0783), male sex (P range: 0.015 to 0.037), and no statistically significant effect was found for subject age (P range: 0.18–0.24). Conclusion Hepatic magnitude-based MRI PDFF estimates using three, four, five, and six echoes, and six-echo parametric maps are accurate compared to reference MRS values, and that accuracy is not meaningfully confounded by age, sex, or BMI. PMID:26201284

Alleviation of harmful effect in stillage reflux in food waste ethanol fermentation based on metabolic and side-product accumulation regulation.

PubMed

Ma, Hongzhi; Yang, Jian; Jia, Yan; Wang, Qunhui; Ma, Xiaoyu; Sonomoto, Kenji

2016-10-01

Stillage reflux fermentation in food waste ethanol fermentation could reduce sewage discharge but exert a harmful effect because of side-product accumulation. In this study, regulation methods based on metabolic regulation and side-product alleviation were conducted. Result demonstrated that controlling the proper oxidation-reduction potential value (-150mV to -250mV) could reduce the harmful effect, improve ethanol yield by 21%, and reduce fermentation time by 20%. The methods of adding calcium carbonate to adjust the accumulated lactic acid showed that ethanol yield increased by 17.3%, and fermentation time decreased by 20%. The accumulated glyceal also shows that these two methods can reduce the harmful effect. Fermentation time lasted for seven times without effect, and metabolic regulation had a better effect than side-product regulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Validation of a T1 and T2* leakage correction method based on multi-echo DSC-MRI using MION as a reference standard

PubMed Central

Stokes, Ashley M.; Semmineh, Natenael; Quarles, C. Chad

2015-01-01

Purpose A combined biophysical- and pharmacokinetic-based method is proposed to separate, quantify, and correct for both T1 and T2* leakage effects using dual-echo DSC acquisitions to provide more accurate hemodynamic measures, as validated by a reference intravascular contrast agent (CA). Methods Dual-echo DSC-MRI data were acquired in two rodent glioma models. The T1 leakage effects were removed and also quantified in order to subsequently correct for the remaining T2* leakage effects. Pharmacokinetic, biophysical, and combined biophysical and pharmacokinetic models were used to obtain corrected cerebral blood volume (CBV) and cerebral blood flow (CBF), and these were compared with CBV and CBF from an intravascular CA. Results T1-corrected CBV was significantly overestimated compared to MION CBV, while T1+T2*-correction yielded CBV values closer to the reference values. The pharmacokinetic and simplified biophysical methods showed similar results and underestimated CBV in tumors exhibiting strong T2* leakage effects. The combined method was effective for correcting T1 and T2* leakage effects across tumor types. Conclusions Correcting for both T1 and T2* leakage effects yielded more accurate measures of CBV. The combined correction method yields more reliable CBV measures than either correction method alone, but for certain brain tumor types (e.g., gliomas) the simplified biophysical method may provide a robust and computationally efficient alternative. PMID:26362714

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

Experiential Learning Methods, Simulation Complexity and Their Effects on Different Target Groups

ERIC Educational Resources Information Center

Kluge, Annette

2007-01-01

This article empirically supports the thesis that there is no clear and unequivocal argument in favor of simulations and experiential learning. Instead the effectiveness of simulation-based learning methods depends strongly on the target group's characteristics. Two methods of supporting experiential learning are compared in two different complex…

The Connection between Teaching Methods and Attribution Errors

ERIC Educational Resources Information Center

Wieman, Carl; Welsh, Ashley

2016-01-01

We collected data at a large, very selective public university on what math and science instructors felt was the biggest barrier to their students' learning. We also determined the extent of each instructor's use of research-based effective teaching methods. Instructors using fewer effective methods were more likely to say the greatest barrier to…

The Reliability, Impact, and Cost-Effectiveness of Value-Added Teacher Assessment Methods

ERIC Educational Resources Information Center

Yeh, Stuart S.

2012-01-01

This article reviews evidence regarding the intertemporal reliability of teacher rankings based on value-added methods. Value-added methods exhibit low reliability, yet are broadly supported by prominent educational researchers and are increasingly being used to evaluate and fire teachers. The article then presents a cost-effectiveness analysis…

A practical method of I-131 thyroid cancer therapy dose optimization using estimated effective renal clearance.

PubMed

Howard, Brandon A; James, Olga G; Perkins, Jennifer M; Pagnanelli, Robert A; Borges-Neto, Salvador; Reiman, Robert E

2017-01-01

In thyroid cancer patients with renal impairment or other complicating factors, it is important to maximize I-131 therapy efficacy while minimizing bone marrow and lung damage. We developed a web-based calculator based on a modified Benua and Leeper method to calculate the maximum I-131 dose to reduce the risk of these toxicities, based on the effective renal clearance of I-123 as measured from two whole-body I-123 scans, performed at 0 and 24 h post-administration.

Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

PubMed

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-05-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU.

Predicting the Effective Elastic Properties of Polymer Bonded Explosives based on Micromechanical Methods

NASA Astrophysics Data System (ADS)

Wang, Jingcheng; Luo, Jingrun

2018-04-01

Due to the extremely high particle volume fraction (greater than 85%) and damage feature of polymer bonded explosives (PBXs), conventional micromechanical methods lead to inaccurate estimates on their effective elastic properties. According to their manufacture characteristics, a multistep approach based on micromechanical methods is proposed. PBXs are treated as pseudo poly-crystal materials consisting of equivalent composite particles (explosive crystals with binder coating), rather than two-phase composites composed of explosive particles and binder matrix. Moduli of composite spheres are obtained by generalized self-consistent method first, and the self-consistent method is modified to calculate the effective moduli of PBX. Defects and particle size distribution are considered by Mori-Tanaka method. Results show that when the multistep approach is applied to PBX 9501, estimates are far more accurate than the conventional micromechanical results. The bulk modulus is 5.75% higher, and shear modulus is 5.78% lower than the experimental values. Further analyses discover that while particle volume fraction and the binder's property have significant influences on the effective moduli of PBX, the moduli of particles present minor influences. Investigation of another particle size distribution indicates that the use of more fine particles will enhance the effective moduli of PBX.

A Real-Time Thermal Self-Elimination Method for Static Mode Operated Freestanding Piezoresistive Microcantilever-Based Biosensors

PubMed Central

Ku, Yu-Fu; Huang, Long-Sun

2018-01-01

Here, we provide a method and apparatus for real-time compensation of the thermal effect of single free-standing piezoresistive microcantilever-based biosensors. The sensor chip contained an on-chip fixed piezoresistor that served as a temperature sensor, and a multilayer microcantilever with an embedded piezoresistor served as a biomolecular sensor. This method employed the calibrated relationship between the resistance and the temperature of piezoresistors to eliminate the thermal effect on the sensor, including the temperature coefficient of resistance (TCR) and bimorph effect. From experimental results, the method was verified to reduce the signal of thermal effect from 25.6 μV/°C to 0.3 μV/°C, which was approximately two orders of magnitude less than that before the processing of the thermal elimination method. Furthermore, the proposed approach and system successfully demonstrated its effective real-time thermal self-elimination on biomolecular detection without any thermostat device to control the environmental temperature. This method realizes the miniaturization of an overall measurement system of the sensor, which can be used to develop portable medical devices and microarray analysis platforms. PMID:29495574

Object-based change detection method using refined Markov random field

NASA Astrophysics Data System (ADS)

Peng, Daifeng; Zhang, Yongjun

2017-01-01

In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.

Graphene-based field-effect transistor biosensors

DOEpatents

Chen; , Junhong; Mao, Shun; Lu, Ganhua

2017-06-14

The disclosure provides a field-effect transistor (FET)-based biosensor and uses thereof. In particular, to FET-based biosensors using thermally reduced graphene-based sheets as a conducting channel decorated with nanoparticle-biomolecule conjugates. The present disclosure also relates to FET-based biosensors using metal nitride/graphene hybrid sheets. The disclosure provides a method for detecting a target biomolecule in a sample using the FET-based biosensor described herein.

Modelling cost-effectiveness of different vasectomy methods in India, Kenya, and Mexico.

PubMed

Seamans, Yancy; Harner-Jay, Claudia M

2007-07-13

Vasectomy is generally considered a safe and effective method of permanent contraception. The historical effectiveness of vasectomy has been questioned by recent research results indicating that the most commonly used method of vasectomy--simple ligation and excision (L and E)--appears to have a relatively high failure rate, with reported pregnancy rates as high as 4%. Updated methods such as fascial interposition (FI) and thermal cautery can lower the rate of failure but may require additional financial investments and may not be appropriate for low-resource clinics. In order to better compare the cost-effectiveness of these different vasectomy methods, we modelled the costs of different vasectomy methods using cost data collected in India, Kenya, and Mexico and effectiveness data from the latest published research. The costs associated with providing vasectomies were determined in each country through interviews with clinic staff. Costs collected were economic, direct, programme costs of fixed vasectomy services but did not include large capital expenses or general recurrent costs for the health care facility. Estimates of the time required to provide service were gained through interviews and training costs were based on the total costs of vasectomy training programmes in each country. Effectiveness data were obtained from recent published studies and comparative cost-effectiveness was determined using cost per couple years of protection (CYP). In each country, the labour to provide the vasectomy and follow-up services accounts for the greatest portion of the overall cost. Because each country almost exclusively used one vasectomy method at all of the clinics included in the study, we modelled costs based on the additional material, labour, and training costs required in each country. Using a model of a robust vasectomy program, more effective methods such as FI and thermal cautery reduce the cost per CYP of a vasectomy by $0.08-$0.55. Based on the results presented, more effective methods of vasectomy--including FI, thermal cautery, and thermal cautery combined with FI--are more cost-effective than L and E alone. Analysis shows that for a programme in which a minimum of 20 clients undergo vasectomies per month, the cost per CYP is reduced in all three countries by updated vasectomy methods.

Thermographic venous blood flow characterization with external cooling stimulation

NASA Astrophysics Data System (ADS)

Saxena, Ashish; Ng, E. Y. K.; Raman, Vignesh

2018-05-01

Experimental characterization of blood flow in a human forearm is done with the application of continuous external cooling based active thermography method. Qualitative and quantitative detection of the blood vessel in a thermal image is done, along with the evaluation of blood vessel diameter, blood flow direction, and velocity in the target blood vessel. Subtraction based image manipulation is performed to enhance the feature contrast of the thermal image acquired after the removal of external cooling. To demonstrate the effect of occlusion diseases (obstruction), an external cuff based occlusion is applied after the removal of cooling and its effect on the skin rewarming is studied. Using external cooling, a transit time method based blood flow velocity estimation is done. From the results obtained, it is evident that an external cooling based active thermography method can be used to develop a diagnosis tool for superficial blood vessel diseases.

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

Meta-analysis of two studies in the presence of heterogeneity with applications in rare diseases.

PubMed

Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat

2017-07-01

Random-effects meta-analyses are used to combine evidence of treatment effects from multiple studies. Since treatment effects may vary across trials due to differences in study characteristics, heterogeneity in treatment effects between studies must be accounted for to achieve valid inference. The standard model for random-effects meta-analysis assumes approximately normal effect estimates and a normal random-effects model. However, standard methods based on this model ignore the uncertainty in estimating the between-trial heterogeneity. In the special setting of only two studies and in the presence of heterogeneity, we investigate here alternatives such as the Hartung-Knapp-Sidik-Jonkman method (HKSJ), the modified Knapp-Hartung method (mKH, a variation of the HKSJ method) and Bayesian random-effects meta-analyses with priors covering plausible heterogeneity values; R code to reproduce the examples is presented in an appendix. The properties of these methods are assessed by applying them to five examples from various rare diseases and by a simulation study. Whereas the standard method based on normal quantiles has poor coverage, the HKSJ and mKH generally lead to very long, and therefore inconclusive, confidence intervals. The Bayesian intervals on the whole show satisfying properties and offer a reasonable compromise between these two extremes. © 2016 The Authors. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization and correction of cupping effect artefacts in cone beam CT

PubMed Central

Hunter, AK; McDavid, WD

2012-01-01

Objective The purpose of this study was to demonstrate and correct the cupping effect artefact that occurs owing to the presence of beam hardening and scatter radiation during image acquisition in cone beam CT (CBCT). Methods A uniform aluminium cylinder (6061) was used to demonstrate the cupping effect artefact on the Planmeca Promax 3D CBCT unit (Planmeca OY, Helsinki, Finland). The cupping effect was studied using a line profile plot of the grey level values using ImageJ software (National Institutes of Health, Bethesda, MD). A hardware-based correction method using copper pre-filtration was used to address this artefact caused by beam hardening and a software-based subtraction algorithm was used to address scatter contamination. Results The hardware-based correction used to address the effects of beam hardening suppressed the cupping effect artefact but did not eliminate it. The software-based correction used to address the effects of scatter resulted in elimination of the cupping effect artefact. Conclusion Compensating for the presence of beam hardening and scatter radiation improves grey level uniformity in CBCT. PMID:22378754

Correction for FDG PET dose extravasations: Monte Carlo validation and quantitative evaluation of patient studies.

PubMed

Silva-Rodríguez, Jesús; Aguiar, Pablo; Sánchez, Manuel; Mosquera, Javier; Luna-Vega, Víctor; Cortés, Julia; Garrido, Miguel; Pombar, Miguel; Ruibal, Alvaro

2014-05-01

Current procedure guidelines for whole body [18F]fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET) state that studies with visible dose extravasations should be rejected for quantification protocols. Our work is focused on the development and validation of methods for estimating extravasated doses in order to correct standard uptake value (SUV) values for this effect in clinical routine. One thousand three hundred sixty-seven consecutive whole body FDG-PET studies were visually inspected looking for extravasation cases. Two methods for estimating the extravasated dose were proposed and validated in different scenarios using Monte Carlo simulations. All visible extravasations were retrospectively evaluated using a manual ROI based method. In addition, the 50 patients with higher extravasated doses were also evaluated using a threshold-based method. Simulation studies showed that the proposed methods for estimating extravasated doses allow us to compensate the impact of extravasations on SUV values with an error below 5%. The quantitative evaluation of patient studies revealed that paravenous injection is a relatively frequent effect (18%) with a small fraction of patients presenting considerable extravasations ranging from 1% to a maximum of 22% of the injected dose. A criterion based on the extravasated volume and maximum concentration was established in order to identify this fraction of patients that might be corrected for paravenous injection effect. The authors propose the use of a manual ROI based method for estimating the effectively administered FDG dose and then correct SUV quantification in those patients fulfilling the proposed criterion.

Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on binary outcomes

PubMed Central

2018-01-01

Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (eg, dose or quantity of medication, income, or years of education). We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of continuous exposures on binary outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. We examined both the use of ordinary least squares to estimate the propensity function and the use of the covariate balancing propensity score algorithm. The use of methods based on the GPS was compared with the use of G‐computation. All methods resulted in essentially unbiased estimation of the population dose‐response function. However, GPS‐based weighting tended to result in estimates that displayed greater variability and had higher mean squared error when the magnitude of confounding was strong. Of the methods based on the GPS, covariate adjustment using the GPS tended to result in estimates with lower variability and mean squared error when the magnitude of confounding was strong. We illustrate the application of these methods by estimating the effect of average neighborhood income on the probability of death within 1 year of hospitalization for an acute myocardial infarction. PMID:29508424

Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on binary outcomes.

PubMed

Austin, Peter C

2018-05-20

Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (eg, dose or quantity of medication, income, or years of education). We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of continuous exposures on binary outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. We examined both the use of ordinary least squares to estimate the propensity function and the use of the covariate balancing propensity score algorithm. The use of methods based on the GPS was compared with the use of G-computation. All methods resulted in essentially unbiased estimation of the population dose-response function. However, GPS-based weighting tended to result in estimates that displayed greater variability and had higher mean squared error when the magnitude of confounding was strong. Of the methods based on the GPS, covariate adjustment using the GPS tended to result in estimates with lower variability and mean squared error when the magnitude of confounding was strong. We illustrate the application of these methods by estimating the effect of average neighborhood income on the probability of death within 1 year of hospitalization for an acute myocardial infarction. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Comparing team-based and mixed active-learning methods in an ambulatory care elective course.

PubMed

Zingone, Michelle M; Franks, Andrea S; Guirguis, Alexander B; George, Christa M; Howard-Thompson, Amanda; Heidel, Robert E

2010-11-10

To assess students' performance and perceptions of team-based and mixed active-learning methods in 2 ambulatory care elective courses, and to describe faculty members' perceptions of team-based learning. Using the 2 teaching methods, students' grades were compared. Students' perceptions were assessed through 2 anonymous course evaluation instruments. Faculty members who taught courses using the team-based learning method were surveyed regarding their impressions of team-based learning. The ambulatory care course was offered to 64 students using team-based learning (n = 37) and mixed active learning (n = 27) formats. The mean quality points earned were 3.7 (team-based learning) and 3.3 (mixed active learning), p < 0.001. Course evaluations for both courses were favorable. All faculty members who used the team-based learning method reported that they would consider using team-based learning in another course. Students were satisfied with both teaching methods; however, student grades were significantly higher in the team-based learning course. Faculty members recognized team-based learning as an effective teaching strategy for small-group active learning.

Parent-Based Adolescent Sexual Health Interventions And Effect on Communication Outcomes: A Systematic Review and Meta-Analyses

PubMed Central

Maria, Diane Santa; Markham, Christine; Mullen, Patricia Dolan; Bluethmann, Shirley

2016-01-01

Context Parent-based adolescent sexual health interventions aim to reduce sexual risk behaviors by bolstering parental protective behaviors. Few studies of theory use, methods, applications, delivery and outcomes of parent-based interventions have been conducted. Methods A systematic search of databases for the period 1998–2013 identified 28 published trials of U.S. parent-based interventions to examine theory use, setting, reach, delivery mode, dose and effects on parent-child communication. Established coding schemes were used to assess use of theory and describe methods employed to achieve behavioral change; intervention effects were explored in meta-analyses. Results Most interventions were conducted with minority parents in group sessions or via self-paced activities; interventions averaged seven hours, and most used theory extensively. Meta-analyses found improvements in sexual health communication: Analysis of 11 controlled trials indicated a medium effect on increasing communication (Cohen's d, 0.5), and analysis of nine trials found a large effect on increasing parental comfort with communication (0.7); effects were positive regardless of delivery mode or intervention dose. Intervention participants were 68% more likely than controls to report increased communication and 75% more likely to report increased comfort. Conclusions These findings point to gaps in the range of programs examined in published trials—for example, interventions for parents of sexual minority youth, programs for custodial grandparents and faith-based services. Yet they provide support for the effectiveness of parent-based interventions in improving communication. Innovative delivery approaches could extend programs' reach, and further research on sexual health outcomes would facilitate the meta-analysis of intervention effectiveness in improving adolescent sexual health behaviors. PMID:25639664

Application of qualitative biospeckle methods for the identification of scar region in a green orange

NASA Astrophysics Data System (ADS)

Retheesh, R.; Ansari, Md. Zaheer; Radhakrishnan, P.; Mujeeb, A.

2018-03-01

This study demonstrates the feasibility of a view-based method, the motion history image (MHI) to map biospeckle activity around the scar region in a green orange fruit. The comparison of MHI with the routine intensity-based methods validated the effectiveness of the proposed method. The results show that MHI can be implementated as an alternative online image processing tool in the biospeckle analysis.

Effective data validation of high-frequency data: time-point-, time-interval-, and trend-based methods.

PubMed

Horn, W; Miksch, S; Egghart, G; Popow, C; Paky, F

1997-09-01

Real-time systems for monitoring and therapy planning, which receive their data from on-line monitoring equipment and computer-based patient records, require reliable data. Data validation has to utilize and combine a set of fast methods to detect, eliminate, and repair faulty data, which may lead to life-threatening conclusions. The strength of data validation results from the combination of numerical and knowledge-based methods applied to both continuously-assessed high-frequency data and discontinuously-assessed data. Dealing with high-frequency data, examining single measurements is not sufficient. It is essential to take into account the behavior of parameters over time. We present time-point-, time-interval-, and trend-based methods for validation and repair. These are complemented by time-independent methods for determining an overall reliability of measurements. The data validation benefits from the temporal data-abstraction process, which provides automatically derived qualitative values and patterns. The temporal abstraction is oriented on a context-sensitive and expectation-guided principle. Additional knowledge derived from domain experts forms an essential part for all of these methods. The methods are applied in the field of artificial ventilation of newborn infants. Examples from the real-time monitoring and therapy-planning system VIE-VENT illustrate the usefulness and effectiveness of the methods.

Improvement of Accuracy for Background Noise Estimation Method Based on TPE-AE

NASA Astrophysics Data System (ADS)

Itai, Akitoshi; Yasukawa, Hiroshi

This paper proposes a method of a background noise estimation based on the tensor product expansion with a median and a Monte carlo simulation. We have shown that a tensor product expansion with absolute error method is effective to estimate a background noise, however, a background noise might not be estimated by using conventional method properly. In this paper, it is shown that the estimate accuracy can be improved by using proposed methods.

Normal response function method for mass and stiffness matrix updating using complex FRFs

NASA Astrophysics Data System (ADS)

Pradhan, S.; Modak, S. V.

2012-10-01

Quite often a structural dynamic finite element model is required to be updated so as to accurately predict the dynamic characteristics like natural frequencies and the mode shapes. Since in many situations undamped natural frequencies and mode shapes need to be predicted, it has generally been the practice in these situations to seek updating of only mass and stiffness matrix so as to obtain a reliable prediction model. Updating using frequency response functions (FRFs) has been one of the widely used approaches for updating, including updating of mass and stiffness matrices. However, the problem with FRF based methods, for updating mass and stiffness matrices, is that these methods are based on use of complex FRFs. Use of complex FRFs to update mass and stiffness matrices is not theoretically correct as complex FRFs are not only affected by these two matrices but also by the damping matrix. Therefore, in situations where updating of only mass and stiffness matrices using FRFs is required, the use of complex FRFs based updating formulation is not fully justified and would lead to inaccurate updated models. This paper addresses this difficulty and proposes an improved FRF based finite element model updating procedure using the concept of normal FRFs. The proposed method is a modified version of the existing response function method that is based on the complex FRFs. The effectiveness of the proposed method is validated through a numerical study of a simple but representative beam structure. The effect of coordinate incompleteness and robustness of method under presence of noise is investigated. The results of updating obtained by the improved method are compared with the existing response function method. The performance of the two approaches is compared for cases of light, medium and heavily damped structures. It is found that the proposed improved method is effective in updating of mass and stiffness matrices in all the cases of complete and incomplete data and with all levels and types of damping.

Financial time series analysis based on effective phase transfer entropy

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian; Lin, Aijing

2017-02-01

Transfer entropy is a powerful technique which is able to quantify the impact of one dynamic system on another system. In this paper, we propose the effective phase transfer entropy method based on the transfer entropy method. We use simulated data to test the performance of this method, and the experimental results confirm that the proposed approach is capable of detecting the information transfer between the systems. We also explore the relationship between effective phase transfer entropy and some variables, such as data size, coupling strength and noise. The effective phase transfer entropy is positively correlated with the data size and the coupling strength. Even in the presence of a large amount of noise, it can detect the information transfer between systems, and it is very robust to noise. Moreover, this measure is indeed able to accurately estimate the information flow between systems compared with phase transfer entropy. In order to reflect the application of this method in practice, we apply this method to financial time series and gain new insight into the interactions between systems. It is demonstrated that the effective phase transfer entropy can be used to detect some economic fluctuations in the financial market. To summarize, the effective phase transfer entropy method is a very efficient tool to estimate the information flow between systems.

Life prediction for high temperature low cycle fatigue of two kinds of titanium alloys based on exponential function

NASA Astrophysics Data System (ADS)

Mu, G. Y.; Mi, X. Z.; Wang, F.

2018-01-01

The high temperature low cycle fatigue tests of TC4 titanium alloy and TC11 titanium alloy are carried out under strain controlled. The relationships between cyclic stress-life and strain-life are analyzed. The high temperature low cycle fatigue life prediction model of two kinds of titanium alloys is established by using Manson-Coffin method. The relationship between failure inverse number and plastic strain range presents nonlinear in the double logarithmic coordinates. Manson-Coffin method assumes that they have linear relation. Therefore, there is bound to be a certain prediction error by using the Manson-Coffin method. In order to solve this problem, a new method based on exponential function is proposed. The results show that the fatigue life of the two kinds of titanium alloys can be predicted accurately and effectively by using these two methods. Prediction accuracy is within ±1.83 times scatter zone. The life prediction capability of new methods based on exponential function proves more effective and accurate than Manson-Coffin method for two kinds of titanium alloys. The new method based on exponential function can give better fatigue life prediction results with the smaller standard deviation and scatter zone than Manson-Coffin method. The life prediction results of two methods for TC4 titanium alloy prove better than TC11 titanium alloy.

Couple Graph Based Label Propagation Method for Hyperspectral Remote Sensing Data Classification

NASA Astrophysics Data System (ADS)

Wang, X. P.; Hu, Y.; Chen, J.

2018-04-01

Graph based semi-supervised classification method are widely used for hyperspectral image classification. We present a couple graph based label propagation method, which contains both the adjacency graph and the similar graph. We propose to construct the similar graph by using the similar probability, which utilize the label similarity among examples probably. The adjacency graph was utilized by a common manifold learning method, which has effective improve the classification accuracy of hyperspectral data. The experiments indicate that the couple graph Laplacian which unite both the adjacency graph and the similar graph, produce superior classification results than other manifold Learning based graph Laplacian and Sparse representation based graph Laplacian in label propagation framework.

Fe-based Fischer Tropsch Synthesis of biomass-derived syngas: Effect of synthesis method

Treesearch

Khiet Mai; Thomas Elder; Les Groom; James J. Spivey

2015-01-01

Two 100Fe/4Cu/4K/6Zn catalysts were prepared using two different methods: coprecipitation or impregnation methods. The effect of the preparation methods on the catalyst structure, catalytic properties, and the conversion of biomass-derived syngas via Fischer–Tropsch synthesis was investigated. Syngas was derived from gasifying Southern pine woodchips and had the...

Comparison of Standard Culture-Based Method to Culture-Independent Method for Evaluation of Hygiene Effects on the Hand Microbiome

PubMed Central

Leff, J.; Henley, J.; Tittl, J.; De Nardo, E.; Butler, M.; Griggs, R.; Fierer, N.

2017-01-01

ABSTRACT Hands play a critical role in the transmission of microbiota on one’s own body, between individuals, and on environmental surfaces. Effectively measuring the composition of the hand microbiome is important to hand hygiene science, which has implications for human health. Hand hygiene products are evaluated using standard culture-based methods, but standard test methods for culture-independent microbiome characterization are lacking. We sampled the hands of 50 participants using swab-based and glove-based methods prior to and following four hand hygiene treatments (using a nonantimicrobial hand wash, alcohol-based hand sanitizer [ABHS], a 70% ethanol solution, or tap water). We compared results among culture plate counts, 16S rRNA gene sequencing of DNA extracted directly from hands, and sequencing of DNA extracted from culture plates. Glove-based sampling yielded higher numbers of unique operational taxonomic units (OTUs) but had less diversity in bacterial community composition than swab-based sampling. We detected treatment-induced changes in diversity only by using swab-based samples (P < 0.001); we were unable to detect changes with glove-based samples. Bacterial cell counts significantly decreased with use of the ABHS (P < 0.05) and ethanol control (P < 0.05). Skin hydration at baseline correlated with bacterial abundances, bacterial community composition, pH, and redness across subjects. The importance of the method choice was substantial. These findings are important to ensure improvement of hand hygiene industry methods and for future hand microbiome studies. On the basis of our results and previously published studies, we propose recommendations for best practices in hand microbiome research. PMID:28351915

Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR

PubMed Central

Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

2010-01-01

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis. PMID:22399894

Intelligent gearbox diagnosis methods based on SVM, wavelet lifting and RBR.

PubMed

Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

2010-01-01

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis.

Effects of Training Leaders in Needs-Based Methods of Running Meetings

ERIC Educational Resources Information Center

Douglass, Emily M.; Malouff, John M.; Rangan, Julie A.

2015-01-01

This study evaluated the effects of brief training in how to lead organizational meetings. The training was based on an attendee-needs-based model of running meetings. Twelve mid-level managers completed the training. The study showed a significant pre to post increase in the number of needs-based behaviors displayed by meeting leaders and in…

Comparison of Standardized Test Scores from Traditional Classrooms and Those Using Problem-Based Learning

ERIC Educational Resources Information Center

Needham, Martha Elaine

2010-01-01

This research compares differences between standardized test scores in problem-based learning (PBL) classrooms and a traditional classroom for 6th grade students using a mixed-method, quasi-experimental and qualitative design. The research shows that problem-based learning is as effective as traditional teaching methods on standardized tests. The…

Modeling Interactions Among Turbulence, Gas-Phase Chemistry, Soot and Radiation Using Transported PDF Methods

NASA Astrophysics Data System (ADS)

Haworth, Daniel

2013-11-01

The importance of explicitly accounting for the effects of unresolved turbulent fluctuations in Reynolds-averaged and large-eddy simulations of chemically reacting turbulent flows is increasingly recognized. Transported probability density function (PDF) methods have emerged as one of the most promising modeling approaches for this purpose. In particular, PDF methods provide an elegant and effective resolution to the closure problems that arise from averaging or filtering terms that correspond to nonlinear point processes, including chemical reaction source terms and radiative emission. PDF methods traditionally have been associated with studies of turbulence-chemistry interactions in laboratory-scale, atmospheric-pressure, nonluminous, statistically stationary nonpremixed turbulent flames; and Lagrangian particle-based Monte Carlo numerical algorithms have been the predominant method for solving modeled PDF transport equations. Recent advances and trends in PDF methods are reviewed and discussed. These include advances in particle-based algorithms, alternatives to particle-based algorithms (e.g., Eulerian field methods), treatment of combustion regimes beyond low-to-moderate-Damköhler-number nonpremixed systems (e.g., premixed flamelets), extensions to include radiation heat transfer and multiphase systems (e.g., soot and fuel sprays), and the use of PDF methods as the basis for subfilter-scale modeling in large-eddy simulation. Examples are provided that illustrate the utility and effectiveness of PDF methods for physics discovery and for applications to practical combustion systems. These include comparisons of results obtained using the PDF method with those from models that neglect unresolved turbulent fluctuations in composition and temperature in the averaged or filtered chemical source terms and/or the radiation heat transfer source terms. In this way, the effects of turbulence-chemistry-radiation interactions can be isolated and quantified.

Including α s1 casein gene information in genomic evaluations of French dairy goats.

PubMed

Carillier-Jacquin, Céline; Larroque, Hélène; Robert-Granié, Christèle

2016-08-04

Genomic best linear unbiased prediction methods assume that all markers explain the same fraction of the genetic variance and do not account effectively for genes with major effects such as the α s1 casein polymorphism in dairy goats. In this study, we investigated methods to include the available α s1 casein genotype effect in genomic evaluations of French dairy goats. First, the α s1 casein genotype was included as a fixed effect in genomic evaluation models based only on bucks that were genotyped at the α s1 casein locus. Less than 1 % of the females with phenotypes were genotyped at the α s1 casein gene. Thus, to incorporate these female phenotypes in the genomic evaluation, two methods that allowed for this large number of missing α s1 casein genotypes were investigated. Probabilities for each possible α s1 casein genotype were first estimated for each female of unknown genotype based on iterative peeling equations. The second method is based on a multiallelic gene content approach. For each model tested, we used three datasets each divided into a training and a validation set: (1) two-breed population (Alpine + Saanen), (2) Alpine population, and (3) Saanen population. The α s1 casein genotype had a significant effect on milk yield, fat content and protein content. Including an α s1 casein effect in genetic and genomic evaluations based only on male known α s1 casein genotypes improved accuracies (from 6 to 27 %). In genomic evaluations based on all female phenotypes, the gene content approach performed better than the other tested methods but the improvement in accuracy was only slightly better (from 1 to 14 %) than that of a genomic model without the α s1 casein effect. Including the α s1 casein effect in a genomic evaluation model for French dairy goats is possible and useful to improve accuracy. Difficulties in predicting the genotypes for ungenotyped animals limited the improvement in accuracy of the obtained estimated breeding values.

Use of a problem-based learning teaching model for undergraduate medical and nursing education: a systematic review and meta-analysis

PubMed Central

Sayyah, Mehdi; Shirbandi, Kiarash; Saki-Malehi, Amal; Rahim, Fakher

2017-01-01

Objectives The aim of this systematic review and meta-analysis was to evaluate the problem-based learning (PBL) method as an alternative to conventional educational methods in Iranian undergraduate medical courses. Materials and methods We systematically searched international datasets banks, including PubMed, Scopus, and Embase, and internal resources of banks, including MagirIran, IranMedex, IranDoc, and Scientific Information Database (SID), using appropriate search terms, such as “PBL”, “problem-based learning”, “based on problems”, “active learning”, and“ learner centered”, to identify PBL studies, and these were combined with other key terms such as “medical”, “undergraduate”, “Iranian”, “Islamic Republic of Iran”, “I.R. of Iran”, and “Iran”. The search included the period from 1980 to 2016 with no language limits. Results Overall, a total of 1,057 relevant studies were initially found, of which 21 studies were included in the systematic review and meta-analysis. Of the 21 studies, 12 (57.14%) had a high methodological quality. Considering the pooled effect size data, there was a significant difference in the scores (standardized mean difference [SMD]=0.80, 95% CI [0.52, 1.08], P<0.000) in favor of PBL, compared with the lecture-based method. Subgroup analysis revealed that using PBL alone is more favorable compared to using a mixed model with other learning methods such as lecture-based learning (LBL). Conclusion The results of this systematic review showed that using PBL may have a positive effect on the academic achievement of undergraduate medical courses. The results suggest that teachers and medical education decision makers give more attention on using this method for effective and proper training. PMID:29042827

The Research of Multiple Attenuation Based on Feedback Iteration and Independent Component Analysis

NASA Astrophysics Data System (ADS)

Xu, X.; Tong, S.; Wang, L.

2017-12-01

How to solve the problem of multiple suppression is a difficult problem in seismic data processing. The traditional technology for multiple attenuation is based on the principle of the minimum output energy of the seismic signal, this criterion is based on the second order statistics, and it can't achieve the multiple attenuation when the primaries and multiples are non-orthogonal. In order to solve the above problems, we combine the feedback iteration method based on the wave equation and the improved independent component analysis (ICA) based on high order statistics to suppress the multiple waves. We first use iterative feedback method to predict the free surface multiples of each order. Then, in order to predict multiples from real multiple in amplitude and phase, we design an expanded pseudo multi-channel matching filtering method to get a more accurate matching multiple result. Finally, we present the improved fast ICA algorithm which is based on the maximum non-Gauss criterion of output signal to the matching multiples and get better separation results of the primaries and the multiples. The advantage of our method is that we don't need any priori information to the prediction of the multiples, and can have a better separation result. The method has been applied to several synthetic data generated by finite-difference model technique and the Sigsbee2B model multiple data, the primaries and multiples are non-orthogonal in these models. The experiments show that after three to four iterations, we can get the perfect multiple results. Using our matching method and Fast ICA adaptive multiple subtraction, we can not only effectively preserve the effective wave energy in seismic records, but also can effectively suppress the free surface multiples, especially the multiples related to the middle and deep areas.

Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Han, Yan; Li, Qingchen; Xu, Wei

2017-02-01

The acceleration of economic globalization gradually shows the linkage of the stock markets in various counties and produces a risk conduction effect. An asymmetric MF-DCCA method is conducted based on the different directions of risk conduction (DMF-ADCCA) and by using the traditional MF-DCCA. To ensure that the empirical results are more objective and robust, this study selects the stock index data of China, the US, Germany, India, and Brazil from January 2011 to September 2014 using the asymmetric MF-DCCA method based on different risk conduction effects and nonlinear Granger causality tests to study the asymmetric cross-correlation between domestic and foreign stock markets. Empirical results indicate the existence of a bidirectional conduction effect between domestic and foreign stock markets, and the greater influence degree from foreign countries to domestic market compared with that from the domestic market to foreign countries.

Measurement of Crystalline Silica Aerosol Using Quantum Cascade Laser-Based Infrared Spectroscopy.

PubMed

Wei, Shijun; Kulkarni, Pramod; Ashley, Kevin; Zheng, Lina

2017-10-24

Inhalation exposure to airborne respirable crystalline silica (RCS) poses major health risks in many industrial environments. There is a need for new sensitive instruments and methods for in-field or near real-time measurement of crystalline silica aerosol. The objective of this study was to develop an approach, using quantum cascade laser (QCL)-based infrared spectroscopy (IR), to quantify airborne concentrations of RCS. Three sampling methods were investigated for their potential for effective coupling with QCL-based transmittance measurements: (i) conventional aerosol filter collection, (ii) focused spot sample collection directly from the aerosol phase, and (iii) dried spot obtained from deposition of liquid suspensions. Spectral analysis methods were developed to obtain IR spectra from the collected particulate samples in the range 750-1030 cm -1 . The new instrument was calibrated and the results were compared with standardized methods based on Fourier transform infrared (FTIR) spectrometry. Results show that significantly lower detection limits for RCS (≈330 ng), compared to conventional infrared methods, could be achieved with effective microconcentration and careful coupling of the particulate sample with the QCL beam. These results offer promise for further development of sensitive filter-based laboratory methods and portable sensors for near real-time measurement of crystalline silica aerosol.

Numerical modeling of the load effect on PZT-induced guided wave for load compensation of damage detection

NASA Astrophysics Data System (ADS)

Sun, Hu; Zhang, Aijia; Wang, Yishou; Qing, Xinlin P.

2017-04-01

Guided wave-based structural health monitoring (SHM) has been given considerable attention and widely studied for large-scale aircraft structures. Nevertheless, it is difficult to apply SHM systems on board or online, for which one of the most serious reasons is the environmental influence. Load is one fact that affects not only the host structure, in which guided wave propagates, but also the PZT, by which guided wave is transmitted and received. In this paper, numerical analysis using finite element method is used to study the load effect on guided wave acquired by PZT. The static loads with different grades are considered to analyze its effect on guided wave signals that PZT transmits and receives. Based on the variation trend of guided waves versus load, a load compensation method is developed to eliminate effects of load in the process of damage detection. The probabilistic reconstruction algorithm based on the signal variation of transmitter-receiver path is employed to identify the damage. Numerical tests is conducted to verify the feasibility and effectiveness of the given method.

A new experimental method for the determination of the effective orifice area based on the acoustical source term

NASA Astrophysics Data System (ADS)

Kadem, L.; Knapp, Y.; Pibarot, P.; Bertrand, E.; Garcia, D.; Durand, L. G.; Rieu, R.

2005-12-01

The effective orifice area (EOA) is the most commonly used parameter to assess the severity of aortic valve stenosis as well as the performance of valve substitutes. Particle image velocimetry (PIV) may be used for in vitro estimation of valve EOA. In the present study, we propose a new and simple method based on Howe’s developments of Lighthill’s aero-acoustic theory. This method is based on an acoustical source term (AST) to estimate the EOA from the transvalvular flow velocity measurements obtained by PIV. The EOAs measured by the AST method downstream of three sharp-edged orifices were in excellent agreement with the EOAs predicted from the potential flow theory used as the reference method in this study. Moreover, the AST method was more accurate than other conventional PIV methods based on streamlines, inflexion point or vorticity to predict the theoretical EOAs. The superiority of the AST method is likely due to the nonlinear form of the AST. There was also an excellent agreement between the EOAs measured by the AST method downstream of the three sharp-edged orifices as well as downstream of a bioprosthetic valve with those obtained by the conventional clinical method based on Doppler-echocardiographic measurements of transvalvular velocity. The results of this study suggest that this new simple PIV method provides an accurate estimation of the aortic valve flow EOA. This new method may thus be used as a reference method to estimate the EOA in experimental investigation of the performance of valve substitutes and to validate Doppler-echocardiographic measurements under various physiologic and pathologic flow conditions.

High-efficient and high-content cytotoxic recording via dynamic and continuous cell-based impedance biosensor technology.

PubMed

Hu, Ning; Fang, Jiaru; Zou, Ling; Wan, Hao; Pan, Yuxiang; Su, Kaiqi; Zhang, Xi; Wang, Ping

2016-10-01

Cell-based bioassays were effective method to assess the compound toxicity by cell viability, and the traditional label-based methods missed much information of cell growth due to endpoint detection, while the higher throughputs were demanded to obtain dynamic information. Cell-based biosensor methods can dynamically and continuously monitor with cell viability, however, the dynamic information was often ignored or seldom utilized in the toxin and drug assessment. Here, we reported a high-efficient and high-content cytotoxic recording method via dynamic and continuous cell-based impedance biosensor technology. The dynamic cell viability, inhibition ratio and growth rate were derived from the dynamic response curves from the cell-based impedance biosensor. The results showed that the biosensors has the dose-dependent manners to diarrhetic shellfish toxin, okadiac acid based on the analysis of the dynamic cell viability and cell growth status. Moreover, the throughputs of dynamic cytotoxicity were compared between cell-based biosensor methods and label-based endpoint methods. This cell-based impedance biosensor can provide a flexible, cost and label-efficient platform of cell viability assessment in the shellfish toxin screening fields.

Source separation of municipal solid waste: The effects of different separation methods and citizens' inclination-case study of Changsha, China.

PubMed

Chen, Haibin; Yang, Yan; Jiang, Wei; Song, Mengjie; Wang, Ying; Xiang, Tiantian

2017-02-01

A case study on the source separation of municipal solid waste (MSW) was performed in Changsha, the capital city of Hunan Province, China. The objective of this study is to analyze the effects of different separation methods and compare their effects with citizens' attitudes and inclination. An effect evaluation method based on accuracy rate and miscellany rate was proposed to study the performance of different separation methods. A large-scale questionnaire survey was conducted to determine citizens' attitudes and inclination toward source separation. Survey result shows that the vast majority of respondents hold consciously positive attitudes toward participation in source separation. Moreover, the respondents ignore the operability of separation methods and would rather choose the complex separation method involving four or more subclassed categories. For the effects of separation methods, the site experiment result demonstrates that the relatively simple separation method involving two categories (food waste and other waste) achieves the best effect with the highest accuracy rate (83.1%) and the lowest miscellany rate (16.9%) among the proposed experimental alternatives. The outcome reflects the inconsistency between people's environmental awareness and behavior. Such inconsistency and conflict may be attributed to the lack of environmental knowledge. Environmental education is assumed to be a fundamental solution to improve the effect of source separation of MSW in Changsha. Important management tips on source separation, including the reformation of the current pay-as-you-throw (PAYT) system, are presented in this work. A case study on the source separation of municipal solid waste was performed in Changsha. An effect evaluation method based on accuracy rate and miscellany rate was proposed to study the performance of different separation methods. The site experiment result demonstrates that the two-category (food waste and other waste) method achieves the best effect. The inconsistency between people's inclination and the effect of source separation exists. The proposed method can be expanded to other cities to determine the most effective separation method during planning stages or to evaluate the performance of running source separation systems.

Alternative evaluation of innovations’ effectiveness in mechanical engineering

NASA Astrophysics Data System (ADS)

Puryaev, A. S.

2017-09-01

The aim of present work is approbation of the developed technique for assessing innovations’ effectiveness. We demonstrate an alternative assessment of innovations’ effectiveness (innovation projects) in mechanical engineering on illustrative example. It is proposed as an alternative to the traditional method technique based on the value concept and the method of “Cash flow”.

Appreciative Accreditation: A Mixed Methods Explanatory Study of Appreciative Inquiry-Based Institutional Effectiveness Results in Higher Education

ERIC Educational Resources Information Center

Thibodeau, John

2011-01-01

This study examined the effects of using Appreciative Inquiry in accreditation and related institutional effectiveness activities within higher education. Using an explanatory participant-selection mixed methods approach, qualitative data from a series of interviews were used to explain the experiences of individuals identified from quantitative…

An Organic Vertical Field-Effect Transistor with Underside-Doped Graphene Electrodes.

PubMed

Kim, Jong Su; Kim, Beom Joon; Choi, Young Jin; Lee, Moo Hyung; Kang, Moon Sung; Cho, Jeong Ho

2016-06-01

High-performance vertical field-effect transistors are developed, which are based on graphene electrodes doped using the underside doping method. The underside doping method enables effective tuning of the graphene work function while maintaining the surface properties of the pristine graphene. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Food, Fun and Fitness Internet program for girls: influencing log-on rate

USDA-ARS?s Scientific Manuscript database

Internet-based interventions hold promise as an effective channel for reaching large numbers of youth. However, log-on rates, a measure of program dose, have been highly variable. Methods to enhance log-on rate are needed. Incentives may be an effective method. This paper reports the effect of reinf...

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

A meta-analytic review of self-reported, clinician-rated, and performance-based motivation measures in schizophrenia: Are we measuring the same "stuff"?

PubMed

Luther, Lauren; Firmin, Ruth L; Lysaker, Paul H; Minor, Kyle S; Salyers, Michelle P

2018-04-07

An array of self-reported, clinician-rated, and performance-based measures has been used to assess motivation in schizophrenia; however, the convergent validity evidence for these motivation assessment methods is mixed. The current study is a series of meta-analyses that summarize the relationships between methods of motivation measurement in 45 studies of people with schizophrenia. The overall mean effect size between self-reported and clinician-rated motivation measures (r = 0.27, k = 33) was significant, positive, and approaching medium in magnitude, and the overall effect size between performance-based and clinician-rated motivation measures (r = 0.21, k = 11) was positive, significant, and small in magnitude. The overall mean effect size between self-reported and performance-based motivation measures was negligible and non-significant (r = -0.001, k = 2), but this meta-analysis was underpowered. Findings suggest modest convergent validity between clinician-rated and both self-reported and performance-based motivation measures, but additional work is needed to clarify the convergent validity between self-reported and performance-based measures. Further, there is likely more variability than similarity in the underlying construct that is being assessed across the three methods, particularly between the performance-based and other motivation measurement types. These motivation assessment methods should not be used interchangeably, and measures should be more precisely described as the specific motivational construct or domain they are capturing. Copyright © 2018 Elsevier Ltd. All rights reserved.

Novel surface modification of polymer-based separation media controlling separation selectivity, retentivity and generation of electroosmotic flow.

PubMed

Hosoya, Ken; Kubo, Takuya; Takahashi, Katsuo; Ikegami, Tohru; Tanaka, Nobuo

2002-12-06

Uniformly sized packing materials based on synthetic polymer particles for high-performance liquid chromatography (HPLC) and capillary electrochromatography (CEC) have been prepared from polymerization mixtures containing methacrylic acid (MAA) as a functional monomer and by using a novel surface modification method. This "dispersion method" affords effectively modified separation media. Both the amount of MAA utilized in the preparation and reaction time affect the selectivity of chromatographic separation in both the HPLC and the CEC mode and electroosmotic flow. This detailed study revealed that the dispersion method effectively modified internal surface of macroporous separation media and, based on the amount of MAA introduced, exclusion mechanism for the separation of certain solutes could be observed.

A Study on Markerless AR-Based Infant Education System Using CBIR

NASA Astrophysics Data System (ADS)

Lim, Ji-Hoon; Kim, Seoksoo

Block play is widely known to be effective to help a child develop emotionally and physically based on learning by a sense of sight and touch. But block play can not expect to have learning effects through a sense of hearing. Therefore, in this study, such limitations are overcome by a method that recognizes an object made up of blocks, not a marker-based method generally used for an AR environment, a matching technology enabling an object to be perceived in every direction, and a technology combining images of the real world with 2D/3D images/pictures/sounds of a similar object. Also, an education system for children aged 3~5 is designed to implement markerless AR with the CBIR method.

AUV Positioning Method Based on Tightly Coupled SINS/LBL for Underwater Acoustic Multipath Propagation.

PubMed

Zhang, Tao; Shi, Hongfei; Chen, Liping; Li, Yao; Tong, Jinwu

2016-03-11

This paper researches an AUV (Autonomous Underwater Vehicle) positioning method based on SINS (Strapdown Inertial Navigation System)/LBL (Long Base Line) tightly coupled algorithm. This algorithm mainly includes SINS-assisted searching method of optimum slant-range of underwater acoustic propagation multipath, SINS/LBL tightly coupled model and multi-sensor information fusion algorithm. Fuzzy correlation peak problem of underwater LBL acoustic propagation multipath could be solved based on SINS positional information, thus improving LBL positional accuracy. Moreover, introduction of SINS-centered LBL locating information could compensate accumulative AUV position error effectively and regularly. Compared to loosely coupled algorithm, this tightly coupled algorithm can still provide accurate location information when there are fewer than four available hydrophones (or within the signal receiving range). Therefore, effective positional calibration area of tightly coupled system based on LBL array is wider and has higher reliability and fault tolerance than loosely coupled. It is more applicable to AUV positioning based on SINS/LBL.

AUV Positioning Method Based on Tightly Coupled SINS/LBL for Underwater Acoustic Multipath Propagation

PubMed Central

Zhang, Tao; Shi, Hongfei; Chen, Liping; Li, Yao; Tong, Jinwu

2016-01-01

This paper researches an AUV (Autonomous Underwater Vehicle) positioning method based on SINS (Strapdown Inertial Navigation System)/LBL (Long Base Line) tightly coupled algorithm. This algorithm mainly includes SINS-assisted searching method of optimum slant-range of underwater acoustic propagation multipath, SINS/LBL tightly coupled model and multi-sensor information fusion algorithm. Fuzzy correlation peak problem of underwater LBL acoustic propagation multipath could be solved based on SINS positional information, thus improving LBL positional accuracy. Moreover, introduction of SINS-centered LBL locating information could compensate accumulative AUV position error effectively and regularly. Compared to loosely coupled algorithm, this tightly coupled algorithm can still provide accurate location information when there are fewer than four available hydrophones (or within the signal receiving range). Therefore, effective positional calibration area of tightly coupled system based on LBL array is wider and has higher reliability and fault tolerance than loosely coupled. It is more applicable to AUV positioning based on SINS/LBL. PMID:26978361

The Effectiveness of Problem-Based Instruction: A Comparative Study of Instructional Methods and Student Characteristics

ERIC Educational Resources Information Center

Mergendoller, John R.; Maxwell, Nan L.; Bellisimo, Yolanda

2006-01-01

This study compared the effectiveness of problem-based learning (PBL) and traditional instructional approaches in developing high-school students' macroeconomics knowledge and examined whether PBL was differentially effective with students demonstrating different levels of four aptitudes: verbal ability, interest in economics, preference for group…

Problem Based Learning: An Alternative to Traditional Education.

ERIC Educational Resources Information Center

Rouse, Michael W.

1990-01-01

A growing number of health care educators are concerned with the effectiveness of the traditional approach for educating health care practitioners. The problem-based learning approach has been advocated as an effective alternative method for addressing many current concerns and for producing a more effective doctor. (Author/MSE)

The Temporal Effect of Training Utility Perceptions on Adopting a Trained Method: The Role of Perceived Organizational Support

ERIC Educational Resources Information Center

Madera, Juan M.; Steele, Stacey T.; Beier, Margaret

2011-01-01

The current study examined the temporal effect of perceived training utility on adoption of a trained method and how perceived organizational support influences the relationship between perceived training utility perceptions and adoption of a trained method. With the use of a correlational-survey-based design, this longitudinal study required…

Effective and cost-effective clinical trial recruitment strategies for postmenopausal women in a community-based, primary care setting.

PubMed

Butt, Debra A; Lock, Michael; Harvey, Bart J

2010-09-01

Little evidence exists to guide investigators on the effectiveness and cost-effectiveness of various recruitment strategies in primary care research. The purpose of this study is to describe the effectiveness and cost-effectiveness of eight clinical trial recruitment methods for postmenopausal women in a community-based setting. A retrospective analysis of the yield and cost of eight different recruitment methods: 1) family physician (FP) recruiters, 2) FP referrals, 3) community presentations, 4) community events, 5) newsletters, 6) direct mailings, 7) posters, and 8) newspaper advertisements that were used to recruit postmenopausal women to a randomized clinical trial (RCT) evaluating the effectiveness of gabapentin in treating hot flashes. We recruited 197 postmenopausal women from a total of 904 screened, with 291 of the remainder being ineligible and 416 declining to participate. Of the 904 women screened, 34 (3.8%) were from FP recruiters and 35 (3.9%) were from other FP referrals while 612 (67.7%) resulted from newspaper advertisements. Of the 197 women enrolled, 141 (72%) were from newspaper advertisements, with 26 (13%) following next from posters. Word of mouth was identified as an additional unanticipated study recruitment strategy. Metropolitan newspaper advertising at $112.73 (Canadian) per enrolled participant and posters at $119.98 were found to be cost-effective recruitment methods. Newspaper advertisements were the most successful method to recruit postmenopausal women into a community-based, primary care RCT. Copyright 2010 Elsevier Inc. All rights reserved.

Chatter detection in milling process based on VMD and energy entropy

NASA Astrophysics Data System (ADS)

Liu, Changfu; Zhu, Lida; Ni, Chenbing

2018-05-01

This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.

High dynamic range image acquisition based on multiplex cameras

NASA Astrophysics Data System (ADS)

Zeng, Hairui; Sun, Huayan; Zhang, Tinghua

2018-03-01

High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

PubMed Central

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods

ERIC Educational Resources Information Center

MacKinnon, David P.; Lockwood, Chondra M.; Williams, Jason

2004-01-01

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal…

Stokes vector based interpolation method to improve the efficiency of bio-inspired polarization-difference imaging in turbid media

NASA Astrophysics Data System (ADS)

Guan, Jinge; Ren, Wei; Cheng, Yaoyu

2018-04-01

We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.

Image fusion based on Bandelet and sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Jiuxing; Zhang, Wei; Li, Xuzhi

2018-04-01

Bandelet transform could acquire geometric regular direction and geometric flow, sparse representation could represent signals with as little as possible atoms on over-complete dictionary, both of which could be used to image fusion. Therefore, a new fusion method is proposed based on Bandelet and Sparse Representation, to fuse Bandelet coefficients of multi-source images and obtain high quality fusion effects. The test are performed on remote sensing images and simulated multi-focus images, experimental results show that the performance of new method is better than tested methods according to objective evaluation indexes and subjective visual effects.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

The Effects of Using Jigsaw Method Based on Cooperative Learning Model in the Undergraduate Science Laboratory Practices

ERIC Educational Resources Information Center

Karacop, Ataman

2017-01-01

The main aim of the present study is to determine the influence of a Jigsaw method based on cooperative learning and a confirmatory laboratory method on prospective science teachers' achievements of physics in science teaching laboratory practice courses. The sample of this study consisted of 33 female and 15 male third-grade prospective science…

Examining Information Problem-Solving, Knowledge, and Application Gains within Two Instructional Methods: Problem-Based and Computer-Mediated Participatory Simulation

ERIC Educational Resources Information Center

Newell, Terrance S.

2008-01-01

This study compared the effectiveness of two instructional methods--problem-based instruction within a face-to-face context and computer-mediated participatory simulation--in increasing students' content knowledge and application gains in the area of information problem-solving. The instructional methods were implemented over a four-week period. A…

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

PubMed Central

Liu, Fang; Shen, Changqing; He, Qingbo; Zhang, Ao; Liu, Yongbin; Kong, Fanrang

2014-01-01

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. PMID:24803197

[Bayesian approach for the cost-effectiveness evaluation of healthcare technologies].

PubMed

Berchialla, Paola; Gregori, Dario; Brunello, Franco; Veltri, Andrea; Petrinco, Michele; Pagano, Eva

2009-01-01

The development of Bayesian statistical methods for the assessment of the cost-effectiveness of health care technologies is reviewed. Although many studies adopt a frequentist approach, several authors have advocated the use of Bayesian methods in health economics. Emphasis has been placed on the advantages of the Bayesian approach, which include: (i) the ability to make more intuitive and meaningful inferences; (ii) the ability to tackle complex problems, such as allowing for the inclusion of patients who generate no cost, thanks to the availability of powerful computational algorithms; (iii) the importance of a full use of quantitative and structural prior information to produce realistic inferences. Much literature comparing the cost-effectiveness of two treatments is based on the incremental cost-effectiveness ratio. However, new methods are arising with the purpose of decision making. These methods are based on a net benefits approach. In the present context, the cost-effectiveness acceptability curves have been pointed out to be intrinsically Bayesian in their formulation. They plot the probability of a positive net benefit against the threshold cost of a unit increase in efficacy.A case study is presented in order to illustrate the Bayesian statistics in the cost-effectiveness analysis. Emphasis is placed on the cost-effectiveness acceptability curves. Advantages and disadvantages of the method described in this paper have been compared to frequentist methods and discussed.

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus.

PubMed

Andrew, R L; Peakall, R; Wallis, I R; Wood, J T; Knight, E J; Foley, W J

2005-12-01

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.

Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

A low-cost rapid upper limb assessment method in manual assembly line based on somatosensory interaction technology

NASA Astrophysics Data System (ADS)

Jiang, Shengqian; Liu, Peng; Fu, Danni; Xue, Yiming; Luo, Wentao; Wang, Mingjie

2017-04-01

As an effective survey method of upper limb disorder, rapid upper limb assessment (RULA) has a wide application in industry period. However, it is very difficult to rapidly evaluate operator's postures in real complex work place. In this paper, a real-time RULA method is proposed to accurately assess the potential risk of operator's postures based on the somatosensory data collected from Kinect sensor, which is a line of motion sensing input devices by Microsoft. First, the static position information of each bone point is collected to obtain the effective angles of body parts based on the calculating methods based on joints angles. Second, a whole RULA score of body is obtained to assess the risk level of current posture in real time. Third, those RULA scores are compared with the results provided by a group of ergonomic practitionerswho were asked to observe the same static postures. All the experiments were carried out in an ergonomic lab. The results show that the proposed method can detect operator's postures more accurately. What's more, this method is applied in a real-time condition which can improve the evaluating efficiency.

SU-E-I-08: Investigation of Deconvolution Methods for Blocker-Based CBCT Scatter Estimation

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

Zhao, C; Jin, M; Ouyang, L

2015-06-15

Purpose: To investigate whether deconvolution methods can improve the scatter estimation under different blurring and noise conditions for blocker-based scatter correction methods for cone-beam X-ray computed tomography (CBCT). Methods: An “ideal” projection image with scatter was first simulated for blocker-based CBCT data acquisition by assuming no blurring effect and no noise. The ideal image was then convolved with long-tail point spread functions (PSF) with different widths to mimic the blurring effect from the finite focal spot and detector response. Different levels of noise were also added. Three deconvolution Methods: 1) inverse filtering; 2) Wiener; and 3) Richardson-Lucy, were used tomore » recover the scatter signal in the blocked region. The root mean square error (RMSE) of estimated scatter serves as a quantitative measure for the performance of different methods under different blurring and noise conditions. Results: Due to the blurring effect, the scatter signal in the blocked region is contaminated by the primary signal in the unblocked region. The direct use of the signal in the blocked region to estimate scatter (“direct method”) leads to large RMSE values, which increase with the increased width of PSF and increased noise. The inverse filtering is very sensitive to noise and practically useless. The Wiener and Richardson-Lucy deconvolution methods significantly improve scatter estimation compared to the direct method. For a typical medium PSF and medium noise condition, both methods (∼20 RMSE) can achieve 4-fold improvement over the direct method (∼80 RMSE). The Wiener method deals better with large noise and Richardson-Lucy works better on wide PSF. Conclusion: We investigated several deconvolution methods to recover the scatter signal in the blocked region for blocker-based scatter correction for CBCT. Our simulation results demonstrate that Wiener and Richardson-Lucy deconvolution can significantly improve the scatter estimation compared to the direct method.« less

A biomolecular detection method based on charge pumping in a nanogap embedded field-effect-transistor biosensor

NASA Astrophysics Data System (ADS)

Kim, Sungho; Ahn, Jae-Hyuk; Park, Tae Jung; Lee, Sang Yup; Choi, Yang-Kyu

2009-06-01

A unique direct electrical detection method of biomolecules, charge pumping, was demonstrated using a nanogap embedded field-effect-transistor (FET). With aid of a charge pumping method, sensitivity can fall below the 1 ng/ml concentration regime in antigen-antibody binding of an avian influenza case. Biomolecules immobilized in the nanogap are mainly responsible for the acute changes of the interface trap density due to modulation of the energy level of the trap. This finding is supported by a numerical simulation. The proposed detection method for biomolecules using a nanogap embedded FET represents a foundation for a chip-based biosensor capable of high sensitivity.

GEE-based SNP set association test for continuous and discrete traits in family-based association studies.

PubMed

Wang, Xuefeng; Lee, Seunggeun; Zhu, Xiaofeng; Redline, Susan; Lin, Xihong

2013-12-01

Family-based genetic association studies of related individuals provide opportunities to detect genetic variants that complement studies of unrelated individuals. Most statistical methods for family association studies for common variants are single marker based, which test one SNP a time. In this paper, we consider testing the effect of an SNP set, e.g., SNPs in a gene, in family studies, for both continuous and discrete traits. Specifically, we propose a generalized estimating equations (GEEs) based kernel association test, a variance component based testing method, to test for the association between a phenotype and multiple variants in an SNP set jointly using family samples. The proposed approach allows for both continuous and discrete traits, where the correlation among family members is taken into account through the use of an empirical covariance estimator. We derive the theoretical distribution of the proposed statistic under the null and develop analytical methods to calculate the P-values. We also propose an efficient resampling method for correcting for small sample size bias in family studies. The proposed method allows for easily incorporating covariates and SNP-SNP interactions. Simulation studies show that the proposed method properly controls for type I error rates under both random and ascertained sampling schemes in family studies. We demonstrate through simulation studies that our approach has superior performance for association mapping compared to the single marker based minimum P-value GEE test for an SNP-set effect over a range of scenarios. We illustrate the application of the proposed method using data from the Cleveland Family GWAS Study. © 2013 WILEY PERIODICALS, INC.

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.

An information hiding method based on LSB and tent chaotic map

NASA Astrophysics Data System (ADS)

Song, Jianhua; Ding, Qun

2011-06-01

In order to protect information security more effectively, a novel information hiding method based on LSB and Tent chaotic map was proposed, first the secret message is Tent chaotic encrypted, and then LSB steganography is executed for the encrypted message in the cover-image. Compared to the traditional image information hiding method, the simulation results indicate that the method greatly improved in imperceptibility and security, and acquired good results.

New Geophysical Technique for Mineral Exploration and Mineral Discrimination Based on Electromagnetic Methods

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

Michael S. Zhdanov

2005-03-09

The research during the first year of the project was focused on developing the foundations of a new geophysical technique for mineral exploration and mineral discrimination, based on electromagnetic (EM) methods. The proposed new technique is based on examining the spectral induced polarization effects in electromagnetic data using modern distributed acquisition systems and advanced methods of 3-D inversion. The analysis of IP phenomena is usually based on models with frequency dependent complex conductivity distribution. One of the most popular is the Cole-Cole relaxation model. In this progress report we have constructed and analyzed a different physical and mathematical model ofmore » the IP effect based on the effective-medium theory. We have developed a rigorous mathematical model of multi-phase conductive media, which can provide a quantitative tool for evaluation of the type of mineralization, using the conductivity relaxation model parameters. The parameters of the new conductivity relaxation model can be used for discrimination of the different types of rock formations, which is an important goal in mineral exploration. The solution of this problem requires development of an effective numerical method for EM forward modeling in 3-D inhomogeneous media. During the first year of the project we have developed a prototype 3-D IP modeling algorithm using the integral equation (IP) method. Our IE forward modeling code INTEM3DIP is based on the contraction IE method, which improves the convergence rate of the iterative solvers. This code can handle various types of sources and receivers to compute the effect of a complex resistivity model. We have tested the working version of the INTEM3DIP code for computer simulation of the IP data for several models including a southwest US porphyry model and a Kambalda-style nickel sulfide deposit. The numerical modeling study clearly demonstrates how the various complex resistivity models manifest differently in the observed EM data. These modeling studies lay a background for future development of the IP inversion method, directed at determining the electrical conductivity and the intrinsic chargeability distributions, as well as the other parameters of the relaxation model simultaneously. The new technology envisioned in this proposal, will be used for the discrimination of different rocks, and in this way will provide an ability to distinguish between uneconomic mineral deposits and the location of zones of economic mineralization and geothermal resources.« less

42 CFR 67.101 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) Section 1142 of the Social Security Act to support research on the outcomes, effectiveness, and... services and procedures; projects to improve methods and data bases for outcomes and effectiveness research..., performance measures, and review criteria; conferences; and research on dissemination methods. (b) The...

Internet-Based Methods to Construct a Stakeholder Network for the Sustainability of Narragansett Bay, Rhode Island

EPA Science Inventory

Background\\Questions\\Methods Conservation coalitions, where numerous organizations collaborate for the augmented environmental protection of a critical habitat, have been shown to reduce redundancy and increase effectiveness. In order to initiate an effective conservation coalit...

Growth and mortality of larval sunfish in backwaters of the upper Mississippi River

USGS Publications Warehouse

Zigler, S.J.; Jennings, C.A.

1993-01-01

The authors estimated the growth and mortality of larval sunfish Lepomis spp. in backwater habitats of the upper Mississippi River with an otolith-based method and a length-based method. Fish were sampled with plankton nets at one station in Navigation Pools 8 and 14 in 1989 and at two stations in Pool 8 in 1990. For both methods, growth was modeled with an exponential equation, and instantaneous mortality was estimated by regressing the natural logarithm of fish catch for each 1-mm size-group against the estimated age of the group, which was derived from the growth equations. At two of the stations, the otolith-based method provided more precise estimates of sunfish growth than the length-based method. We were able to compare length-based and otolith-based estimates of sunfish mortality only at the two stations where we caught the largest numbers of sunfish. Estimates of mortality were similar for both methods in Pool 14, where catches were higher, but the length-based method gave significantly higher estimates in Pool 8, where the catches were lower. The otolith- based method required more laboratory analysis, but provided better estimates of the growth and mortality than the length-based method when catches were low. However, the length-based method was more cost- effective for estimating growth and mortality when catches were large.

Mixed-Methods for Comparing Tobacco Cessation Interventions

PubMed Central

Momin, Behnoosh; Neri, Antonio; Zhang, Lei; Kahende, Jennifer; Duke, Jennifer; Green, Sonya Goode; Malarcher, Ann; Stewart, Sherri L.

2017-01-01

Introduction The National Comprehensive Cancer Control Program (NCCCP) and National Tobacco Control Program (NTCP) are both well-positioned to promote the use of population-based tobacco cessation interventions, such as state quitlines and Web-based interventions. Aims This paper outlines the methodology used to conduct a comparative effectiveness research study of traditional and Web-based tobacco cessation and quitline promotion approaches. Methods A mixed-methods study with three components was designed to address the effect of promotional activities on service usage and the comparative effectiveness of population-based smoking cessation activities across multiple states. Results/Findings The cessation intervention component followed 7,902 smokers (4,307 quitline users and 3,595 Web intervention users) to ascertain prevalence of 30-day abstinence rates 7 months after registering for smoking cessation services. User characteristics and quit success was compared across the two modalities. In the promotions component, reach and use of traditional and innovative promotion strategies were assessed for 24 states, including online advertising, state Web sites, social media, mobile applications, and their effects on quitline call volume. The partnership intervention component studied the extent of collaboration among six selected NCCCPs and NTCPs. Conclusions This study will guide program staff and clinicians with evidence-based recommendations and best practices for implementation of tobacco cessation within their patient and community populations and establish an evidence base that can be used for decision making. PMID:28243318

Recent developments in detection and enumeration of waterborne bacteria: a retrospective minireview.

PubMed

Deshmukh, Rehan A; Joshi, Kopal; Bhand, Sunil; Roy, Utpal

2016-12-01

Waterborne diseases have emerged as global health problems and their rapid and sensitive detection in environmental water samples is of great importance. Bacterial identification and enumeration in water samples is significant as it helps to maintain safe drinking water for public consumption. Culture-based methods are laborious, time-consuming, and yield false-positive results, whereas viable but nonculturable (VBNCs) microorganisms cannot be recovered. Hence, numerous methods have been developed for rapid detection and quantification of waterborne pathogenic bacteria in water. These rapid methods can be classified into nucleic acid-based, immunology-based, and biosensor-based detection methods. This review summarizes the principle and current state of rapid methods for the monitoring and detection of waterborne bacterial pathogens. Rapid methods outlined are polymerase chain reaction (PCR), digital droplet PCR, real-time PCR, multiplex PCR, DNA microarray, Next-generation sequencing (pyrosequencing, Illumina technology and genomics), and fluorescence in situ hybridization that are categorized as nucleic acid-based methods. Enzyme-linked immunosorbent assay (ELISA) and immunofluorescence are classified into immunology-based methods. Optical, electrochemical, and mass-based biosensors are grouped into biosensor-based methods. Overall, these methods are sensitive, specific, time-effective, and important in prevention and diagnosis of waterborne bacterial diseases. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Detecting and treating occlusal caries lesions: a cost-effectiveness analysis.

PubMed

Schwendicke, F; Stolpe, M; Meyer-Lueckel, H; Paris, S

2015-02-01

The health gains and costs resulting from using different caries detection strategies might not only depend on the accuracy of the used method but also the treatment emanating from its use in different populations. We compared combinations of visual-tactile, radiographic, or laser-fluorescence-based detection methods with 1 of 3 treatments (non-, micro-, and invasive treatment) initiated at different cutoffs (treating all or only dentinal lesions) in populations with low or high caries prevalence. A Markov model was constructed to follow an occlusal surface in a permanent molar in an initially 12-y-old male German patient over his lifetime. Prevalence data and transition probabilities were extracted from the literature, while validity parameters of different methods were synthesized or obtained from systematic reviews. Microsimulations were performed to analyze the model, assuming a German health care setting and a mixed public-private payer perspective. Radiographic and fluorescence-based methods led to more overtreatments, especially in populations with low prevalence. For the latter, combining visual-tactile or radiographic detection with microinvasive treatment retained teeth longest (mean 66 y) at lowest costs (329 and 332 Euro, respectively), while combining radiographic or fluorescence-based detections with invasive treatment was the least cost-effective (<60 y, >700 Euro). In populations with high prevalence, combining radiographic detection with microinvasive treatment was most cost-effective (63 y, 528 Euro), while sensitive detection methods combined with invasive treatments were again the least cost-effective (<59 y, >690 Euro). The suitability of detection methods differed significantly between populations, and the cost-effectiveness was greatly influenced by the treatment initiated after lesion detection. The accuracy of a detection method relative to a "gold standard" did not automatically convey into better health or reduced costs. Detection methods should be evaluated not only against their criterion validity but also the long-term effects resulting from their use in different populations. © International & American Associations for Dental Research 2014.

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

An analysis of shock coalescence including three-dimensional effects with application to sonic boom extrapolation. Ph.D. Thesis - George Washington Univ.

NASA Technical Reports Server (NTRS)

Darden, C. M.

1984-01-01

A method for analyzing shock coalescence which includes three dimensional effects was developed. The method is based on an extension of the axisymmetric solution, with asymmetric effects introduced through an additional set of governing equations, derived by taking the second circumferential derivative of the standard shock equations in the plane of symmetry. The coalescence method is consistent with and has been combined with a nonlinear sonic boom extrapolation program which is based on the method of characteristics. The extrapolation program, is able to extrapolate pressure signatures which include embedded shocks from an initial data line in the plane of symmetry at approximately one body length from the axis of the aircraft to the ground. The axisymmetric shock coalescence solution, the asymmetric shock coalescence solution, the method of incorporating these solutions into the extrapolation program, and the methods used to determine spatial derivatives needed in the coalescence solution are described. Results of the method are shown for a body of revolution at a small, positive angle of attack.

State Recognition of High Voltage Isolation Switch Based on Background Difference and Iterative Search

NASA Astrophysics Data System (ADS)

Xu, Jiayuan; Yu, Chengtao; Bo, Bin; Xue, Yu; Xu, Changfu; Chaminda, P. R. Dushantha; Hu, Chengbo; Peng, Kai

2018-03-01

The automatic recognition of the high voltage isolation switch by remote video monitoring is an effective means to ensure the safety of the personnel and the equipment. The existing methods mainly include two ways: improving monitoring accuracy and adopting target detection technology through equipment transformation. Such a method is often applied to specific scenarios, with limited application scope and high cost. To solve this problem, a high voltage isolation switch state recognition method based on background difference and iterative search is proposed in this paper. The initial position of the switch is detected in real time through the background difference method. When the switch starts to open and close, the target tracking algorithm is used to track the motion trajectory of the switch. The opening and closing state of the switch is determined according to the angle variation of the switch tracking point and the center line. The effectiveness of the method is verified by experiments on different switched video frames of switching states. Compared with the traditional methods, this method is more robust and effective.

No major differences found between the effects of microwave-based and conventional heat treatment methods on two different liquid foods.

PubMed

Géczi, Gábor; Horváth, Márk; Kaszab, Tímea; Alemany, Gonzalo Garnacho

2013-01-01

Extension of shelf life and preservation of products are both very important for the food industry. However, just as with other processes, speed and higher manufacturing performance are also beneficial. Although microwave heating is utilized in a number of industrial processes, there are many unanswered questions about its effects on foods. Here we analyze whether the effects of microwave heating with continuous flow are equivalent to those of traditional heat transfer methods. In our study, the effects of heating of liquid foods by conventional and continuous flow microwave heating were studied. Among other properties, we compared the stability of the liquid foods between the two heat treatments. Our goal was to determine whether the continuous flow microwave heating and the conventional heating methods have the same effects on the liquid foods, and, therefore, whether microwave heat treatment can effectively replace conventional heat treatments. We have compared the colour, separation phenomena of the samples treated by different methods. For milk, we also monitored the total viable cell count, for orange juice, vitamin C contents in addition to the taste of the product by sensory analysis. The majority of the results indicate that the circulating coil microwave method used here is equivalent to the conventional heating method based on thermal conduction and convection. However, some results in the analysis of the milk samples show clear differences between heat transfer methods. According to our results, the colour parameters (lightness, red-green and blue-yellow values) of the microwave treated samples differed not only from the untreated control, but also from the traditional heat treated samples. The differences are visually undetectable, however, they become evident through analytical measurement with spectrophotometer. This finding suggests that besides thermal effects, microwave-based food treatment can alter product properties in other ways as well.

No Major Differences Found between the Effects of Microwave-Based and Conventional Heat Treatment Methods on Two Different Liquid Foods

PubMed Central

Géczi, Gábor; Horváth, Márk; Kaszab, Tímea; Alemany, Gonzalo Garnacho

2013-01-01

Extension of shelf life and preservation of products are both very important for the food industry. However, just as with other processes, speed and higher manufacturing performance are also beneficial. Although microwave heating is utilized in a number of industrial processes, there are many unanswered questions about its effects on foods. Here we analyze whether the effects of microwave heating with continuous flow are equivalent to those of traditional heat transfer methods. In our study, the effects of heating of liquid foods by conventional and continuous flow microwave heating were studied. Among other properties, we compared the stability of the liquid foods between the two heat treatments. Our goal was to determine whether the continuous flow microwave heating and the conventional heating methods have the same effects on the liquid foods, and, therefore, whether microwave heat treatment can effectively replace conventional heat treatments. We have compared the colour, separation phenomena of the samples treated by different methods. For milk, we also monitored the total viable cell count, for orange juice, vitamin C contents in addition to the taste of the product by sensory analysis. The majority of the results indicate that the circulating coil microwave method used here is equivalent to the conventional heating method based on thermal conduction and convection. However, some results in the analysis of the milk samples show clear differences between heat transfer methods. According to our results, the colour parameters (lightness, red-green and blue-yellow values) of the microwave treated samples differed not only from the untreated control, but also from the traditional heat treated samples. The differences are visually undetectable, however, they become evident through analytical measurement with spectrophotometer. This finding suggests that besides thermal effects, microwave-based food treatment can alter product properties in other ways as well. PMID:23341982

Numerical solution of the unsteady diffusion-convection-reaction equation based on improved spectral Galerkin method

NASA Astrophysics Data System (ADS)

Zhong, Jiaqi; Zeng, Cheng; Yuan, Yupeng; Zhang, Yuzhe; Zhang, Ye

2018-04-01

The aim of this paper is to present an explicit numerical algorithm based on improved spectral Galerkin method for solving the unsteady diffusion-convection-reaction equation. The principal characteristics of this approach give the explicit eigenvalues and eigenvectors based on the time-space separation method and boundary condition analysis. With the help of Fourier series and Galerkin truncation, we can obtain the finite-dimensional ordinary differential equations which facilitate the system analysis and controller design. By comparing with the finite element method, the numerical solutions are demonstrated via two examples. It is shown that the proposed method is effective.

Infrared image segmentation method based on spatial coherence histogram and maximum entropy

NASA Astrophysics Data System (ADS)

Liu, Songtao; Shen, Tongsheng; Dai, Yao

2014-11-01

In order to segment the target well and suppress background noises effectively, an infrared image segmentation method based on spatial coherence histogram and maximum entropy is proposed. First, spatial coherence histogram is presented by weighting the importance of the different position of these pixels with the same gray-level, which is obtained by computing their local density. Then, after enhancing the image by spatial coherence histogram, 1D maximum entropy method is used to segment the image. The novel method can not only get better segmentation results, but also have a faster computation time than traditional 2D histogram-based segmentation methods.

Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects.

PubMed

Goto, Masami; Abe, Osamu; Aoki, Shigeki; Hayashi, Naoto; Miyati, Tosiaki; Takao, Hidemasa; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2013-07-01

This study aimed to investigate whether the effect of scanner for cortex volumetry with atlas-based method is reduced using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) normalization compared with standard normalization. Three-dimensional T1-weighted magnetic resonance images (3D-T1WIs) of 21 healthy subjects were obtained and evaluated for effect of scanner in cortex volumetry. 3D-T1WIs of the 21 subjects were obtained with five MRI systems. Imaging of each subject was performed on each of five different MRI scanners. We used the Voxel-Based Morphometry 8 tool implemented in Statistical Parametric Mapping 8 and WFU PickAtlas software (Talairach brain atlas theory). The following software default settings were used as bilateral region-of-interest labels: "Frontal Lobe," "Hippocampus," "Occipital Lobe," "Orbital Gyrus," "Parietal Lobe," "Putamen," and "Temporal Lobe." Effect of scanner for cortex volumetry using the atlas-based method was reduced with DARTEL normalization compared with standard normalization in Frontal Lobe, Occipital Lobe, Orbital Gyrus, Putamen, and Temporal Lobe; was the same in Hippocampus and Parietal Lobe; and showed no increase with DARTEL normalization for any region of interest (ROI). DARTEL normalization reduces the effect of scanner, which is a major problem in multicenter studies.

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

Unkelbach, Jan, E-mail: junkelbach@mgh.harvard.edu; Botas, Pablo; Faculty of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg

Purpose: We describe a treatment plan optimization method for intensity modulated proton therapy (IMPT) that avoids high values of linear energy transfer (LET) in critical structures located within or near the target volume while limiting degradation of the best possible physical dose distribution. Methods and Materials: To allow fast optimization based on dose and LET, a GPU-based Monte Carlo code was extended to provide dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dosemore » objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of LET and physical dose (LET×D). To first approximation, LET×D represents a measure of the additional biological dose that is caused by high LET. Results: The method is effective for treatments where serial critical structures with maximum dose constraints are located within or near the target. We report on 5 patients with intracranial tumors (high-grade meningiomas, base-of-skull chordomas, ependymomas) in whom the target volume overlaps with the brainstem and optic structures. In all cases, high LET×D in critical structures could be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based reoptimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and relative biological effectiveness (RBE)-based planning. The method makes IMPT treatments safer by mitigating a potentially increased risk of side effects resulting from elevated RBE of proton beams near the end of range.« less

An effective framework for finding similar cases of dengue from audio and text data using domain thesaurus and case base reasoning

NASA Astrophysics Data System (ADS)

Sandhu, Rajinder; Kaur, Jaspreet; Thapar, Vivek

2018-02-01

Dengue, also known as break-bone fever, is a tropical disease transmitted by mosquitoes. If the similarity between dengue infected users can be identified, it can help government's health agencies to manage the outbreak more effectively. To find similarity between cases affected by Dengue, user's personal and health information are the two fundamental requirements. Identification of similar symptoms, causes, effects, predictions and treatment procedures, is important. In this paper, an effective framework is proposed which finds similar patients suffering from dengue using keyword aware domain thesaurus and case base reasoning method. This paper focuses on the use of ontology dependent domain thesaurus technique to extract relevant keywords and then build cases with the help of case base reasoning method. Similar cases can be shared with users, nearby hospitals and health organizations to manage the problem more adequately. Two million case bases were generated to test the proposed similarity method. Experimental evaluations of proposed framework resulted in high accuracy and low error rate for finding similar cases of dengue as compared to UPCC and IPCC algorithms. The framework developed in this paper is for dengue but can easily be extended to other domains also.

Paper-Based and Computer-Based Concept Mappings: The Effects on Computer Achievement, Computer Anxiety and Computer Attitude

ERIC Educational Resources Information Center

Erdogan, Yavuz

2009-01-01

The purpose of this paper is to compare the effects of paper-based and computer-based concept mappings on computer hardware achievement, computer anxiety and computer attitude of the eight grade secondary school students. The students were randomly allocated to three groups and were given instruction on computer hardware. The teaching methods used…

Study protocol Implementation of the Veder contact method (VCM) in daily nursing home care for people with dementia: an evaluation based on the RE-AIM framework.

PubMed

Boersma, Petra; Van Weert, Julia C M; van Meijel, Berno; van de Ven, Peter M; Dröes, Rose-Marie

2017-07-01

People with dementia in nursing homes benefit from person-centred care methods. Studies examining the effect of these methods often fail to report about the implementation of these methods. The present study aims to describe the implementation of the Veder contact method (VCM) in daily nursing home care. A process analysis will be conducted based on qualitative data from focus groups with caregivers and interviews with key figures. To investigate whether the implementation of VCM is reflected in the attitude and behaviour of caregivers and in the behaviour and quality of life of people with dementia, a controlled observational cohort study will be conducted. Six nursing home wards implementing VCM will be compared with six control wards providing Care As Usual. Quantitative data from caregivers and residents will be collected before (T0), and 9-12 months after the implementation (T1). Qualitative analysis and multilevel analyses will be carried out on the collected data and structured based on the constructs of the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, Maintenance). By using the RE-AIM framework this study introduces a structured and comprehensive way of investigating the implementation process and implementation effectiveness of person-centred care methods in daily dementia care.

A new multiscale noise tuning stochastic resonance for enhanced fault diagnosis in wind turbine drivetrains

NASA Astrophysics Data System (ADS)

Hu, Bingbing; Li, Bing

2016-02-01

It is very difficult to detect weak fault signatures due to the large amount of noise in a wind turbine system. Multiscale noise tuning stochastic resonance (MSTSR) has proved to be an effective way to extract weak signals buried in strong noise. However, the MSTSR method originally based on discrete wavelet transform (DWT) has disadvantages such as shift variance and the aliasing effects in engineering application. In this paper, the dual-tree complex wavelet transform (DTCWT) is introduced into the MSTSR method, which makes it possible to further improve the system output signal-to-noise ratio and the accuracy of fault diagnosis by the merits of DTCWT (nearly shift invariant and reduced aliasing effects). Moreover, this method utilizes the relationship between the two dual-tree wavelet basis functions, instead of matching the single wavelet basis function to the signal being analyzed, which may speed up the signal processing and be employed in on-line engineering monitoring. The proposed method is applied to the analysis of bearing outer ring and shaft coupling vibration signals carrying fault information. The results confirm that the method performs better in extracting the fault features than the original DWT-based MSTSR, the wavelet transform with post spectral analysis, and EMD-based spectral analysis methods.

A label-free amplified fluorescence DNA detection based on isothermal circular strand-displacement polymerization reaction and graphene oxide.

PubMed

Li, Zhen; Zhu, Wenping; Zhang, Jinwen; Jiang, Jianhui; Shen, Guoli; Yu, Ruqin

2013-07-07

A label-free fluorescent DNA biosensor has been presented based on isothermal circular strand-displacement polymerization reaction (ICSDPR) combined with graphene oxide (GO) binding. The proposed method is simple and cost-effective with a low detection limit of 4 pM, which compares favorably with other GO-based homogenous DNA detection methods.

Clinical Teachers' Attitudes toward the Efficacy of Evidence-Based Medicine Workshop and Self-Reported Ability in Evidence-Based Practice in Iran

ERIC Educational Resources Information Center

Kouhpayehzadeh, Jalil; Baradaran, Hamid; Arabshahi, Kamran Soltani; Knill-Jones, Robin

2006-01-01

Introduction: Evidence-based medicine (EBM) has been introduced in medical schools worldwide, but there is little known about effective methods for teaching EBM skills, particularly in developing countries. This study assesses the impact of an EBM workshop on clinical teachers' attitudes and use of EBM skills. Methods: Seventy-two clinical…

Masking as an effective quality control method for next-generation sequencing data analysis.

PubMed

Yun, Sajung; Yun, Sijung

2014-12-13

Next generation sequencing produces base calls with low quality scores that can affect the accuracy of identifying simple nucleotide variation calls, including single nucleotide polymorphisms and small insertions and deletions. Here we compare the effectiveness of two data preprocessing methods, masking and trimming, and the accuracy of simple nucleotide variation calls on whole-genome sequence data from Caenorhabditis elegans. Masking substitutes low quality base calls with 'N's (undetermined bases), whereas trimming removes low quality bases that results in a shorter read lengths. We demonstrate that masking is more effective than trimming in reducing the false-positive rate in single nucleotide polymorphism (SNP) calling. However, both of the preprocessing methods did not affect the false-negative rate in SNP calling with statistical significance compared to the data analysis without preprocessing. False-positive rate and false-negative rate for small insertions and deletions did not show differences between masking and trimming. We recommend masking over trimming as a more effective preprocessing method for next generation sequencing data analysis since masking reduces the false-positive rate in SNP calling without sacrificing the false-negative rate although trimming is more commonly used currently in the field. The perl script for masking is available at http://code.google.com/p/subn/. The sequencing data used in the study were deposited in the Sequence Read Archive (SRX450968 and SRX451773).

Unsupervised malaria parasite detection based on phase spectrum.

PubMed

Fang, Yuming; Xiong, Wei; Lin, Weisi; Chen, Zhenzhong

2011-01-01

In this paper, we propose a novel method for malaria parasite detection based on phase spectrum. The method first obtains the amplitude spectrum and phase spectrum for blood smear images through Quaternion Fourier Transform (QFT). Then it gets the reconstructed image based on Inverse Quaternion Fourier transform (IQFT) on a constant amplitude spectrum and the original phase spectrum. The malaria parasite areas can be detected easily from the reconstructed blood smear images. Extensive experiments have demonstrated the effectiveness of this novel method.

New Methods of Low-Field Magnetic Resonance Imaging for Application to Traumatic Brain Injury

DTIC Science & Technology

2013-02-01

magnet based ), the development of novel high-speed parallel imaging detection systems, and work on advanced adaptive reconstruction methods ...signal many times within the acquisition time . We present here a new method for 3D OMRI based on b-SSFP at a constant field of 6.5 mT that provides up...developing injury-sensitive MRI based on the detection of free radicals associat- ed with injury using the Overhauser effect and subsequently imaging that

Effective numerical method of spectral analysis of quantum graphs

NASA Astrophysics Data System (ADS)

Barrera-Figueroa, Víctor; Rabinovich, Vladimir S.

2017-05-01

We present in the paper an effective numerical method for the determination of the spectra of periodic metric graphs equipped by Schrödinger operators with real-valued periodic electric potentials as Hamiltonians and with Kirchhoff and Neumann conditions at the vertices. Our method is based on the spectral parameter power series method, which leads to a series representation of the dispersion equation, which is suitable for both analytical and numerical calculations. Several important examples demonstrate the effectiveness of our method for some periodic graphs of interest that possess potentials usually found in quantum mechanics.

The method of a joint intraday security check system based on cloud computing

NASA Astrophysics Data System (ADS)

Dong, Wei; Feng, Changyou; Zhou, Caiqi; Cai, Zhi; Dan, Xu; Dai, Sai; Zhang, Chuancheng

2017-01-01

The intraday security check is the core application in the dispatching control system. The existing security check calculation only uses the dispatch center’s local model and data as the functional margin. This paper introduces the design of all-grid intraday joint security check system based on cloud computing and its implementation. To reduce the effect of subarea bad data on the all-grid security check, a new power flow algorithm basing on comparison and adjustment with inter-provincial tie-line plan is presented. And the numerical example illustrated the effectiveness and feasibility of the proposed method.

Mindfulness-Based Approaches in the Treatment of Disordered Gambling: A Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Maynard, Brandy R.; Wilson, Alyssa N.; Labuzienski, Elizabeth; Whiting, Seth W.

2018-01-01

Background and Aims: To examine the effects of mindfulness-based interventions on gambling behavior and symptoms, urges, and financial outcomes. Method: Systematic review and meta-analytic procedures were employed to search, select, code, and analyze studies conducted between 1980 and 2014, assessing the effects of mindfulness-based interventions…

Using Trial-Based Functional Analysis to Design Effective Interventions for Students Diagnosed with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Larkin, Wallace; Hawkins, Renee O.; Collins, Tai

2016-01-01

Functional behavior assessments and function-based interventions are effective methods for addressing the challenging behaviors of children; however, traditional functional analysis has limitations that impact usability in applied settings. Trial-based functional analysis addresses concerns relating to the length of time, level of expertise…

The Effect of Virtual versus Traditional Learning in Achieving Competency-Based Skills

ERIC Educational Resources Information Center

Mosalanejad, Leili; Shahsavari, Sakine; Sobhanian, Saeed; Dastpak, Mehdi

2012-01-01

Background: By rapid developing of the network technology, the internet-based learning methods are substituting the traditional classrooms making them expand to the virtual network learning environment. The purpose of this study was to determine the effectiveness of virtual systems on competency-based skills of first-year nursing students.…

Leadership Preparation Program's Effects on Principals' Preparedness: Traditional University-Based vs. Alternative

ERIC Educational Resources Information Center

Gagliardi, Karen M.

2012-01-01

In this mixed-method causal comparative and interview-based study, I developed an understanding of the way in which school principals perceived their level of preparedness. The effectiveness of two types of leadership preparation programs, traditional-university based and alternative, were considered on principal preparedness. One hundred and…

An Intelligent Model for Pairs Trading Using Genetic Algorithms.

PubMed

Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

An Intelligent Model for Pairs Trading Using Genetic Algorithms

PubMed Central

Hsu, Chi-Jen; Chen, Chi-Chung; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

Space-based optical image encryption.

PubMed

Chen, Wen; Chen, Xudong

2010-12-20

In this paper, we propose a new method based on a three-dimensional (3D) space-based strategy for the optical image encryption. The two-dimensional (2D) processing of a plaintext in the conventional optical encryption methods is extended to a 3D space-based processing. Each pixel of the plaintext is considered as one particle in the proposed space-based optical image encryption, and the diffraction of all particles forms an object wave in the phase-shifting digital holography. The effectiveness and advantages of the proposed method are demonstrated by numerical results. The proposed method can provide a new optical encryption strategy instead of the conventional 2D processing, and may open up a new research perspective for the optical image encryption.

The Seepage Simulation of Single Hole and Composite Gas Drainage Based on LB Method

NASA Astrophysics Data System (ADS)

Chen, Yanhao; Zhong, Qiu; Gong, Zhenzhao

2018-01-01

Gas drainage is the most effective method to prevent and solve coal mine gas power disasters. It is very important to study the seepage flow law of gas in fissure coal gas. The LB method is a simplified computational model based on micro-scale, especially for the study of seepage problem. Based on fracture seepage mathematical model on the basis of single coal gas drainage, using the LB method during coal gas drainage of gas flow numerical simulation, this paper maps the single-hole drainage gas, symmetric slot and asymmetric slot, the different width of the slot combined drainage area gas flow under working condition of gas cloud of gas pressure, flow path diagram and flow velocity vector diagram, and analyses the influence on gas seepage field under various working conditions, and also discusses effective drainage method of the center hole slot on both sides, and preliminary exploration that is related to the combination of gas drainage has been carried on as well.

Effects of different preservation methods on inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) molecular markers in botanic samples.

PubMed

Wang, Xiaolong; Li, Lin; Zhao, Jiaxin; Li, Fangliang; Guo, Wei; Chen, Xia

2017-04-01

To evaluate the effects of different preservation methods (stored in a -20°C ice chest, preserved in liquid nitrogen and dried in silica gel) on inter simple sequence repeat (ISSR) or random amplified polymorphic DNA (RAPD) analyses in various botanical specimens (including broad-leaved plants, needle-leaved plants and succulent plants) for different times (three weeks and three years), we used a statistical analysis based on the number of bands, genetic index and cluster analysis. The results demonstrate that methods used to preserve samples can provide sufficient amounts of genomic DNA for ISSR and RAPD analyses; however, the effect of different preservation methods on these analyses vary significantly, and the preservation time has little effect on these analyses. Our results provide a reference for researchers to select the most suitable preservation method depending on their study subject for the analysis of molecular markers based on genomic DNA. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Comparison of 2 resident learning tools-interactive screen-based simulated case scenarios versus problem-based learning discussions: a prospective quasi-crossover cohort study.

PubMed

Rajan, Shobana; Khanna, Ashish; Argalious, Maged; Kimatian, Stephen J; Mascha, Edward J; Makarova, Natalya; Nada, Eman M; Elsharkawy, Hesham; Firoozbakhsh, Farhad; Avitsian, Rafi

2016-02-01

Simulation-based learning is emerging as an alternative educational tool in this era of a relative shortfall of teaching anesthesiologists. The objective of the study is to assess whether screen-based (interactive computer simulated) case scenarios are more effective than problem-based learning discussions (PBLDs) in improving test scores 4 and 8 weeks after these interventions in anesthesia residents during their first neuroanesthesia rotation. Prospective, nonblinded quasi-crossover study. Cleveland Clinic. Anesthesiology residents. Two case scenarios were delivered from the Anesoft software as screen-based sessions, and parallel scripts were developed for 2 PBLDs. Each resident underwent both types of training sessions, starting with the PBLD session, and the 2 cases were alternated each month (ie, in 1 month, the screen-based intervention used case 1 and the PBLD used case 2, and vice versa for the next month). Test scores before the rotation (baseline), immediately after the rotation (4 weeks after the start of the rotation), and 8 weeks after the start of rotation were collected on each topic from each resident. The effect of training method on improvement in test scores was assessed using a linear mixed-effects model. Compared to the departmental standard of PBLD, the simulation method did not improve either the 4- or 8-week mean test scores (P = .41 and P = .40 for training method effect on 4- and 8-week scores, respectively). Resident satisfaction with the simulation module on a 5-point Likert scale showed subjective evidence of a positive impact on resident education. Screen-based simulators were not more effective than PBLD for education during the neuroanesthesia rotation in anesthesia residency. Copyright © 2016 Elsevier Inc. All rights reserved.

A temperature compensation methodology for piezoelectric based sensor devices

NASA Astrophysics Data System (ADS)

Wang, Dong F.; Lou, Xueqiao; Bao, Aijian; Yang, Xu; Zhao, Ji

2017-08-01

A temperature compensation methodology comprising a negative temperature coefficient thermistor with the temperature characteristics of a piezoelectric material is proposed to improve the measurement accuracy of piezoelectric sensing based devices. The piezoelectric disk is characterized by using a disk-shaped structure and is also used to verify the effectiveness of the proposed compensation method. The measured output voltage shows a nearly linear relationship with respect to the applied pressure by introducing the proposed temperature compensation method in a temperature range of 25-65 °C. As a result, the maximum measurement accuracy is observed to be improved by 40%, and the higher the temperature, the more effective the method. The effective temperature range of the proposed method is theoretically analyzed by introducing the constant coefficient of the thermistor (B), the resistance of initial temperature (R0), and the paralleled resistance (Rx). The proposed methodology can not only eliminate the influence of piezoelectric temperature dependent characteristics on the sensing accuracy but also decrease the power consumption of piezoelectric sensing based devices by the simplified sensing structure.

A Cascaded Approach for Correcting Ionospheric Contamination with Large Amplitude in HF Skywave Radars

PubMed Central

Wei, Yinsheng; Guo, Rujiang; Xu, Rongqing; Tang, Xiudong

2014-01-01

Ionospheric phase perturbation with large amplitude causes broadening sea clutter's Bragg peaks to overlap each other; the performance of traditional decontamination methods about filtering Bragg peak is poor, which greatly limits the detection performance of HF skywave radars. In view of the ionospheric phase perturbation with large amplitude, this paper proposes a cascaded approach based on improved S-method to correct the ionospheric phase contamination. This approach consists of two correction steps. At the first step, a time-frequency distribution method based on improved S-method is adopted and an optimal detection method is designed to obtain a coarse ionospheric modulation estimation from the time-frequency distribution. At the second correction step, based on the phase gradient algorithm (PGA) is exploited to eliminate the residual contamination. Finally, use the measured data to verify the effectiveness of the method. Simulation results show the time-frequency resolution of this method is high and is not affected by the interference of the cross term; ionospheric phase perturbation with large amplitude can be corrected in low signal-to-noise (SNR); such a cascade correction method has a good effect. PMID:24578656

Evaluation of Two Outlier-Detection-Based Methods for Detecting Tissue-Selective Genes from Microarray Data

PubMed Central

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-01-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU. PMID:19936074

Extending the Distributed Lag Model framework to handle chemical mixtures.

PubMed

Bello, Ghalib A; Arora, Manish; Austin, Christine; Horton, Megan K; Wright, Robert O; Gennings, Chris

2017-07-01

Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation Methods for Assessing Users’ Psychological Experiences of Web-Based Psychosocial Interventions: A Systematic Review

PubMed Central

Howson, Moira; Ritchie, Linda; Carter, Philip D; Parry, David Tudor; Koziol-McLain, Jane

2016-01-01

Background The use of Web-based interventions to deliver mental health and behavior change programs is increasingly popular. They are cost-effective, accessible, and generally effective. Often these interventions concern psychologically sensitive and challenging issues, such as depression or anxiety. The process by which a person receives and experiences therapy is important to understanding therapeutic process and outcomes. While the experience of the patient or client in traditional face-to-face therapy has been evaluated in a number of ways, there appeared to be a gap in the evaluation of patient experiences of therapeutic interventions delivered online. Evaluation of Web-based artifacts has focused either on evaluation of experience from a computer Web-design perspective through usability testing or on evaluation of treatment effectiveness. Neither of these methods focuses on the psychological experience of the person while engaged in the therapeutic process. Objective This study aimed to investigate what methods, if any, have been used to evaluate the in situ psychological experience of users of Web-based self-help psychosocial interventions. Methods A systematic literature review was undertaken of interdisciplinary databases with a focus on health and computer sciences. Studies that met a predetermined search protocol were included. Results Among 21 studies identified that examined psychological experience of the user, only 1 study collected user experience in situ. The most common method of understanding users’ experience was through semistructured interviews conducted posttreatment or questionnaires administrated at the end of an intervention session. The questionnaires were usually based on standardized tools used to assess user experience with traditional face-to-face treatment. Conclusions There is a lack of methods specified in the literature to evaluate the interface between Web-based mental health or behavior change artifacts and users. Main limitations in the research were the nascency of the topic and cross-disciplinary nature of the field. There is a need to develop and deliver methods of understanding users’ psychological experiences while using an intervention. PMID:27363519

Testing an Adapted Modified Delphi Method: Synthesizing Multiple Stakeholder Ratings of Health Care Service Effectiveness.

PubMed

Escaron, Anne L; Chang Weir, Rosy; Stanton, Petra; Vangala, Sitaram; Grogan, Tristan R; Clarke, Robin M

2016-03-01

The Affordable Care Act incentivizes health systems for better meeting patient needs, but often guidance about patient preferences for particular health services is limited. All too often vulnerable patient populations are excluded from these decision-making settings. A community-based participatory approach harnesses the in-depth knowledge of those experiencing barriers to health care. We made three modifications to the RAND-UCLA appropriateness method, a modified Delphi approach, involving patients, adding an advisory council group to characterize existing knowledge in this little studied area, and using effectiveness rather than "appropriateness" as the basis for rating. As a proof of concept, we tested this method by examining the broadly delivered but understudied nonmedical services that community health centers provide. This method created discrete, new knowledge about these services by defining 6 categories and 112 unique services and by prioritizing among these services based on effectiveness using a 9-point scale. Consistent with the appropriateness method, we found statistical convergence of ratings among the panelists. Challenges include time commitment and adherence to a clear definition of effectiveness of services. This diverse stakeholder engagement method efficiently addresses gaps in knowledge about the effectiveness of health care services to inform population health management. © 2015 Society for Public Health Education.

A knowledge-driven approach to biomedical document conceptualization.

PubMed

Zheng, Hai-Tao; Borchert, Charles; Jiang, Yong

2010-06-01

Biomedical document conceptualization is the process of clustering biomedical documents based on ontology-represented domain knowledge. The result of this process is the representation of the biomedical documents by a set of key concepts and their relationships. Most of clustering methods cluster documents based on invariant domain knowledge. The objective of this work is to develop an effective method to cluster biomedical documents based on various user-specified ontologies, so that users can exploit the concept structures of documents more effectively. We develop a flexible framework to allow users to specify the knowledge bases, in the form of ontologies. Based on the user-specified ontologies, we develop a key concept induction algorithm, which uses latent semantic analysis to identify key concepts and cluster documents. A corpus-related ontology generation algorithm is developed to generate the concept structures of documents. Based on two biomedical datasets, we evaluate the proposed method and five other clustering algorithms. The clustering results of the proposed method outperform the five other algorithms, in terms of key concept identification. With respect to the first biomedical dataset, our method has the F-measure values 0.7294 and 0.5294 based on the MeSH ontology and gene ontology (GO), respectively. With respect to the second biomedical dataset, our method has the F-measure values 0.6751 and 0.6746 based on the MeSH ontology and GO, respectively. Both results outperforms the five other algorithms in terms of F-measure. Based on the MeSH ontology and GO, the generated corpus-related ontologies show informative conceptual structures. The proposed method enables users to specify the domain knowledge to exploit the conceptual structures of biomedical document collections. In addition, the proposed method is able to extract the key concepts and cluster the documents with a relatively high precision. Copyright 2010 Elsevier B.V. All rights reserved.

Theory of viscous transonic flow over airfoils at high Reynolds number

NASA Technical Reports Server (NTRS)

Melnik, R. E.; Chow, R.; Mead, H. R.

1977-01-01

This paper considers viscous flows with unseparated turbulent boundary layers over two-dimensional airfoils at transonic speeds. Conventional theoretical methods are based on boundary layer formulations which do not account for the effect of the curved wake and static pressure variations across the boundary layer in the trailing edge region. In this investigation an extended viscous theory is developed that accounts for both effects. The theory is based on a rational analysis of the strong turbulent interaction at airfoil trailing edges. The method of matched asymptotic expansions is employed to develop formal series solutions of the full Reynolds equations in the limit of Reynolds numbers tending to infinity. Procedures are developed for combining the local trailing edge solution with numerical methods for solving the full potential flow and boundary layer equations. Theoretical results indicate that conventional boundary layer methods account for only about 50% of the viscous effect on lift, the remaining contribution arising from wake curvature and normal pressure gradient effects.

Lexical and semantic representations in the acquisition of L2 cognate and non-cognate words: evidence from two learning methods in children.

PubMed

Comesaña, Montserrat; Soares, Ana Paula; Sánchez-Casas, Rosa; Lima, Cátia

2012-08-01

How bilinguals represent words in two languages and which mechanisms are responsible for second language acquisition are important questions in the bilingual and vocabulary acquisition literature. This study aims to analyse the effect of two learning methods (picture- vs. word-based method) and two types of words (cognates and non-cognates) in early stages of children's L2 acquisition. Forty-eight native speakers of European Portuguese, all sixth graders (mean age = 10.87 years; SD= 0.85), participated in the study. None of them had prior knowledge of Basque (the L2 in this study). After a learning phase in which L2 words were learned either by a picture- or a word-based method, children were tested in a backward-word translation recognition task at two times (immediately vs. one week later). Results showed that the participants made more errors when rejecting semantically related than semantically unrelated words as correct translations (semantic interference effect). The magnitude of this effect was higher in the delayed test condition regardless of the learning method. Moreover, the overall performance of participants from the word-based method was better than the performance of participants from the picture-word method. Results were discussed concerning the most significant bilingual lexical processing models. ©2011 The British Psychological Society.

An evaluation method for nanoscale wrinkle

NASA Astrophysics Data System (ADS)

Liu, Y. P.; Wang, C. G.; Zhang, L. M.; Tan, H. F.

2016-06-01

In this paper, a spectrum-based wrinkling analysis method via two-dimensional Fourier transformation is proposed aiming to solve the difficulty of nanoscale wrinkle evaluation. It evaluates the wrinkle characteristics including wrinkling wavelength and direction simply using a single wrinkling image. Based on this method, the evaluation results of nanoscale wrinkle characteristics show agreement with the open experimental results within an error of 6%. It is also verified to be appropriate for the macro wrinkle evaluation without scale limitations. The spectrum-based wrinkling analysis is an effective method for nanoscale evaluation, which contributes to reveal the mechanism of nanoscale wrinkling.

The Research on Automatic Construction of Domain Model Based on Deep Web Query Interfaces

NASA Astrophysics Data System (ADS)

JianPing, Gu

The integration of services is transparent, meaning that users no longer face the millions of Web services, do not care about the required data stored, but do not need to learn how to obtain these data. In this paper, we analyze the uncertainty of schema matching, and then propose a series of similarity measures. To reduce the cost of execution, we propose the type-based optimization method and schema matching pruning method of numeric data. Based on above analysis, we propose the uncertain schema matching method. The experiments prove the effectiveness and efficiency of our method.

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

Biases and power for groups comparison on subjective health measurements.

PubMed

Hamel, Jean-François; Hardouin, Jean-Benoit; Le Neel, Tanguy; Kubis, Gildas; Roquelaure, Yves; Sébille, Véronique

2012-01-01

Subjective health measurements are increasingly used in clinical research, particularly for patient groups comparisons. Two main types of analytical strategies can be used for such data: so-called classical test theory (CTT), relying on observed scores and models coming from Item Response Theory (IRT) relying on a response model relating the items responses to a latent parameter, often called latent trait. Whether IRT or CTT would be the most appropriate method to compare two independent groups of patients on a patient reported outcomes measurement remains unknown and was investigated using simulations. For CTT-based analyses, groups comparison was performed using t-test on the scores. For IRT-based analyses, several methods were compared, according to whether the Rasch model was considered with random effects or with fixed effects, and the group effect was included as a covariate or not. Individual latent traits values were estimated using either a deterministic method or by stochastic approaches. Latent traits were then compared with a t-test. Finally, a two-steps method was performed to compare the latent trait distributions, and a Wald test was performed to test the group effect in the Rasch model including group covariates. The only unbiased IRT-based method was the group covariate Wald's test, performed on the random effects Rasch model. This model displayed the highest observed power, which was similar to the power using the score t-test. These results need to be extended to the case frequently encountered in practice where data are missing and possibly informative.

Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on survival or time-to-event outcomes.

PubMed

Austin, Peter C

2018-01-01

Propensity score methods are frequently used to estimate the effects of interventions using observational data. The propensity score was originally developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (e.g. pack-years of cigarettes smoked, dose of medication, or years of education). We describe how the GPS can be used to estimate the effect of continuous exposures on survival or time-to-event outcomes. To do so we modified the concept of the dose-response function for use with time-to-event outcomes. We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of quantitative exposures on survival or time-to-event outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. The use of methods based on the GPS was compared with the use of conventional G-computation and weighted G-computation. Conventional G-computation resulted in estimates of the dose-response function that displayed the lowest bias and the lowest variability. Amongst the two GPS-based methods, covariate adjustment using the GPS tended to have the better performance. We illustrate the application of these methods by estimating the effect of average neighbourhood income on the probability of survival following hospitalization for an acute myocardial infarction.

Cleaning and sterilisation of infant feeding equipment: a systematic review.

PubMed

Renfrew, Mary J; McLoughlin, Marie; McFadden, Alison

2008-11-01

To assess the clinical and cost-effectiveness of different methods of cleaning and sterilisation of infant feeding equipment used in the home. Systematic review of studies from developed countries on the effectiveness of methods of cleaning and sterilisation of infant feeding equipment used in the home. A brief telephone survey of UK-based manufacturers of infant feeding equipment and formula to ascertain the evidence base used for their recommendations, and a comparison of current relevant guidelines in developed countries, informed the work. National guidelines from six countries demonstrated variation and lack of evidence to support current guidance. Manufacturers did not report evidence of effectiveness to support their recommendations. Nine studies were identified; eight conducted between 1962 and 1985 and one in 1997. All had methodological weaknesses. Hand-washing was identified as fundamentally important. Health professionals were reported as not providing appropriate education on the importance and methods of cleaning and sterilisation. Mothers of subsequent babies and women from lower socio-economic groups were less likely to follow recommended procedures. There is a lack of good-quality evidence on effective ways of cleaning and sterilising infant feeding equipment in the home. The evidence base does not answer the question about which of the methods in common use is most effective or most likely to be used by parents. Hand-washing before handling feeding equipment remains important. Further research on the range of methods used in the home environment, including assessment of the views of parents and carers, is required.

The Effect of Project Exhibition Event on Physics Success and Prospective Teachers' Opinions about Projects

ERIC Educational Resources Information Center

Güven Yildirim, Ezgi; Köklükaya, Ayse Nesibe

2018-01-01

The purposes of this study were first to investigate the effects of the project-based learning (PBL) method and project exhibition event on the success of physics teacher candidates, and second, to reveal the experiment group students' views toward this learning method and project exhibition. The research model called explanatory mixed method, in…

Investigating Measurement Invariance in Computer-Based Personality Testing: The Impact of Using Anchor Items on Effect Size Indices

ERIC Educational Resources Information Center

Egberink, Iris J. L.; Meijer, Rob R.; Tendeiro, Jorge N.

2015-01-01

A popular method to assess measurement invariance of a particular item is based on likelihood ratio tests with all other items as anchor items. The results of this method are often only reported in terms of statistical significance, and researchers proposed different methods to empirically select anchor items. It is unclear, however, how many…

Relative Packing Groups in Template-Based Structure Prediction: Cooperative Effects of True Positive Constraints

PubMed Central

Day, Ryan; Qu, Xiaotao; Swanson, Rosemarie; Bohannan, Zach; Bliss, Robert

2011-01-01

Abstract Most current template-based structure prediction methods concentrate on finding the correct backbone conformation and then packing sidechains within that backbone. Our packing-based method derives distance constraints from conserved relative packing groups (RPGs). In our refinement approach, the RPGs provide a level of resolution that restrains global topology while allowing conformational sampling. In this study, we test our template-based structure prediction method using 51 prediction units from CASP7 experiments. RPG-based constraints are able to substantially improve approximately two-thirds of starting templates. Upon deeper investigation, we find that true positive spatial constraints, especially those non-local in sequence, derived from the RPGs were important to building nearer native models. Surprisingly, the fraction of incorrect or false positive constraints does not strongly influence the quality of the final candidate. This result indicates that our RPG-based true positive constraints sample the self-consistent, cooperative interactions of the native structure. The lack of such reinforcing cooperativity explains the weaker effect of false positive constraints. Generally, these findings are encouraging indications that RPGs will improve template-based structure prediction. PMID:21210729

Contact resistance extraction methods for short- and long-channel carbon nanotube field-effect transistors

NASA Astrophysics Data System (ADS)

Pacheco-Sanchez, Anibal; Claus, Martin; Mothes, Sven; Schröter, Michael

2016-11-01

Three different methods for the extraction of the contact resistance based on both the well-known transfer length method (TLM) and two variants of the Y-function method have been applied to simulation and experimental data of short- and long-channel CNTFETs. While for TLM special CNT test structures are mandatory, standard electrical device characteristics are sufficient for the Y-function methods. The methods have been applied to CNTFETs with low and high channel resistance. It turned out that the standard Y-function method fails to deliver the correct contact resistance in case of a relatively high channel resistance compared to the contact resistances. A physics-based validation is also given for the application of these methods based on applying traditional Si MOSFET theory to quasi-ballistic CNTFETs.

Fast and robust standard-deviation-based method for bulk motion compensation in phase-based functional OCT.

PubMed

Wei, Xiang; Camino, Acner; Pi, Shaohua; Cepurna, William; Huang, David; Morrison, John C; Jia, Yali

2018-05-01

Phase-based optical coherence tomography (OCT), such as OCT angiography (OCTA) and Doppler OCT, is sensitive to the confounding phase shift introduced by subject bulk motion. Traditional bulk motion compensation methods are limited by their accuracy and computing cost-effectiveness. In this Letter, to the best of our knowledge, we present a novel bulk motion compensation method for phase-based functional OCT. Bulk motion associated phase shift can be directly derived by solving its equation using a standard deviation of phase-based OCTA and Doppler OCT flow signals. This method was evaluated on rodent retinal images acquired by a prototype visible light OCT and human retinal images acquired by a commercial system. The image quality and computational speed were significantly improved, compared to two conventional phase compensation methods.

Comparing effectiveness of two client follow-up approaches in sustaining the use of Long Acting Reversible Contraceptives (LARC) among the underserved in rural Punjab, Pakistan: a study protocol and participants' profile.

PubMed

Azmat, Syed Khurram; Hameed, Waqas; Ali, Moazzam; Ishaque, Muhammad; Mustafa, Ghulam; Khan, Omar Farooq; Abbas, Ghazunfer; Munroe, Erik

2015-03-18

Pakistan observes a very high i.e. 37 percent modern contraceptive method related discontinuation rates within 12 months of their initiation. And almost 10 percent of these episodes of discontinuation happened due to the side effects or health concerns experienced by the women. Most importantly, it was noted that more than 12,000 first-level care facilities are located in the rural areas, including rural health centers, basic health units, and family welfare centers, but more than 30% of these facilities are nonfunctional. This paper presents a study protocol and participants' profiling of a prospective cohort follow-up to compare the effectiveness of household based and telephonic approaches in sustaining the use of Long Acting Reversible Contraceptives (LARC) whilst to facilitate lowering method related discontinuation and increasing switching amongst the contraceptive users. A 12-month multi-centre, non-inferiority prospective user follow-up is employed using three different study categories: a) household based follow-up; b) telephonic follow-up; and c) passive or need-based follow-up along with the hypothetical assumption that the telephonic client follow-up is not inferior to the household based follow-up by continuation rate of LARC and the telephonic follow-up is less-costly than the household based client follow-up. This follow-up will be conducted in 22 health facilities - (16 rural and 6 urban based facilities) in district Chakwal. The first two study categories will receive scheduled but different follow-up from the field workers at 1, 3, 6, 9, and 12 month while the third one i.e. the 'passive or need-based follow-up' will serve as a control group. Using sampling software PASS 11, it was estimated to have 414 clients in each study category and around 1366 clients will be recruited to account for 10% attrition rate. The study will help us to examine a more convenient method of effective follow-up for managing side effects, decreasing method discontinuation and increasing switching amongst users. The study information will also facilitate to develop a robust, effective and efficient mechanism for client follow-up to promote the continuation rates of LARC methods. The follow-up results and lessons learnt will be widely shared with stakeholders for their implementation and streamlining in health system.

Schema-Based Instruction on Learning English Polysemous Words: Effects of Instruction and Learners' Perceptions

ERIC Educational Resources Information Center

Mitsugi, Makoto

2017-01-01

The purpose of this study is to investigate the effectiveness of two instruction methods for teaching polysemous English prepositions ("at, in, on") and to explore learners' perception on learning tools used in the instruction when learning polysemous words. The first study investigated the effectiveness of schema-based instruction…

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

NASA Astrophysics Data System (ADS)

An, Lu; Guo, Baolong

2018-03-01

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

A time domain frequency-selective multivariate Granger causality approach.

PubMed

Leistritz, Lutz; Witte, Herbert

2016-08-01

The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions. It is based on a comparison of prediction errors of multivariate autoregressive models fitted to systematically modified time series. These modifications are based on signal decompositions, which enable a targeted cancellation of specific signal components with specific spectral properties. Depending on the embedded signal decomposition method, a frequency-selective or data-driven signal-adaptive Granger Causality Index may be derived.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography.

PubMed

Prakash, Jaya; Yalavarthy, Phaneendra K

2013-03-01

Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time.

Effect of tensile mean stress on fatigue behavior of single-crystal and directionally solidified superalloys

NASA Technical Reports Server (NTRS)

Kalluri, Sreeramesh; Mcgaw, Michael A.

1990-01-01

Two nickel base superalloys, single crystal PWA 1480 and directionally solidified MAR-M 246 + Hf, were studied in view of the potential usage of the former and usage of the latter as blade materials for the turbomachinery of the space shuttle main engine. The baseline zero mean stress (ZMS) fatigue life (FL) behavior of these superalloys was established, and then the effect of tensile mean stress (TMS) on their FL behavior was characterized. At room temperature these superalloys have lower ductilities and higher strengths than most polycrystalline engineering alloys. The cycle stress-strain response was thus nominally elastic in most of the fatigue tests. Therefore, a stress range based FL prediction approach was used to characterize both the ZMS and TMS fatigue data. In the past, several researchers have developed methods to account for the detrimental effect of tensile mean stress on the FL for polycrystalline engineering alloys. However, the applicability of these methods to single crystal and directionally solidified superalloys has not been established. In this study, these methods were applied to characterize the TMS fatigue data of single crystal PWA 1480 and directionally solidified MAR-M 246 + Hf and were found to be unsatisfactory. Therefore, a method of accounting for the TMS effect on FL, that is based on a technique proposed by Heidmann and Manson was developed to characterize the TMS fatigue data of these superalloys. Details of this method and its relationship to the conventionally used mean stress methods in FL prediction are discussed.

Teaching/Learning Methods and Students' Classification of Food Items

ERIC Educational Resources Information Center

Hamilton-Ekeke, Joy-Telu; Thomas, Malcolm

2011-01-01

Purpose: This study aims to investigate the effectiveness of a teaching method (TLS (Teaching/Learning Sequence)) based on a social constructivist paradigm on students' conceptualisation of classification of food. Design/methodology/approach: The study compared the TLS model developed by the researcher based on the social constructivist paradigm…

Study on the oxidative stability of poly a-olefin aviation lubricating base oil using PDSC method

NASA Astrophysics Data System (ADS)

Wu, N.; Fei, Y. W.; Yang, H. W.; Wang, Y. M.; Zong, Z. M.

2016-08-01

The oxidation stability of the domestic and import PAO aviation lubricating base oil was studied by the method of pressurized differential scanning calorimetry testing the initial oxidation temperature. The effects of anti-oxidants were investigated, and the best ratio of antioxidants was determined.

Study on load forecasting to data centers of high power density based on power usage effectiveness

NASA Astrophysics Data System (ADS)

Zhou, C. C.; Zhang, F.; Yuan, Z.; Zhou, L. M.; Wang, F. M.; Li, W.; Yang, J. H.

2016-08-01

There is usually considerable energy consumption in data centers. Load forecasting to data centers is in favor of formulating regional load density indexes and of great benefit to getting regional spatial load forecasting more accurately. The building structure and the other influential factors, i.e. equipment, geographic and climatic conditions, are considered for the data centers, and a method to forecast the load of the data centers based on power usage effectiveness is proposed. The cooling capacity of a data center and the index of the power usage effectiveness are used to forecast the power load of the data center in the method. The cooling capacity is obtained by calculating the heat load of the data center. The index is estimated using the group decision-making method of mixed language information. An example is given to prove the applicability and accuracy of this method.

Pretreatment of Biomass by Aqueous Ammonia for Bioethanol Production

NASA Astrophysics Data System (ADS)

Kim, Tae Hyun; Gupta, Rajesh; Lee, Y. Y.

The methods of pretreatment of lignocellulosic biomass using aqueous ammonia are described. The main effect of ammonia treatment of biomass is delignification without significantly affecting the carbohydrate contents. It is a very effective pretreatment method especially for substrates that have low lignin contents such as agricultural residues and herbaceous feedstock. The ammonia-based pretreatment is well suited for simultaneous saccharification and co-fermentation (SSCF) because the treated biomass retains cellulose as well as hemicellulose. It has been demonstrated that overall ethanol yield above 75% of the theoretical maximum on the basis of total carbohydrate is achievable from corn stover pretreated with aqueous ammonia by way of SSCF. There are two different types of pretreatment methods based on aqueous ammonia: (1) high severity, low contact time process (ammonia recycle percolation; ARP), (2) low severity, high treatment time process (soaking in aqueous ammonia; SAA). Both of these methods are described and discussed for their features and effectiveness.

Effects of modal truncation and condensation methods on the Frequency Response Function of a stage reducer connected by rigid coupling to a planetary gear system

NASA Astrophysics Data System (ADS)

Bouslema, Marwa; Frikha, Ahmed; Abdennadhar, Moez; Fakhfakh, Tahar; Nasri, Rachid; Haddar, Mohamed

2017-12-01

The present paper is aimed at the application of a substructure methodology, based on the Frequency Response Function (FRF) simulation technique, to analyze the vibration of a stage reducer connected by a rigid coupling to a planetary gear system. The computation of the vibration response was achieved using the FRF-based substructuring method. First of all, the two subsystems were analyzed separately and their FRF were obtained. Then the coupled model was analyzed indirectly using the substructuring technique. A comparison between the full system response and the coupled model response using the FRF substructuring was investigated to validate the coupling method. Furthermore, a parametric study of the effect of the shaft coupling stiffness on the FRF was discussed and the effects of modal truncation and condensation methods on the FRF of subsystems were analyzed.

A compensation controller based on a regional pole-assignment method for AMD control systems with a time-varying delay

NASA Astrophysics Data System (ADS)

Li, Zuohua; Chen, Chaojun; Teng, Jun; Wang, Ying

2018-04-01

Active mass damper/driver (AMD) control system has been proposed as an effective tool for high-rise buildings to resist strong dynamic loads. However, such disadvantage as time-varying delay in AMD control systems impedes their application in practices. Time-varying delay, which has an effect on the performance and stability of single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems, is considered in the paper. In addition, a new time-delay compensation controller based on regional pole-assignment method is presented. To verify its effectiveness, the proposed method is applied to a numerical example of a ten-storey frame and an experiment of a single span four-storey steel frame. Both numerical and experimental results demonstrate that the proposed method can enhance the performances of an AMD control system with time-varying delays.

The Effect of Brain Based Learning on Academic Achievement: A Meta-Analytical Study

ERIC Educational Resources Information Center

Gozuyesil, Eda; Dikici, Ayhan

2014-01-01

This study's aim is to measure the effect sizes of the quantitative studies that examined the effectiveness of brain-based learning on students' academic achievement and to examine with the meta-analytical method if there is a significant difference in effect in terms of the factors of education level, subject matter, sampling size, and the…

The Effect of Multiple Intelligences Theory-Based Education on Academic Achievement: A Meta-Analytic Review

ERIC Educational Resources Information Center

Bas, Gökhan

2016-01-01

The main purpose of this study is to determine the effect of multiple intelligences theory (MIT)-based education on students' academic achievement. In this research, the meta-analytic method was adopted to determine this effect, and studies related to this subject carried out in Turkey were compiled. The effect sizes of the studies included in the…

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity.

PubMed

Napoletano, Paolo; Piccoli, Flavio; Schettini, Raimondo

2018-01-12

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art.

The Extraction of Post-Earthquake Building Damage Informatiom Based on Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Chen, M.; Wang, X.; Dou, A.; Wu, X.

2018-04-01

The seismic damage information of buildings extracted from remote sensing (RS) imagery is meaningful for supporting relief and effective reduction of losses caused by earthquake. Both traditional pixel-based and object-oriented methods have some shortcoming in extracting information of object. Pixel-based method can't make fully use of contextual information of objects. Object-oriented method faces problem that segmentation of image is not ideal, and the choice of feature space is difficult. In this paper, a new stratage is proposed which combines Convolution Neural Network (CNN) with imagery segmentation to extract building damage information from remote sensing imagery. the key idea of this method includes two steps. First to use CNN to predicate the probability of each pixel and then integrate the probability within each segmentation spot. The method is tested through extracting the collapsed building and uncollapsed building from the aerial image which is acquired in Longtoushan Town after Ms 6.5 Ludian County, Yunnan Province earthquake. The results show that the proposed method indicates its effectiveness in extracting damage information of buildings after earthquake.

New approach to CT pixel-based photon dose calculations in heterogeneous media

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

Wong, J.W.; Henkelman, R.M.

The effects of small cavities on dose in water and the dose in a homogeneous nonunit density medium illustrate that inhomogeneities do not act independently in photon dose perturbation, and serve as two constraints which should be satisfied by approximate methods of computed tomography (CT) pixel-based dose calculations. Current methods at best satisfy only one of the two constraints and show inadequacies in some intermediate geometries. We have developed an approximate method that satisfies both these constraints and treats much of the synergistic effect of multiple inhomogeneities correctly. The method calculates primary and first-scatter doses by first-order ray tracing withmore » the first-scatter contribution augmented by a component of second scatter that behaves like first scatter. Multiple-scatter dose perturbation values extracted from small cavity experiments are used in a function which approximates the small residual multiple-scatter dose. For a wide range of geometries tested, our method agrees very well with measurements. The average deviation is less than 2% with a maximum of 3%. In comparison, calculations based on existing methods can have errors larger than 10%.« less

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

Accurate estimation of human body orientation from RGB-D sensors.

PubMed

Liu, Wu; Zhang, Yongdong; Tang, Sheng; Tang, Jinhui; Hong, Richang; Li, Jintao

2013-10-01

Accurate estimation of human body orientation can significantly enhance the analysis of human behavior, which is a fundamental task in the field of computer vision. However, existing orientation estimation methods cannot handle the various body poses and appearances. In this paper, we propose an innovative RGB-D-based orientation estimation method to address these challenges. By utilizing the RGB-D information, which can be real time acquired by RGB-D sensors, our method is robust to cluttered environment, illumination change and partial occlusions. Specifically, efficient static and motion cue extraction methods are proposed based on the RGB-D superpixels to reduce the noise of depth data. Since it is hard to discriminate all the 360 (°) orientation using static cues or motion cues independently, we propose to utilize a dynamic Bayesian network system (DBNS) to effectively employ the complementary nature of both static and motion cues. In order to verify our proposed method, we build a RGB-D-based human body orientation dataset that covers a wide diversity of poses and appearances. Our intensive experimental evaluations on this dataset demonstrate the effectiveness and efficiency of the proposed method.

Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses.

PubMed

Ye, Jun

2015-03-01

In pattern recognition and medical diagnosis, similarity measure is an important mathematical tool. To overcome some disadvantages of existing cosine similarity measures of simplified neutrosophic sets (SNSs) in vector space, this paper proposed improved cosine similarity measures of SNSs based on cosine function, including single valued neutrosophic cosine similarity measures and interval neutrosophic cosine similarity measures. Then, weighted cosine similarity measures of SNSs were introduced by taking into account the importance of each element. Further, a medical diagnosis method using the improved cosine similarity measures was proposed to solve medical diagnosis problems with simplified neutrosophic information. The improved cosine similarity measures between SNSs were introduced based on cosine function. Then, we compared the improved cosine similarity measures of SNSs with existing cosine similarity measures of SNSs by numerical examples to demonstrate their effectiveness and rationality for overcoming some shortcomings of existing cosine similarity measures of SNSs in some cases. In the medical diagnosis method, we can find a proper diagnosis by the cosine similarity measures between the symptoms and considered diseases which are represented by SNSs. Then, the medical diagnosis method based on the improved cosine similarity measures was applied to two medical diagnosis problems to show the applications and effectiveness of the proposed method. Two numerical examples all demonstrated that the improved cosine similarity measures of SNSs based on the cosine function can overcome the shortcomings of the existing cosine similarity measures between two vectors in some cases. By two medical diagnoses problems, the medical diagnoses using various similarity measures of SNSs indicated the identical diagnosis results and demonstrated the effectiveness and rationality of the diagnosis method proposed in this paper. The improved cosine measures of SNSs based on cosine function can overcome some drawbacks of existing cosine similarity measures of SNSs in vector space, and then their diagnosis method is very suitable for handling the medical diagnosis problems with simplified neutrosophic information and demonstrates the effectiveness and rationality of medical diagnoses. Copyright © 2014 Elsevier B.V. All rights reserved.

Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves.

PubMed

Ma, Yunbei; Zhou, Xiao-Hua

2017-02-01

For time-to-event data in a randomized clinical trial, we proposed two new methods for selecting an optimal treatment for a patient based on the covariate-specific treatment effect curve, which is used to represent the clinical utility of a predictive biomarker. To select an optimal treatment for a patient with a specific biomarker value, we proposed pointwise confidence intervals for each covariate-specific treatment effect curve and the difference between covariate-specific treatment effect curves of two treatments. Furthermore, to select an optimal treatment for a future biomarker-defined subpopulation of patients, we proposed confidence bands for each covariate-specific treatment effect curve and the difference between each pair of covariate-specific treatment effect curve over a fixed interval of biomarker values. We constructed the confidence bands based on a resampling technique. We also conducted simulation studies to evaluate finite-sample properties of the proposed estimation methods. Finally, we illustrated the application of the proposed method in a real-world data set.

Automated time series forecasting for biosurveillance.

PubMed

Burkom, Howard S; Murphy, Sean Patrick; Shmueli, Galit

2007-09-30

For robust detection performance, traditional control chart monitoring for biosurveillance is based on input data free of trends, day-of-week effects, and other systematic behaviour. Time series forecasting methods may be used to remove this behaviour by subtracting forecasts from observations to form residuals for algorithmic input. We describe three forecast methods and compare their predictive accuracy on each of 16 authentic syndromic data streams. The methods are (1) a non-adaptive regression model using a long historical baseline, (2) an adaptive regression model with a shorter, sliding baseline, and (3) the Holt-Winters method for generalized exponential smoothing. Criteria for comparing the forecasts were the root-mean-square error, the median absolute per cent error (MedAPE), and the median absolute deviation. The median-based criteria showed best overall performance for the Holt-Winters method. The MedAPE measures over the 16 test series averaged 16.5, 11.6, and 9.7 for the non-adaptive regression, adaptive regression, and Holt-Winters methods, respectively. The non-adaptive regression forecasts were degraded by changes in the data behaviour in the fixed baseline period used to compute model coefficients. The mean-based criterion was less conclusive because of the effects of poor forecasts on a small number of calendar holidays. The Holt-Winters method was also most effective at removing serial autocorrelation, with most 1-day-lag autocorrelation coefficients below 0.15. The forecast methods were compared without tuning them to the behaviour of individual series. We achieved improved predictions with such tuning of the Holt-Winters method, but practical use of such improvements for routine surveillance will require reliable data classification methods.

Analysis on accuracy improvement of rotor-stator rubbing localization based on acoustic emission beamforming method.

PubMed

He, Tian; Xiao, Denghong; Pan, Qiang; Liu, Xiandong; Shan, Yingchun

2014-01-01

This paper attempts to introduce an improved acoustic emission (AE) beamforming method to localize rotor-stator rubbing fault in rotating machinery. To investigate the propagation characteristics of acoustic emission signals in casing shell plate of rotating machinery, the plate wave theory is used in a thin plate. A simulation is conducted and its result shows the localization accuracy of beamforming depends on multi-mode, dispersion, velocity and array dimension. In order to reduce the effect of propagation characteristics on the source localization, an AE signal pre-process method is introduced by combining plate wave theory and wavelet packet transform. And the revised localization velocity to reduce effect of array size is presented. The accuracy of rubbing localization based on beamforming and the improved method of present paper are compared by the rubbing test carried on a test table of rotating machinery. The results indicate that the improved method can localize rub fault effectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Clustering gene expression data based on predicted differential effects of GV interaction.

PubMed

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

The effect of instructional methodology on high school students natural sciences standardized tests scores

NASA Astrophysics Data System (ADS)

Powell, P. E.

Educators have recently come to consider inquiry based instruction as a more effective method of instruction than didactic instruction. Experience based learning theory suggests that student performance is linked to teaching method. However, research is limited on inquiry teaching and its effectiveness on preparing students to perform well on standardized tests. The purpose of the study to investigate whether one of these two teaching methodologies was more effective in increasing student performance on standardized science tests. The quasi experimental quantitative study was comprised of two stages. Stage 1 used a survey to identify teaching methods of a convenience sample of 57 teacher participants and determined level of inquiry used in instruction to place participants into instructional groups (the independent variable). Stage 2 used analysis of covariance (ANCOVA) to compare posttest scores on a standardized exam by teaching method. Additional analyses were conducted to examine the differences in science achievement by ethnicity, gender, and socioeconomic status by teaching methodology. Results demonstrated a statistically significant gain in test scores when taught using inquiry based instruction. Subpopulation analyses indicated all groups showed improved mean standardized test scores except African American students. The findings benefit teachers and students by presenting data supporting a method of content delivery that increases teacher efficacy and produces students with a greater cognition of science content that meets the school's mission and goals.

Crack image segmentation based on improved DBC method

NASA Astrophysics Data System (ADS)

Cao, Ting; Yang, Nan; Wang, Fengping; Gao, Ting; Wang, Weixing

2017-11-01

With the development of computer vision technology, crack detection based on digital image segmentation method arouses global attentions among researchers and transportation ministries. Since the crack always exhibits the random shape and complex texture, it is still a challenge to accomplish reliable crack detection results. Therefore, a novel crack image segmentation method based on fractal DBC (differential box counting) is introduced in this paper. The proposed method can estimate every pixel fractal feature based on neighborhood information which can consider the contribution from all possible direction in the related block. The block moves just one pixel every time so that it could cover all the pixels in the crack image. Unlike the classic DBC method which only describes fractal feature for the related region, this novel method can effectively achieve crack image segmentation according to the fractal feature of every pixel. The experiment proves the proposed method can achieve satisfactory results in crack detection.

Predicting missing links via correlation between nodes

NASA Astrophysics Data System (ADS)

Liao, Hao; Zeng, An; Zhang, Yi-Cheng

2015-10-01

As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the Pearson correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

Competitive region orientation code for palmprint verification and identification

NASA Astrophysics Data System (ADS)

Tang, Wenliang

2015-11-01

Orientation features of the palmprint have been widely investigated in coding-based palmprint-recognition methods. Conventional orientation-based coding methods usually used discrete filters to extract the orientation feature of palmprint. However, in real operations, the orientations of the filter usually are not consistent with the lines of the palmprint. We thus propose a competitive region orientation-based coding method. Furthermore, an effective weighted balance scheme is proposed to improve the accuracy of the extracted region orientation. Compared with conventional methods, the region orientation of the palmprint extracted using the proposed method can precisely and robustly describe the orientation feature of the palmprint. Extensive experiments on the baseline PolyU and multispectral palmprint databases are performed and the results show that the proposed method achieves a promising performance in comparison to conventional state-of-the-art orientation-based coding methods in both palmprint verification and identification.

Effects of problem-based learning in Chinese radiology education

PubMed Central

Zhang, Song; Xu, Jiancheng; Wang, Hongwei; Zhang, Dong; Zhang, Qichuan; Zou, Liguang

2018-01-01

Abstract Background: In recent years, the problem-based learning (PBL) teaching method has been extensively applied as an experimental educational method in Chinese radiology education. However, the results of individual studies were inconsistent and inconclusive. A meta-analysis was performed to evaluate the effects of PBL on radiology education in China. Methods: Databases of Chinese and English languages were searched from inception up to November 2017. The standard mean difference (SMD) with its 95% confidence interval (95% CI) was used to determine the over effects of PBL compared with the traditional teaching method. Results: Seventeen studies involving 1487 participants were included in this meta-analysis. Of them, 16 studies provided sufficient data for the pooled analysis and showed that PBL teaching method had a positive effect on achieving higher theoretical scores compared with the traditional teaching method (SMD = 1.20, 95% CI [0.68, 1.71]). Thirteen studies provided sufficient data on skill scores, and a significant difference in favor of PBL was also observed (SMD = 2.10, 95% CI [1.38, 2.83]). Questionnaire surveys were applied in most of the included studies and indicated positive effects of PBL on students’ learning interest, scope of knowledge, team spirit, and oral expression. Conclusion: The result shows that PBL appears to be more effective on radiology education than traditional teaching method in China. However, the heterogeneity of the included studies cannot be neglected. Further well-designed studies about this topic are needed to confirm the above findings. PMID:29489669

A Multi-level Fuzzy Evaluation Method for Smart Distribution Network Based on Entropy Weight

NASA Astrophysics Data System (ADS)

Li, Jianfang; Song, Xiaohui; Gao, Fei; Zhang, Yu

2017-05-01

Smart distribution network is considered as the future trend of distribution network. In order to comprehensive evaluate smart distribution construction level and give guidance to the practice of smart distribution construction, a multi-level fuzzy evaluation method based on entropy weight is proposed. Firstly, focus on both the conventional characteristics of distribution network and new characteristics of smart distribution network such as self-healing and interaction, a multi-level evaluation index system which contains power supply capability, power quality, economy, reliability and interaction is established. Then, a combination weighting method based on Delphi method and entropy weight method is put forward, which take into account not only the importance of the evaluation index in the experts’ subjective view, but also the objective and different information from the index values. Thirdly, a multi-level evaluation method based on fuzzy theory is put forward. Lastly, an example is conducted based on the statistical data of some cites’ distribution network and the evaluation method is proved effective and rational.

Shape-Based Virtual Screening with Volumetric Aligned Molecular Shapes

PubMed Central

Koes, David Ryan; Camacho, Carlos J.

2014-01-01

Shape-based virtual screening is an established and effective method for identifying small molecules that are similar in shape and function to a reference ligand. We describe a new method of shape-based virtual screening, volumetric aligned molecular shapes (VAMS). VAMS uses efficient data structures to encode and search molecular shapes. We demonstrate that VAMS is an effective method for shape-based virtual screening and that it can be successfully used as a pre-filter to accelerate more computationally demanding search algorithms. Unique to VAMS is a novel minimum/maximum shape constraint query for precisely specifying the desired molecular shape. Shape constraint searches in VAMS are particularly efficient and millions of shapes can be searched in a fraction of a second. We compare the performance of VAMS with two other shape-based virtual screening algorithms a benchmark of 102 protein targets consisting of more than 32 million molecular shapes and find that VAMS provides a competitive trade-off between run-time performance and virtual screening performance. PMID:25049193

An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach.

PubMed

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance.

An Efficient Diagnosis System for Parkinson's Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

PubMed Central

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance. PMID:25484912

Patient-based surveying: a cost-effective approach for reaching large markets.

PubMed

Byer, S

1995-01-01

Member-based surveying is an important tool for managed care companies to discern newer and better ways in which to keep their current members satisfied, develop products that will attract new members, and to gauge changes of course in health consumer opinion. This article discusses a consumer friendly and cost-effective method to survey members and the general public that has produced a very positive response for a modest investment. The response rate will likely improve over time as the method gains broader acceptance.

A peaking-regulation-balance-based method for wind & PV power integrated accommodation

NASA Astrophysics Data System (ADS)

Zhang, Jinfang; Li, Nan; Liu, Jun

2018-02-01

Rapid development of China’s new energy in current and future should be focused on cooperation of wind and PV power. Based on the analysis of system peaking balance, combined with the statistical features of wind and PV power output characteristics, a method of comprehensive integrated accommodation analysis of wind and PV power is put forward. By the electric power balance during night peaking load period in typical day, wind power installed capacity is determined firstly; then PV power installed capacity could be figured out by midday peak load hours, which effectively solves the problem of uncertainty when traditional method hard determines the combination of the wind and solar power simultaneously. The simulation results have validated the effectiveness of the proposed method.

Power line identification of millimeter wave radar based on PCA-GS-SVM

NASA Astrophysics Data System (ADS)

Fang, Fang; Zhang, Guifeng; Cheng, Yansheng

2017-12-01

Aiming at the problem that the existing detection method can not effectively solve the security of UAV's ultra low altitude flight caused by power line, a power line recognition method based on grid search (GS) and the principal component analysis and support vector machine (PCA-SVM) is proposed. Firstly, the candidate line of Hough transform is reduced by PCA, and the main feature of candidate line is extracted. Then, upport vector machine (SVM is) optimized by grid search method (GS). Finally, using support vector machine classifier optimized parameters to classify the candidate line. MATLAB simulation results show that this method can effectively identify the power line and noise, and has high recognition accuracy and algorithm efficiency.

Investigating the Effectiveness of an Arts-Based and Mindfulness-Based Group Program for the Improvement of Resilience in Children in Need

ERIC Educational Resources Information Center

Coholic, Diana; Eys, Mark; Lougheed, Sean

2012-01-01

We discuss preliminary findings from a study that investigated the effectiveness of a Holistic Arts-Based Group Program (HAP) for the development of resilience in children in need. The HAP teaches mindfulness using arts-based methods, and aims to teach children how to understand their feelings and develop their strengths. We assessed the…

[Evaluation of four dark object atmospheric correction methods based on ZY-3 CCD data].

PubMed

Guo, Hong; Gu, Xing-fa; Xie, Yong; Yu, Tao; Gao, Hai-liang; Wei, Xiang-qin; Liu, Qi-yue

2014-08-01

The present paper performed the evaluation of four dark-object subtraction(DOS) atmospheric correction methods based on 2012 Inner Mongolia experimental data The authors analyzed the impacts of key parameters of four DOS methods when they were applied to ZY-3 CCD data The results showed that (1) All four DOS methods have significant atmospheric correction effect at band 1, 2 and 3. But as for band 4, the atmospheric correction effect of DOS4 is the best while DOS2 is the worst; both DOS1 and DOS3 has no obvious atmospheric correction effect. (2) The relative error (RE) of DOS1 atmospheric correction method is larger than 10% at four bands; The atmospheric correction effect of DOS2 works the best at band 1(AE (absolute error)=0.0019 and RE=4.32%) and the worst error appears at band 4(AE=0.0464 and RE=19.12%); The RE of DOS3 is about 10% for all bands. (3) The AE of atmospheric correction results for DOS4 method is less than 0. 02 and the RE is less than 10% for all bands. Therefore, the DOS4 method provides the best accuracy of atmospheric correction results for ZY-3 image.

Gate frequency sweep: An effective method to evaluate the dynamic performance of AlGaN/GaN power heterojunction field effect transistors

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

Santi, C. de; Meneghini, M., E-mail: matteo.meneghini@dei.unipd.it; Meneghesso, G.

2014-08-18

With this paper we propose a test method for evaluating the dynamic performance of GaN-based transistors, namely, gate-frequency sweep measurements: the effectiveness of the method is verified by characterizing the dynamic performance of Gate Injection Transistors. We demonstrate that this method can provide an effective description of the impact of traps on the transient performance of Heterojunction Field Effect Transistors, and information on the properties (activation energy and cross section) of the related defects. Moreover, we discuss the relation between the results obtained by gate-frequency sweep measurements and those collected by conventional drain current transients and double pulse characterization.

Transfer of a Mycobacterium tuberculosis genotyping method, Spoligotyping, from a reverse line-blot hybridization, membrane-based assay to the Luminex multianalyte profiling system.

PubMed

Cowan, Lauren S; Diem, Lois; Brake, Mary Catherine; Crawford, Jack T

2004-01-01

Spoligotyping using Luminex technology was shown to be a highly reproducible method suitable for high-throughput analysis. Spoligotyping of 48 isolates using the traditional membrane-based assay and the Luminex assay yielded concordant results for all isolates. The Luminex platform provides greater flexibility and cost effectiveness than the membrane-based assay.

Low-dose CT reconstruction with patch based sparsity and similarity constraints

NASA Astrophysics Data System (ADS)

Xu, Qiong; Mou, Xuanqin

2014-03-01

As the rapid growth of CT based medical application, low-dose CT reconstruction becomes more and more important to human health. Compared with other methods, statistical iterative reconstruction (SIR) usually performs better in lowdose case. However, the reconstructed image quality of SIR highly depends on the prior based regularization due to the insufficient of low-dose data. The frequently-used regularization is developed from pixel based prior, such as the smoothness between adjacent pixels. This kind of pixel based constraint cannot distinguish noise and structures effectively. Recently, patch based methods, such as dictionary learning and non-local means filtering, have outperformed the conventional pixel based methods. Patch is a small area of image, which expresses structural information of image. In this paper, we propose to use patch based constraint to improve the image quality of low-dose CT reconstruction. In the SIR framework, both patch based sparsity and similarity are considered in the regularization term. On one hand, patch based sparsity is addressed by sparse representation and dictionary learning methods, on the other hand, patch based similarity is addressed by non-local means filtering method. We conducted a real data experiment to evaluate the proposed method. The experimental results validate this method can lead to better image with less noise and more detail than other methods in low-count and few-views cases.

Functionalization of graphene by size and doping control and its optoelectronic applications

NASA Astrophysics Data System (ADS)

Tang, Libin; Ji, Rongbin; Tian, Pin; Kong, Jincheng; Xiang, Jinzhong

2017-02-01

Graphene has received intensive attention in recent years because of the special physical and chemical properties. However, up to now graphene has not been widely used in optoelectronic fields yet, which is mainly caused by its semimetal properties. Therefore, changing its properties from semimetal to semiconductor is becoming a focal point. Recently, aiming at tuning the energy band of graphene, we have carried out systematic studies on the preparations of graphene based materials and devices, the CVD growth techniques of monolayer and double layer graphenes have been developed, the large-area doped graphene films have been fabricated to tune the structure-related optical and electrical properties. A novel graphene oxide (GO) preparation method namely "Tang-Lau method" has been invented, the graphene quantum dots growths by microwave assisted hydrothermal method and "Soft-Template method" have been developed, the Cl, S and K doped graphene quantum dots preparations by hydrothermal methods have also been invented. Systematic investigations have been carried out for the effect of preparation parameters on the properties of graphene based materials, the effects of size, doping elements on the energy level of graphene based materials have been explored and discussed. Based on the semiconducting graphene based materials, some novel room temperature photodetectors covering detection wavebands from UV, Vis and NIR have been designed and fabricated.

Bandwidth correction for LED chromaticity based on Levenberg-Marquardt algorithm

NASA Astrophysics Data System (ADS)

Huang, Chan; Jin, Shiqun; Xia, Guo

2017-10-01

Light emitting diode (LED) is widely employed in industrial applications and scientific researches. With a spectrometer, the chromaticity of LED can be measured. However, chromaticity shift will occur due to the broadening effects of the spectrometer. In this paper, an approach is put forward to bandwidth correction for LED chromaticity based on Levenberg-Marquardt algorithm. We compare chromaticity of simulated LED spectra by using the proposed method and differential operator method to bandwidth correction. The experimental results show that the proposed approach achieves an excellent performance in bandwidth correction which proves the effectiveness of the approach. The method has also been tested on true blue LED spectra.

[Multifactorial method for assessing the physical work capacity of mice].

PubMed

Dubovik, B V; Bogomazov, S D

1987-01-01

Based on the swimming test according to Kiplinger, in experiments on (CBA X C57BL)F1 mice there were elaborated criteria for animal performance evaluation in the process of repeated swimming of a standard distance thus measuring power, volume of work and rate of the fatigue development in relative units. From the study of effects of sydnocarb, bemethyl and phenazepam on various parameters of physical performance of mice a conclusion was made that the proposed method provides a more informative evaluation of the pharmacological effect on physical performance of animals as compared to the methods based on the record of time of performing the load.

Validation of a low cost computer-based method for quantification of immunohistochemistry-stained sections.

PubMed

Montgomery, Jill D; Hensler, Heather R; Jacobson, Lisa P; Jenkins, Frank J

2008-07-01

The aim of the present study was to determine if the Alpha DigiDoc RT system would be an effective method of quantifying immunohistochemical staining as compared with a manual counting method, which is considered the gold standard. Two readers were used to count 31 samples by both methods. The results obtained using the Bland-Altman for concordance deemed no statistical difference between the 2 methods. Thus, the Alpha DigiDoc RT system is an effective, low cost method to quantify immunohistochemical data.

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

NASA Astrophysics Data System (ADS)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Reference voltage calculation method based on zero-sequence component optimisation for a regional compensation DVR

NASA Astrophysics Data System (ADS)

Jian, Le; Cao, Wang; Jintao, Yang; Yinge, Wang

2018-04-01

This paper describes the design of a dynamic voltage restorer (DVR) that can simultaneously protect several sensitive loads from voltage sags in a region of an MV distribution network. A novel reference voltage calculation method based on zero-sequence voltage optimisation is proposed for this DVR to optimise cost-effectiveness in compensation of voltage sags with different characteristics in an ungrounded neutral system. Based on a detailed analysis of the characteristics of voltage sags caused by different types of faults and the effect of the wiring mode of the transformer on these characteristics, the optimisation target of the reference voltage calculation is presented with several constraints. The reference voltages under all types of voltage sags are calculated by optimising the zero-sequence component, which can reduce the degree of swell in the phase-to-ground voltage after compensation to the maximum extent and can improve the symmetry degree of the output voltages of the DVR, thereby effectively increasing the compensation ability. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Asthma management simulation for children: translating theory, methods, and strategies to effect behavior change.

PubMed

Shegog, Ross; Bartholomew, L Kay; Gold, Robert S; Pierrel, Elaine; Parcel, Guy S; Sockrider, Marianna M; Czyzewski, Danita I; Fernandez, Maria E; Berlin, Nina J; Abramson, Stuart

2006-01-01

Translating behavioral theories, models, and strategies to guide the development and structure of computer-based health applications is well recognized, although a continued challenge for program developers. A stepped approach to translate behavioral theory in the design of simulations to teach chronic disease management to children is described. This includes the translation steps to: 1) define target behaviors and their determinants, 2) identify theoretical methods to optimize behavioral change, and 3) choose educational strategies to effectively apply these methods and combine these into a cohesive computer-based simulation for health education. Asthma is used to exemplify a chronic health management problem and a computer-based asthma management simulation (Watch, Discover, Think and Act) that has been evaluated and shown to effect asthma self-management in children is used to exemplify the application of theory to practice. Impact and outcome evaluation studies have indicated the effectiveness of these steps in providing increased rigor and accountability, suggesting their utility for educators and developers seeking to apply simulations to enhance self-management behaviors in patients.

Social value and individual choice: The value of a choice-based decision-making process in a collectively funded health system.

PubMed

Espinoza, Manuel Antonio; Manca, Andrea; Claxton, Karl; Sculpher, Mark

2018-02-01

Evidence about cost-effectiveness is increasingly being used to inform decisions about the funding of new technologies that are usually implemented as guidelines from centralized decision-making bodies. However, there is also an increasing recognition for the role of patients in determining their preferred treatment option. This paper presents a method to estimate the value of implementing a choice-based decision process using the cost-effectiveness analysis toolbox. This value is estimated for 3 alternative scenarios. First, it compares centralized decisions, based on population average cost-effectiveness, against a decision process based on patient choice. Second, it compares centralized decision based on patients' subgroups versus an individual choice-based decision process. Third, it compares a centralized process based on average cost-effectiveness against a choice-based process where patients choose according to a different measure of outcome to that used by the centralized decision maker. The methods are applied to a case study for the management of acute coronary syndrome. It is concluded that implementing a choice-based process of treatment allocation may be an option in collectively funded health systems. However, its value will depend on the specific health problem and the social values considered relevant to the health system. Copyright © 2017 John Wiley & Sons, Ltd.

Development of Speaking Skills through Activity Based Learning at the Elementary Level

ERIC Educational Resources Information Center

Ul-Haq, Zahoor; Khurram, Bushra Ahmed; Bangash, Arshad Khan

2017-01-01

Purpose: This paper discusses an effective instructional method called "activity based learning" that can be used to develop the speaking skills of students in the elementary school level. The present study was conducted to determine the effect of activity based learning on the development of the speaking skills of low and high achievers…

The Effectiveness of the Creative Writing Instruction Program Based on Speaking Activities (CWIPSA)

ERIC Educational Resources Information Center

Bayat, Seher

2016-01-01

This study aims to develop a creative writing instruction program based on speaking activities and to investigate its effect on fourth-grade primary school students' creative writing achievements and writing attitudes. The experimental method based on the pre-test/post-test model was used in this research. The research was conducted with 42…

A Systematic Review of Parent and Family-Based Intervention Effectiveness on Sexual Outcomes in Young People

ERIC Educational Resources Information Center

Downing, Jennifer; Jones, Lisa; Bates, Geoff; Sumnall, Harry; Bellis, Mark A.

2011-01-01

Limited evidence exists about the effectiveness of parent/family-based interventions for preventing poor sexual health outcomes, thus a systematic review was conducted as part of a wider review of community-based sex and relationships and alcohol education. Method guidance from the UK's National Institute for Health and Clinical Excellence was…

Multiband tangent space mapping and feature selection for classification of EEG during motor imagery.

PubMed

Islam, Md Rabiul; Tanaka, Toshihisa; Molla, Md Khademul Islam

2018-05-08

When designing multiclass motor imagery-based brain-computer interface (MI-BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of covariance matrices is an effective technique. This paper aims to introduce a method using TSM for finding accurate operational frequency bands related brain activities associated with MI tasks. A multichannel electroencephalogram (EEG) signal is decomposed into multiple subbands, and tangent features are then estimated on each subband. A mutual information analysis-based effective algorithm is implemented to select subbands containing features capable of improving motor imagery classification accuracy. Thus obtained features of selected subbands are combined to get feature space. A principal component analysis-based approach is employed to reduce the features dimension and then the classification is accomplished by a support vector machine (SVM). Offline analysis demonstrates the proposed multiband tangent space mapping with subband selection (MTSMS) approach outperforms state-of-the-art methods. It acheives the highest average classification accuracy for all datasets (BCI competition dataset 2a, IIIa, IIIb, and dataset JK-HH1). The increased classification accuracy of MI tasks with the proposed MTSMS approach can yield effective implementation of BCI. The mutual information-based subband selection method is implemented to tune operation frequency bands to represent actual motor imagery tasks.

A novel method for overlapping community detection using Multi-objective optimization

NASA Astrophysics Data System (ADS)

Ebrahimi, Morteza; Shahmoradi, Mohammad Reza; Heshmati, Zainabolhoda; Salehi, Mostafa

2018-09-01

The problem of community detection as one of the most important applications of network science can be addressed effectively by multi-objective optimization. In this paper, we aim to present a novel efficient method based on this approach. Also, in this study the idea of using all Pareto fronts to detect overlapping communities is introduced. The proposed method has two main advantages compared to other multi-objective optimization based approaches. The first advantage is scalability, and the second is the ability to find overlapping communities. Despite most of the works, the proposed method is able to find overlapping communities effectively. The new algorithm works by extracting appropriate communities from all the Pareto optimal solutions, instead of choosing the one optimal solution. Empirical experiments on different features of separated and overlapping communities, on both synthetic and real networks show that the proposed method performs better in comparison with other methods.

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.

Repeatability, Reproducibility, Separative Power and Subjectivity of Different Fish Morphometric Analysis Methods

PubMed Central

Takács, Péter

2016-01-01

We compared the repeatability, reproducibility (intra- and inter-measurer similarity), separative power and subjectivity (measurer effect on results) of four morphometric methods frequently used in ichthyological research, the “traditional” caliper-based (TRA) and truss-network (TRU) distance methods and two geometric methods that compare landmark coordinates on the body (GMB) and scales (GMS). In each case, measurements were performed three times by three measurers on the same specimen of three common cyprinid species (roach Rutilus rutilus (Linnaeus, 1758), bleak Alburnus alburnus (Linnaeus, 1758) and Prussian carp Carassius gibelio (Bloch, 1782)) collected from three closely-situated sites in the Lake Balaton catchment (Hungary) in 2014. TRA measurements were made on conserved specimens using a digital caliper, while TRU, GMB and GMS measurements were undertaken on digital images of the bodies and scales. In most cases, intra-measurer repeatability was similar. While all four methods were able to differentiate the source populations, significant differences were observed in their repeatability, reproducibility and subjectivity. GMB displayed highest overall repeatability and reproducibility and was least burdened by measurer effect. While GMS showed similar repeatability to GMB when fish scales had a characteristic shape, it showed significantly lower reproducability (compared with its repeatability) for each species than the other methods. TRU showed similar repeatability as the GMS. TRA was the least applicable method as measurements were obtained from the fish itself, resulting in poor repeatability and reproducibility. Although all four methods showed some degree of subjectivity, TRA was the only method where population-level detachment was entirely overwritten by measurer effect. Based on these results, we recommend a) avoidance of aggregating different measurer’s datasets when using TRA and GMS methods; and b) use of image-based methods for morphometric surveys. Automation of the morphometric workflow would also reduce any measurer effect and eliminate measurement and data-input errors. PMID:27327896

[Comparison of two algorithms for development of design space-overlapping method and probability-based method].

PubMed

Shao, Jing-Yuan; Qu, Hai-Bin; Gong, Xing-Chu

2018-05-01

In this work, two algorithms (overlapping method and the probability-based method) for design space calculation were compared by using the data collected from extraction process of Codonopsis Radix as an example. In the probability-based method, experimental error was simulated to calculate the probability of reaching the standard. The effects of several parameters on the calculated design space were studied, including simulation number, step length, and the acceptable probability threshold. For the extraction process of Codonopsis Radix, 10 000 times of simulation and 0.02 for the calculation step length can lead to a satisfactory design space. In general, the overlapping method is easy to understand, and can be realized by several kinds of commercial software without coding programs, but the reliability of the process evaluation indexes when operating in the design space is not indicated. Probability-based method is complex in calculation, but can provide the reliability to ensure that the process indexes can reach the standard within the acceptable probability threshold. In addition, there is no probability mutation in the edge of design space by probability-based method. Therefore, probability-based method is recommended for design space calculation. Copyright© by the Chinese Pharmaceutical Association.

[Evidence based medicine and cost-effectiveness analysis in ophthalmology].

PubMed

Nováková, D; Rozsíval, P

2004-09-01

To make the reader familiar with the term evidence based medicine (EBM), to explain the principle of cost-effectiveness analysis (price-profit), and to show its usefulness to compare the effectiveness of different medical procedures. Based on few examples, in this article the relevance and calculation of important parameters of cost-effectiveness analysis (CE), as utility value (UV), quality adjusted life years (QALY) is explained. In addition, calculation of UV and QALY for the cataract surgery, including its complications, is provided. According to this method, laser photocoagulation and cryocoagulation of the early stages of retinopathy of prematurity, treatment of amblyopia, cataract surgery of one or both eyes, from the vitreoretinal procedures the early vitrectomy in cases of hemophtalmus in proliferative diabetic retinopathy or grid laser photocoagulation in diabetic macular edema or worsening of the visual acuity due to the branch retinal vein occlusion belong to highly effective procedures. On the other hand, to the procedures with low cost effectiveness belongs the treating of the central retinal artery occlusion with anterior chamber paracentesis, as well as with CO2 inhalation, or photodynamic therapy in choroidal neovascularization in age-related macular degeneration with visual acuity of the better eye 20/200. Cost-effectiveness analysis is a new perspective method evaluating successfulness of medical procedure comparing the final effect with the financial costs. In evaluation of effectiveness of individual procedures, three main aspects are considered: subjective feeling of influence of the disease on the patient's life, objective results of clinical examination and financial costs of the procedure. According to this method, the cataract surgery, as well as procedures in the pediatric ophthalmology belong to the most effective surgical methods.

Unsupervised background-constrained tank segmentation of infrared images in complex background based on the Otsu method.

PubMed

Zhou, Yulong; Gao, Min; Fang, Dan; Zhang, Baoquan

2016-01-01

In an effort to implement fast and effective tank segmentation from infrared images in complex background, the threshold of the maximum between-class variance method (i.e., the Otsu method) is analyzed and the working mechanism of the Otsu method is discussed. Subsequently, a fast and effective method for tank segmentation from infrared images in complex background is proposed based on the Otsu method via constraining the complex background of the image. Considering the complexity of background, the original image is firstly divided into three classes of target region, middle background and lower background via maximizing the sum of their between-class variances. Then, the unsupervised background constraint is implemented based on the within-class variance of target region and hence the original image can be simplified. Finally, the Otsu method is applied to simplified image for threshold selection. Experimental results on a variety of tank infrared images (880 × 480 pixels) in complex background demonstrate that the proposed method enjoys better segmentation performance and even could be comparative with the manual segmentation in segmented results. In addition, its average running time is only 9.22 ms, implying the new method with good performance in real time processing.

Three dimensional iterative beam propagation method for optical waveguide devices

NASA Astrophysics Data System (ADS)

Ma, Changbao; Van Keuren, Edward

2006-10-01

The finite difference beam propagation method (FD-BPM) is an effective model for simulating a wide range of optical waveguide structures. The classical FD-BPMs are based on the Crank-Nicholson scheme, and in tridiagonal form can be solved using the Thomas method. We present a different type of algorithm for 3-D structures. In this algorithm, the wave equation is formulated into a large sparse matrix equation which can be solved using iterative methods. The simulation window shifting scheme and threshold technique introduced in our earlier work are utilized to overcome the convergence problem of iterative methods for large sparse matrix equation and wide-angle simulations. This method enables us to develop higher-order 3-D wide-angle (WA-) BPMs based on Pade approximant operators and the multistep method, which are commonly used in WA-BPMs for 2-D structures. Simulations using the new methods will be compared to the analytical results to assure its effectiveness and applicability.

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

NASA Astrophysics Data System (ADS)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

Research on Centralized Voltage and Effective Inequality Identification Based on Circuit Analysis Method

NASA Astrophysics Data System (ADS)

Su, Yi; Wang, Feifeng; Lu, Yufeng; Huang, Huimin; Xia, Xiaofei

2017-09-01

This paper is based on affine function equation of the grid and OPF problem, discusses the equivalent of some inequality constraints variables optimizing. Further, we propose the model of injection current and set up the constraint sensitivity index of affine characteristics. The index can be used to identify the central point voltage and effective inequality of the system automatically. And then we can know how to compensate reactive power of the corresponding generator node and control the voltage to ensure the quality of the system voltage. When checking the effective inequalities we introduce cross-solving method of power flow. This provide a different idea for solving the power flow. The paper uses the results of the IEEE5 node examples to illustrate the validity and practicality of the proposed method.

Link prediction based on nonequilibrium cooperation effect

NASA Astrophysics Data System (ADS)

Li, Lanxi; Zhu, Xuzhen; Tian, Hui

2018-04-01

Link prediction in complex networks has become a common focus of many researchers. But most existing methods concentrate on neighbors, and rarely consider degree heterogeneity of two endpoints. Node degree represents the importance or status of endpoints. We describe the large-degree heterogeneity as the nonequilibrium between nodes. This nonequilibrium facilitates a stable cooperation between endpoints, so that two endpoints with large-degree heterogeneity tend to connect stably. We name such a phenomenon as the nonequilibrium cooperation effect. Therefore, this paper proposes a link prediction method based on the nonequilibrium cooperation effect to improve accuracy. Theoretical analysis will be processed in advance, and at the end, experiments will be performed in 12 real-world networks to compare the mainstream methods with our indices in the network through numerical analysis.

Sieve estimation of Cox models with latent structures.

PubMed

Cao, Yongxiu; Huang, Jian; Liu, Yanyan; Zhao, Xingqiu

2016-12-01

This article considers sieve estimation in the Cox model with an unknown regression structure based on right-censored data. We propose a semiparametric pursuit method to simultaneously identify and estimate linear and nonparametric covariate effects based on B-spline expansions through a penalized group selection method with concave penalties. We show that the estimators of the linear effects and the nonparametric component are consistent. Furthermore, we establish the asymptotic normality of the estimator of the linear effects. To compute the proposed estimators, we develop a modified blockwise majorization descent algorithm that is efficient and easy to implement. Simulation studies demonstrate that the proposed method performs well in finite sample situations. We also use the primary biliary cirrhosis data to illustrate its application. © 2016, The International Biometric Society.

The Co-simulation of Humanoid Robot Based on Solidworks, ADAMS and Simulink

NASA Astrophysics Data System (ADS)

Song, Dalei; Zheng, Lidan; Wang, Li; Qi, Weiwei; Li, Yanli

A simulation method of adaptive controller is proposed for the humanoid robot system based on co-simulation of Solidworks, ADAMS and Simulink. A complex mathematical modeling process is avoided by this method, and the real time dynamic simulating function of Simulink would be exerted adequately. This method could be generalized to other complicated control system. This method is adopted to build and analyse the model of humanoid robot. The trajectory tracking and adaptive controller design also proceed based on it. The effect of trajectory tracking is evaluated by fitting-curve theory of least squares method. The anti-interference capability of the robot is improved a lot through comparative analysis.

Video-based noncooperative iris image segmentation.

PubMed

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

Results of Propellant Mixing Variable Study Using Precise Pressure-Based Burn Rate Calculations

NASA Technical Reports Server (NTRS)

Stefanski, Philip L.

2014-01-01

A designed experiment was conducted in which three mix processing variables (pre-curative addition mix temperature, pre-curative addition mixing time, and mixer speed) were varied to estimate their effects on within-mix propellant burn rate variability. The chosen discriminator for the experiment was the 2-inch diameter by 4-inch long (2x4) Center-Perforated (CP) ballistic evaluation motor. Motor nozzle throat diameters were sized to produce a common targeted chamber pressure. Initial data analysis did not show a statistically significant effect. Because propellant burn rate must be directly related to chamber pressure, a method was developed that showed statistically significant effects on chamber pressure (either maximum or average) by adjustments to the process settings. Burn rates were calculated from chamber pressures and these were then normalized to a common pressure for comparative purposes. The pressure-based method of burn rate determination showed significant reduction in error when compared to results obtained from the Brooks' modification of the propellant web-bisector burn rate determination method. Analysis of effects using burn rates calculated by the pressure-based method showed a significant correlation of within-mix burn rate dispersion to mixing duration and the quadratic of mixing duration. The findings were confirmed in a series of mixes that examined the effects of mixing time on burn rate variation, which yielded the same results.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Sensor Drift Compensation Algorithm based on PDF Distance Minimization

NASA Astrophysics Data System (ADS)

Kim, Namyong; Byun, Hyung-Gi; Persaud, Krishna C.; Huh, Jeung-Soo

2009-05-01

In this paper, a new unsupervised classification algorithm is introduced for the compensation of sensor drift effects of the odor sensing system using a conducting polymer sensor array. The proposed method continues updating adaptive Radial Basis Function Network (RBFN) weights in the testing phase based on minimizing Euclidian Distance between two Probability Density Functions (PDFs) of a set of training phase output data and another set of testing phase output data. The output in the testing phase using the fixed weights of the RBFN are significantly dispersed and shifted from each target value due mostly to sensor drift effect. In the experimental results, the output data by the proposed methods are observed to be concentrated closer again to their own target values significantly. This indicates that the proposed method can be effectively applied to improved odor sensing system equipped with the capability of sensor drift effect compensation

Tolerance analysis of null lenses using an end-use system performance criterion

NASA Astrophysics Data System (ADS)

Rodgers, J. Michael

2000-07-01

An effective method of assigning tolerances to a null lens is to determine the effects of null-lens fabrication and alignment errors on the end-use system itself, not simply the null lens. This paper describes a method to assign null- lens tolerances based on their effect on any performance parameter of the end-use system.

Study on Privacy Protection Algorithm Based on K-Anonymity

NASA Astrophysics Data System (ADS)

FeiFei, Zhao; LiFeng, Dong; Kun, Wang; Yang, Li

Basing on the study of K-Anonymity algorithm in privacy protection issue, this paper proposed a "Degree Priority" method of visiting Lattice nodes on the generalization tree to improve the performance of K-Anonymity algorithm. This paper also proposed a "Two Times K-anonymity" methods to reduce the information loss in the process of K-Anonymity. Finally, we used experimental results to demonstrate the effectiveness of these methods.

Hearing and Seeing Tone through Color: An Efficacy Study of Web-Based, Multimodal Chinese Tone Perception Training

ERIC Educational Resources Information Center

Godfroid, Aline; Lin, Chin-Hsi; Ryu, Catherine

2017-01-01

Multimodal approaches have been shown to be effective for many learning tasks. In this study, we compared the effectiveness of five multimodal methods for second language (L2) Mandarin tone perception training: three single-cue methods (number, pitch contour, color) and two dual-cue methods (color and number, color and pitch contour). A total of…

Comparing problem-based learning and lecture as methods to teach whole-systems design to engineering students

NASA Astrophysics Data System (ADS)

Dukes, Michael Dickey

The objective of this research is to compare problem-based learning and lecture as methods to teach whole-systems design to engineering students. A case study, Appendix A, exemplifying successful whole-systems design was developed and written by the author in partnership with the Rocky Mountain Institute. Concepts to be tested were then determined, and a questionnaire was developed to test students' preconceptions. A control group of students was taught using traditional lecture methods, and a sample group of students was taught using problem-based learning methods. After several weeks, the students were given the same questionnaire as prior to the instruction, and the data was analyzed to determine if the teaching methods were effective in correcting misconceptions. A statistically significant change in the students' preconceptions was observed in both groups on the topic of cost related to the design process. There was no statistically significant change in the students' preconceptions concerning the design process, technical ability within five years, and the possibility of drastic efficiency gains with current technologies. However, the results were inconclusive in determining that problem-based learning is more effective than lecture as a method for teaching the concept of whole-systems design, or vice versa.

Accuracy of two simple methods for estimation of thyroidal {sup 131}I kinetics for dosimetry-based treatment of Graves' disease

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

Traino, A. C.; Xhafa, B.; Sezione di Fisica Medica, U.O. Fisica Sanitaria, Azienda Ospedaliero-Universitaria Pisana, via Roma n. 67, Pisa 56125

2009-04-15

One of the major challenges to the more widespread use of individualized, dosimetry-based radioiodine treatment of Graves' disease is the development of a reasonably fast, simple, and cost-effective method to measure thyroidal {sup 131}I kinetics in patients. Even though the fixed activity administration method does not optimize the therapy, giving often too high or too low a dose to the gland, it provides effective treatment for almost 80% of patients without consuming excessive time and resources. In this article two simple methods for the evaluation of the kinetics of {sup 131}I in the thyroid gland are presented and discussed. Themore » first is based on two measurements 4 and 24 h after a diagnostic {sup 131}I administration and the second on one measurement 4 h after such an administration and a linear correlation between this measurement and the maximum uptake in the thyroid. The thyroid absorbed dose calculated by each of the two methods is compared to that calculated by a more complete {sup 131}I kinetics evaluation, based on seven thyroid uptake measurements for 35 patients at various times after the therapy administration. There are differences in the thyroid absorbed doses between those derived by each of the two simpler methods and the ''reference'' value (derived by more complete uptake measurements following the therapeutic {sup 131}I administration), with 20% median and 40% 90-percentile differences for the first method (i.e., based on two thyroid uptake measurements at 4 and 24 h after {sup 131}I administration) and 25% median and 45% 90-percentile differences for the second method (i.e., based on one measurement at 4 h post-administration). Predictably, although relatively fast and convenient, neither of these simpler methods appears to be as accurate as thyroid dose estimates based on more complete kinetic data.« less

Phase-Shifted Based Numerical Method for Modeling Frequency-Dependent Effects on Seismic Reflections

NASA Astrophysics Data System (ADS)

Chen, Xuehua; Qi, Yingkai; He, Xilei; He, Zhenhua; Chen, Hui

2016-08-01

The significant velocity dispersion and attenuation has often been observed when seismic waves propagate in fluid-saturated porous rocks. Both the magnitude and variation features of the velocity dispersion and attenuation are frequency-dependent and related closely to the physical properties of the fluid-saturated porous rocks. To explore the effects of frequency-dependent dispersion and attenuation on the seismic responses, in this work, we present a numerical method for seismic data modeling based on the diffusive and viscous wave equation (DVWE), which introduces the poroelastic theory and takes into account diffusive and viscous attenuation in diffusive-viscous-theory. We derive a phase-shift wave extrapolation algorithm in frequencywavenumber domain for implementing the DVWE-based simulation method that can handle the simultaneous lateral variations in velocity, diffusive coefficient and viscosity. Then, we design a distributary channels model in which a hydrocarbon-saturated sand reservoir is embedded in one of the channels. Next, we calculated the synthetic seismic data to analytically and comparatively illustrate the seismic frequency-dependent behaviors related to the hydrocarbon-saturated reservoir, by employing DVWE-based and conventional acoustic wave equation (AWE) based method, respectively. The results of the synthetic seismic data delineate the intrinsic energy loss, phase delay, lower instantaneous dominant frequency and narrower bandwidth due to the frequency-dependent dispersion and attenuation when seismic wave travels through the hydrocarbon-saturated reservoir. The numerical modeling method is expected to contribute to improve the understanding of the features and mechanism of the seismic frequency-dependent effects resulted from the hydrocarbon-saturated porous rocks.

An AIS-Based E-mail Classification Method

NASA Astrophysics Data System (ADS)

Qing, Jinjian; Mao, Ruilong; Bie, Rongfang; Gao, Xiao-Zhi

This paper proposes a new e-mail classification method based on the Artificial Immune System (AIS), which is endowed with good diversity and self-adaptive ability by using the immune learning, immune memory, and immune recognition. In our method, the features of spam and non-spam extracted from the training sets are combined together, and the number of false positives (non-spam messages that are incorrectly classified as spam) can be reduced. The experimental results demonstrate that this method is effective in reducing the false rate.

Evaluation of methods for measuring particulate matter emissions from gas turbines.

PubMed

Petzold, Andreas; Marsh, Richard; Johnson, Mark; Miller, Michael; Sevcenco, Yura; Delhaye, David; Ibrahim, Amir; Williams, Paul; Bauer, Heidi; Crayford, Andrew; Bachalo, William D; Raper, David

2011-04-15

The project SAMPLE evaluated methods for measuring particle properties in the exhaust of aircraft engines with respect to the development of standardized operation procedures for particulate matter measurement in aviation industry. Filter-based off-line mass methods included gravimetry and chemical analysis of carbonaceous species by combustion methods. Online mass methods were based on light absorption measurement or used size distribution measurements obtained from an electrical mobility analyzer approach. Number concentrations were determined using different condensation particle counters (CPC). Total mass from filter-based methods balanced gravimetric mass within 8% error. Carbonaceous matter accounted for 70% of gravimetric mass while the remaining 30% were attributed to hydrated sulfate and noncarbonaceous organic matter fractions. Online methods were closely correlated over the entire range of emission levels studied in the tests. Elemental carbon from combustion methods and black carbon from optical methods deviated by maximum 5% with respect to mass for low to medium emission levels, whereas for high emission levels a systematic deviation between online methods and filter based methods was found which is attributed to sampling effects. CPC based instruments proved highly reproducible for number concentration measurements with a maximum interinstrument standard deviation of 7.5%.

Liquid disinfection using power impulse laser

NASA Astrophysics Data System (ADS)

Gribin, S.; Assaoul, Viktor; Markova, Elena; Gromova, Ludmila P.; Spesivtsev, Boris; Bazanov, V.

1996-05-01

The presented method is based on the bactericidal effect of micro-blast induced by various sources (laser breakdown, electrohydraulic effect...). Using elaborated conception of physical phenomena providing liquid disinfection it is possible to determine optimal conditions of water treatment. The problem of optimization is solved using methods of mathematical modeling and special experiments.

Parenting Matters: What Works in Parenting Education?

ERIC Educational Resources Information Center

Lloyd, Eva, Ed.

Because the expansion of parenting education is likely to continue, it is important to ensure that methods involved in parenting education are effective. This report summarizes research on the effectiveness of parenting education and provides information to help practitioners develop methods of working with parents that are based on sound research…

Liquid disinfection using power impulse laser

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

Gribin, S.; Assaoul, V.; Markova, E.

1996-12-31

The presented method is based on the bactericidal effect of micro-blast induced by various sources (laser breakdown, electrohydraulic effect ... ). Using elaborated conception of physical phenomena providing liquid disinfection it is possible to determine optimal conditions of water treatment. The problem of optimization is solved using methods of mathematical modeling and special experiments.

An Effective Method for Detecting Potential Woodland Vernal Pools Using High-Resolution LiDAR Data and Aerial Imagery

EPA Science Inventory

Effective conservation of woodland vernal pools – important components of regional amphibian diversity and ecosystem services – depends on locating and mapping these pools accurately. Current methods for identifying potential vernal pools are primarily based on visual interpretat...

The problem of estimating recent genetic connectivity in a changing world.

PubMed

Samarasin, Pasan; Shuter, Brian J; Wright, Stephen I; Rodd, F Helen

2017-02-01

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent-based method (Migrate-n) and a disequilibrium-based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over-estimated recent migration rates; (ii) the coalescent-based method (Migrate-n) provided better estimates of recent migration rate than the disequilibrium-based method (BayesAss); (iii) the coalescent-based method did not accurately reflect long-term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic-connectivity changes over time could lead to inaccurate conclusions. © 2016 Society for Conservation Biology.

Skin Effect Modeling in Conductors of Arbitrary Shape Through a Surface Admittance Operator and the Contour Integral Method

NASA Astrophysics Data System (ADS)

Patel, Utkarsh R.; Triverio, Piero

2016-09-01

An accurate modeling of skin effect inside conductors is of capital importance to solve transmission line and scattering problems. This paper presents a surface-based formulation to model skin effect in conductors of arbitrary cross section, and compute the per-unit-length impedance of a multiconductor transmission line. The proposed formulation is based on the Dirichlet-Neumann operator that relates the longitudinal electric field to the tangential magnetic field on the boundary of a conductor. We demonstrate how the surface operator can be obtained through the contour integral method for conductors of arbitrary shape. The proposed algorithm is simple to implement, efficient, and can handle arbitrary cross-sections, which is a main advantage over the existing approach based on eigenfunctions, which is available only for canonical conductor's shapes. The versatility of the method is illustrated through a diverse set of examples, which includes transmission lines with trapezoidal, curved, and V-shaped conductors. Numerical results demonstrate the accuracy, versatility, and efficiency of the proposed technique.

Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation

ERIC Educational Resources Information Center

Austin, Peter C.

2012-01-01

Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to the production of high-quality evidence is the ability to reduce or minimize the confounding that frequently occurs in observational studies. When using the potential outcome framework to define causal treatment effects, one…

Effects of a 2-Year School-Based Intervention of Enhanced Physical Education in the Primary School

ERIC Educational Resources Information Center

Sacchetti, Rossella; Ceciliani, Andrea; Garulli, Andrea; Dallolio, Laura; Beltrami, Patrizia; Leoni, Erica

2013-01-01

Background: This study aimed to assess whether a school-based physical education intervention was effective in improving physical abilities and influencing daily physical activity habits in primary school children. The possible effect on body mass index (BMI) was also considered. Methods: Twenty-six 3rd-grade classes were randomly selected…

Pixel-based speckle adjustment for noise reduction in Fourier-domain OCT images.

PubMed

Zhang, Anqi; Xi, Jiefeng; Sun, Jitao; Li, Xingde

2017-03-01

Speckle resides in OCT signals and inevitably effects OCT image quality. In this work, we present a novel method for speckle noise reduction in Fourier-domain OCT images, which utilizes the phase information of complex OCT data. In this method, speckle area is pre-delineated pixelwise based on a phase-domain processing method and then adjusted by the results of wavelet shrinkage of the original image. Coefficient shrinkage method such as wavelet or contourlet is applied afterwards for further suppressing the speckle noise. Compared with conventional methods without speckle adjustment, the proposed method demonstrates significant improvement of image quality.

Traditional use of indigenous mosquito-repellents to protect humans against mosquitoes and other insect bites in a rural community of Cameroon.

PubMed

Ntonifor, N N; Ngufor, C A; Kimbi, H K; Oben, B O

2006-10-01

To document and test the efficacy of indigenous traditional personal protection methods against mosquito bites and general nuisance. A prospective study based on a survey and field evaluation of selected plant-based personal protection methods against mosquito bites. Bolifamba, a rural setting of the Mount Cameroon region. A structured questionnaire was administered to 179 respondents and two anti-mosquito measures were tested under field conditions. Identified traditional anti-mosquito methods used by indigenes of Bolifamba. Two plants tested under field conditions were found to be effective. Of the 179 respondents, 88 (49.16%) used traditional anti-mosquito methods; 57 (64.77%) used plant-based methods while 31 (35.2%) used various petroleum oils. The rest of the respondents, 91 (50.8%) used conventional personal protection methods. Reasons for using traditional methods were because they were available, affordable and lack of known more effective alternatives. The demerits of these methods were: labourious to implement, stain dresses, produce a lot of smoke/ repulsive odours when used; those of conventional methods were lack of adequate information about them, high cost and non-availability. When the two most frequently used plants, Saccharum officinarium and Ocimum basilicum were evaluated under field conditions, each gave a better protection than the control. Most plants used against mosquitoes in the area are known potent mosquito repellents but others identified in the study warrant further research. The two tested under field conditions were effective though less than the commonly used commercial diethyltoluamide.

On-machine precision preparation and dressing of ball-headed diamond wheel for the grinding of fused silica

NASA Astrophysics Data System (ADS)

Chen, Mingjun; Li, Ziang; Yu, Bo; Peng, Hui; Fang, Zhen

2013-09-01

In the grinding of high quality fused silica parts with complex surface or structure using ball-headed metal bonded diamond wheel with small diameter, the existing dressing methods are not suitable to dress the ball-headed diamond wheel precisely due to that they are either on-line in process dressing which may causes collision problem or without consideration for the effects of the tool setting error and electrode wear. An on-machine precision preparation and dressing method is proposed for ball-headed diamond wheel based on electrical discharge machining. By using this method the cylindrical diamond wheel with small diameter is manufactured to hemispherical-headed form. The obtained ball-headed diamond wheel is dressed after several grinding passes to recover geometrical accuracy and sharpness which is lost due to the wheel wear. A tool setting method based on high precision optical system is presented to reduce the wheel center setting error and dimension error. The effect of electrode tool wear is investigated by electrical dressing experiments, and the electrode tool wear compensation model is established based on the experimental results which show that the value of wear ratio coefficient K' tends to be constant with the increasing of the feed length of electrode and the mean value of K' is 0.156. Grinding experiments of fused silica are carried out on a test bench to evaluate the performance of the preparation and dressing method. The experimental results show that the surface roughness of the finished workpiece is 0.03 μm. The effect of the grinding parameter and dressing frequency on the surface roughness is investigated based on the measurement results of the surface roughness. This research provides an on-machine preparation and dressing method for ball-headed metal bonded diamond wheel used in the grinding of fused silica, which provides a solution to the tool setting method and the effect of electrode tool wear.

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control.

PubMed

Li, Ruiying; Ma, Wenting; Huang, Ning; Kang, Rui

2017-01-01

A sophisticated method for node deployment can efficiently reduce the energy consumption of a Wireless Sensor Network (WSN) and prolong the corresponding network lifetime. Pioneers have proposed many node deployment based lifetime optimization methods for WSNs, however, the retransmission mechanism and the discrete power control strategy, which are widely used in practice and have large effect on the network energy consumption, are often neglected and assumed as a continuous one, respectively, in the previous studies. In this paper, both retransmission and discrete power control are considered together, and a more realistic energy-consumption-based network lifetime model for linear WSNs is provided. Using this model, we then propose a generic deployment-based optimization model that maximizes network lifetime under coverage, connectivity and transmission rate success constraints. The more accurate lifetime evaluation conduces to a longer optimal network lifetime in the realistic situation. To illustrate the effectiveness of our method, both one-tiered and two-tiered uniformly and non-uniformly distributed linear WSNs are optimized in our case studies, and the comparisons between our optimal results and those based on relatively inaccurate lifetime evaluation show the advantage of our method when investigating WSN lifetime optimization problems.

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

Simple fluorescence-based high throughput cell viability assay for filamentous fungi.

PubMed

Chadha, S; Kale, S P

2015-09-01

Filamentous fungi are important model organisms to understand the eukaryotic process and have been frequently exploited in research and industry. These fungi are also causative agents of serious diseases in plants and humans. Disease management strategies include in vitro susceptibility testing of the fungal pathogens to environmental conditions and antifungal agents. Conventional methods used for antifungal susceptibilities are cumbersome, time-consuming and are not suitable for a large-scale analysis. Here, we report a rapid, high throughput microplate-based fluorescence method for investigating the toxicity of antifungal and stress (osmotic, salt and oxidative) agents on Magnaporthe oryzae and compared it with agar dilution method. This bioassay is optimized for the resazurin reduction to fluorescent resorufin by the fungal hyphae. Resazurin bioassay showed inhibitory rates and IC50 values comparable to the agar dilution method and to previously reported IC50 or MICs for M. oryzae and other fungi. The present method can screen range of test agents from different chemical classes with different modes of action for antifungal activities in a simple, sensitive, time and cost effective manner. A simple fluorescence-based high throughput method is developed to test the effects of stress and antifungal agents on viability of filamentous fungus Magnaporthe oryzae. This resazurin fluorescence assay can detect inhibitory effects comparable to those obtained using the growth inhibition assay with added advantages of simplicity, time and cost effectiveness. This high throughput viability assay has a great potential in large-scale screening of the chemical libraries of antifungal agents, for evaluating the effects of environmental conditions and hyphal kinetic studies in mutant and natural populations of filamentous fungi. © 2015 The Society for Applied Microbiology.

Design of optical seven-segment decoder using Pockel's effect inside lithium niobate-based waveguide

NASA Astrophysics Data System (ADS)

Pal, Amrindra; Kumar, Santosh; Sharma, Sandeep

2017-01-01

Seven-segment decoder is a device that allows placing digital information from many inputs to many outputs optically, having 11 Mach-Zehnder interferometers (MZIs) for their implementation. The layout of the circuit is implemented to fit the electrical method on an optical logic circuit based on the beam propagation method (BPM). Seven-segment decoder is proposed using electro-optic effect inside lithium niobate-based MZIs. MZI structures are able to switch an optical signal to a desired output port. It consists of a mathematical explanation about the proposed device. The BPM is also used to analyze the study.

Effects of Problem-Based Learning on Attitude: A Meta-Analysis Study

ERIC Educational Resources Information Center

Demirel, Melek; Dagyar, Miray

2016-01-01

To date, researchers have frequently investigated students' attitudes toward courses supported by problem-based learning. There are several studies with different results in the literature. It is necessary to combine and interpret the findings of these studies through a meta-analysis method. This method aims to combine different results of similar…

Scaffolding Wiki-Supported Collaborative Learning for Small-Group Projects and Whole-Class Collaborative Knowledge Building

ERIC Educational Resources Information Center

Lin, C-Y.; Reigeluth, C. M.

2016-01-01

While educators value wikis' potential, wikis may fail to support collaborative constructive learning without careful scaffolding. This article proposes literature-based instructional methods, revised based on two expert instructors' input, presents the collected empirical evidence on the effects of these methods and proposes directions for future…

Using Inquiry-Based Strategies for Enhancing Students' STEM Education Learning

ERIC Educational Resources Information Center

Lai, Ching-San

2018-01-01

The major purpose of this study was to investigate whether or not the inquiry-based method is effective in improving students' learning in STEM (Science, Technology, Engineering, and Mathematics) education. Both quantitative and qualitative methods were used. A total of 73 college students studying Information Technology (IT) were chosen as…

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

PubMed Central

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-01

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

PubMed

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-08

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.

PubMed

Carrascal, A; Manrique, D; Ríos, J; Rossi, C

2003-01-01

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.

A Literature Survey of Private Sector Methods of Determining Personal Financial Responsibility

DTIC Science & Technology

1988-09-01

private sector methods to the public sector is also discussed. The judgmental and empirical methods are each effective. Their utilization is based upon their respective abilities to minimize cost while achieving the organization’s

The introduction and effectiveness of simulation-based learning in medical education.

PubMed

Nara, Nobuo; Beppu, Masashi; Tohda, Shuji; Suzuki, Toshiya

2009-01-01

To contribute to reforming the medical education system in Japan, we visited overseas medical schools and observed the methods utilized in medical education. We visited 28 medical schools and five institutes in the United States, Europe, Australia and Asia in 2008. We met deans and specialists in medical affairs and observed the medical schools' facilities. Among the several effective educational methods used in overseas medical schools, simulation-based learning was being used in all that we visited. Simulation-based learning is used to promote medical students' mastery of communication skills, medical interviewing, physical examination and basic clinical procedures. Students and tutors both recognize the effectiveness of simulation-based learning in medical education. In contrast to overseas medical schools, simulation-based learning is not common in Japan. There remain many barriers to introduce simulation-based education in Japan, such as a shortage of medical tutors, staff, mannequins and budget. However, enhancing the motivation of tutors is likely the most important factor to facilitate simulation-based education in Japanese medical schools to become common place.

Optimisation of reconstruction--reprojection-based motion correction for cardiac SPECT.

PubMed

Kangasmaa, Tuija S; Sohlberg, Antti O

2014-07-01

Cardiac motion is a challenging cause of image artefacts in myocardial perfusion SPECT. A wide range of motion correction methods have been developed over the years, and so far automatic algorithms based on the reconstruction--reprojection principle have proved to be the most effective. However, these methods have not been fully optimised in terms of their free parameters and implementational details. Two slightly different implementations of reconstruction--reprojection-based motion correction techniques were optimised for effective, good-quality motion correction and then compared with each other. The first of these methods (Method 1) was the traditional reconstruction-reprojection motion correction algorithm, where the motion correction is done in projection space, whereas the second algorithm (Method 2) performed motion correction in reconstruction space. The parameters that were optimised include the type of cost function (squared difference, normalised cross-correlation and mutual information) that was used to compare measured and reprojected projections, and the number of iterations needed. The methods were tested with motion-corrupt projection datasets, which were generated by adding three different types of motion (lateral shift, vertical shift and vertical creep) to motion-free cardiac perfusion SPECT studies. Method 2 performed slightly better overall than Method 1, but the difference between the two implementations was small. The execution time for Method 2 was much longer than for Method 1, which limits its clinical usefulness. The mutual information cost function gave clearly the best results for all three motion sets for both correction methods. Three iterations were sufficient for a good quality correction using Method 1. The traditional reconstruction--reprojection-based method with three update iterations and mutual information cost function is a good option for motion correction in clinical myocardial perfusion SPECT.

Aberration corrections for free-space optical communications in atmosphere turbulence using orbital angular momentum states.

PubMed

Zhao, S M; Leach, J; Gong, L Y; Ding, J; Zheng, B Y

2012-01-02

The effect of atmosphere turbulence on light's spatial structure compromises the information capacity of photons carrying the Orbital Angular Momentum (OAM) in free-space optical (FSO) communications. In this paper, we study two aberration correction methods to mitigate this effect. The first one is the Shack-Hartmann wavefront correction method, which is based on the Zernike polynomials, and the second is a phase correction method specific to OAM states. Our numerical results show that the phase correction method for OAM states outperforms the Shark-Hartmann wavefront correction method, although both methods improve significantly purity of a single OAM state and the channel capacities of FSO communication link. At the same time, our experimental results show that the values of participation functions go down at the phase correction method for OAM states, i.e., the correction method ameliorates effectively the bad effect of atmosphere turbulence.

Effectiveness and efficacy of minimally invasive lung volume reduction surgery for emphysema

PubMed Central

Pertl, Daniela; Eisenmann, Alexander; Holzer, Ulrike; Renner, Anna-Theresa; Valipour, A.

2014-01-01

Lung emphysema is a chronic, progressive and irreversible destruction of the lung tissue. Besides non-medical therapies and the well established medical treatment there are surgical and minimally invasive methods for lung volume reduction (LVR) to treat severe emphysema. This report deals with the effectiveness and cost-effectiveness of minimally invasive methods compared to other treatments for LVR in patients with lung emphysema. Furthermore, legal and ethical aspects are discussed. No clear benefit of minimally invasive methods compared to surgical methods can be demonstrated based on the identified and included evidence. In order to assess the different methods for LVR regarding their relative effectiveness and safety in patients with lung emphysema direct comparative studies are necessary. PMID:25295123

Effectiveness and efficacy of minimally invasive lung volume reduction surgery for emphysema.

PubMed

Pertl, Daniela; Eisenmann, Alexander; Holzer, Ulrike; Renner, Anna-Theresa; Valipour, A

2014-01-01

Lung emphysema is a chronic, progressive and irreversible destruction of the lung tissue. Besides non-medical therapies and the well established medical treatment there are surgical and minimally invasive methods for lung volume reduction (LVR) to treat severe emphysema. This report deals with the effectiveness and cost-effectiveness of minimally invasive methods compared to other treatments for LVR in patients with lung emphysema. Furthermore, legal and ethical aspects are discussed. No clear benefit of minimally invasive methods compared to surgical methods can be demonstrated based on the identified and included evidence. In order to assess the different methods for LVR regarding their relative effectiveness and safety in patients with lung emphysema direct comparative studies are necessary.

Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

NASA Astrophysics Data System (ADS)

Okamura, Rintaro; Iwabuchi, Hironobu; Schmidt, K. Sebastian

2017-12-01

Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.

Is supervision necessary? Examining the effects of internet-based CBT training with and without supervision.

PubMed

Rakovshik, Sarah G; McManus, Freda; Vazquez-Montes, Maria; Muse, Kate; Ougrin, Dennis

2016-03-01

To investigate the effect of Internet-based training (IBT), with and without supervision, on therapists' (N = 61) cognitive-behavioral therapy (CBT) skills in routine clinical practice. Participants were randomized into 3 conditions: (1) Internet-based training with use of a consultation worksheet (IBT-CW); (2) Internet-based training with CBT supervision via Skype (IBT-S); and (3) "delayed-training" controls (DTs), who did not receive the training until all data collection was completed. The IBT participants received access to training over a period of 3 months. CBT skills were evaluated at pre-, mid- and posttraining/wait using assessor competence ratings of recorded therapy sessions. Hierarchical linear analysis revealed that the IBT-S participants had significantly greater CBT competence at posttraining than did IBT-CW and DT participants at both the mid- and posttraining/wait assessment points. There were no significant differences between IBT-CW and the delayed (no)-training DTs. IBT programs that include supervision may be a scalable and effective method of disseminating CBT into routine clinical practice, particularly for populations without ready access to more-traditional "live" methods of training. There was no evidence for a significant effect of IBT without supervision over a nontraining control, suggesting that merely providing access to IBT programs may not be an effective method of disseminating CBT to routine clinical practice. (c) 2016 APA, all rights reserved).

Effectiveness of team-based learning methodology in teaching transfusion medicine to medical undergraduates in third semester: A comparative study.

PubMed

Doshi, Neena Piyush

2017-01-01

Team-based learning (TBL) combines small and large group learning by incorporating multiple small groups in a large group setting. It is a teacher-directed method that encourages student-student interaction. This study compares student learning and teaching satisfaction between conventional lecture and TBL in the subject of pathology. The present study is aimed to assess the effectiveness of TBL method of teaching over the conventional lecture. The present study was conducted in the Department of Pathology, GMERS Medical College and General Hospital, Gotri, Vadodara, Gujarat. The study population comprised 126 students of second-year MBBS, in their third semester of the academic year 2015-2016. "Hemodynamic disorders" were taught by conventional method and "transfusion medicine" by TBL method. Effectiveness of both the methods was assessed. A posttest multiple choice question was conducted at the end of "hemodynamic disorders." Assessment of TBL was based on individual score, team score, and each member's contribution to the success of the team. The individual score and overall score were compared with the posttest score on "hemodynamic disorders." A feedback was taken from the students regarding their experience with TBL. Tukey's multiple comparisons test and ANOVA summary were used to find the significance of scores between didactic and TBL methods. Student feedback was taken using "Student Satisfaction Scale" based on Likert scoring method. The mean of student scores by didactic, Individual Readiness Assurance Test (score "A"), and overall (score "D") was 49.8% (standard deviation [SD]-14.8), 65.6% (SD-10.9), and 65.6% (SD-13.8), respectively. The study showed positive educational outcome in terms of knowledge acquisition, participation and engagement, and team performance with TBL.

Comparison of two hardware-based hit filtering methods for trackers in high-pileup environments

NASA Astrophysics Data System (ADS)

Gradin, J.; Mårtensson, M.; Brenner, R.

2018-04-01

As experiments in high energy physics aim to measure increasingly rare processes, the experiments continually strive to increase the expected signal yields. In the case of the High Luminosity upgrade of the LHC, the luminosity is raised by increasing the number of simultaneous proton-proton interactions, so-called pile-up. This increases the expected yields of signal and background processes alike. The signal is embedded in a large background of processes that mimic that of signal events. It is therefore imperative for the experiments to develop new triggering methods to effectively distinguish the interesting events from the background. We present a comparison of two methods for filtering detector hits to be used for triggering on particle tracks: one based on a pattern matching technique using Associative Memory (AM) chips and the other based on the Hough transform. Their efficiency and hit rejection are evaluated for proton-proton collisions with varying amounts of pile-up using a simulation of a generic silicon tracking detector. It is found that, while both methods are feasible options for a track trigger with single muon efficiencies around 98–99%, the AM based pattern matching produces a lower number of hit combinations with respect to the Hough transform whilst keeping more of the true signal hits. We also present the effect on the two methods of increasing the amount of support material in the detector and of introducing inefficiencies by deactivating detector modules. The increased support material has negligable effects on the efficiency for both methods, while dropping 5% (10%) of the available modules decreases the efficiency to about 95% (87%) for both methods, irrespective of the amount of pile-up.

Perceived racial, socioeconomic and gender discrimination and its impact on contraceptive choice

PubMed Central

Kossler, Karla; Kuroki, Lindsay M.; Allsworth, Jenifer E.; Secura, Gina M.; Roehl, Kimberly A.; Peipert, Jeffrey F.

2012-01-01

Background The study was conducted to determine whether perceived racial, economic, and gender discrimination has an impact on contraception use and choice of method. Methods We analyzed the first 2,500 women, aged 14–45 years enrolled in the Contraceptive CHOICE Project, a prospective cohort study aimed to reduce barriers to long-acting reversible contraception. Items from the “Experiences of Discrimination” (EOD) scale measured experienced race-, gender-, and economic-based discrimination. Results Overall, 57% of women reported a history of discrimination. Thirty-three percent reported gender- or race-based discrimination and 24% reported discrimination attributed to socioeconomic status (SES). Prior to study enrollment, women reporting discrimination were more likely to report any contraception use (61% vs. 51%, p<0.001), but were more likely to use less effective methods (e.g., barrier methods, natural family planning or withdrawal; 41% vs. 32%, p<0.001). In adjusted analyses, gender-, race- or SES-based discrimination were associated with increased current use of less effective methods (adjusted risk ratio (aRR) 1.22, CI 1.06–1.41; aRR 1.25, CI 1.08–1.45; aRR 1.23, CI 1.06–1.43, respectively). After enrollment, 67% of women with history of experience of discrimination chose a long-acting reversible contraceptive method (intrauterine device or implantable) and 33% chose a depo-medroxyprogesterone acetate or contraceptive pill, patch or ring. Conclusions Discrimination negatively impacts a woman’s use of contraception. However, after financial and structural barriers to contraceptive use were eliminated, women with EOD overwhelmingly selected effective methods of contraception. Future interventions to improve access and utilization of contraception should focus on eliminating barriers and targeting interventions that encompass race-, gender-, and economic-based discrimination. PMID:21843693

Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Mi; Xu, Wen; Li, Deren; Gong, Jianya; Pi, Yingdong

2017-12-01

The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs.

Angular Multigrid Preconditioner for Krylov-Based Solution Techniques Applied to the Sn Equations with Highly Forward-Peaked Scattering

NASA Astrophysics Data System (ADS)

Turcksin, Bruno; Ragusa, Jean C.; Morel, Jim E.

2012-01-01

It is well known that the diffusion synthetic acceleration (DSA) methods for the Sn equations become ineffective in the Fokker-Planck forward-peaked scattering limit. In response to this deficiency, Morel and Manteuffel (1991) developed an angular multigrid method for the 1-D Sn equations. This method is very effective, costing roughly twice as much as DSA per source iteration, and yielding a maximum spectral radius of approximately 0.6 in the Fokker-Planck limit. Pautz, Adams, and Morel (PAM) (1999) later generalized the angular multigrid to 2-D, but it was found that the method was unstable with sufficiently forward-peaked mappings between the angular grids. The method was stabilized via a filtering technique based on diffusion operators, but this filtering also degraded the effectiveness of the overall scheme. The spectral radius was not bounded away from unity in the Fokker-Planck limit, although the method remained more effective than DSA. The purpose of this article is to recast the multidimensional PAM angular multigrid method without the filtering as an Sn preconditioner and use it in conjunction with the Generalized Minimal RESidual (GMRES) Krylov method. The approach ensures stability and our computational results demonstrate that it is also significantly more efficient than an analogous DSA-preconditioned Krylov method.

Fast Reduction Method in Dominance-Based Information Systems

NASA Astrophysics Data System (ADS)

Li, Yan; Zhou, Qinghua; Wen, Yongchuan

2018-01-01

In real world applications, there are often some data with continuous values or preference-ordered values. Rough sets based on dominance relations can effectively deal with these kinds of data. Attribute reduction can be done in the framework of dominance-relation based approach to better extract decision rules. However, the computational cost of the dominance classes greatly affects the efficiency of attribute reduction and rule extraction. This paper presents an efficient method of computing dominance classes, and further compares it with traditional method with increasing attributes and samples. Experiments on UCI data sets show that the proposed algorithm obviously improves the efficiency of the traditional method, especially for large-scale data.

Prediction techniques for jet-induced effects in hover on STOVL aircraft

NASA Technical Reports Server (NTRS)

Wardwell, Douglas A.; Kuhn, Richard E.

1991-01-01

Prediction techniques for jet induced lift effects during hover are available, relatively easy to use, and produce adequate results for preliminary design work. Although deficiencies of the current method were found, it is still currently the best way to estimate jet induced lift effects short of using computational fluid dynamics. Its use is summarized. The new summarized method, represents the first step toward the use of surface pressure data in an empirical method, as opposed to just balance data in the current method, for calculating jet induced effects. Although the new method is currently limited to flat plate configurations having two circular jets of equal thrust, it has the potential of more accurately predicting jet induced effects including a means for estimating the pitching moment in hover. As this method was developed from a very limited amount of data, broader applications of the method require the inclusion of new data on additional configurations. However, within this small data base, the new method does a better job in predicting jet induced effects in hover than the current method.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Vorticity vector-potential method based on time-dependent curvilinear coordinates for two-dimensional rotating flows in closed configurations

NASA Astrophysics Data System (ADS)

Fu, Yuan; Zhang, Da-peng; Xie, Xi-lin

2018-04-01

In this study, a vorticity vector-potential method for two-dimensional viscous incompressible rotating driven flows is developed in the time-dependent curvilinear coordinates. The method is applicable in both inertial and non-inertial frames of reference with the advantage of a fixed and regular calculation domain. The numerical method is applied to triangle and curved triangle configurations in constant and varying rotational angular velocity cases respectively. The evolutions of flow field are studied. The geostrophic effect, unsteady effect and curvature effect on the evolutions are discussed.

Vorticity vector-potential method based on time-dependent curvilinear coordinates for two-dimensional rotating flows in closed configurations

NASA Astrophysics Data System (ADS)

Fu, Yuan; Zhang, Da-peng; Xie, Xi-lin

2018-03-01

In this study, a vorticity vector-potential method for two-dimensional viscous incompressible rotating driven flows is developed in the time-dependent curvilinear coordinates. The method is applicable in both inertial and non-inertial frames of reference with the advantage of a fixed and regular calculation domain. The numerical method is applied to triangle and curved triangle configurations in constant and varying rotational angular velocity cases respectively. The evolutions of flow field are studied. The geostrophic effect, unsteady effect and curvature effect on the evolutions are discussed.

The Effectiveness of TBL with Real Patients in Neurology Education in Terms of Knowledge Retention, In-Class Engagement, and Learner Reactions

ERIC Educational Resources Information Center

Alimoglu, Mustafa Kemal; Yardim, Selda; Uysal, Hilmi

2017-01-01

In our medical school, we changed from a lecture-based method to a team-based learning (TBL) method to teach "polyneuropathies" in the neurology clerkship starting from the 2014 to 2015 academic year. Real patients were used instead of written scenarios in TBL sessions. This study aimed to compare former lecture-based and the current TBL…

Transfer of a Mycobacterium tuberculosis Genotyping Method, Spoligotyping, from a Reverse Line-Blot Hybridization, Membrane-Based Assay to the Luminex Multianalyte Profiling System

PubMed Central

Cowan, Lauren S.; Diem, Lois; Brake, Mary Catherine; Crawford, Jack T.

2004-01-01

Spoligotyping using Luminex technology was shown to be a highly reproducible method suitable for high-throughput analysis. Spoligotyping of 48 isolates using the traditional membrane-based assay and the Luminex assay yielded concordant results for all isolates. The Luminex platform provides greater flexibility and cost effectiveness than the membrane-based assay. PMID:14715809

Compensation of the Ionospheric Effects on SAR Interferogram Based on Range Split-Spectrum and Azimuth Offset Methods - a Case Study of Yushu Earthquake

NASA Astrophysics Data System (ADS)

He, Y. F.; Zhu, W.; Zhang, Q.; Zhang, W. T.

2018-04-01

InSAR technique can measure the surface deformation with the accuracy of centimeter-level or even millimeter and therefore has been widely used in the deformation monitoring associated with earthquakes, volcanoes, and other geologic process. However, ionospheric irregularities can lead to the wavy fringes in the low frequency SAR interferograms, which disturb the actual information of geophysical processes and thus put severe limitations on ground deformations measurements. In this paper, an application of two common methods, the range split-spectrum and azimuth offset methods are exploited to estimate the contributions of the ionosphere, with the aim to correct ionospheric effects in interferograms. Based on the theoretical analysis and experiment, a performance analysis is conducted to evaluate the efficiency of these two methods. The result indicates that both methods can mitigate the ionospheric effect in SAR interferograms and the range split-spectrum method is more precise than the other one. However, it is also found that the range split-spectrum is easily contaminated by the noise, and the achievable accuracy of the azimuth offset method is limited by the ambiguous integral constant, especially with the strong azimuth variations induced by the ionosphere disturbance.

The effect on cadaver blood DNA identification by the use of targeted and whole body post-mortem computed tomography angiography.

PubMed

Rutty, Guy N; Barber, Jade; Amoroso, Jasmin; Morgan, Bruno; Graham, Eleanor A M

2013-12-01

Post-mortem computed tomography angiography (PMCTA) involves the injection of contrast agents. This could have both a dilution effect on biological fluid samples and could affect subsequent post-contrast analytical laboratory processes. We undertook a small sample study of 10 targeted and 10 whole body PMCTA cases to consider whether or not these two methods of PMCTA could affect post-PMCTA cadaver blood based DNA identification. We used standard methodology to examine DNA from blood samples obtained before and after the PMCTA procedure. We illustrate that neither of these PMCTA methods had an effect on the alleles called following short tandem repeat based DNA profiling, and therefore the ability to undertake post-PMCTA blood based DNA identification.

[Development of selective determination methods for quinones with fluorescence and chemiluminescence detection and their application to environmental and biological samples].

PubMed

Kishikawa, Naoya

2010-10-01

Quinones are compounds that have various characteristics such as a biological electron transporter, an industrial product and a harmful environmental pollutant. Therefore, an effective determination method for quinones is required in many fields. This review describes the development of sensitive and selective determination methods for quinones based on some detection principles and their application to analyses in environmental, pharmaceutical and biological samples. Firstly, a fluorescence method was developed based on fluorogenic derivatization of quinones and applied to environmental analysis. Secondly, a luminol chemiluminescence method was developed based on generation of reactive oxygen species through the redox cycle of quinone and applied to pharmaceutical analysis. Thirdly, a photo-induced chemiluminescence method was developed based on formation of reactive oxygen species and fluorophore or chemiluminescence enhancer by the photoreaction of quinones and applied to biological and environmental analyses.

Impervious surface mapping with Quickbird imagery

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio

2010-01-01

This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance. PMID:21643434

A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum.

PubMed

Liu, Pan; Deng, Xiaoyan; Tang, Xin; Shen, Shijian

2017-05-01

This paper presents a wavelet-based Gaussian method (WGM) for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF). The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.

A two-dimensional matrix image based feature extraction method for classification of sEMG: A comparative analysis based on SVM, KNN and RBF-NN.

PubMed

Wen, Tingxi; Zhang, Zhongnan; Qiu, Ming; Zeng, Ming; Luo, Weizhen

2017-01-01

The computer mouse is an important human-computer interaction device. But patients with physical finger disability are unable to operate this device. Surface EMG (sEMG) can be monitored by electrodes on the skin surface and is a reflection of the neuromuscular activities. Therefore, we can control limbs auxiliary equipment by utilizing sEMG classification in order to help the physically disabled patients to operate the mouse. To develop a new a method to extract sEMG generated by finger motion and apply novel features to classify sEMG. A window-based data acquisition method was presented to extract signal samples from sEMG electordes. Afterwards, a two-dimensional matrix image based feature extraction method, which differs from the classical methods based on time domain or frequency domain, was employed to transform signal samples to feature maps used for classification. In the experiments, sEMG data samples produced by the index and middle fingers at the click of a mouse button were separately acquired. Then, characteristics of the samples were analyzed to generate a feature map for each sample. Finally, the machine learning classification algorithms (SVM, KNN, RBF-NN) were employed to classify these feature maps on a GPU. The study demonstrated that all classifiers can identify and classify sEMG samples effectively. In particular, the accuracy of the SVM classifier reached up to 100%. The signal separation method is a convenient, efficient and quick method, which can effectively extract the sEMG samples produced by fingers. In addition, unlike the classical methods, the new method enables to extract features by enlarging sample signals' energy appropriately. The classical machine learning classifiers all performed well by using these features.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

PubMed Central

Schettini, Raimondo

2018-01-01

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art. PMID:29329268

A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

PubMed Central

Wu, Xianhua; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries. PMID:24578666

A comprehensive estimation of the economic effects of meteorological services based on the input-output method.

PubMed

Wu, Xianhua; Wei, Guo; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

Team-Based Learning Enhances Performance in Introductory Biology

ERIC Educational Resources Information Center

Carmichael, Jeffrey

2009-01-01

Given the problems associated with the traditional lecture method, the constraints associated with large classes, and the effectiveness of active learning, continued development and testing of efficient student-centered learning approaches are needed. This study explores the effectiveness of team-based learning (TBL) in a large-enrollment…

Exploring stability of entropy analysis for signal with different trends

NASA Astrophysics Data System (ADS)

Zhang, Yin; Li, Jin; Wang, Jun

2017-03-01

Considering the effects of environment disturbances and instrument systems, the actual detecting signals always are carrying different trends, which result in that it is difficult to accurately catch signals complexity. So choosing steady and effective analysis methods is very important. In this paper, we applied entropy measures-the base-scale entropy and approximate entropy to analyze signal complexity, and studied the effect of trends on the ideal signal and the heart rate variability (HRV) signals, that is, linear, periodic, and power-law trends which are likely to occur in actual signals. The results show that approximate entropy is unsteady when we embed different trends into the signals, so it is not suitable to analyze signal with trends. However, the base-scale entropy has preferable stability and accuracy for signal with different trends. So the base-scale entropy is an effective method to analyze the actual signals.

Shrink-induced silica multiscale structures for enhanced fluorescence from DNA microarrays.

PubMed

Sharma, Himanshu; Wood, Jennifer B; Lin, Sophia; Corn, Robert M; Khine, Michelle

2014-09-23

We describe a manufacturable and scalable method for fabrication of multiscale wrinkled silica (SiO2) structures on shrink-wrap film to enhance fluorescence signals in DNA fluorescence microarrays. We are able to enhance the fluorescence signal of hybridized DNA by more than 120 fold relative to a planar glass slide. Notably, our substrate has improved detection sensitivity (280 pM) relative to planar glass slide (11 nM). Furthermore, this is accompanied by a 30-45 times improvement in the signal-to-noise ratio (SNR). Unlike metal enhanced fluorescence (MEF) based enhancements, this is a far-field and uniform effect based on surface concentration and photophysical effects from the nano- to microscale SiO2 structures. Notably, the photophysical effects contribute an almost 2.5 fold enhancement over the concentration effects alone. Therefore, this simple and robust method offers an efficient technique to enhance the detection capabilities of fluorescence based DNA microarrays.

Shrink-Induced Silica Multiscale Structures for Enhanced Fluorescence from DNA Microarrays

PubMed Central

2015-01-01

We describe a manufacturable and scalable method for fabrication of multiscale wrinkled silica (SiO2) structures on shrink-wrap film to enhance fluorescence signals in DNA fluorescence microarrays. We are able to enhance the fluorescence signal of hybridized DNA by more than 120 fold relative to a planar glass slide. Notably, our substrate has improved detection sensitivity (280 pM) relative to planar glass slide (11 nM). Furthermore, this is accompanied by a 30–45 times improvement in the signal-to-noise ratio (SNR). Unlike metal enhanced fluorescence (MEF) based enhancements, this is a far-field and uniform effect based on surface concentration and photophysical effects from the nano- to microscale SiO2 structures. Notably, the photophysical effects contribute an almost 2.5 fold enhancement over the concentration effects alone. Therefore, this simple and robust method offers an efficient technique to enhance the detection capabilities of fluorescence based DNA microarrays. PMID:25191785

Recruitment strategies and costs for a community-based physical activity program.

PubMed

Peck, Lara E; Sharpe, Patricia A; Burroughs, Ericka L; Granner, Michelle L

2008-04-01

A community-based participatory research project using social marketing strategies was implemented to promote physical activity among women aged 35 to 54 who were insufficiently active or completely inactive. A variety of media were used to disseminate messages about how to enroll in Step Up. Step Out! This article describes the effectiveness and cost of the recruitment strategies and lessons learned in recruiting the women. Of the total inquiries (n = 691), 430 women were eligible and enrolled in the program. Based on data from questionnaires, the most effective method of recruiting women into Step Up. Step Out! was word of mouth (36%). Newspaper ads accounted for 29% of the women's responses. The least effective method was billboards. Mass media was not as effective in recruiting women for the program as interpersonal efforts such as word of mouth. Interpersonal efforts are a valuable and possibly underrated recruitment and promotion tool.

Scale-based fuzzy connectivity: a novel image segmentation methodology and its validation

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Udupa, Jayaram K.

1999-05-01

This paper extends a previously reported theory and algorithms for fuzzy connected object definition. It introduces `object scale' for determining the neighborhood size for defining affinity, the degree of local hanging togetherness between image elements. Object scale allows us to use a varying neighborhood size in different parts of the image. This paper argues that scale-based fuzzy connectivity is natural in object definition and demonstrates that this leads to a more effective object segmentation than without using scale in fuzzy concentrations. Affinity is described as consisting of a homogeneity-based and an object-feature- based component. Families of non scale-based and scale-based affinity relations are constructed. An effective method for giving a rough estimate of scale at different locations in the image is presented. The original theoretical and algorithmic framework remains more-or-less the same but considerably improved segmentations result. A quantitative statistical comparison between the non scale-based and the scale-based methods was made based on phantom images generated from patient MR brain studies by first segmenting the objects, and then by adding noise and blurring, and background component. Both the statistical and the subjective tests clearly indicate the superiority of scale- based method in capturing details and in robustness to noise.

Connecting clinical and actuarial prediction with rule-based methods.

PubMed

Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

2015-06-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

A rapid, Web-based method for obtaining patient views on effects and side-effects of antidepressants.

PubMed

Rizo, Carlos; Deshpande, Amol; Ing, Alton; Seeman, Neil

2011-04-01

This project was undertaken to develop a rapid method for obtaining a widespread sample of patient views on the efficacy and side-effects of antidepressants. A Web-based method is described for rapidly and objectively obtaining patient views on the effects and side-effects of treatment with antidepressants. The method entails a systematized search of many URLs (Uniform Resource Locators, or Web page addresses), using keywords and phrases to extract the named drug and symptom that are reliably relevant to the medication being taken by the individual reporting the experience online. Unwanted medical conditions (e.g., cancer) are excluded. Three successive searches of thousands of Web pages revealed a cumulative total of 835 "mentions" of patient experience on duloxetine, 756 for venlafaxine, 637 for citalopram, 636 for sertraline, 559 for paroxetine, 457 for fluoxetine, 318 for desvenlafaxine, 289 for fluvoxamine, and 210 for mirtazapine, in association with various symptoms. A comparison of the associated symptoms for each of the antidepressants found that the prevalence of the combined factor of fatigue, drowsiness, tiredness or lethargy ranged from 6.4±0.8% down to 2.9±0.15% of the mentions, where the S.E. was derived from three repeats of the Web-based analysis. The prevalence of dizziness or vertigo ranged from 7.6±0.8% down to 1.9±0.3% of the mentions. Given the increasing number of patient narratives about drug experiences on open-access Web forums, this rapid novel method will have increasing utility in post-marketing surveillance and in comparing the effects of psychiatric medications. Copyright © 2010 Elsevier B.V. All rights reserved.