Generating virtual training samples for sparse representation of face images and face recognition

NASA Astrophysics Data System (ADS)

Du, Yong; Wang, Yu

2016-03-01

There are many challenges in face recognition. In real-world scenes, images of the same face vary with changing illuminations, different expressions and poses, multiform ornaments, or even altered mental status. Limited available training samples cannot convey these possible changes in the training phase sufficiently, and this has become one of the restrictions to improve the face recognition accuracy. In this article, we view the multiplication of two images of the face as a virtual face image to expand the training set and devise a representation-based method to perform face recognition. The generated virtual samples really reflect some possible appearance and pose variations of the face. By multiplying a training sample with another sample from the same subject, we can strengthen the facial contour feature and greatly suppress the noise. Thus, more human essential information is retained. Also, uncertainty of the training data is simultaneously reduced with the increase of the training samples, which is beneficial for the training phase. The devised representation-based classifier uses both the original and new generated samples to perform the classification. In the classification phase, we first determine K nearest training samples for the current test sample by calculating the Euclidean distances between the test sample and training samples. Then, a linear combination of these selected training samples is used to represent the test sample, and the representation result is used to classify the test sample. The experimental results show that the proposed method outperforms some state-of-the-art face recognition methods.

An improved SRC method based on virtual samples for face recognition

NASA Astrophysics Data System (ADS)

Fu, Lijun; Chen, Deyun; Lin, Kezheng; Li, Ao

2018-07-01

The sparse representation classifier (SRC) performs classification by evaluating which class leads to the minimum representation error. However, in real world, the number of available training samples is limited due to noise interference, training samples cannot accurately represent the test sample linearly. Therefore, in this paper, we first produce virtual samples by exploiting original training samples at the aim of increasing the number of training samples. Then, we take the intra-class difference as data representation of partial noise, and utilize the intra-class differences and training samples simultaneously to represent the test sample in a linear way according to the theory of SRC algorithm. Using weighted score level fusion, the respective representation scores of the virtual samples and the original training samples are fused together to obtain the final classification results. The experimental results on multiple face databases show that our proposed method has a very satisfactory classification performance.

Operation of a sampling train for the analysis of environmental species in coal gasification gas-phase process streams

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

Pochan, M.J.; Massey, M.J.

1979-02-01

This report discusses the results of actual raw product gas sampling efforts and includes: Rationale for raw product gas sampling efforts; design and operation of the CMU gas sampling train; development and analysis of a sampling train data base; and conclusions and future application of results. The results of sampling activities at the CO/sub 2/-Acceptor and Hygas pilot plants proved that: The CMU gas sampling train is a valid instrument for characterization of environmental parameters in coal gasification gas-phase process streams; depending on the particular process configuration, the CMU gas sampling train can reduce gasifier effluent characterization activity to amore » single location in the raw product gas line; and in contrast to the slower operation of the EPA SASS Train, CMU's gas sampling train can collect representative effluent data at a rapid rate (approx. 2 points per hour) consistent with the rate of change of process variables, and thus function as a tool for process engineering-oriented analysis of environmental characteristics.« less

Appearance-based representative samples refining method for palmprint recognition

NASA Astrophysics Data System (ADS)

Wen, Jiajun; Chen, Yan

2012-07-01

The sparse representation can deal with the lack of sample problem due to utilizing of all the training samples. However, the discrimination ability will degrade when more training samples are used for representation. We propose a novel appearance-based palmprint recognition method. We aim to find a compromise between the discrimination ability and the lack of sample problem so as to obtain a proper representation scheme. Under the assumption that the test sample can be well represented by a linear combination of a certain number of training samples, we first select the representative training samples according to the contributions of the samples. Then we further refine the training samples by an iteration procedure, excluding the training sample with the least contribution to the test sample for each time. Experiments on PolyU multispectral palmprint database and two-dimensional and three-dimensional palmprint database show that the proposed method outperforms the conventional appearance-based palmprint recognition methods. Moreover, we also explore and find out the principle of the usage for the key parameters in the proposed algorithm, which facilitates to obtain high-recognition accuracy.

30 CFR 75.338 - Training.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Training. 75.338 Section 75.338 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.338 Training. (a) Certified persons conducting sampling shall be trained in the use of appropriate sampling equipment, procedures, location of sampling...

30 CFR 75.338 - Training.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Training. 75.338 Section 75.338 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.338 Training. (a) Certified persons conducting sampling shall be trained in the use of appropriate sampling equipment, procedures, location of sampling...

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

NASA Technical Reports Server (NTRS)

Tan, Bin; Brown de Colstoun, Eric; Wolfe, Robert E.; Tilton, James C.; Huang, Chengquan; Smith, Sarah E.

2012-01-01

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Robust kernel collaborative representation for face recognition

NASA Astrophysics Data System (ADS)

Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

2015-05-01

One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

Consistently Sampled Correlation Filters with Space Anisotropic Regularization for Visual Tracking

PubMed Central

Shi, Guokai; Xu, Tingfa; Luo, Jiqiang; Li, Yuankun

2017-01-01

Most existing correlation filter-based tracking algorithms, which use fixed patches and cyclic shifts as training and detection measures, assume that the training samples are reliable and ignore the inconsistencies between training samples and detection samples. We propose to construct and study a consistently sampled correlation filter with space anisotropic regularization (CSSAR) to solve these two problems simultaneously. Our approach constructs a spatiotemporally consistent sample strategy to alleviate the redundancies in training samples caused by the cyclical shifts, eliminate the inconsistencies between training samples and detection samples, and introduce space anisotropic regularization to constrain the correlation filter for alleviating drift caused by occlusion. Moreover, an optimization strategy based on the Gauss-Seidel method was developed for obtaining robust and efficient online learning. Both qualitative and quantitative evaluations demonstrate that our tracker outperforms state-of-the-art trackers in object tracking benchmarks (OTBs). PMID:29231876

Binning in Gaussian Kernel Regularization

DTIC Science & Technology

2005-04-01

OSU-SVM Matlab package, the SVM trained on 966 bins has a comparable test classification rate as the SVM trained on 27,179 samples, but reduces the...71.40%) on 966 randomly sampled data. Using the OSU-SVM Matlab package, the SVM trained on 966 bins has a comparable test classification rate as the...the OSU-SVM Matlab package, the SVM trained on 966 bins has a comparable test classification rate as the SVM trained on 27,179 samples, and reduces

Asymmetrical Sample Training and Asymmetrical Retention Functions in One-to-One and Many-to-One Matching in Pigeons

ERIC Educational Resources Information Center

Grant, Douglas S.

2006-01-01

Pigeons were trained in a matching task with either color (group color-first) or line (group line-first) samples. After asymmetrical training in which each group was initially trained with the same sample on all trials, marked retention asymmetries were obtained. In both groups, accuracy dropped precipitously on trials involving the initially…

Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers

PubMed Central

2018-01-01

Hyperspectral image classification with a limited number of training samples without loss of accuracy is desirable, as collecting such data is often expensive and time-consuming. However, classifiers trained with limited samples usually end up with a large generalization error. To overcome the said problem, we propose a fuzziness-based active learning framework (FALF), in which we implement the idea of selecting optimal training samples to enhance generalization performance for two different kinds of classifiers, discriminative and generative (e.g. SVM and KNN). The optimal samples are selected by first estimating the boundary of each class and then calculating the fuzziness-based distance between each sample and the estimated class boundaries. Those samples that are at smaller distances from the boundaries and have higher fuzziness are chosen as target candidates for the training set. Through detailed experimentation on three publically available datasets, we showed that when trained with the proposed sample selection framework, both classifiers achieved higher classification accuracy and lower processing time with the small amount of training data as opposed to the case where the training samples were selected randomly. Our experiments demonstrate the effectiveness of our proposed method, which equates favorably with the state-of-the-art methods. PMID:29304512

Target discrimination method for SAR images based on semisupervised co-training

NASA Astrophysics Data System (ADS)

Wang, Yan; Du, Lan; Dai, Hui

2018-01-01

Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

The development of radioactive sample surrogates for training and exercises

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

Martha Finck; Bevin Brush; Dick Jansen

2012-03-01

The development of radioactive sample surrogates for training and exercises Source term information is required for to reconstruct a device used in a dispersed radiological dispersal device. Simulating a radioactive environment to train and exercise sampling and sample characterization methods with suitable sample materials is a continued challenge. The Idaho National Laboratory has developed and permitted a Radioactive Response Training Range (RRTR), an 800 acre test range that is approved for open air dispersal of activated KBr, for training first responders in the entry and exit from radioactively contaminated areas, and testing protocols for environmental sampling and field characterization. Membersmore » from the Department of Defense, Law Enforcement, and the Department of Energy participated in the first contamination exercise that was conducted at the RRTR in the July 2011. The range was contaminated using a short lived radioactive Br-82 isotope (activated KBr). Soil samples contaminated with KBr (dispersed as a solution) and glass particles containing activated potassium bromide that emulated dispersed radioactive materials (such as ceramic-based sealed source materials) were collected to assess environmental sampling and characterization techniques. This presentation summarizes the performance of a radioactive materials surrogate for use as a training aide for nuclear forensics.« less

Key considerations for the experimental training and evaluation of cancer odour detection dogs: lessons learnt from a double-blind, controlled trial of prostate cancer detection

PubMed Central

2014-01-01

Background Cancer detection using sniffer dogs is a potential technology for clinical use and research. Our study sought to determine whether dogs could be trained to discriminate the odour of urine from men with prostate cancer from controls, using rigorous testing procedures and well-defined samples from a major research hospital. Methods We attempted to train ten dogs by initially rewarding them for finding and indicating individual prostate cancer urine samples (Stage 1). If dogs were successful in Stage 1, we then attempted to train them to discriminate prostate cancer samples from controls (Stage 2). The number of samples used to train each dog varied depending on their individual progress. Overall, 50 unique prostate cancer and 67 controls were collected and used during training. Dogs that passed Stage 2 were tested for their ability to discriminate 15 (Test 1) or 16 (Tests 2 and 3) unfamiliar prostate cancer samples from 45 (Test 1) or 48 (Tests 2 and 3) unfamiliar controls under double-blind conditions. Results Three dogs reached training Stage 2 and two of these learnt to discriminate potentially familiar prostate cancer samples from controls. However, during double-blind tests using new samples the two dogs did not indicate prostate cancer samples more frequently than expected by chance (Dog A sensitivity 0.13, specificity 0.71, Dog B sensitivity 0.25, specificity 0.75). The other dogs did not progress past Stage 1 as they did not have optimal temperaments for the sensitive odour discrimination training. Conclusions Although two dogs appeared to have learnt to select prostate cancer samples during training, they did not generalise on a prostate cancer odour during robust double-blind tests involving new samples. Our study illustrates that these rigorous tests are vital to avoid drawing misleading conclusions about the abilities of dogs to indicate certain odours. Dogs may memorise the individual odours of large numbers of training samples rather than generalise on a common odour. The results do not exclude the possibility that dogs could be trained to detect prostate cancer. We recommend that canine olfactory memory is carefully considered in all future studies and rigorous double-blind methods used to avoid confounding effects. PMID:24575737

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

NASA Astrophysics Data System (ADS)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process and in sample creation.

Reduction in training time of a deep learning model in detection of lesions in CT

NASA Astrophysics Data System (ADS)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

Sampling Methods and the Accredited Population in Athletic Training Education Research

ERIC Educational Resources Information Center

Carr, W. David; Volberding, Jennifer

2009-01-01

Context: We describe methods of sampling the widely-studied, yet poorly defined, population of accredited athletic training education programs (ATEPs). Objective: There are two purposes to this study; first to describe the incidence and types of sampling methods used in athletic training education research, and second to clearly define the…

Improvement of Predictive Ability by Uniform Coverage of the Target Genetic Space

PubMed Central

Bustos-Korts, Daniela; Malosetti, Marcos; Chapman, Scott; Biddulph, Ben; van Eeuwijk, Fred

2016-01-01

Genome-enabled prediction provides breeders with the means to increase the number of genotypes that can be evaluated for selection. One of the major challenges in genome-enabled prediction is how to construct a training set of genotypes from a calibration set that represents the target population of genotypes, where the calibration set is composed of a training and validation set. A random sampling protocol of genotypes from the calibration set will lead to low quality coverage of the total genetic space by the training set when the calibration set contains population structure. As a consequence, predictive ability will be affected negatively, because some parts of the genotypic diversity in the target population will be under-represented in the training set, whereas other parts will be over-represented. Therefore, we propose a training set construction method that uniformly samples the genetic space spanned by the target population of genotypes, thereby increasing predictive ability. To evaluate our method, we constructed training sets alongside with the identification of corresponding genomic prediction models for four genotype panels that differed in the amount of population structure they contained (maize Flint, maize Dent, wheat, and rice). Training sets were constructed using uniform sampling, stratified-uniform sampling, stratified sampling and random sampling. We compared these methods with a method that maximizes the generalized coefficient of determination (CD). Several training set sizes were considered. We investigated four genomic prediction models: multi-locus QTL models, GBLUP models, combinations of QTL and GBLUPs, and Reproducing Kernel Hilbert Space (RKHS) models. For the maize and wheat panels, construction of the training set under uniform sampling led to a larger predictive ability than under stratified and random sampling. The results of our methods were similar to those of the CD method. For the rice panel, all training set construction methods led to similar predictive ability, a reflection of the very strong population structure in this panel. PMID:27672112

Sample Selection for Training Cascade Detectors.

PubMed

Vállez, Noelia; Deniz, Oscar; Bueno, Gloria

2015-01-01

Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represent anything except the object of interest. In this respect, the negative set typically contains orders of magnitude more images than the positive set. However, imbalanced training databases lead to biased classifiers. In this paper, we focus our attention on a negative sample selection method to properly balance the training data for cascade detectors. The method is based on the selection of the most informative false positive samples generated in one stage to feed the next stage. The results show that the proposed cascade detector with sample selection obtains on average better partial AUC and smaller standard deviation than the other compared cascade detectors.

Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

PubMed

Wang, Rong

2015-01-01

In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

A Comparison of Match-to-Sample and Respondent-Type Training of Equivalence Classes

ERIC Educational Resources Information Center

Clayton, Michael C.; Hayes, Linda J.

2004-01-01

Throughout the 25-year history of research on stimulus equivalence, one feature of the training procedure has remained constant, namely, the requirement of operant responding during the training procedures. The present investigation compared the traditional match-to-sample (MTS) training with a more recent respondent-type (ReT) procedure. Another…

Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

NASA Astrophysics Data System (ADS)

Yan, Yue

2018-03-01

A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

Macroscopic inhomogeneous deformation behavior arising in single crystal Ni-Mn-Ga foils under tensile loading

NASA Astrophysics Data System (ADS)

Murasawa, Go; Yeduru, Srinivasa R.; Kohl, Manfred

2016-12-01

This study investigated macroscopic inhomogeneous deformation occurring in single-crystal Ni-Mn-Ga foils under uniaxial tensile loading. Two types of single-crystal Ni-Mn-Ga foil samples were examined as-received and after thermo-mechanical training. Local strain and the strain field were measured under tensile loading using laser speckle and digital image correlation. The as-received sample showed a strongly inhomogeneous strain field with intermittence under progressive deformation, but the trained sample result showed strain field homogeneity throughout the specimen surface. The as-received sample is a mainly polycrystalline-like state composed of the domain structure. The sample contains many domain boundaries and large domain structures in the body. Its structure would cause large local strain band nucleation with intermittence. However, the trained one is an ideal single-crystalline state with a transformation preferential orientation of variants after almost all domain boundary and large domain structures vanish during thermo-mechanical training. As a result, macroscopic homogeneous deformation occurs on the trained sample surface during deformation.

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies

PubMed Central

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-01-01

Background The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study Aim To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. Design and setting A three-part longitudinal predictive validity study of selection into training for UK general practice. Method In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Results Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. Conclusion In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered. PMID:24267856

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

PubMed

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-11-01

The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

The Effect of Multiprofessional Simulation-Based Obstetric Team Training on Patient-Reported Quality of Care: A Pilot Study.

PubMed

Truijens, Sophie E M; Banga, Franyke R; Fransen, Annemarie F; Pop, Victor J M; van Runnard Heimel, Pieter J; Oei, S Guid

2015-08-01

This study aimed to explore whether multiprofessional simulation-based obstetric team training improves patient-reported quality of care during pregnancy and childbirth. Multiprofessional teams from a large obstetric collaborative network in the Netherlands were trained in teamwork skills using the principles of crew resource management. Patient-reported quality of care was measured with the validated Pregnancy and Childbirth Questionnaire (PCQ) at 6 weeks postpartum. Before the training, 76 postpartum women (sample I) completed the questionnaire 6 weeks postpartum. Three months after the training, another sample of 68 postpartum women (sample II) completed the questionnaire. In sample II (after the training), the mean (SD) score of 108.9 (10.9) on the PCQ questionnaire was significantly higher than the score of 103.5 (11.6) in sample I (before training) (t = 2.75, P = 0.007). The effect size of the increase in PCQ total score was 0.5. Moreover, the subscales "personal treatment during pregnancy" and "educational information" showed a significant increase after the team training (P < 0.001). Items with the largest increase in mean scores included communication between health care professionals, clear leadership, involvement in planning, and better provision of information. Despite the methodological restrictions of a pilot study, the preliminary results indicate that multiprofessional simulation-based obstetric team training seems to improve patient-reported quality of care. The possibility that this improvement relates to the training is supported by the fact that the items with the largest increase are about the principles of crew resource management, used in the training.

Anomaly detection for machine learning redshifts applied to SDSS galaxies

NASA Astrophysics Data System (ADS)

Hoyle, Ben; Rau, Markus Michael; Paech, Kerstin; Bonnett, Christopher; Seitz, Stella; Weller, Jochen

2015-10-01

We present an analysis of anomaly detection for machine learning redshift estimation. Anomaly detection allows the removal of poor training examples, which can adversely influence redshift estimates. Anomalous training examples may be photometric galaxies with incorrect spectroscopic redshifts, or galaxies with one or more poorly measured photometric quantity. We select 2.5 million `clean' SDSS DR12 galaxies with reliable spectroscopic redshifts, and 6730 `anomalous' galaxies with spectroscopic redshift measurements which are flagged as unreliable. We contaminate the clean base galaxy sample with galaxies with unreliable redshifts and attempt to recover the contaminating galaxies using the Elliptical Envelope technique. We then train four machine learning architectures for redshift analysis on both the contaminated sample and on the preprocessed `anomaly-removed' sample and measure redshift statistics on a clean validation sample generated without any preprocessing. We find an improvement on all measured statistics of up to 80 per cent when training on the anomaly removed sample as compared with training on the contaminated sample for each of the machine learning routines explored. We further describe a method to estimate the contamination fraction of a base data sample.

32 CFR Appendix E to Part 110 - Application of 4-Week Summer Field Training Formula (Sample)

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 1 2014-07-01 2014-07-01 false Application of 4-Week Summer Field Training Formula (Sample) E Appendix E to Part 110 National Defense Department of Defense OFFICE OF THE SECRETARY... Appendix E to Part 110—Application of 4-Week Summer Field Training Formula (Sample) Zone I Zone II Total...

32 CFR Appendix E to Part 110 - Application of 4-Week Summer Field Training Formula (Sample)

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 1 2013-07-01 2013-07-01 false Application of 4-Week Summer Field Training Formula (Sample) E Appendix E to Part 110 National Defense Department of Defense OFFICE OF THE SECRETARY... Appendix E to Part 110—Application of 4-Week Summer Field Training Formula (Sample) Zone I Zone II Total...

32 CFR Appendix E to Part 110 - Application of 4-Week Summer Field Training Formula (Sample)

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 1 2012-07-01 2012-07-01 false Application of 4-Week Summer Field Training Formula (Sample) E Appendix E to Part 110 National Defense Department of Defense OFFICE OF THE SECRETARY... Appendix E to Part 110—Application of 4-Week Summer Field Training Formula (Sample) Zone I Zone II Total...

32 CFR Appendix E to Part 110 - Application of 4-Week Summer Field Training Formula (Sample)

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 1 2011-07-01 2011-07-01 false Application of 4-Week Summer Field Training Formula (Sample) E Appendix E to Part 110 National Defense Department of Defense OFFICE OF THE SECRETARY... Appendix E to Part 110—Application of 4-Week Summer Field Training Formula (Sample) Zone I Zone II Total...

32 CFR Appendix E to Part 110 - Application of 4-Week Summer Field Training Formula (Sample)

Code of Federal Regulations, 2010 CFR

2010-07-01

... Formula (Sample) E Appendix E to Part 110 National Defense Department of Defense OFFICE OF THE SECRETARY... COMMUTATION INSTEAD OF UNIFORMS FOR MEMBERS OF THE SENIOR RESERVE OFFICERS' TRAINING CORPS Pt. 110, App. E Appendix E to Part 110—Application of 4-Week Summer Field Training Formula (Sample) Zone I Zone II Total...

How large a training set is needed to develop a classifier for microarray data?

PubMed

Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

2008-01-01

A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

Effects of a Specifically Designed Physical Conditioning Program on the Load Carriage and Lifting Performance of Female Soldiers.

DTIC Science & Technology

1997-11-01

66 TRAINING AND TESTING RELATED INJURIES ................ 68 iv Pre-tests ................................................ 68 T raining...74 BASIC TRAINING VS. THE EXPERIMENTAL PROGRAM ......... 74 INDIVIDUAL DIFFERENCES IN RESPONSIVENESS TO TRAINING.. 74 INJURY RISK IN HIGH-LEVEL...USED FOR TRAINING ............ SAMPLE WORKOUTS .................................... vi Sample Monday and Thursday Weightlifting and Running W orkout

Evaluation of pyramid training as a method to increase diagnostic sampling capacity during an emergency veterinary response to a swine disease outbreak.

PubMed

Canon, Abbey J; Lauterbach, Nicholas; Bates, Jessica; Skoland, Kristin; Thomas, Paul; Ellingson, Josh; Ruston, Chelsea; Breuer, Mary; Gerardy, Kimberlee; Hershberger, Nicole; Hayman, Kristen; Buckley, Alexis; Holtkamp, Derald; Karriker, Locke

2017-06-15

OBJECTIVE To develop and evaluate a pyramid training method for teaching techniques for collection of diagnostic samples from swine. DESIGN Experimental trial. SAMPLE 45 veterinary students. PROCEDURES Participants went through a preinstruction assessment to determine their familiarity with the equipment needed and techniques used to collect samples of blood, nasal secretions, feces, and oral fluid from pigs. Participants were then shown a series of videos illustrating the correct equipment and techniques for collecting samples and were provided hands-on pyramid-based instruction wherein a single swine veterinarian trained 2 or 3 participants on each of the techniques and each of those participants, in turn, trained additional participants. Additional assessments were performed after the instruction was completed. RESULTS Following the instruction phase, percentages of participants able to collect adequate samples of blood, nasal secretions, feces, and oral fluid increased, as did scores on a written quiz assessing participants' ability to identify the correct equipment, positioning, and procedures for collection of samples. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that the pyramid training method may be a feasible way to rapidly increase diagnostic sampling capacity during an emergency veterinary response to a swine disease outbreak.

Soils Sampling and Testing Training Guide for Field and Laboratory Technicians on Roadway Construction

DOT National Transportation Integrated Search

1999-12-01

This manual has been developed as a training guide for field and laboratory technicians responsible for sampling and testing of soils used in roadway construction. Soils training and certification will increase the knowledge of laboratory, production...

[Perceptions about continuous training of Chilean health care teachers].

PubMed

Pérez V, Cristhian; Fasce H, Eduardo; Coloma N, Katherine; Vaccarezza G, Giulietta; Ortega B, Javiera

2013-06-01

Continuous training of teachers, in discipline and pedagogical topics, is a key step to improve the quality of educational processes. To report the perception of Chilean teachers of undergraduate health care programs, about continuous training activities. Twenty teachers working at different undergraduate health care programs in Chile were interviewed. Maximum variation and theoretical sampling methods were used to select the sample. Data was analyzed by open coding, according to the Grounded Theory guidelines. Nine categories emerged from data analysis: Access to continuous training, meaning of training in discipline, activities of continuous training in discipline, meaning of continuous training in pedagogy, kinds of continuous training in pedagogy, quality of continuous training in pedagogy, ideal of continuous training in pedagogy, outcomes of continuous training in pedagogy and needs for continuous training in pedagogy. Teachers of health care programs prefer to participate in contextualized training activities. Also, they emphasize their need of training in evaluation and teaching strategies.

Rigorous Training of Dogs Leads to High Accuracy in Human Scent Matching-To-Sample Performance

PubMed Central

Marchal, Sophie; Bregeras, Olivier; Puaux, Didier; Gervais, Rémi; Ferry, Barbara

2016-01-01

Human scent identification is based on a matching-to-sample task in which trained dogs are required to compare a scent sample collected from an object found at a crime scene to that of a suspect. Based on dogs’ greater olfactory ability to detect and process odours, this method has been used in forensic investigations to identify the odour of a suspect at a crime scene. The excellent reliability and reproducibility of the method largely depend on rigor in dog training. The present study describes the various steps of training that lead to high sensitivity scores, with dogs matching samples with 90% efficiency when the complexity of the scents presented during the task in the sample is similar to that presented in the in lineups, and specificity reaching a ceiling, with no false alarms in human scent matching-to-sample tasks. This high level of accuracy ensures reliable results in judicial human scent identification tests. Also, our data should convince law enforcement authorities to use these results as official forensic evidence when dogs are trained appropriately. PMID:26863620

Predicting the required number of training samples. [for remotely sensed image data based on covariance matrix estimate quality criterion of normal distribution

NASA Technical Reports Server (NTRS)

Kalayeh, H. M.; Landgrebe, D. A.

1983-01-01

A criterion which measures the quality of the estimate of the covariance matrix of a multivariate normal distribution is developed. Based on this criterion, the necessary number of training samples is predicted. Experimental results which are used as a guide for determining the number of training samples are included. Previously announced in STAR as N82-28109

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

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

Ground Training Devices in Job Sample Approach to UPT [Undergraduate Pilot Training] Selection and Screening. Final Report, September 1972-August 1974.

ERIC Educational Resources Information Center

LeMaster, W. Dean; Gray, Thomas H.

The purpose of this study was to develop a screening procedure for undergraduate pilot training (UPT). This procedure was based upon the use of ground-based instrument trainers in which UPT candidates, naive to flying, were evaluated in their performance of job sample tasks; i.e., basic instrument flying. Training and testing sessions were…

Methods for Integrating Environmental Awareness Training into Army Programs of Instruction

DTIC Science & Technology

1993-06-01

generations. iv NTIS CRA&I ) F -IC TAB U.a’mot’::ed El By .. . ... ....... By .......................... ...... . .. DiO t, ib., tion I CONTENTS...Training Support Package ................... E-1-E-19 Appendix F . Sample of Officer Basic Course Instructor’s Lesson Plan with Embedded Information... F -1- F -7 Appendix G. Samples of Situational Training Exercises ........... G-1-G 9 Appendix H. Samples of Pre-Command Course Guest Speaker

Short communication: Ability of dogs to detect cows in estrus from sniffing saliva samples.

PubMed

Fischer-Tenhagen, C; Tenhagen, B-A; Heuwieser, W

2013-02-01

Efficient estrus detection in high-producing dairy cows is a permanent challenge for successful reproductive performance. In former studies, dogs have been trained to identify estrus-specific odor in vaginal fluid, milk, urine, and blood samples under laboratory conditions with an accuracy of more than 80%. For on-farm utilization of estrus-detection dogs it would be beneficial in terms of hygiene and safety if dogs could identify cows from the feed alley. The objective of this proof of concept study was to test if dogs can be trained to detect estrus-specific scent in saliva of cows. Saliva samples were collected from cows in estrus and diestrus. Thirteen dogs of various breeds and both sexes were trained in this study. Five dogs had no experience in scent detection, whereas 8 dogs had been formerly trained for detection of narcotics or cancer. In the training and test situation, dogs had to detect 1 positive out of 4 samples. Dog training was based on positive reinforcement and dogs were rewarded with a clicker and food for indicating saliva samples of cows in estrus. A false indication was ignored and documented in the test situation. Dogs with and without prior training were trained for 1 and 5 d, respectively. For determining the accuracy of detection, the position of the positive sample was unknown to the dog handler, to avoid hidden cues to the dog. The overall percentage of correct positive indications was 57.6% (175/304), with a range from 40 (1 dog) to 75% (3 dogs). To our knowledge, this is the first indication that dogs are able to detect estrus-specific scent in saliva of cows. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Over-Selectivity as a Learned Response

ERIC Educational Resources Information Center

Reed, Phil; Petrina, Neysa; McHugh, Louise

2011-01-01

An experiment investigated the effects of different levels of task complexity in pre-training on over-selectivity in a subsequent match-to-sample (MTS) task. Twenty human participants were divided into two groups; exposed either to a 3-element, or a 9-element, compound stimulus as a sample during MTS training. After the completion of training,…

Dynamic spiking studies using the DNPH sampling train

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

Steger, J.L.; Knoll, J.E.

1996-12-31

The proposed aldehyde and ketone sampling method using aqueous 2,4-dinitrophenylhydrazine (DNPH) was evaluated in the laboratory and in the field. The sampling trains studied were based on the train described in SW 846 Method 0011. Nine compounds were evaluated: formaldehyde, acetaldehyde, quinone, acrolein, propionaldeyde, methyl isobutyl ketone, methyl ethyl ketone, acetophenone, and isophorone. In the laboratory, the trains were spiked both statistically and dynamically. Laboratory studies also investigated potential interferences to the method. Based on their potential to hydrolyze in acid solution to form formaldehyde, dimethylolurea, saligenin, s-trioxane, hexamethylenetetramine, and paraformaldehyde were investigated. Ten runs were performed using quadruplicate samplingmore » trains. Two of the four trains were dynamically spiked with the nine aldehydes and ketones. The test results were evaluated using the EPA method 301 criteria for method precision (< + pr - 50% relative standard deviation) and bias (correction factor of 1.00 + or - 0.30).« less

Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

PubMed

Wu, Dongrui; Lance, Brent J; Parsons, Thomas D

2013-01-01

Brain-computer interaction (BCI) and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL), active class selection (ACS), and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.

Collaborative Filtering for Brain-Computer Interaction Using Transfer Learning and Active Class Selection

PubMed Central

Wu, Dongrui; Lance, Brent J.; Parsons, Thomas D.

2013-01-01

Brain-computer interaction (BCI) and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL), active class selection (ACS), and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing. PMID:23437188

Train the Trainer. Facilitator Guide Sample. Basic Blueprint Reading (Chapter One).

ERIC Educational Resources Information Center

Saint Louis Community Coll., MO.

This publication consists of three sections: facilitator's guide--train the trainer, facilitator's guide sample--Basic Blueprint Reading (Chapter 1), and participant's guide sample--basic blueprint reading (chapter 1). Section I addresses why the trainer should learn new classroom techniques; lecturing versus facilitating; learning styles…

Evaluation of a Traffic Sign Detector by Synthetic Image Data for Advanced Driver Assistance Systems

NASA Astrophysics Data System (ADS)

Hanel, A.; Kreuzpaintner, D.; Stilla, U.

2018-05-01

Recently, several synthetic image datasets of street scenes have been published. These datasets contain various traffic signs and can therefore be used to train and test machine learning-based traffic sign detectors. In this contribution, selected datasets are compared regarding ther applicability for traffic sign detection. The comparison covers the process to produce the synthetic images and addresses the virtual worlds, needed to produce the synthetic images, and their environmental conditions. The comparison covers variations in the appearance of traffic signs and the labeling strategies used for the datasets, as well. A deep learning traffic sign detector is trained with multiple training datasets with different ratios between synthetic and real training samples to evaluate the synthetic SYNTHIA dataset. A test of the detector on real samples only has shown that an overall accuracy and ROC AUC of more than 95 % can be achieved for both a small rate of synthetic samples and a large rate of synthetic samples in the training dataset.

Dynamic stress effects in technical superconductors and the ''training'' problem of superconducting magnets

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

Pasztor, G.; Schmidt, C.

The behavior of NbTi superconductors under dynamic mechanical stress was investigated. A training effect was found in short-sample tests when the conductor was strained in a magnetic field and with a transport current applied. Possible mechanisms are discussed which were proposed to explain training in short samples and in magnets. A stress-induced microplastic as well as an incomplete pseudoelastic behavior of NbTi was detected by monitoring acoustic emission. The experiments support the hypothesis that microplastic or shape memory effects in NbTi involving dislocation processes are responsible for training. The minimum energy needed to induce a normal transition in short-sample testsmore » is calculated with a computer program, which gives the exact solution of the heat equation. A prestrain treatment of the conductor at room temperature is shown to be a simple method of reducing training of short samples and of magnets. This is a direct proof that the same mechanisms are involved in both cases.« less

Sample selection via angular distance in the space of the arguments of an artificial neural network

NASA Astrophysics Data System (ADS)

Fernández Jaramillo, J. M.; Mayerle, R.

2018-05-01

In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.

ANALYSIS RESULTS FOR BUILDING 241 702-AZ A TRAIN

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

DUNCAN JB; FRYE JM; COOKE CA

2006-12-13

This report presents the analyses results for three samples obtained under RPP-PLAN-28509, Sampling and Analysis Plan for Building 241 702-AZ A Train. The sampling and analysis was done in response to problem evaluation request number PER-2004-6139, 702-AZ Filter Rooms Need Radiological Cleanup Efforts.

Stemless Ball Valve

NASA Technical Reports Server (NTRS)

Burgess, Robert K.; Yakos, David; Walthall, Bryan

2012-01-01

This invention utilizes a new method of opening and closing a ball valve. Instead of rotating the ball with a perpendicular stem (as is the case with standard ball valves), the ball is rotated around a fixed axis by two guide pins. This innovation eliminates the leak point that is present in all standard ball valves due to the penetration of an actuation stem through the valve body. The VOST (Venturi Off-Set-Technology) valve has been developed for commercial applications. The standard version of the valve consists of an off-set venturi flow path through the valve. This path is split at the narrowest portion of the venturi, allowing the section upstream from the venturi to be rotated. As this rotation takes place, the venturi becomes restricted as one face rotates with respect to the other, eventually closing off the flow path. A spring-loaded seal made of resilient material is embedded in the upstream face of the valve, making a leak-proof seal between the faces; thus a valve is formed. The spring-loaded lip seal is the only seal that can provide a class six, or bubble-tight, seal against the opposite face of the valve. Tearing action of the seal by high-velocity gas on this early design required relocation of the seal to the downstream face of the valve. In the stemless embodiment of this valve, inner and outer magnetic cartridges are employed to transfer mechanical torque from the outside of the valve to the inside without the use of a stem. This eliminates the leak path caused by the valve stems in standard valves because the stems penetrate through the bodies of these valves.

Estimating the circuit delay of FPGA with a transfer learning method

NASA Astrophysics Data System (ADS)

Cui, Xiuhai; Liu, Datong; Peng, Yu; Peng, Xiyuan

2017-10-01

With the increase of FPGA (Field Programmable Gate Array, FPGA) functionality, FPGA has become an on-chip system platform. Due to increase the complexity of FPGA, estimating the delay of FPGA is a very challenge work. To solve the problems, we propose a transfer learning estimation delay (TLED) method to simplify the delay estimation of different speed grade FPGA. In fact, the same style different speed grade FPGA comes from the same process and layout. The delay has some correlation among different speed grade FPGA. Therefore, one kind of speed grade FPGA is chosen as a basic training sample in this paper. Other training samples of different speed grade can get from the basic training samples through of transfer learning. At the same time, we also select a few target FPGA samples as training samples. A general predictive model is trained by these samples. Thus one kind of estimation model is used to estimate different speed grade FPGA circuit delay. The framework of TRED includes three phases: 1) Building a basic circuit delay library which includes multipliers, adders, shifters, and so on. These circuits are used to train and build the predictive model. 2) By contrasting experiments among different algorithms, the forest random algorithm is selected to train predictive model. 3) The target circuit delay is predicted by the predictive model. The Artix-7, Kintex-7, and Virtex-7 are selected to do experiments. Each of them includes -1, -2, -2l, and -3 different speed grade. The experiments show the delay estimation accuracy score is more than 92% with the TLED method. This result shows that the TLED method is a feasible delay assessment method, especially in the high-level synthesis stage of FPGA tool, which is an efficient and effective delay assessment method.

Effect of finite sample size on feature selection and classification: a simulation study.

PubMed

Way, Ted W; Sahiner, Berkman; Hadjiiski, Lubomir M; Chan, Heang-Ping

2010-02-01

The small number of samples available for training and testing is often the limiting factor in finding the most effective features and designing an optimal computer-aided diagnosis (CAD) system. Training on a limited set of samples introduces bias and variance in the performance of a CAD system relative to that trained with an infinite sample size. In this work, the authors conducted a simulation study to evaluate the performances of various combinations of classifiers and feature selection techniques and their dependence on the class distribution, dimensionality, and the training sample size. The understanding of these relationships will facilitate development of effective CAD systems under the constraint of limited available samples. Three feature selection techniques, the stepwise feature selection (SFS), sequential floating forward search (SFFS), and principal component analysis (PCA), and two commonly used classifiers, Fisher's linear discriminant analysis (LDA) and support vector machine (SVM), were investigated. Samples were drawn from multidimensional feature spaces of multivariate Gaussian distributions with equal or unequal covariance matrices and unequal means, and with equal covariance matrices and unequal means estimated from a clinical data set. Classifier performance was quantified by the area under the receiver operating characteristic curve Az. The mean Az values obtained by resubstitution and hold-out methods were evaluated for training sample sizes ranging from 15 to 100 per class. The number of simulated features available for selection was chosen to be 50, 100, and 200. It was found that the relative performance of the different combinations of classifier and feature selection method depends on the feature space distributions, the dimensionality, and the available training sample sizes. The LDA and SVM with radial kernel performed similarly for most of the conditions evaluated in this study, although the SVM classifier showed a slightly higher hold-out performance than LDA for some conditions and vice versa for other conditions. PCA was comparable to or better than SFS and SFFS for LDA at small samples sizes, but inferior for SVM with polynomial kernel. For the class distributions simulated from clinical data, PCA did not show advantages over the other two feature selection methods. Under this condition, the SVM with radial kernel performed better than the LDA when few training samples were available, while LDA performed better when a large number of training samples were available. None of the investigated feature selection-classifier combinations provided consistently superior performance under the studied conditions for different sample sizes and feature space distributions. In general, the SFFS method was comparable to the SFS method while PCA may have an advantage for Gaussian feature spaces with unequal covariance matrices. The performance of the SVM with radial kernel was better than, or comparable to, that of the SVM with polynomial kernel under most conditions studied.

Does On-the-Job Training Improve an Employee's Job Performance?

ERIC Educational Resources Information Center

Duff, Juanita

A study examined the link between on-the-job training (OJT) and job performance in a randomly selected sample of 50 skilled maintenance craftpersons employed by the city of Chicago. The sample was identified from the training sheets signed by 160 employees who participated in OJT in a 1-month period. The majority of the employees agreed with…

Is exercise used as medicine? Association of meeting strength training guidelines and functional limitations among older US adults.

PubMed

Kraschnewski, Jennifer L; Sciamanna, Christopher N; Ciccolo, Joseph T; Rovniak, Liza S; Lehman, Erik B; Candotti, Carolina; Ballentine, Noel H

2014-09-01

To determine the association between meeting strength training guidelines (≥2 times per week) and the presence of functional limitations among older adults. This cross-sectional study used data from older adult participants (N=6763) of the National Health Interview Survey conducted in 2011 in the United States. Overall, 16.1% of older adults reported meeting strength training guidelines. For each of nine functional limitations, those with the limitation were less likely to meet strength training recommendations than those without the limitation. For example, 20.0% of those who reported no difficulty walking one-quarter mile met strength training guidelines, versus only 10.1% of those who reported difficulty (p<.001). In sum, 21.7% of those with no limitations (33.7% of sample) met strength training guidelines, versus only 15.9% of those reporting 1-4 limitations (38.5% of sample) and 9.8% of those reporting 5-9 limitations (27.8% of sample) (p<.001). Strength training is uncommon among older adults and even less common among those who need it the most. The potential for strength training to improve the public's health is therefore substantial, as those who have the most to gain from strength training participate the least. Copyright © 2014 Elsevier Inc. All rights reserved.

[Assessment of laparoscopic training based on eye tracker and electroencephalograph].

PubMed

Liu, Yun; Wang, Shuyi; Zhang, Yangun; Xu, Mingzhe; Ye, Shasha; Wang, Peng

2017-02-01

The aim of this study is to evaluate the effect of laparoscopic simulation training with different attention. Attention was appraised using the sample entropy and θ/β value, which were calculated according to electroencephalograph(EEG) signal collected with Brain Link. The effect of laparoscopic simulation training was evaluated using the completion time, error number and fixation number, which were calculated according to eye movement signal collected with Tobii eye tracker. Twenty volunteers were recruited in this study. Those with the sample entropy lower than0.77 were classified into group A and those higher than 0.77 into group B. The results showed that the sample entropy of group A was lower than that of group B, and fluctuations of A were more steady. However, the sample entropy of group B showed steady fluctuations in the first five trainings, and then demonstrated relatively dramatic fluctuates in the later five trainings. Compared with that of group B, the θ/β value of group A was smaller and shows steady fluctuations. Group A has a shorter completion time, less errors and faster decrease of fixation number. Therefore, this study reached the following conclusion that the attention of the trainees would affect the training effect. Members in group A, who had a higher attention were more efficient and faster training. For those in group B, although their training skills have been improved, they needed a longer time to reach a plateau.

A preliminary investigation to explore the cognitive resources of physicians experiencing difficulty in training.

PubMed

Patterson, Fiona; Cousans, Fran; Coyne, Iain; Jones, Jo; Macleod, Sheona; Zibarras, Lara

2017-05-15

Treating patients is complex, and research shows that there are differences in cognitive resources between physicians who experience difficulties, and those who do not. It is possible that differences in some cognitive resources could explain the difficulties faced by some physicians. In this study, we explore differences in cognitive resources between different groups of physicians (that is, between native (UK) physicians and International Medical Graduates (IMG); those who continue with training versus those who were subsequently removed from the training programme); and also between physicians experiencing difficulties compared with the general population. A secondary evaluation was conducted on an anonymised dataset provided by the East Midlands Professional Support Unit (PSU). One hundred and twenty one postgraduate trainee physicians took part in an Educational Psychology assessment through PSU. Referrals to the PSU were mainly on the basis of problems with exam progression and difficulties in communication skills, organisation and confidence. Cognitive resources were assessed using the Wechsler Adult Intelligence Scale (WAIS-IV). Physicians were categorised into three PSU outcomes: 'Continued in training', 'Removed from training' and 'Active' (currently accessing the PSU). Using a one-sample Z test, we compared the referred physician sample to a UK general population sample on the WAIS-IV and found the referred sample significantly higher in Verbal Comprehension (VCI; z = 8.78) and significantly lower in Working Memory (WMI; z = -4.59). In addition, the native sample were significantly higher in Verbal Comprehension than the UK general population sample (VCI; native physicians: z = 9.95, p < .001, d = 1.25), whilst there was a lesser effect for the difference between the IMG sample and the UK general population (z = 2.13, p = .03, d = 0.29). Findings also showed a significant difference in VCI scores between those physicians who were 'Removed from training' and those who 'Continued in training'. Our results suggest it is important to understand the cognitive resources of physicians to provide a more focussed explanation of those who experience difficulties in training. This will help to implement more targeted interventions to help physicians develop compensatory strategies.

Using partially labeled data for normal mixture identification with application to class definition

NASA Technical Reports Server (NTRS)

Shahshahani, Behzad M.; Landgrebe, David A.

1992-01-01

The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

CTEPP STANDARD OPERATING PROCEDURE FOR CONDUCTING STAFF AND PARTICIPANT TRAINING (SOP-2.27)

EPA Science Inventory

This SOP describes the method to train project staff and participants to collect various field samples and questionnaire data for the study. The training plan consists of two separate components: project staff training and participant training. Before project activities begin,...

A Pilot Investigation Comparing Instructional Packages for MTS Training: "Manual Alone" vs. "Manual-Plus-Computer-Aided Personalized System of Instruction"

ERIC Educational Resources Information Center

Oliveira, Marileide; Goyos, Celso; Pear, Joseph

2012-01-01

Matching-to-sample (MTS) training consists of presenting a stimulus as a sample followed by stimuli called comparisons from which a subject makes a choice. This study presents results of a pilot investigation comparing two packages for teaching university students to conduct MTS training. Two groups--control and experimental--with 2 participants…

Integrating conventional and inverse representation for face recognition.

PubMed

Xu, Yong; Li, Xuelong; Yang, Jian; Lai, Zhihui; Zhang, David

2014-10-01

Representation-based classification methods are all constructed on the basis of the conventional representation, which first expresses the test sample as a linear combination of the training samples and then exploits the deviation between the test sample and the expression result of every class to perform classification. However, this deviation does not always well reflect the difference between the test sample and each class. With this paper, we propose a novel representation-based classification method for face recognition. This method integrates conventional and the inverse representation-based classification for better recognizing the face. It first produces conventional representation of the test sample, i.e., uses a linear combination of the training samples to represent the test sample. Then it obtains the inverse representation, i.e., provides an approximation representation of each training sample of a subject by exploiting the test sample and training samples of the other subjects. Finally, the proposed method exploits the conventional and inverse representation to generate two kinds of scores of the test sample with respect to each class and combines them to recognize the face. The paper shows the theoretical foundation and rationale of the proposed method. Moreover, this paper for the first time shows that a basic nature of the human face, i.e., the symmetry of the face can be exploited to generate new training and test samples. As these new samples really reflect some possible appearance of the face, the use of them will enable us to obtain higher accuracy. The experiments show that the proposed conventional and inverse representation-based linear regression classification (CIRLRC), an improvement to linear regression classification (LRC), can obtain very high accuracy and greatly outperforms the naive LRC and other state-of-the-art conventional representation based face recognition methods. The accuracy of CIRLRC can be 10% greater than that of LRC.

Play Therapy Training among School Psychology, Social Work, and School Counseling Graduate Training Programs

ERIC Educational Resources Information Center

Pascarella, Christina Bechle

2012-01-01

This study examined play therapy training across the nation among school psychology, social work, and school counseling graduate training programs. It also compared current training to previous training among school psychology and school counseling programs. A random sample of trainers was selected from lists of graduate programs provided by…

Using complex auditory-visual samples to produce emergent relations in children with autism.

PubMed

Groskreutz, Nicole C; Karsina, Allen; Miguel, Caio F; Groskreutz, Mark P

2010-03-01

Six participants with autism learned conditional relations between complex auditory-visual sample stimuli (dictated words and pictures) and simple visual comparisons (printed words) using matching-to-sample training procedures. Pre- and posttests examined potential stimulus control by each element of the complex sample when presented individually and emergence of additional conditional relations and oral labeling. Tests revealed class-consistent performance for all participants following training.

Manifold Regularized Experimental Design for Active Learning.

PubMed

Zhang, Lining; Shum, Hubert P H; Shao, Ling

2016-12-02

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.

New method for detection of gastric cancer by hyperspectral imaging: a pilot study

NASA Astrophysics Data System (ADS)

Kiyotoki, Shu; Nishikawa, Jun; Okamoto, Takeshi; Hamabe, Kouichi; Saito, Mari; Goto, Atsushi; Fujita, Yusuke; Hamamoto, Yoshihiko; Takeuchi, Yusuke; Satori, Shin; Sakaida, Isao

2013-02-01

We developed a new, easy, and objective method to detect gastric cancer using hyperspectral imaging (HSI) technology combining spectroscopy and imaging A total of 16 gastroduodenal tumors removed by endoscopic resection or surgery from 14 patients at Yamaguchi University Hospital, Japan, were recorded using a hyperspectral camera (HSC) equipped with HSI technology Corrected spectral reflectance was obtained from 10 samples of normal mucosa and 10 samples of tumors for each case The 16 cases were divided into eight training cases (160 training samples) and eight test cases (160 test samples) We established a diagnostic algorithm with training samples and evaluated it with test samples Diagnostic capability of the algorithm for each tumor was validated, and enhancement of tumors by image processing using the HSC was evaluated The diagnostic algorithm used the 726-nm wavelength, with a cutoff point established from training samples The sensitivity, specificity, and accuracy rates of the algorithm's diagnostic capability in the test samples were 78.8% (63/80), 92.5% (74/80), and 85.6% (137/160), respectively Tumors in HSC images of 13 (81.3%) cases were well enhanced by image processing Differences in spectral reflectance between tumors and normal mucosa suggested that tumors can be clearly distinguished from background mucosa with HSI technology.

A visual training tool for the Photoload sampling technique

Treesearch

Violet J. Holley; Robert E. Keane

2010-01-01

This visual training aid is designed to provide Photoload users a tool to increase the accuracy of fuel loading estimations when using the Photoload technique. The Photoload Sampling Technique (RMRS-GTR-190) provides fire managers a sampling method for obtaining consistent, accurate, inexpensive, and quick estimates of fuel loading. It is designed to require only one...

An Assessment of Workplace Skills Acquired by Students of Vocational and Technical Education Institutions

ERIC Educational Resources Information Center

Bakar, Ab Rahim; Mohamed, Shamsiah; Hamzah, Ramlah

2013-01-01

This study was performed to identify the employability skills of technical students from the Industrial Training Institutes (ITI) and Indigenous People's Trust Council (MARA) Skills Training Institutes (IKM) in Malaysia. The study sample consisted of 850 final year trainees of IKM and ITI. The sample was chosen by a random sampling procedure from…

There is a long way to go: a nationwide survey of professional training for mental health practitioners in China.

PubMed

Gao, Xiao; Jackson, Todd; Chen, Hong; Liu, Yanmei; Wang, Ruiqiang; Qian, Mingyi; Huang, Xiting

2010-04-01

This nationwide survey of professional training for mental health practitioners (i.e., psychiatrists, psychiatric nurses, clinical psychologists, and the counselors working in industry, prisons, and schools) investigated sociodemographic characteristics, training experiences, and training perceptions of mental health service providers in China. Participants included service providers recruited from hospitals, universities, high/middle schools, private mental health service organizations and counseling centers operated by government, prisons or corporations from 25 provinces and four cities directly under the Central Government in China. In order to obtain a broad and representative sample, stratified multi-stage sampling procedures were utilized. From a total of 2000 questionnaire packets distributed via regular mail, the final sample comprised of 1391 respondents (525 men, 866 women). About 70% of the sample had a bachelor's level education or lower degree, only 36.4% majored in psychology, and nearly 60% were employed part time. Fewer than half of participants were certified and nearly 40% reported no affiliation with any 'professional' association. Training and continuing education programs were reported to be primarily short term and theory-based with limited assessment and follow-up. A high proportion of respondents reported having received no supervision or opportunities for case conferences or consultations. With respect to perceptions of and satisfaction with training, many agreed that training had been very helpful to their work but quality of supervision and the capability of supervisors were common issues of concern. In light of these findings, three general recommendations were made to improve the quality of training among mental health service providers in China. First, increased input from professional organizations of various disciplines involving mental health service provision is needed to guide training and shape policy. Second, universities and colleges should have a more vital role in developing accredited professional training programs. Finally, on-the-job supervision and continuing education should be mandated within discipline-specific training programs. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Working Memory Training and Transfer in Older Adults: Effects of Age, Baseline Performance, and Training Gains

ERIC Educational Resources Information Center

Zinke, Katharina; Zeintl, Melanie; Rose, Nathan S.; Putzmann, Julia; Pydde, Andrea; Kliegel, Matthias

2014-01-01

Recent studies suggest that working memory training may benefit older adults; however, findings regarding training and transfer effects are mixed. The current study aimed to investigate the effects of a process-based training intervention in a diverse sample of older adults and explored possible moderators of training and transfer effects. For…

Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Kan, Jianquan

2018-04-01

In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

Short-Term Effects of Different Loading Schemes in Fitness-Related Resistance Training.

PubMed

Eifler, Christoph

2016-07-01

Eifler, C. Short-term effects of different loading schemes in fitness-related resistance training. J Strength Cond Res 30(7): 1880-1889, 2016-The purpose of this investigation was to analyze the short-term effects of different loading schemes in fitness-related resistance training and to identify the most effective loading method for advanced recreational athletes. The investigation was designed as a longitudinal field-test study. Two hundred healthy mature subjects with at least 12 months' experience in resistance training were randomized in 4 samples of 50 subjects each. Gender distribution was homogenous in all samples. Training effects were quantified by 10 repetition maximum (10RM) and 1 repetition maximum (1RM) testing (pre-post-test design). Over a period of 6 weeks, a standardized resistance training protocol with 3 training sessions per week was realized. Testing and training included 8 resistance training exercises in a standardized order. The following loading schemes were randomly matched to each sample: constant load (CL) with constant volume of repetitions, increasing load (IL) with decreasing volume of repetitions, decreasing load (DL) with increasing volume of repetitions, daily changing load (DCL), and volume of repetitions. For all loading schemes, significant strength gains (p < 0.001) could be noted for all resistance training exercises and both dependent variables (10RM, 1RM). In all cases, DCL obtained significantly higher strength gains (p < 0.001) than CL, IL, and DL. There were no significant differences in strength gains between CL, IL, and DL. The present data indicate that resistance training following DCL is more effective for advanced recreational athletes than CL, IL, or DL. Considering that DCL is widely unknown in fitness-related resistance training, the present data indicate, there is potential for improving resistance training in commercial fitness clubs.

Effective Sequential Classifier Training for SVM-Based Multitemporal Remote Sensing Image Classification

NASA Astrophysics Data System (ADS)

Guo, Yiqing; Jia, Xiuping; Paull, David

2018-06-01

The explosive availability of remote sensing images has challenged supervised classification algorithms such as Support Vector Machines (SVM), as training samples tend to be highly limited due to the expensive and laborious task of ground truthing. The temporal correlation and spectral similarity between multitemporal images have opened up an opportunity to alleviate this problem. In this study, a SVM-based Sequential Classifier Training (SCT-SVM) approach is proposed for multitemporal remote sensing image classification. The approach leverages the classifiers of previous images to reduce the required number of training samples for the classifier training of an incoming image. For each incoming image, a rough classifier is firstly predicted based on the temporal trend of a set of previous classifiers. The predicted classifier is then fine-tuned into a more accurate position with current training samples. This approach can be applied progressively to sequential image data, with only a small number of training samples being required from each image. Experiments were conducted with Sentinel-2A multitemporal data over an agricultural area in Australia. Results showed that the proposed SCT-SVM achieved better classification accuracies compared with two state-of-the-art model transfer algorithms. When training data are insufficient, the overall classification accuracy of the incoming image was improved from 76.18% to 94.02% with the proposed SCT-SVM, compared with those obtained without the assistance from previous images. These results demonstrate that the leverage of a priori information from previous images can provide advantageous assistance for later images in multitemporal image classification.

Research and development of a field-ready protocol for sampling of phosgene from stationary source emissions: Diethylamine reagent studies. Research report, 11 July 1995--30 September 1996

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

Steger, J.L.; Bursey, J.T.; Merrill, R.G.

1999-03-01

This report presents the results of laboratory studies to develop and evaluate a method for the sampling and analysis of phosgene from stationary sources of air emissions using diethylamine (DEA) in toluene as the collection media. The method extracts stack gas from emission sources and stabilizes the reactive gas for subsequent analysis. DEA was evaluated both in a benchtop study and in a laboratory train spiking study. This report includes results for both the benchtop study and the train spiking study. Benchtop studies to evaluate the suitability of DEA for collecting and analyzing phosgene investigated five variables: storage time, DEAmore » concentration, moisture/pH, phosgene concentration, and sample storage temperature. Prototype sampling train studies were performed to determine if the benchtop chemical studies were transferable to a Modified Method 5 sampling train collecting phosgene in the presence of clean air mixed with typical stack gas components. Four conditions, which varied the moisture and phosgene spike were evaluated in triplicate. In addition to research results, the report includes a detailed draft method for sampling and analysis of phosgene from stationary source emissions.« less

Pre-Test and Post-Test Applications to Shape the Education of Phlebotomists in A Quality Management Program: An Experience in a Training Hospital

PubMed Central

Keşapli, Mustafa; Aydin, Özgür; Esen, Hatice; Yeğin, Ayşenur; Güngör, Faruk; Yilmaz, Necat

2016-01-01

Summary Background After the introduction of modern laboratory instruments and information systems, preanalytic phase is the new field of battle. Errors in preanalytical phase account for approximately half of total errors in clinical laboratory. The objective of this study was to share an experience of an education program that was believed to be successful in decreasing the number of rejected samples received from the Emergency Department (ED). Methods An education program about laboratory procedures, quality requirements in the laboratory, patient and health-care worker safety was planned by the quality team to be performed on 36 people who were responsible for sample collection in the ED. A questionary which included 11 questions about the preanalytic phase was applied to all the attendees before and after training. The number of rejected samples per million was discovered with right proportion account over the number of accepted and rejected samples to laboratory after and before the training period. Results Most of the attendees were nurses (n: 22/55%), with over 12 years of experience in general and 2–4 years experience in the ED. Knowledge level of the attendees was calculated before training as 58.9% and after training as 91.8%. While the total rate of sample rejection before training was 2.35% (sigma value 3.37–3.50), the rate after training was 1.56% (sigma value 3.62–3.75). Conclusions Increasing the knowledge of staff has a direct positive impact on the preanalytic phase. The application of a pre-test was observed to be a feasible tool to shape group specific education programs. PMID:28356887

Pre-Test and Post-Test Applications to Shape the Education of Phlebotomists in A Quality Management Program: An Experience in a Training Hospital.

PubMed

Aykal, Güzin; Keşapli, Mustafa; Aydin, Özgür; Esen, Hatice; Yeğin, Ayşenur; Güngör, Faruk; Yilmaz, Necat

2016-09-01

After the introduction of modern laboratory instruments and information systems, preanalytic phase is the new field of battle. Errors in preanalytical phase account for approximately half of total errors in clinical laboratory. The objective of this study was to share an experience of an education program that was believed to be successful in decreasing the number of rejected samples received from the Emergency Department (ED). An education program about laboratory procedures, quality requirements in the laboratory, patient and health-care worker safety was planned by the quality team to be performed on 36 people who were responsible for sample collection in the ED. A questionary which included 11 questions about the preanalytic phase was applied to all the attendees before and after training. The number of rejected samples per million was discovered with right proportion account over the number of accepted and rejected samples to laboratory after and before the training period. Most of the attendees were nurses (n: 22/55%), with over 12 years of experience in general and 2-4 years experience in the ED. Knowledge level of the attendees was calculated before training as 58.9% and after training as 91.8%. While the total rate of sample rejection before training was 2.35% (sigma value 3.37-3.50), the rate after training was 1.56% (sigma value 3.62-3.75). Increasing the knowledge of staff has a direct positive impact on the preanalytic phase. The application of a pre-test was observed to be a feasible tool to shape group specific education programs.

Fluid and Electrolyte Needs for Training, Competition, and Recovery

DTIC Science & Technology

2011-01-01

begin both training and competition in a state of fluid deficit. Analysis of samples collected from elite football ( soccer ) players before training...surprisingly, samples collected from players before a competitive game revealed that 8 of the 20 outfield players had a urine osmolality in excess of...2007) reported that basketball players attempted fewer shots and were less able to make shots linked with movement (e.g. lay-up) when dehydration had

Mining big data sets of plankton images: a zero-shot learning approach to retrieve labels without training data

NASA Astrophysics Data System (ADS)

Orenstein, E. C.; Morgado, P. M.; Peacock, E.; Sosik, H. M.; Jaffe, J. S.

2016-02-01

Technological advances in instrumentation and computing have allowed oceanographers to develop imaging systems capable of collecting extremely large data sets. With the advent of in situ plankton imaging systems, scientists must now commonly deal with "big data" sets containing tens of millions of samples spanning hundreds of classes, making manual classification untenable. Automated annotation methods are now considered to be the bottleneck between collection and interpretation. Typically, such classifiers learn to approximate a function that predicts a predefined set of classes for which a considerable amount of labeled training data is available. The requirement that the training data span all the classes of concern is problematic for plankton imaging systems since they sample such diverse, rapidly changing populations. These data sets may contain relatively rare, sparsely distributed, taxa that will not have associated training data; a classifier trained on a limited set of classes will miss these samples. The computer vision community, leveraging advances in Convolutional Neural Networks (CNNs), has recently attempted to tackle such problems using "zero-shot" object categorization methods. Under a zero-shot framework, a classifier is trained to map samples onto a set of attributes rather than a class label. These attributes can include visual and non-visual information such as what an organism is made out of, where it is distributed globally, or how it reproduces. A second stage classifier is then used to extrapolate a class. In this work, we demonstrate a zero-shot classifier, implemented with a CNN, to retrieve out-of-training-set labels from images. This method is applied to data from two continuously imaging, moored instruments: the Scripps Plankton Camera System (SPCS) and the Imaging FlowCytobot (IFCB). Results from simulated deployment scenarios indicate zero-shot classifiers could be successful at recovering samples of rare taxa in image sets. This capability will allow ecologists to identify trends in the distribution of difficult to sample organisms in their data.

Effect of a training programme on blood culture contamination rate in critical care.

PubMed

Sánchez-Sánchez, M M; Arias-Rivera, S; Fraile-Gamo, P; Jareño-Collado, R; López-Román, S; Vadillo-Obesso, P; García-González, S; Pulido-Martos, M T; Sánchez-Muñoz, E I; Cacho-Calvo, J; Martín-Pellicer, A; Panadero-Del Olmo, L; Frutos-Vivar, F

2018-03-30

Blood culture contamination can occur from extraction to processing; its rate should not exceed 3%. To evaluate the impact of a training programme on the rate of contaminated blood cultures after the implementation of sample extraction recommendations based on the best evidence. Prospective before-after study in a polyvalent intensive care unit with 18 beds. Two phases were established (January-June 2012, October 2012-October 2015) with a training period between them. Main recommendations: sterile technique, surgical mask, double skin disinfection (70° alcohol and 2% alcoholic chlorhexidine), 70° alcohol disinfection of culture flasks and injection of samples without changing needles. Including all blood cultures of patients with extraction request. demographic, severity, pathology, reason for admission, stay and results of blood cultures (negative, positive and contaminated). Basic descriptive statistics: mean (standard deviation), median (interquartile range) and percentage (95% confidence interval). Calculated contamination rates per 100 blood cultures extracted. Bivariate analysis between periods. Four hundred and eight patients were included. Eight hundred and forty-one blood cultures were taken, 33 of which were contaminated. In the demographic variables, severity, diagnosis and stay of patients with contaminated samples, no differences were observed from those with uncontaminated samples. Pre-training vs post-training contamination rates: 14 vs 5.6 per 100 blood cultures extracted (P=.00003). An evidence-based training programme reduced the contamination of samples. It is necessary to continue working on the planning of activities and care to improve the detection of pollutants and prevent contamination of samples. Copyright © 2018 Sociedad Española de Enfermería Intensiva y Unidades Coronarias (SEEIUC). Publicado por Elsevier España, S.L.U. All rights reserved.

NOAA Freedom of Information Act (FOIA) Training and Tutorials

Science.gov Websites

Commerce FOIA Program Sample Letters FOIA Training and Tutorials FOIA Training and Tutorials Welcome to the National Oceanic and Atmospheric Administration's (NOAA) Freedom of Information Act (FOIA)Training Tutorial Training Tutorial is listed alphabetically by subject, so that individuals will not have to read the entire

Support vector regression to predict porosity and permeability: Effect of sample size

NASA Astrophysics Data System (ADS)

Al-Anazi, A. F.; Gates, I. D.

2012-02-01

Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function type and loss functions used.

Occupational exposure decisions: can limited data interpretation training help improve accuracy?

PubMed

Logan, Perry; Ramachandran, Gurumurthy; Mulhausen, John; Hewett, Paul

2009-06-01

Accurate exposure assessments are critical for ensuring that potentially hazardous exposures are properly identified and controlled. The availability and accuracy of exposure assessments can determine whether resources are appropriately allocated to engineering and administrative controls, medical surveillance, personal protective equipment and other programs designed to protect workers. A desktop study was performed using videos, task information and sampling data to evaluate the accuracy and potential bias of participants' exposure judgments. Desktop exposure judgments were obtained from occupational hygienists for material handling jobs with small air sampling data sets (0-8 samples) and without the aid of computers. In addition, data interpretation tests (DITs) were administered to participants where they were asked to estimate the 95th percentile of an underlying log-normal exposure distribution from small data sets. Participants were presented with an exposure data interpretation or rule of thumb training which included a simple set of rules for estimating 95th percentiles for small data sets from a log-normal population. DIT was given to each participant before and after the rule of thumb training. Results of each DIT and qualitative and quantitative exposure judgments were compared with a reference judgment obtained through a Bayesian probabilistic analysis of the sampling data to investigate overall judgment accuracy and bias. There were a total of 4386 participant-task-chemical judgments for all data collections: 552 qualitative judgments made without sampling data and 3834 quantitative judgments with sampling data. The DITs and quantitative judgments were significantly better than random chance and much improved by the rule of thumb training. In addition, the rule of thumb training reduced the amount of bias in the DITs and quantitative judgments. The mean DIT % correct scores increased from 47 to 64% after the rule of thumb training (P < 0.001). The accuracy for quantitative desktop judgments increased from 43 to 63% correct after the rule of thumb training (P < 0.001). The rule of thumb training did not significantly impact accuracy for qualitative desktop judgments. The finding that even some simple statistical rules of thumb improve judgment accuracy significantly suggests that hygienists need to routinely use statistical tools while making exposure judgments using monitoring data.

Microscopic Analysis of Activated Sludge. Training Manual.

ERIC Educational Resources Information Center

Office of Water Program Operations (EPA), Cincinnati, OH. National Training and Operational Technology Center.

This training manual presents material on the use of a compound microscope to analyze microscope communities, present in wastewater treatment processes, for operational control. Course topics include: sampling techniques, sample handling, laboratory analysis, identification of organisms, data interpretation, and use of the compound microscope.…

Training Program Efficacy in Developing Health Life Skills among Sample Selected from Kindergarten Children

ERIC Educational Resources Information Center

Al Mohtadi, Reham Mohammad; Al Zboon, Habis Sa'ad

2017-01-01

This study drove at identifying the training program efficacy in developing the health life skills among sample selected from Kindergarten children. Study sample consisted of 60 children of both genders, ages of which are ranged from 5-6 years old. We have applied herein the pre and post dimension of health life skills scale; consisting of 28…

Irisin and exercise training in humans - results from a randomized controlled training trial.

PubMed

Hecksteden, Anne; Wegmann, Melissa; Steffen, Anke; Kraushaar, Jochen; Morsch, Arne; Ruppenthal, Sandra; Kaestner, Lars; Meyer, Tim

2013-11-05

The recent discovery of a new myokine (irisin) potentially involved in health-related training effects has gained great attention, but evidence for a training-induced increase in irisin remains preliminary. Therefore, the present study aimed to determine whether irisin concentration is increased after regular exercise training in humans. In a randomized controlled design, two guideline conforming training interventions were studied. Inclusion criteria were age 30 to 60 years, <1 hour/week regular activity, non-smoker, and absence of major diseases. 102 participants could be included in the analysis. Subjects in the training groups exercised 3 times per week for 26 weeks. The minimum compliance was defined at 70%. Aerobic endurance training (AET) consisted of 45 minutes of walking/running at 60% heart rate reserve. Strength endurance training (SET) consisted of 8 machine-based exercises (2 sets of 15 repetitions with 100% of the 20 repetition maximum). Serum irisin concentrations in frozen serum samples were determined in a single blinded measurement immediately after the end of the training study. Physical performance provided positive control for the overall efficacy of training. Differences between groups were tested for significance using analysis of variance. For post hoc comparisons with the control group, Dunnett's test was used. Maximum performance increased significantly in the training groups compared with controls (controls: ±0.0 ± 0.7 km/h; AET: 1.1 ± 0.6 km/h, P < 0.01; SET: +0.5 ± 0.7 km/h, P = 0.01). Changes in irisin did not differ between groups (controls: 101 ± 81 ng/ml; AET: 44 ± 93 ng/ml; SET: 60 ± 92 ng/ml; in both cases: P = 0.99 (one-tailed testing), 1-β error probability = 0.7). The general upward trend was mainly accounted for by a negative association of irisin concentration with the storage duration of frozen serum samples (P < 0.01, β = -0.33). After arithmetically eliminating this confounder, the differences between groups remained non-significant. A training-induced increase in circulating irisin could not be confirmed, calling into question its proposed involvement in health-related training effects. Because frozen samples are prone to irisin degradation over time, positive results from uncontrolled trials might exclusively reflect the longer storage of samples from initial tests.

System and method for resolving gamma-ray spectra

DOEpatents

Gentile, Charles A.; Perry, Jason; Langish, Stephen W.; Silber, Kenneth; Davis, William M.; Mastrovito, Dana

2010-05-04

A system for identifying radionuclide emissions is described. The system includes at least one processor for processing output signals from a radionuclide detecting device, at least one training algorithm run by the at least one processor for analyzing data derived from at least one set of known sample data from the output signals, at least one classification algorithm derived from the training algorithm for classifying unknown sample data, wherein the at least one training algorithm analyzes the at least one sample data set to derive at least one rule used by said classification algorithm for identifying at least one radionuclide emission detected by the detecting device.

Private Training Providers in Australia: Their Characteristics and Training Activities. A National Vocational Education and Training Research and Evaluation Program Report

ERIC Educational Resources Information Center

Harris, Roger; Simons, Michele; McCarthy, Carmel

2006-01-01

This study examines the nature of the training activity of private registered training organisations (RTOs) offered to Australian students in 2003, based on data from a national sample of 330 RTOs. The study also provides estimates of the private sector's overall contribution to the total vocational education and training (VET) effort in Australia…

A Review and Annotated Bibliography of Armor Gunnery Training Device Effectiveness Literature

DTIC Science & Technology

1993-11-01

training effectiveness (skill acquisition, skill reten-tion, performance prediction, transfer of training) and (b) research limitations (sample size...standalone, tank-appended, subcaliber, and laser) and four areas of training effectiveness (skill acquisition, skill retention, performance prediction, and...standalone, tank-appended, subcaliber, laser) and areas of training effectiveness (skill acquisition, skill retention, performance prediction, transfer of

Impact of auditory training for perceptual assessment of voice executed by undergraduate students in Speech-Language Pathology.

PubMed

Silva, Regiane Serafim Abreu; Simões-Zenari, Marcia; Nemr, Nair Kátia

2012-01-01

To analyze the impact of auditory training for auditory-perceptual assessment carried out by Speech-Language Pathology undergraduate students. During two semesters, 17 undergraduate students enrolled in theoretical subjects regarding phonation (Phonation/Phonation Disorders) analyzed samples of altered and unaltered voices (selected for this purpose), using the GRBAS scale. All subjects received auditory training during nine 15-minute meetings. In each meeting, a different parameter was presented using the different voices sample, with predominance of the trained aspect in each session. Sample assessment using the scale was carried out before and after training, and in other four opportunities throughout the meetings. Students' assessments were compared to an assessment carried out by three voice-experts speech-language pathologists who were the judges. To verify training effectiveness, the Friedman's test and the Kappa index were used. The rate of correct answers in the pre-training was considered between regular and good. It was observed maintenance of the number of correct answers throughout assessments, for most of the scale parameters. In the post-training moment, the students showed improvements in the analysis of asthenia, a parameter that was emphasized during training after the students reported difficulties analyzing it. There was a decrease in the number of correct answers for the roughness parameter after it was approached segmented into hoarseness and harshness, and observed in association with different diagnoses and acoustic parameters. Auditory training enhances students' initial abilities to perform the evaluation, aside from guiding adjustments in the dynamics of the university subject.

Efficient method of image edge detection based on FSVM

NASA Astrophysics Data System (ADS)

Cai, Aiping; Xiong, Xiaomei

2013-07-01

For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

Application of the Kohonen artificial neural network in the identification of proteinaceous binders in samples of panel painting using gas chromatography-mass spectrometry.

PubMed

Lletí, R; Sarabia, L A; Ortiz, M C; Todeschini, R; Colombini, M P

2003-03-01

Historically, three types of proteinaceous matter--casein, egg and animal glue--were used as binders for pigments or as adhesives in easel and wall painting. The relative percentage content of alanine, glycine, valine, leucine, isoleucine, serine, tyrosine, phenylalanine, aspartic acid, glutamic acid, lysine, methionine, proline and hydroxyproline, as determined by GC-MS, is used for binder identification. In this paper we analyse the viability of a multivariate modelling using Kohonen's neural network to characterise the wood adhesive in 16 old samples from Italian panel paintings of the 12-16th centuries. As a training set we use the amino acid composition of 141 samples contributed by the Opificio delle Pietre Dure of Florence (Cultural Heritage Ministry, Italy). Of the 141 samples, 113 were used to train the Kohonen neural network and the remaining 28 as the evaluation set. A specificity and sensitivity of 100% was achieved in training and 92-100% in prediction depending on the assignation criteria employed. The neural network thus trained and evaluated was applied to the old samples, achieving identification of all of them. In addition, the map obtained for each amino acid provides relevant information as to its importance in the characterisation of the sample.

Training set optimization under population structure in genomic selection

USDA-ARS?s Scientific Manuscript database

The optimization of the training set (TRS) in genomic selection (GS) has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the Coefficient of D...

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

EPA Science Inventory

Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

Active learning based segmentation of Crohns disease from abdominal MRI.

PubMed

Mahapatra, Dwarikanath; Vos, Franciscus M; Buhmann, Joachim M

2016-05-01

This paper proposes a novel active learning (AL) framework, and combines it with semi supervised learning (SSL) for segmenting Crohns disease (CD) tissues from abdominal magnetic resonance (MR) images. Robust fully supervised learning (FSL) based classifiers require lots of labeled data of different disease severities. Obtaining such data is time consuming and requires considerable expertise. SSL methods use a few labeled samples, and leverage the information from many unlabeled samples to train an accurate classifier. AL queries labels of most informative samples and maximizes gain from the labeling effort. Our primary contribution is in designing a query strategy that combines novel context information with classification uncertainty and feature similarity. Combining SSL and AL gives a robust segmentation method that: (1) optimally uses few labeled samples and many unlabeled samples; and (2) requires lower training time. Experimental results show our method achieves higher segmentation accuracy than FSL methods with fewer samples and reduced training effort. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Heart rate deceleration runs for postinfarction risk prediction.

PubMed

Guzik, Przemyslaw; Piskorski, Jaroslaw; Barthel, Petra; Bauer, Axel; Müller, Alexander; Junk, Nadine; Ulm, Kurt; Malik, Marek; Schmidt, Georg

2012-01-01

A method for counting episodes of uninterrupted beat-to-beat heart rate decelerations was developed. The method was set up and evaluated using 24-hour electrocardiogram Holter recordings of 1455 (training sample) and 946 (validation sample) postinfarction patients. During a median follow-up of 24 months, 70, 46, and 19 patients of the training sample suffered from total, cardiac, and sudden cardiac mortality, respectively. In the validation sample, these numbers were 39, 25, and 15. Episodes of consecutive beat-to-beat heart rate decelerations (deceleration runs [DRs]) were characterized by their length. Deceleration runs of 2 to 10 cycles were significantly less frequent in nonsurvivors. Multivariate model of DRs of 2, 4, and 8 cycles identified low-, intermediate-, and high-risk groups. In these groups of the training sample, the total mortalities were 1.8%, 6.1%, and 24%, respectively. In the validation sample, these numbers were 1.8%, 4.1%, and 21.9%. Infrequent DRs during 24-hour Holter indicate high risk of postinfarction mortality. Copyright © 2012 Elsevier Inc. All rights reserved.

Family Therapy Training in Child and Adolescent Psychiatry Fellowship Programs

ERIC Educational Resources Information Center

Rait, Douglas Samuel

2012-01-01

Objective: This study describes the current state of family therapy training in a sample of child and adolescent psychiatry fellowship programs. Method: Child and adolescent psychiatry fellows (N = 66) from seven training programs completed a questionnaire assessing demographics, family therapy training experiences, common models of treatment and…

Experience of Social Media, Training and Development on Work Proficiency: A Qualitative Study with Security Personnel

ERIC Educational Resources Information Center

Okyireh, Rexford Owusu; Okyireh, Marijke Akua Adobea

2016-01-01

How useful is social media and training programs to the development of professionals in the security sector? In this study the researchers examined three key issues pertaining to training programs. These were marketing of training programs, participant experiences of training content and work proficiency. A sample of ten participants of a forensic…

The Effect of Training on Italian Firms' Productivity: Microeconomic and Macroeconomic Perspectives

ERIC Educational Resources Information Center

Guerrazzi, Marco

2016-01-01

In this article, I explore the effect of training on the productivity of a sample of Italian firms and the impact of training on EU economic growth. Specifically, retrieving data from a survey performed by the Italian Institute for the Development of Vocational Training in 2009, I find that employer-sponsored training displays a positive and…

Level 1 environmental assessment performance evaluation. Final report jun 77-oct 78

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

Estes, E.D.; Smith, F.; Wagoner, D.E.

1979-02-01

The report gives results of a two-phased evaluation of Level 1 environmental assessment procedures. Results from Phase I, a field evaluation of the Source Assessment Sampling System (SASS), showed that the SASS train performed well within the desired factor of 3 Level 1 accuracy limit. Three sample runs were made with two SASS trains sampling simultaneously and from approximately the same sampling point in a horizontal duct. A Method-5 train was used to estimate the 'true' particulate loading. The sampling systems were upstream of the control devices to ensure collection of sufficient material for comparison of total particulate, particle sizemore » distribution, organic classes, and trace elements. Phase II consisted of providing each of three organizations with three types of control samples to challenge the spectrum of Level 1 analytical procedures: an artificial sample in methylene chloride, an artificial sample on a flyash matrix, and a real sample composed of the combined XAD-2 resin extracts from all Phase I runs. Phase II results showed that when the Level 1 analytical procedures are carefully applied, data of acceptable accuracy is obtained. Estimates of intralaboratory and interlaboratory precision are made.« less

Progressive sparse representation-based classification using local discrete cosine transform evaluation for image recognition

NASA Astrophysics Data System (ADS)

Song, Xiaoning; Feng, Zhen-Hua; Hu, Guosheng; Yang, Xibei; Yang, Jingyu; Qi, Yunsong

2015-09-01

This paper proposes a progressive sparse representation-based classification algorithm using local discrete cosine transform (DCT) evaluation to perform face recognition. Specifically, the sum of the contributions of all training samples of each subject is first taken as the contribution of this subject, then the redundant subject with the smallest contribution to the test sample is iteratively eliminated. Second, the progressive method aims at representing the test sample as a linear combination of all the remaining training samples, by which the representation capability of each training sample is exploited to determine the optimal "nearest neighbors" for the test sample. Third, the transformed DCT evaluation is constructed to measure the similarity between the test sample and each local training sample using cosine distance metrics in the DCT domain. The final goal of the proposed method is to determine an optimal weighted sum of nearest neighbors that are obtained under the local correlative degree evaluation, which is approximately equal to the test sample, and we can use this weighted linear combination to perform robust classification. Experimental results conducted on the ORL database of faces (created by the Olivetti Research Laboratory in Cambridge), the FERET face database (managed by the Defense Advanced Research Projects Agency and the National Institute of Standards and Technology), AR face database (created by Aleix Martinez and Robert Benavente in the Computer Vision Center at U.A.B), and USPS handwritten digit database (gathered at the Center of Excellence in Document Analysis and Recognition at SUNY Buffalo) demonstrate the effectiveness of the proposed method.

The effectiveness of empowering in-service training programs for foreign nurse aides in community-based long-term care facilities.

PubMed

Wu, Li-yu; Yin, Teresa J C; Li, I-chuan

2005-01-01

The objective of the study was to examine the effectiveness of empowering in-service training programs for foreign nurse aides working in community-based long-term care (LTC) facilities. The design was a pretest and post-test design with experiment and control groups. The sample consisted of purposeful sampling from 10 LTC facilities in the Shihlin and Peitou areas of Taipei. A total of 35 foreign nurse aides participated in this study; 16 in the experimental group and 19 in the control group. The experimental group attended the training program for a 3-month period, whereas the control group did not receive any training. The research findings reveal that the training program was effective in increasing the work stress of workload/scheduling (Z = 2.01, p

The influence of staff training on challenging behaviour in individuals with intellectual disability: a review.

PubMed

Cox, Alison D; Dube, Charmayne; Temple, Beverley

2015-03-01

Many individuals with intellectual disability engage in challenging behaviour. This can significantly limit quality of life and also negatively impact caregivers (e.g., direct care staff, family caregivers and teachers). Fortunately, efficacious staff training may alleviate some negative side effects of client challenging behaviour. Currently, a systematic review of studies evaluating whether staff training influences client challenging behaviour has not been conducted. The purpose of this article was to identify emerging patterns, knowledge gaps and make recommendations for future research on this topic. The literature search resulted in a total of 19 studies that met our inclusion criteria. Articles were separated into four staff training categories. Studies varied across sample size, support staff involved in training, study design, training duration and data collection strategy. A small sample size (n = 19) and few replication studies, alongside several other procedural limitations prohibited the identification of a best practice training approach. © The Author(s) 2014.

Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification

NASA Astrophysics Data System (ADS)

Huang, Jian; Liu, Gui-xiong

2016-09-01

The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm ( k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z ' if T z ' was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.

Building Extraction Based on an Optimized Stacked Sparse Autoencoder of Structure and Training Samples Using LIDAR DSM and Optical Images.

PubMed

Yan, Yiming; Tan, Zhichao; Su, Nan; Zhao, Chunhui

2017-08-24

In this paper, a building extraction method is proposed based on a stacked sparse autoencoder with an optimized structure and training samples. Building extraction plays an important role in urban construction and planning. However, some negative effects will reduce the accuracy of extraction, such as exceeding resolution, bad correction and terrain influence. Data collected by multiple sensors, as light detection and ranging (LIDAR), optical sensor etc., are used to improve the extraction. Using digital surface model (DSM) obtained from LIDAR data and optical images, traditional method can improve the extraction effect to a certain extent, but there are some defects in feature extraction. Since stacked sparse autoencoder (SSAE) neural network can learn the essential characteristics of the data in depth, SSAE was employed to extract buildings from the combined DSM data and optical image. A better setting strategy of SSAE network structure is given, and an idea of setting the number and proportion of training samples for better training of SSAE was presented. The optical data and DSM were combined as input of the optimized SSAE, and after training by an optimized samples, the appropriate network structure can extract buildings with great accuracy and has good robustness.

Feasibility and Efficacy of Brief Computerized Training to Improve Emotion Recognition in Premanifest and Early-Symptomatic Huntington's Disease.

PubMed

Kempnich, Clare L; Wong, Dana; Georgiou-Karistianis, Nellie; Stout, Julie C

2017-04-01

Deficits in the recognition of negative emotions emerge before clinical diagnosis in Huntington's disease (HD). To address emotion recognition deficits, which have been shown in schizophrenia to be improved by computerized training, we conducted a study of the feasibility and efficacy of computerized training of emotion recognition in HD. We randomly assigned 22 individuals with premanifest or early symptomatic HD to the training or control group. The training group used a self-guided online training program, MicroExpression Training Tool (METT), twice weekly for 4 weeks. All participants completed measures of emotion recognition at baseline and post-training time-points. Participants in the training group also completed training adherence measures. Participants in the training group completed seven of the eight sessions on average. Results showed a significant group by time interaction, indicating that METT training was associated with improved accuracy in emotion recognition. Although sample size was small, our study demonstrates that emotion recognition remediation using the METT is feasible in terms of training adherence. The evidence also suggests METT may be effective in premanifest or early-symptomatic HD, opening up a potential new avenue for intervention. Further study with a larger sample size is needed to replicate these findings, and to characterize the durability and generalizability of these improvements, and their impact on functional outcomes in HD. (JINS, 2017, 23, 314-321).

Training effect of the exchange bias in sputter deposited Fe3O4 thin films with varying thickness

NASA Astrophysics Data System (ADS)

Muhammed Shameem, P. V.; Senthil Kumar, M.

2018-07-01

The training effect property of the exchange bias in the reactively sputtered polycrystalline Fe3O4 thin films of varying thicknesses in the range 25-200 nm are studied. Structural studies by X-ray diffraction, X-ray photoelectron spectroscopy and selected area electron diffraction confirm the formation of single phase Fe3O4. The scanning electron spectroscopy images show that the grains are uniformly distributed. All the samples show clear and consistent exchange bias training behaviour due to the dynamics of the spins at the interface of the ferrimagnetic core and the spin glass-like surface of the grains. The analysis of the training effect data of the exchange bias field HE measured at 2 K by using three different models show that the model based on the relaxation of the frozen and rotatable spin components at the interface gives the best description for all the samples. From this model, it is found that the reversible interface spins relax around 7 times faster than the frozen interface spins at 2 K for all the samples and that their relative relaxation rates are independent of the sample thickness. This constancy show that the relative relaxation rates of the interfacial frozen and rotatable spin components is a material dependent property. The frozen component of the interfacial spins of each sample is found to be dominated at the initial stage of the training. A direct equivalence between the HE and remanence asymmetry ME is observed. Above the spin freezing temperature, the training effect measurements at 75 K show that the HE decreases sharply with successive field cycling as compared to the measurements made at 2 K and the HE vanishes after first few cycles.

Collaborative Job Training in Rural Areas

ERIC Educational Resources Information Center

Green, Gary Paul; Galetto, Valeria; Haines, Anna

2003-01-01

We examine collaborative efforts by employers to provide job training in rural areas and assess how this collaboration affects the willingness of employers to train workers. Data are drawn from a telephone survey conducted in 2001 of a stratified random sample of 1,590 nonmetropolitan firms in the U.S. The literature on job training suggests that…

A Model of the Antecedents of Training Transfer

ERIC Educational Resources Information Center

Mohammed Turab, Ghaneemah; Casimir, Gian

2015-01-01

Many organizations have invested heavily in training. However, only a small percentage of what is learnt from training is applied or transferred to the workplace. This study examines factors that influence training transfer. A conceptual model based on the Theory of Reasoned Action is hypothesized and tested. The sample consisted of 123 full-time…

A Study of Best Practices in Training Transfer and Proposed Model of Transfer

ERIC Educational Resources Information Center

Burke, Lisa A.; Hutchins, Holly M.

2008-01-01

Data were gathered from a sample of training professionals of an American Society of Training and Development (ASTD) chapter in the southern United States regarding best practices for supporting training transfer. Content analysis techniques, based on a rigorous methodology proposed by Insch, Moore, & Murphy (1997), were used to analyze the…

How iSamples (Internet of Samples in the Earth Sciences) Improves Sample and Data Stewardship in the Next Generation of Geoscientists

NASA Astrophysics Data System (ADS)

Hallett, B. W.; Dere, A. L. D.; Lehnert, K.; Carter, M.

2016-12-01

Vast numbers of physical samples are routinely collected by geoscientists to probe key scientific questions related to global climate change, biogeochemical cycles, magmatic processes, mantle dynamics, etc. Despite their value as irreplaceable records of nature the majority of these samples remain undiscoverable by the broader scientific community because they lack a digital presence or are not well-documented enough to facilitate their discovery and reuse for future scientific and educational use. The NSF EarthCube iSamples Research Coordination Network seeks to develop a unified approach across all Earth Science disciplines for the registration, description, identification, and citation of physical specimens in order to take advantage of the new opportunities that cyberinfrastructure offers. Even as consensus around best practices begins to emerge, such as the use of the International Geo Sample Number (IGSN), more work is needed to communicate these practices to investigators to encourage widespread adoption. Recognizing the importance of students and early career scientists in particular to transforming data and sample management practices, the iSamples Education and Training Working Group is developing training modules for sample collection, documentation, and management workflows. These training materials are made available to educators/research supervisors online at http://earthcube.org/group/isamples and can be modularized for supervisors to create a customized research workflow. This study details the design and development of several sample management tutorials, created by early career scientists and documented in collaboration with undergraduate research students in field and lab settings. Modules under development focus on rock outcrops, rock cores, soil cores, and coral samples, with an emphasis on sample management throughout the collection, analysis and archiving process. We invite others to share their sample management/registration workflows and to develop training modules. This educational approach, with evolving digital materials, can help prepare future scientists to perform research in a way that will contribute to EarthCube data integration and discovery.

Comparison of Hybrid Classifiers for Crop Classification Using Normalized Difference Vegetation Index Time Series: A Case Study for Major Crops in North Xinjiang, China

PubMed Central

Hao, Pengyu; Wang, Li; Niu, Zheng

2015-01-01

A range of single classifiers have been proposed to classify crop types using time series vegetation indices, and hybrid classifiers are used to improve discriminatory power. Traditional fusion rules use the product of multi-single classifiers, but that strategy cannot integrate the classification output of machine learning classifiers. In this research, the performance of two hybrid strategies, multiple voting (M-voting) and probabilistic fusion (P-fusion), for crop classification using NDVI time series were tested with different training sample sizes at both pixel and object levels, and two representative counties in north Xinjiang were selected as study area. The single classifiers employed in this research included Random Forest (RF), Support Vector Machine (SVM), and See 5 (C 5.0). The results indicated that classification performance improved (increased the mean overall accuracy by 5%~10%, and reduced standard deviation of overall accuracy by around 1%) substantially with the training sample number, and when the training sample size was small (50 or 100 training samples), hybrid classifiers substantially outperformed single classifiers with higher mean overall accuracy (1%~2%). However, when abundant training samples (4,000) were employed, single classifiers could achieve good classification accuracy, and all classifiers obtained similar performances. Additionally, although object-based classification did not improve accuracy, it resulted in greater visual appeal, especially in study areas with a heterogeneous cropping pattern. PMID:26360597

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

A New Measurement of On-the-Job Training: The Determination and Effect of Training.

ERIC Educational Resources Information Center

Cline, Harold Michael

A study examined the types of individuals receiving on-the-job-training and the effect of such training on productivity and earnings. Two years of data from the Michigan Panel Study of Income Dynamics (an 11-year longitudinal study with a sample size of about 200 individuals) concerning the on-the-job-training, labor market experience, and income…

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

NASA Technical Reports Server (NTRS)

Morris, Richard; Anderson, R.; Clegg, S. M.; Bell, J. F., III

2010-01-01

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Extensive monitoring through multiple blood samples in professional soccer players.

PubMed

Heisterberg, Mette F; Fahrenkrug, Jan; Krustrup, Peter; Storskov, Anders; Kjær, Michael; Andersen, Jesper L

2013-05-01

The aim of this study was to make a comprehensive gathering of consecutive detailed blood samples from professional soccer players and to analyze different blood parameters in relation to seasonal changes in training and match exposure. Blood samples were collected 5 times during a 6-month period and analyzed for 37 variables in 27 professional soccer players from the best Danish league. Additionally, the players were tested for body composition, V[Combining Dot Above]O2max and physical performance by the Yo-Yo intermittent endurance submax test (IE2). Multiple variations in blood parameters occurred during the observation period, including a decrease in hemoglobin and an increase in hematocrit as the competitive season progressed. Iron and transferrin were stable, whereas ferritin showed a decrease at the end of the season. The immunoglobulin A (IgA) and IgM increased in the period with basal physical training and at the end of the season. Leucocytes decreased with increased physical training. Lymphocytes decreased at the end of the season. The V[Combining Dot Above]O2max decreased toward the end of the season, whereas no significant changes were observed in the IE2 test. The regular blood samples from elite soccer players reveal significant changes that may be related to changes in training pattern, match exposure, or length of the match season. Especially the end of the preparation season and at the end of the competitive season seem to be time points were the blood-derived values indicate that the players are under excessive physical strain and might be more subjected to a possible overreaching-overtraining conditions. We suggest that regular analyses of blood samples could be an important initiative to optimize training adaptation, training load, and game participation, but sampling has to be regular, and a database has to be built for each individual player.

Microbiological quality of food in relation to hazard analysis systems and food hygiene training in UK catering and retail premises.

PubMed

Little, C L; Lock, D; Barnes, J; Mitchell, R T

2003-09-01

A meta-analysis of eight UK food studies was carried out to determine the microbiological quality of food and its relationship with the presence in food businesses of hazard analysis systems and food hygiene training. Of the 19,022 premises visited to collect food samples in these studies between 1997 and 2002, two thirds (66%) were catering premises and one third (34%) were retail premises. Comparison with PHLS Microbiological Guidelines revealed that significantly more ready-to-eat food samples from catering premises (20%; 2,511/12,703) were of unsatisfactory or unacceptable microbiological quality compared to samples from retail premises (12%; 1,039/8,462) (p < 0.00001). Three quarters (76%) of retail premises had hazard analysis systems in place compared with 59% of catering premises (p < 0.00001). In 87% of retail premises the manager had received some form of food hygiene training compared with 80% of catering premises (p < 0.00001). From premises where the manager had received no food hygiene training a greater proportion of samples were of unsatisfactory and unacceptable microbiological quality (20% retail, 27% catering) compared with premises where the manager had received food hygiene training (11% retail, 19% catering) (p < 0.00001). Where the manager of the premises had received food hygiene training, documented hazard analysis systems were more likely to be in place (p < 0.00001). Higher proportions of samples of unsatisfactory and unacceptable microbiological quality (17% retail, 22% catering) were from premises where there was no hazard analysis system in place compared to premises that had a documented hazard analysis system in place (10% retail, 18% catering) (p < 0.00001). Our meta-analysis suggests that the lower microbiological quality of ready-to-eat foods from catering premises compared with those collected from retail premises may reflect differences in management food hygiene training and the presence of a hazard analysis system. The importance of adequate training for food handlers and their managers as a pre-requisite for effective hazard analysis and critical control point (HACCP) based controls is therefore emphasised.

An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition.

PubMed

Niu, Li; Li, Wen; Xu, Dong; Cai, Jianfei

2018-02-01

In this paper, we propose a new exemplar-based multi-view domain generalization (EMVDG) framework for visual recognition by learning robust classifier that are able to generalize well to arbitrary target domain based on the training samples with multiple types of features (i.e., multi-view features). In this framework, we aim to address two issues simultaneously. First, the distribution of training samples (i.e., the source domain) is often considerably different from that of testing samples (i.e., the target domain), so the performance of the classifiers learnt on the source domain may drop significantly on the target domain. Moreover, the testing data are often unseen during the training procedure. Second, when the training data are associated with multi-view features, the recognition performance can be further improved by exploiting the relation among multiple types of features. To address the first issue, considering that it has been shown that fusing multiple SVM classifiers can enhance the domain generalization ability, we build our EMVDG framework upon exemplar SVMs (ESVMs), in which a set of ESVM classifiers are learnt with each one trained based on one positive training sample and all the negative training samples. When the source domain contains multiple latent domains, the learnt ESVM classifiers are expected to be grouped into multiple clusters. To address the second issue, we propose two approaches under the EMVDG framework based on the consensus principle and the complementary principle, respectively. Specifically, we propose an EMVDG_CO method by adding a co-regularizer to enforce the cluster structures of ESVM classifiers on different views to be consistent based on the consensus principle. Inspired by multiple kernel learning, we also propose another EMVDG_MK method by fusing the ESVM classifiers from different views based on the complementary principle. In addition, we further extend our EMVDG framework to exemplar-based multi-view domain adaptation (EMVDA) framework when the unlabeled target domain data are available during the training procedure. The effectiveness of our EMVDG and EMVDA frameworks for visual recognition is clearly demonstrated by comprehensive experiments on three benchmark data sets.

Measurement of trained speech patterns in stuttering: interjudge and intrajudge agreement of experts by means of modified time-interval analysis.

PubMed

Alpermann, Anke; Huber, Walter; Natke, Ulrich; Willmes, Klaus

2010-09-01

Improved fluency after stuttering therapy is usually measured by the percentage of stuttered syllables. However, outcome studies rarely evaluate the use of trained speech patterns that speakers use to manage stuttering. This study investigated whether the modified time interval analysis can distinguish between trained speech patterns, fluent speech, and stuttered speech. Seventeen German experts on stuttering judged a speech sample on two occasions. Speakers of the sample were stuttering adults, who were not undergoing therapy, as well as participants in a fluency shaping and a stuttering modification therapy. Results showed satisfactory inter-judge and intra-judge agreement above 80%. Intervals with trained speech patterns were identified as consistently as stuttered and fluent intervals. We discuss limitations of the study, as well as implications of our findings for the development of training for identification of trained speech patterns and future outcome studies. The reader will be able to (a) explain different methods to measure the use of trained speech patterns, (b) evaluate whether German experts are able to discriminate intervals with trained speech patterns reliably from fluent and stuttered intervals and (c) describe how the measurement of trained speech patterns can contribute to outcome studies.

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

Machine learning from computer simulations with applications in rail vehicle dynamics

NASA Astrophysics Data System (ADS)

Taheri, Mehdi; Ahmadian, Mehdi

2016-05-01

The application of stochastic modelling for learning the behaviour of a multibody dynamics (MBD) models is investigated. Post-processing data from a simulation run are used to train the stochastic model that estimates the relationship between model inputs (suspension relative displacement and velocity) and the output (sum of suspension forces). The stochastic model can be used to reduce the computational burden of the MBD model by replacing a computationally expensive subsystem in the model (suspension subsystem). With minor changes, the stochastic modelling technique is able to learn the behaviour of a physical system and integrate its behaviour within MBD models. The technique is highly advantageous for MBD models where real-time simulations are necessary, or with models that have a large number of repeated substructures, e.g. modelling a train with a large number of railcars. The fact that the training data are acquired prior to the development of the stochastic model discards the conventional sampling plan strategies like Latin Hypercube sampling plans where simulations are performed using the inputs dictated by the sampling plan. Since the sampling plan greatly influences the overall accuracy and efficiency of the stochastic predictions, a sampling plan suitable for the process is developed where the most space-filling subset of the acquired data with ? number of sample points that best describes the dynamic behaviour of the system under study is selected as the training data.

Assessing the readability of thirty-nine behavior-modification training manuals and primers

PubMed Central

Andrasik, Frank; Murphy, William D.

1977-01-01

Thirty-nine behavior-modification training manuals and primers, sampling various topical areas, were subjected to a readability analysis. Reading-ease scores were computed by the formula developed by Flesch. The texts sampled ranged from very difficult (appropriate for college graduates) to fairly easy (appropriate for readers at the seventh-grade level). PMID:16795559

Training Needs of Governmental Schools' Principals Hosting Kindergartens Classes: The Case for Jordan

ERIC Educational Resources Information Center

Ashraah, Mamdouh M.; Al-Olaimat, Ali M.; Takash, Hanan M.

2015-01-01

This study aimed at identifying the training needs of governmental schools' principals with kindergarten classes. The sample of the study consisted of a random sample of (62) female principal. The instrument of the study was developed by the researchers and included 60 items distributed on four domains (planning, organizing, guidance, and…

A Development of Participation of Primary School Students in Conservation of School Environments

ERIC Educational Resources Information Center

Klongyut, Somsak; Singseewo, Adisak; Suksringarm, Paitool

2015-01-01

This study aimed to investigate and compare knowledge, attitudes and participating behaviors of students who participated in a training session. A training manual based on the participatory process was used. The sample consisted of 30 grade 5 students and 30 grade 6 students using a voluntary sampling technique. Research instruments included 1) a…

Attitudes of a Sample of English, Maltese and German Teachers towards Media Education

ERIC Educational Resources Information Center

Lauri, M. A.; Borg, J.; Gunnel, T.; Gillum, R.

2010-01-01

Media education forms part of the National Minimum Curriculum of England, Malta and Germany. Teacher training courses differ greatly in how teachers are prepared to teach media education. In this paper we shall investigate the attitudes of a sample of teachers trained in England, Malta and in Germany towards their perceived importance of media…

Testing Response-Stimulus Equivalence Relations Using Differential Responses as a Sample

ERIC Educational Resources Information Center

Shimizu, Hirofumi

2006-01-01

This study tested the notion that an equivalence relation may include a response when differential responses are paired with stimuli presented during training. Eight normal adults learned three kinds of computer mouse movements as differential response topographies (R1, R2, and R3). Next, in matching-to-sample training, one of the response…

A Comparison of Momentary Time Sampling and Partial-Interval Recording for Assessment of Effects of Social Skills Training

ERIC Educational Resources Information Center

Radley, Keith C.; O'Handley, Roderick D.; Labrot, Zachary C.

2015-01-01

Assessment in social skills training often utilizes procedures such as partial-interval recording (PIR) and momentary time sampling (MTS) to estimate changes in duration in social engagements due to intervention. Although previous research suggests PIR to be more inaccurate than MTS in estimating levels of behavior, treatment analysis decisions…

Calibrating a Respirable Dust Sampling Device. Module 24. Vocational Education Training in Environmental Health Sciences.

ERIC Educational Resources Information Center

Consumer Dynamics Inc., Rockville, MD.

This module, one of 25 on vocational education training for careers in environmental health occupations, contains self-instructional materials on calibrating a respirable dust sampling device. Following guidelines for students and instructors and an introduction that explains what the student will learn, are three lessons: (1) naming each part of…

AN INVESTIGATION OF THE TRAINING AND SKILL REQUIREMENTS OF INDUSTRIAL MACHINERY MAINTENANCE WORKERS. VOLUME II. FINAL REPORT.

ERIC Educational Resources Information Center

LYNN, FRANK

THE APPENDIXES FOR "AN INVESTIGATION OF THE TRAINING AND SKILL REQUIREMENTS OF INDUSTRIAL MACHINERY MAINTENANCE WORKERS, FINAL REPORT, VOLUME I" (VT 004 006) INCLUDE (1) TWO LETTERS FROM PLANT ENGINEERS STRESSING THE IMPORTANCE OF TRAINING MACHINERY MAINTENANCE WORKERS, (2) A DESCRIPTION OF THE MAINTENANCE TRAINING SURVEY, A SAMPLE QUESTIONNAIRE,…

Go/No-Go Procedure with Compound Stimuli: Effects of Training Structure on the Emergence of Equivalence Classes

ERIC Educational Resources Information Center

Grisante, Priscila C.; Galesi, Fernanda L.; Sabino, Nathali M.; Debert, Paula; Arntzen, Erik; McIlvane, William J.

2013-01-01

When the matching-to-sample (MTS) procedure is used, different training structures imply differences in the successive discriminations required in training and test conditions. When the go/no-go procedure with compound stimuli is used, however, differences in training structures do not imply such differences. This study assessed whether the…

Response of School Personnel to Student Threat Assessment Training

ERIC Educational Resources Information Center

Allen, Korrie; Cornell, Dewey; Lorek, Edward; Sheras, Peter

2008-01-01

School safety has become an important area of concern for school improvement. This study examined the effects of staff training as means of improving school responses to student threats of violence. A multidisciplinary sample of 351 staff from 2 school divisions completed pre-post training surveys as part of a 1-day training program using the…

Professional Profile of National Health Service Physicians in Greece and Their Self-Expressed Training Needs

ERIC Educational Resources Information Center

Kyriopoulos, John; Gregory, Susan; Georgoussi, Eugenia; Dolgeras, Apostolos

2003-01-01

Introduction: Continuing medical education is not yet mandatory in Greece, but an increasing number of training courses is becoming available. In recent years, 32 training centers have been accredited. Method: A postal survey of a national sample of 500 National Health Service doctors, weighted toward hospitals with accredited training centers,…

Persistence in the Determination of Work-Related Training Participation: Evidence from the BHPS, 1991-1997

ERIC Educational Resources Information Center

Sousounis, Panos; Bladen-Hovell, Robin

2010-01-01

In this paper we investigate the role of workers' training history in determining current training-incidence. The analysis is conducted on an unbalanced sample comprising information on approximately 5000 employees from the first seven waves of the BHPS. Training participation is modelled as a dynamic random effects probit model where the effects…

Does Vocational Training Matter for Young Adults in the Labour Market?

ERIC Educational Resources Information Center

Murray, Asa; Skarlind, Anders

2005-01-01

The impact of vocational training on employment and income is investigated for young adults. Young adults without further education and training are compared to young adults with two-years and young adults with three-years of vocational training. The sample consists of 41 000 Swedish young adults born in 1974. The employment of these young adults…

Explosive detection using high-volume vapor sampling and analysis by trained canines and ultra-trace detection equipment

NASA Astrophysics Data System (ADS)

Fisher, Mark; Sikes, John; Prather, Mark

2004-09-01

The dog's nose is an effective, highly-mobile sampling system, while the canine olfactory organs are an extremely sensitive detector. Having been trained to detect a wide variety of substances with exceptional results, canines are widely regarded as the 'gold standard' in chemical vapor detection. Historically, attempts to mimic the ability of dogs to detect vapors of explosives using electronic 'dogs noses' has proven difficult. However, recent advances in technology have resulted in development of detection (i.e., sampling and sensor) systems with performance that is rapidly approaching that of trained canines. The Nomadics Fido was the first sensor to demonstrate under field conditions the detection of landmines with performance approaching that of canines. More recently, comparative testing of Fido against canines has revealed that electronic vapor detection, when coupled with effective sampling methods, can produce results comparable to that of highly-trained canines. The results of these comparative tests will be presented, as will recent test results in which explosives hidden in cargo were detected using Fido with a high-volume sampling technique. Finally, the use of canines along with electronic sensors will be discussed as a means of improving the performance and expanding the capabilities of both methods.

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

Strong Selection at MHC in Mexicans since Admixture

PubMed Central

Zhou, Quan; Zhao, Liang; Guan, Yongtao

2016-01-01

Mexicans are a recent admixture of Amerindians, Europeans, and Africans. We performed local ancestry analysis of Mexican samples from two genome-wide association studies obtained from dbGaP, and discovered that at the MHC region Mexicans have excessive African ancestral alleles compared to the rest of the genome, which is the hallmark of recent selection for admixed samples. The estimated selection coefficients are 0.05 and 0.07 for two datasets, which put our finding among the strongest known selections observed in humans, namely, lactase selection in northern Europeans and sickle-cell trait in Africans. Using inaccurate Amerindian training samples was a major concern for the credibility of previously reported selection signals in Latinos. Taking advantage of the flexibility of our statistical model, we devised a model fitting technique that can learn Amerindian ancestral haplotype from the admixed samples, which allows us to infer local ancestries for Mexicans using only European and African training samples. The strong selection signal at the MHC remains without Amerindian training samples. Finally, we note that medical history studies suggest such a strong selection at MHC is plausible in Mexicans. PMID:26863142

Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error

PubMed Central

Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

2013-01-01

A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation. PMID:23878526

Analogical reasoning in amazons.

PubMed

Obozova, Tanya; Smirnova, Anna; Zorina, Zoya; Wasserman, Edward

2015-11-01

Two juvenile orange-winged amazons (Amazona amazonica) were initially trained to match visual stimuli by color, shape, and number of items, but not by size. After learning these three identity matching-to-sample tasks, the parrots transferred discriminative responding to new stimuli from the same categories that had been used in training (other colors, shapes, and numbers of items) as well as to stimuli from a different category (stimuli varying in size). In the critical testing phase, both parrots exhibited reliable relational matching-to-sample (RMTS) behavior, suggesting that they perceived and compared the relationship between objects in the sample stimulus pair to the relationship between objects in the comparison stimulus pairs, even though no physical matches were possible between items in the sample and comparison pairs. The parrots spontaneously exhibited this higher-order relational responding without having ever before been trained on RMTS tasks, therefore joining apes and crows in displaying this abstract cognitive behavior.

Investigation of the Effluents Produced during the Functioning of Black and White Colored Smoke Devices.

DTIC Science & Technology

1986-01-31

and 4% diatomaceous earth (binder). Modified EPA Method 5 Sampling Train F The modified EPA Method 5 sampling train used was similar to the one...the fiber glass filter paper were taken by the Amberlite XAD-2. The XAD-2 is a porous polymer adsorbent used to sample organic vapors in effluents...from different kinds of combustion processes. Although a careful clean-up procedure was taken to wash the adsorbents before using, the polymer may still

Hydration status in adolescent runners: pre and post training

NASA Astrophysics Data System (ADS)

Ashadi, K.; Mirza, D. N.; Siantoro, G.

2018-01-01

The adequacy of body fluids is important for athletes in supporting performance. The purpose of this research was to determine the hydration status of athletes before and after training. The study was a qualitative descriptive by using random sampling. All athletes were trained for approximately 60 minutes. And they were asked to analyze their body fluid pattern routinely. Data were obtained through urine color measurement. The urinary was taken at pre and post training and was immediately assessed in the afternoon. Based on pre-training urine samples, a mean of urine color scale was 3.1 point. It meant that only 31.2% of the athletes were in dehydrated condition. However, after exercising, urine color index showed scale 4.1. And 62.5% of the athletes experienced dehydration. The results showed that there was a significant change in hydration level before and after training. It can be concluded that training for a long time increases the risk of dehydration. It is important for athletes to meet the needs of body fluids in order to avoid functional impairment in the body during sports activities.

A model for addressing navigation limitations and metacognitive constraints in hypermedia training systems

NASA Technical Reports Server (NTRS)

Freedman, Glenn B.

1990-01-01

A model for addressing navigation limitations and metacognitive constraints in hypermedia training systems is presented in the form of the viewgraphs. The following subject areas are covered: samples of software and people problems; system design; and hypermedia training system.

Multicultural Training Experiences as Predictors of Multicultural Competencies: Students' Perspectives

ERIC Educational Resources Information Center

Dickson, Ginger L.; Jepsen, David A.

2007-01-01

The authors surveyed a national sample of master's-level counseling students regarding their multicultural training experiences and their multicultural counseling competencies. A series of hierarchical regression models tested the prediction of inventoried competencies from measures of selected training experiences: (a) program cultural ambience…

Improving working memory in children with low language abilities

PubMed Central

Holmes, Joni; Butterfield, Sally; Cormack, Francesca; van Loenhoud, Anita; Ruggero, Leanne; Kashikar, Linda; Gathercole, Susan

2015-01-01

This study investigated whether working memory training is effective in enhancing verbal memory in children with low language abilities (LLA). Cogmed Working Memory Training was completed by a community sample of children aged 8–11 years with LLA and a comparison group with matched non-verbal abilities and age-typical language performance. Short-term memory (STM), working memory, language, and IQ were assessed before and after training. Significant and equivalent post-training gains were found in visuo-spatial short-term memory in both groups. Exploratory analyses across the sample established that low verbal IQ scores were strongly and highly specifically associated with greater gains in verbal STM, and that children with higher verbal IQs made greater gains in visuo-spatial short-term memory following training. This provides preliminary evidence that intensive working memory training may be effective for enhancing the weakest aspects of STM in children with low verbal abilities, and may also be of value in developing compensatory strategies. PMID:25983703

Family Carers and the Prevention of Heroin Overdose Deaths: Unmet Training Need and Overlooked Intervention Opportunity of Resuscitation Training and Supply of Naloxone

ERIC Educational Resources Information Center

Strang, John; Manning, Victoria; Mayet, Soraya; Titherington, Emily; Offor, Liz; Semmler, Claudia; Williams, Anna

2008-01-01

Aim: To assess (a) carers' experiences of witnessing overdose; (b) their training needs; and (c) their interest in receiving training in overdose management. Design: Postal questionnaire distributed through consenting participating local carer group coordinators in England. Sample: 147 carers attending local support groups for friends and families…

Training sample selection based on self-training for liver cirrhosis classification using ultrasound images

NASA Astrophysics Data System (ADS)

Fujita, Yusuke; Mitani, Yoshihiro; Hamamoto, Yoshihiko; Segawa, Makoto; Terai, Shuji; Sakaida, Isao

2017-03-01

Ultrasound imaging is a popular and non-invasive tool used in the diagnoses of liver disease. Cirrhosis is a chronic liver disease and it can advance to liver cancer. Early detection and appropriate treatment are crucial to prevent liver cancer. However, ultrasound image analysis is very challenging, because of the low signal-to-noise ratio of ultrasound images. To achieve the higher classification performance, selection of training regions of interest (ROIs) is very important that effect to classification accuracy. The purpose of our study is cirrhosis detection with high accuracy using liver ultrasound images. In our previous works, training ROI selection by MILBoost and multiple-ROI classification based on the product rule had been proposed, to achieve high classification performance. In this article, we propose self-training method to select training ROIs effectively. Evaluation experiments were performed to evaluate effect of self-training, using manually selected ROIs and also automatically selected ROIs. Experimental results show that self-training for manually selected ROIs achieved higher classification performance than other approaches, including our conventional methods. The manually ROI definition and sample selection are important to improve classification accuracy in cirrhosis detection using ultrasound images.

Co-Labeling for Multi-View Weakly Labeled Learning.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi-view datasets clearly demonstrate that our proposed co-labeling approach achieves state-of-the-art performance for various multi-view weakly labeled learning problems including multi-view SSL, multi-view MIL and multi-view ROD.

Skills Acquisition in Plantain Flour Processing Enterprises: A Validation of Training Modules for Senior Secondary Schools

ERIC Educational Resources Information Center

Udofia, Nsikak-Abasi; Nlebem, Bernard S.

2013-01-01

This study was to validate training modules that can help provide requisite skills for Senior Secondary school students in plantain flour processing enterprises for self-employment and to enable them pass their examination. The study covered Rivers State. Purposive sampling technique was used to select a sample size of 205. Two sets of structured…

Training Valence, Instrumentality, and Expectancy Scale (T-VIES-it): Factor Structure and Nomological Network in an Italian Sample

ERIC Educational Resources Information Center

Zaniboni, Sara; Fraccaroli, Franco; Truxillo, Donald M.; Bertolino, Marilena; Bauer, Talya N.

2011-01-01

Purpose: The purpose of this study is to validate, in an Italian sample, a multidimensional training motivation measure (T-VIES-it) based on expectancy (VIE) theory, and to examine the nomological network surrounding the construct. Design/methodology/approach: Using a cross-sectional design study, 258 public sector employees in Northeast Italy…

Training, Wages, and the Human Capital Model. National Longitudinal Surveys Discussion Paper.

ERIC Educational Resources Information Center

Veum, Jonathan R.

Recent data from the National Longitudinal Survey of Youth (NLSY) were used to examine the validity of the traditional human capital model, which predicts that training lowers starting wages and increases wage growth. The primary data sample was restricted to those 4,309 members of the NLSY sample who were working for pay and not enrolled in…

A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network

PubMed Central

Ahmed, Afaz Uddin; Tariqul Islam, Mohammad; Ismail, Mahamod; Kibria, Salehin; Arshad, Haslina

2014-01-01

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle. The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation. PMID:25133214

A novel user classification method for femtocell network by using affinity propagation algorithm and artificial neural network.

PubMed

Ahmed, Afaz Uddin; Islam, Mohammad Tariqul; Ismail, Mahamod; Kibria, Salehin; Arshad, Haslina

2014-01-01

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle. The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation.

Training of polyp staging systems using mixed imaging modalities.

PubMed

Wimmer, Georg; Gadermayr, Michael; Kwitt, Roland; Häfner, Michael; Tamaki, Toru; Yoshida, Shigeto; Tanaka, Shinji; Merhof, Dorit; Uhl, Andreas

2018-05-04

In medical image data sets, the number of images is usually quite small. The small number of training samples does not allow to properly train classifiers which leads to massive overfitting to the training data. In this work, we investigate whether increasing the number of training samples by merging datasets from different imaging modalities can be effectively applied to improve predictive performance. Further, we investigate if the extracted features from the employed image representations differ between different imaging modalities and if domain adaption helps to overcome these differences. We employ twelve feature extraction methods to differentiate between non-neoplastic and neoplastic lesions. Experiments are performed using four different classifier training strategies, each with a different combination of training data. The specifically designed setup for these experiments enables a fair comparison between the four training strategies. Combining high definition with high magnification training data and chromoscopic with non-chromoscopic training data partly improved the results. The usage of domain adaptation has only a small effect on the results compared to just using non-adapted training data. Merging datasets from different imaging modalities turned out to be partially beneficial for the case of combining high definition endoscopic data with high magnification endoscopic data and for combining chromoscopic with non-chromoscopic data. NBI and chromoendoscopy on the other hand are mostly too different with respect to the extracted features to combine images of these two modalities for classifier training. Copyright © 2018 Elsevier Ltd. All rights reserved.

Teller Training Module: Off-Line Banking System. High-Technology Training Module.

ERIC Educational Resources Information Center

Lund, Candyce J.

This teller training module on offline banking systems is intended to be part of a postsecondary financial applications course. The module contains the following sections: module objective; specific objective; content--electronic audit machine key functions, practice packet--sample bank transactions and practicing procedures, and…

Medicine in the Encyclopédie (1751-1780) of Diderot and d'Alembert.

PubMed

De Santo, Natale G; Bisaccia, Carmela; Cirillo, Massimo; Richet, Gabriel

2011-01-01

On July 1, 1751, the royal Parisian printer Le Breton published the first volume of the Encyclopédie of Diderot and d'Alembert, a rational dictionary, in folio and in alphabetical order, sold by subscription. The whole work was completed in 1780 (a total of 35 volumes, of which 12 were of illustrations, 4 of supplements and 2 of indices). In 1782 it was followed by the Encyclopédie méthodique, printed by Panckoucke, which ended in 1832 with volume number 166. The frontispiece of the first volume, designed by Charles-Nicolas Cochin Jr. and engraved by Benoît-Louis Prévost showed the columns of an Ionic temple where the Truth appears between Reason and Philosophy. Reason is shown trying to break the veil of Truth, and Philosophy trying to embellish it. Below are the philosophers, their eyes fixed on Truth. Theology is on his knees with his back facing Truth, and seems to receive light from the top. The subsequent chain of figures depicts Memory, Ancient History, Modern History, Geometry, Astronomy and Physics. Below are Optics, Botany, Chemistry and Agriculture. On the bottom line one finds the representatives of arts and professions derived from science. In a 42-page preface ("Discours préliminaire") d'Alembert discussed the path to new knowledge as one "based on what we receive through senses. Ideas depend on senses." The medical collaborators were, or became, famous. Medicine was considered to be rooted in experiment, in patients and in measurements. Functions started to be described with numbers. It was the birth of determinism which was later reinforced by Magendie and Claude Bernard. Albrecht Haller, president of the Academy of Science at Göttingen, as well as a member of all European academies, wrote seminal entries. New accurate definitions appeared for life, disease, death, infections, plague, epidemics, hygiene, fevers and edema. Semiology, the study of signs, became the visible explanation of deranged function, diagnosis and prognosis.

Are tree ontogenetic structure and allometric relationship independent of vegetation formation type? A case study with Cordia oncocalyx in the Brazilian caatinga

NASA Astrophysics Data System (ADS)

Silveira, Andréa P.; Martins, Fernando R.; Araújo, Francisca S.

2012-08-01

In temperate and tropical rainforests, ontogenetic structure and allometry during tree ontogeny are often associated with light gradients. Light is not considered a limiting resource in deciduous thorny woodland (DTW), but establishment and growth occur during a short rainy period, when the canopy is fully leaved and light in the understory may be modified. Our aim was to investigate whether the light gradient in DTW and the biomechanical limitations of tree growth would be enough to produce an ontogenetic structure and allometric growth similar to rainforest canopy trees. We investigated the ontogenetic stages and diameter-height relationship of Cordia oncocalyx (Boraginaceae), a dominant canopy tree of the DTW of semiarid northeastern Brazil. We tagged, measured and classified the ontogenetic stages of 2.895 individuals in a 1 ha area (5°6'58.1″S and 40°52'19.4″W). In the rainy season only 4.7% of the light falling on the canopy reached the ground. Initial ontogenetic stages, mainly infant (50.9%) and seedling (42.1%), were predominant in the population, with the remaining 7% distributed among juvenile, immature, virginile and reproductive. The ontogenetic structure was similar to that of rainforest tree species, but the population formed both permanent seed and infant banks in response to long dry periods and erratic rainy spells. Like many other Boraginaceae tree species in tropical rainforests, C. oncocalyx has a Prévost architectural model, but allometric growth was quite different from rainforest trees. C. oncocalyx invested slightly more in diameter at first, then in height and finally invested greatly in diameter and attained an asymptotic height. The continued high investment in diameter growth at late stages and the asymptotic height point to low tree density and more frequent xylem embolism as the main drivers of tree allometric shape in DTW. This indicates that tree ontogenetic structure and allometric relationships depend on vegetation formation type.

The effect of sample size and disease prevalence on supervised machine learning of narrative data.

PubMed Central

McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George

2002-01-01

This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

An evaluation of cold chain system for vaccines in Bangalore.

PubMed

Sudarshan, M K; Sundar, M; Girish, N; Narendra, S; Patel, N G

1994-01-01

The cold chain plays a major role in the universal immunization programme which helps in preventing against six major killer diseases in children. We collected 144 study samples randomly from different parts of Bangalore to know the training status of personnel, refrigeration facilities, storage, monitoring and potency of vaccines. It was observed that 6.6% of general practitioners were trained under Universal Immunization Programme, monitoring was not satisfactory, and two of the OPV samples from medical practitioners had an unsatisfactory titre dose. Comprehensive orientation/training on cold chain is essential for medical practitioners and other professionals.

Why did persons invited to train in cardiopulmonary resuscitation not do so?

PubMed

Lejeune, P O; Delooz, H H

1987-03-01

All citizens (N = 22066) aged 16 to 65 of a medium-sized Belgian town were personally invited to CPR training sessions held in their neighbourhood. 1152 responded by attending a training session. Those who did not so respond were surveyed (random sample N = 600) for reasons of their not coming. The sample fitted well with census data for gender, age and suburb location but not for job, because retired persons and women at home were overrepresented. 123 persons did not want to answer the questions. 116 persons said they were already trained in CPR, 276 said they would accept on a future occasion and 82 said they would not. Three persons did not answer this question. There was no discrimination for job, gender and suburb location between those who did not accept a future training opportunity, nor was the existence of a heart patient among relatives. The older the person, the less inclined was that person to participate in CPR training (age effect chi 2 = 17 X 17, d.f. = 9, P less than 0.05). The 276 who accepted future training, chose their workplace (221) and/or their social meeting place (club etc.) as the place where this future training should be held. We suggest that CPR training is well accepted and that the training opportunities should be given at places of work and social gatherings.

Machine Learning for Big Data: A Study to Understand Limits at Scale

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

Sukumar, Sreenivas R.; Del-Castillo-Negrete, Carlos Emilio

This report aims to empirically understand the limits of machine learning when applied to Big Data. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical data mining and machine learning under more scrutiny, evaluation and application for gleaning insights from the data than ever before. Much is expected from algorithms without understanding their limitations at scale while dealing with massive datasets. In that context, we pose and address the following questions How does a machine learning algorithm perform on measuresmore » such as accuracy and execution time with increasing sample size and feature dimensionality? Does training with more samples guarantee better accuracy? How many features to compute for a given problem? Do more features guarantee better accuracy? Do efforts to derive and calculate more features and train on larger samples worth the effort? As problems become more complex and traditional binary classification algorithms are replaced with multi-task, multi-class categorization algorithms do parallel learners perform better? What happens to the accuracy of the learning algorithm when trained to categorize multiple classes within the same feature space? Towards finding answers to these questions, we describe the design of an empirical study and present the results. We conclude with the following observations (i) accuracy of the learning algorithm increases with increasing sample size but saturates at a point, beyond which more samples do not contribute to better accuracy/learning, (ii) the richness of the feature space dictates performance - both accuracy and training time, (iii) increased dimensionality often reflected in better performance (higher accuracy in spite of longer training times) but the improvements are not commensurate the efforts for feature computation and training and (iv) accuracy of the learning algorithms drop significantly with multi-class learners training on the same feature matrix and (v) learning algorithms perform well when categories in labeled data are independent (i.e., no relationship or hierarchy exists among categories).« less

Training School Administrators in Computer Use.

ERIC Educational Resources Information Center

Spuck, Dennis W.; Bozeman, William C.

1988-01-01

Presents results of a survey of faculty members in doctoral-level educational administration programs that examined the use of computers in administrative training programs. The present status and future directions of technological training of school administrators are discussed, and a sample curriculum for a course in technology and computing is…

Evaluating Entrepreneurship Development Programmes in Practice.

ERIC Educational Resources Information Center

Harper, Malcolm; Mahajan, Vijay

1995-01-01

In India, a survey of samples of 126 business owners with entrepreneurship training and 120 without found that trained owners broke even significantly sooner and had lower capital-outlet ratios. Another study of 2 groups of 30 found trained owners had significantly higher personal earnings, company profits, and numbers employed. (SK)

NHEXAS PHASE I MARYLAND STUDY--STANDARD OPERATING PROCEDURE FOR TRAINING OF FIELD TECHNICIANS (G07)

EPA Science Inventory

The purpose of this SOP is to describe the method used for training field technicians. The SOP outlines the responsibilities of the Field Technician (FT) and the Field Coordination Center Supervisor (FCC-S) before, during, and after sampling at residences, and the training syste...

Individualism-Collectivism and the Role of Goal Orientation in Organizational Training

ERIC Educational Resources Information Center

Rogers, Altovise; Spitzmueller, Christiane

2009-01-01

This research examines how individualism-collectivism and goal orientation impact training effectiveness through study of an internationally diverse sample of engineers who were undergoing technical training. In light of contemporary views of individualism-collectivism, we argue that collectivism will moderate the influence of learning and…

The Efficacy of Relaxation Training in Treating Anxiety

ERIC Educational Resources Information Center

Francesco, Pagnini; Mauro, Manzoni Gian; Gianluca, Castelnuovo; Enrico, Molinari

2009-01-01

This paper provides a review of scientific literature about relaxation training and its effects on anxiety. Research investigating progressive relaxation, meditation, applied relaxation and autogenic training were considered. All these methods proved to be effective in reducing anxiety in all kind of samples, affected or not by physical or…

Training set optimization under population structure in genomic selection.

PubMed

Isidro, Julio; Jannink, Jean-Luc; Akdemir, Deniz; Poland, Jesse; Heslot, Nicolas; Sorrells, Mark E

2015-01-01

Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation captured by a sampling method in the TRS is desirable. The wheat dataset showed mild population structure, and CDmean and stratified CDmean methods showed the highest accuracies for all the traits except for test weight and heading date. The rice dataset had strong population structure and the approach based on stratified sampling showed the highest accuracies for all traits. In general, CDmean minimized the relationship between genotypes in the TRS, maximizing the relationship between TRS and the test set. This makes it suitable as an optimization criterion for long-term selection. Our results indicated that the best selection criterion used to optimize the TRS seems to depend on the interaction of trait architecture and population structure.

[Identification of Dendrobium varieties by infrared spectroscopy].

PubMed

Liu, Fei; Wang, Yuan-Zhong; Yang, Chun-Yan; Jin, Hang

2014-11-01

The difference of Dendrobium varieties were analyzed by Fourier transform infrared (FTIR) spectroscopy. The infrared spectra of 206 stems from 30 Dendrobium varieties were obtained, and showed that polysaccharides, especially fiber, were the main components in Dendrobium plants. FTIR combined with Wilks' Lambda stepwise discriminative analysis was used to identify Dendrobium varieties. The effects of spectral range and number of training samples on the discrimination results were also analysed. Two hundred eighty seven variables in the spectral range of 1 800-1 250 cm(-1) were studied, and showed that the return discrimination is 100% correct when the training samples number of each species was 2, 3, 4, 5, and 6, respectively, whereas for the remaining samples the correct rates of identification were equal to 79.4%, 91.3%, 93.0%, 98.2%, and 100%, respectively. The same discriminative analyses on five different training samples in the spectral range of 1 800-1 500, 1 500-1 250, 1 250-600, 1 250-950 and 950-650 cm(-1) were compared, which showed that the variables in the range of 1 800-1 250, 1 800-1 500 and 950-600 cm(-1) were more suitable for variety identification, and one can obtain the satisfactory result for discriminative analysis when the training sample is more than 3. Our results indicate that FTIR combined with stepwise discriminative analysis is an effective way to distinguish different Dendrobium varieties.

Constructed-response matching to sample and spelling instruction.

PubMed Central

Dube, W V; McDonald, S J; McIlvane, W J; Mackay, H A

1991-01-01

The development of interactive programmed instruction using a microcomputer as a teaching machine is described. The program applied a constructed-response matching-to-sample procedure to computer-assisted spelling instruction and review. On each trial, subjects were presented with a sample stimulus and a choice pool consisting of 10 individual letters. In initial training, sample stimuli were arrays of letters, and subjects were taught to construct identical arrays by touching the matching letters in the choice pool. After generalized constructed-response identity matching was established, pictures (line drawings) of common objects were presented as samples. At first, correct spelling was prompted by also presenting the printed name to be "copied" via identity matching; then the prompts were faded out. The program was implemented with 2 mentally retarded individuals. Assessment trials determined appropriate words for training. Correct spelling was established via the prompt-fading procedure; training trials were interspersed among baseline trials that reviewed and maintained spelling of previously learned words. As new words were learned, they were added to a cumulative baseline to generate an individualized review and practice battery for each subject. PMID:1890049

Driver training interests of a Spanish sample of young drivers and its relationship with their self-assessment skills concerning risky driving behavior.

PubMed

Molina, J Gabriel; Sanmartín, Jaime; Keskinen, Esko

2013-03-01

Poor driving self-assessment skills (e.g., over-confidence) have been pointed out as an important explanatory factor behind young drivers' accident involvement. This paper explores (1) what young drivers miss in their training as drivers in order to analyze whether an assessment of one's own driving skills plays an important role in their desire to improve as drivers, and (2) how these training interests are related to an estimate of their self-assessment skills concerning risky driving behavior. For this purpose, a study was conducted using a survey with a blocked sampling design of novice drivers. The survey solicited respondents' self-report about (1) the contents of training courses that they feel would improve their driving, (2) their risky driving behavior, and (3) their likelihood of being involved in a risky driving situation. From the initial sample invited to participate, of nearly 1300 people, we finally obtained complete data from 321 young Spanish drivers. Two main results were apparent from our data analysis: (1) the novice drivers were mainly interested in improving their ability to recognize their strengths and weaknesses as drivers (i.e., self-assessment skills); (2) a significant relationship was found between novice drivers' interests and their current self-assessment skills concerning risky driving behavior. Specifically, there was greater general interest expressed in post-license training by the under-confident self-assessors than the over-confident ones. These results provide a relevant input which should be taken into account when designing driver training programs for novice drivers. Moreover, the relationship between their training interests and their risky driving self-assessment skills introduces an additional factor to be considered in the implementation of these training programs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Application of Deep Learning in GLOBELAND30-2010 Product Refinement

NASA Astrophysics Data System (ADS)

Liu, T.; Chen, X.

2018-04-01

GlobeLand30, as one of the best Global Land Cover (GLC) product at 30-m resolution, has been widely used in many research fields. Due to the significant spectral confusion among different land cover types and limited textual information of Landsat data, the overall accuracy of GlobeLand30 is about 80 %. Although such accuracy is much higher than most other global land cover products, it cannot satisfy various applications. There is still a great need of an effective method to improve the quality of GlobeLand30. The explosive high-resolution satellite images and remarkable performance of Deep Learning on image classification provide a new opportunity to refine GlobeLand30. However, the performance of deep leaning depends on quality and quantity of training samples as well as model training strategy. Therefore, this paper 1) proposed an automatic training sample generation method via Google earth to build a large training sample set; and 2) explore the best training strategy for land cover classification using GoogleNet (Inception V3), one of the most widely used deep learning network. The result shows that the fine-tuning from first layer of Inception V3 using rough large sample set is the best strategy. The retrained network was then applied in one selected area from Xi'an city as a case study of GlobeLand30 refinement. The experiment results indicate that the proposed approach with Deep Learning and google earth imagery is a promising solution for further improving accuracy of GlobeLand30.

Coordinated Analysis 101: A Joint Training Session Sponsored by LPI and ARES/JSC

NASA Technical Reports Server (NTRS)

Draper, D. S.; Treiman, A. H.

2017-01-01

The Lunar and Planetary Institute (LPI) and the Astromaterials Research and Exploration Science (ARES) Division, part of the Exploration Integration and Science Directorate at NASA Johnson Space Center (JSC), co-sponsored a training session in November 2016 for four early-career scientists in the techniques of coordinated analysis. Coordinated analysis refers to the approach of systematically performing high-resolution and -precision analytical studies on astromaterials, particularly the very small particles typical of recent and near-future sample return missions such as Stardust, Hayabusa, Hayabusa2, and OSIRIS-REx. A series of successive analytical steps is chosen to be performed on the same particle, as opposed to separate subsections of a sample, in such a way that the initial steps do not compromise the results from later steps in the sequence. The data from the entire series can then be integrated for these individual specimens, revealing important in-sights obtainable no other way. ARES/JSC scientists have played a leading role in the development and application of this approach for many years. Because the coming years will bring new sample collections from these and other planned NASA and international exploration missions, it is timely to begin disseminating specialized techniques for the study of small and precious astromaterial samples. As part of the Cooperative Agreement between NASA and the LPI, this training workshop was intended as the first in a series of similar training exercises that the two organizations will jointly sponsor in the coming years. These workshops will span the range of analytical capabilities and sample types available at ARES/JSC in the Astromaterials Research and Astro-materials Acquisition and Curation Offices. Here we summarize the activities and participants in this initial training.

Influence of vine training and sunlight exposure on the 3-alkyl-2-methoxypyrazines content in musts and wines from the Vitis vinifera variety cabernet sauvignon.

PubMed

Sala, Cristina; Busto, Olga; Guasch, Josep; Zamora, Fernando

2004-06-02

The influence of vine training and sunlight exposure on the 3-alkyl-2-methoxypyrazines contents in musts and wines was studied by means of two previously reported methods based on headspace solid-phase micro-extraction. Experimental samples were monitored throughout grape ripening and wine making. 3-Isobutyl-2-methoxypyrazine, 3-sec-butyl-2-methoxypyrazine and 3-isopropyl-2-methoxypyrazine were identified. The 3-isobutyl-2-methoxypyrazine content decreased throughout grape ripening in all of the sample types studied. After 1 day of maceration with the skins, there was an increase, but after racking, no further increase was observed. No significant differences between samples were found during grape ripening. Wines from goblet-trained vines, however, contained significantly less 3-isobutyl-2-methoxypyrazine. Clusters protected from sunlight since the beginning of the veraison resulted in wines with a significantly lower content of this compound than the control samples.

Detecting Staphylococcus aureus in milk from dairy cows using sniffer dogs.

PubMed

Fischer-Tenhagen, C; Theby, V; Krömker, V; Heuwieser, W

2018-05-01

Fast and accurate identification of disease-causing pathogens is essential for specific antimicrobial therapy in human and veterinary medicine. In these experiments, dogs were trained to identify Staphylococcus aureus and differentiate it from other common mastitis-causing pathogens by smell. Headspaces from agar plates, inoculated raw milk samples, or field samples collected from cows with Staphylococcus aureus and other mastitis-causing pathogens were used for training and testing. The ability to learn the specific odor of Staphylococcus aureus in milk depended on the concentration of the pathogens in the training samples. Sensitivity and specificity for identifying Staphylococcus aureus were 91.3 and 97.9%, respectively, for pathogens grown on agar plates; 83.8 and 98.0% for pathogens inoculated in raw milk; and 59.0 and 93.2% for milk samples from mastitic cows. The results of these experiments underline the potential of odor detection as a diagnostic tool for pathogen diagnosis. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Estimating a Logistic Discrimination Functions When One of the Training Samples Is Subject to Misclassification: A Maximum Likelihood Approach.

PubMed

Nagelkerke, Nico; Fidler, Vaclav

2015-01-01

The problem of discrimination and classification is central to much of epidemiology. Here we consider the estimation of a logistic regression/discrimination function from training samples, when one of the training samples is subject to misclassification or mislabeling, e.g. diseased individuals are incorrectly classified/labeled as healthy controls. We show that this leads to zero-inflated binomial model with a defective logistic regression or discrimination function, whose parameters can be estimated using standard statistical methods such as maximum likelihood. These parameters can be used to estimate the probability of true group membership among those, possibly erroneously, classified as controls. Two examples are analyzed and discussed. A simulation study explores properties of the maximum likelihood parameter estimates and the estimates of the number of mislabeled observations.

Coping food craving with neurofeedback. Evaluation of the usefulness of alpha/theta training in a non-clinical sample.

PubMed

Imperatori, Claudio; Valenti, Enrico Maria; Della Marca, Giacomo; Amoroso, Noemi; Massullo, Chiara; Carbone, Giuseppe Alessio; Maestoso, Giulia; Quintiliani, Maria Isabella; Contardi, Anna; Farina, Benedetto

2017-02-01

The aim of the present study was to explore the usefulness of the alpha/theta (A/T) training in reducing Food Craving (FC) in a non-clinical sample. The modifications of electroencephalographic (EEG) power spectra associated with A/T training was also investigated. Fifty subjects were enrolled in the study and randomly assigned to receive ten sessions of A/T training [neurofeedback group (NFG)=25], or to act as controls [waiting list group (WLG)=25]. All participants were administered the Food Cravings Questionnaire-Trait, the Eating Disorder Examination Questionnaire and the Symptom Checklist-90-Revised. In the post training assessment, compared to the WLG, the NFG showed a significant reduction of intentions and plans to consume food (F 1; 49 =4.90; p=.033; d=0.626) and of craving as a physiological state (F 1; 49 =8.09; p=.007; d=803). In NFG, changes in FC persisted after 4months follow-up. Furthermore, A/T training was associated with significant a increase of resting EEG alpha power in several brain areas involved in FC (e.g., insula) and food cue reactivity (e.g., parahippocampal gyrus, inferior and superior temporal gyrus). Taken together, our results showed that ten sessions of A/T training are associated with a decrease of self-reported FC in a non-clinical sample. These findings suggest that this brain-directed intervention may be useful in the treatment of dysfunctional eating behaviors characterized by FC. Copyright © 2016 Elsevier B.V. All rights reserved.

Mindfulness meditation training alters stress-related amygdala resting state functional connectivity: a randomized controlled trial

PubMed Central

Taren, Adrienne A.; Gianaros, Peter J.; Greco, Carol M.; Lindsay, Emily K.; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K.; Ferris, Jennifer L.; Julson, Erica; Marsland, Anna L.; Bursley, James K.; Ramsburg, Jared

2015-01-01

Recent studies indicate that mindfulness meditation training interventions reduce stress and improve stress-related health outcomes, but the neural pathways for these effects are unknown. The present research evaluates whether mindfulness meditation training alters resting state functional connectivity (rsFC) of the amygdala, a region known to coordinate stress processing and physiological stress responses. We show in an initial discovery study that higher perceived stress over the past month is associated with greater bilateral amygdala-subgenual anterior cingulate cortex (sgACC) rsFC in a sample of community adults (n = 130). A follow-up, single-blind randomized controlled trial shows that a 3-day intensive mindfulness meditation training intervention (relative to a well-matched 3-day relaxation training intervention without a mindfulness component) reduced right amygdala-sgACC rsFC in a sample of stressed unemployed community adults (n = 35). Although stress may increase amygdala-sgACC rsFC, brief training in mindfulness meditation could reverse these effects. This work provides an initial indication that mindfulness meditation training promotes functional neuroplastic changes, suggesting an amygdala-sgACC pathway for stress reduction effects. PMID:26048176

Odor Perception by Dogs: Evaluating Two Training Approaches for Odor Learning of Sniffer Dogs.

PubMed

Fischer-Tenhagen, Carola; Johnen, Dorothea; Heuwieser, Wolfgang; Becker, Roland; Schallschmidt, Kristin; Nehls, Irene

2017-06-01

In this study, a standardized experimental set-up with various combinations of herbs as odor sources was designed. Two training approaches for sniffer dogs were compared; first, training with a pure reference odor, and second, training with a variety of odor mixtures with the target odor as a common denominator. The ability of the dogs to identify the target odor in a new context was tested. Six different herbs (basil, St. John's wort, dandelion, marjoram, parsley, ribwort) were chosen to produce reference materials in various mixtures with (positive) and without (negative) chamomile as the target odor source. The dogs were trained to show 1 of 2 different behaviors, 1 for the positive, and 1 for the negative sample as a yes/no task. Tests were double blind with one sample presented at a time. In both training approaches, dogs were able to detect chamomile as the target odor in any presented mixture with an average sensitivity of 72% and a specificity of 84%. Dogs trained with odor mixture containing the target odor had more correct indications in the transfer task. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Value of Being a Conscientious Learner: Examining the Effects of the Big Five Personality Traits on Self-Reported Learning from Training

ERIC Educational Resources Information Center

Woods, Stephen A.; Patterson, Fiona C.; Koczwara, Anna; Sofat, Juilitta A.

2016-01-01

Purpose: The aim of this paper is to examine the impact of personality traits of the Big Five model on training outcomes to help explain variation in training effectiveness. Design/Methodology/ Approach: Associations of the Big Five with self-reported learning following training were tested in a pre- and post-design in a field sample of junior…

Estimating High Tech Army Recruiting Markets

DTIC Science & Technology

1992-09-01

SCORES: 1963-1988 11 TABLE 4 AVERAGE AMERICAN COLLEGE TESTING ( ACT ) SCORES: 1970-1988 12 TABLE 5 DISTRIBUTION OF THE NLSY SAMPLE BY GENDER AND RACE 21...training, competent leaders, sufficient resources and funds to equip the force 1 . In order to maximize the quality of training, recruiting success is...training policies to current conditions in the ’educational training market 1 . Recruiting success is highly dependent on the nature of the civilian

Classification of Parkinson's disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples.

PubMed

Zhang, He-Hua; Yang, Liuyang; Liu, Yuchuan; Wang, Pin; Yin, Jun; Li, Yongming; Qiu, Mingguo; Zhu, Xueru; Yan, Fang

2016-11-16

The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis methods applicable to Parkinsonism for building predictive tele-diagnosis and tele-monitoring models. One of the obstacles in optimizing classifications is to reduce noise within the collected speech samples, thus ensuring better classification accuracy and stability. While the currently used methods are effect, the ability to invoke instance selection has been seldomly examined. In this study, a PD classification algorithm was proposed and examined that combines a multi-edit-nearest-neighbor (MENN) algorithm and an ensemble learning algorithm. First, the MENN algorithm is applied for selecting optimal training speech samples iteratively, thereby obtaining samples with high separability. Next, an ensemble learning algorithm, random forest (RF) or decorrelated neural network ensembles (DNNE), is used to generate trained samples from the collected training samples. Lastly, the trained ensemble learning algorithms are applied to the test samples for PD classification. This proposed method was examined using a more recently deposited public datasets and compared against other currently used algorithms for validation. Experimental results showed that the proposed algorithm obtained the highest degree of improved classification accuracy (29.44%) compared with the other algorithm that was examined. Furthermore, the MENN algorithm alone was found to improve classification accuracy by as much as 45.72%. Moreover, the proposed algorithm was found to exhibit a higher stability, particularly when combining the MENN and RF algorithms. This study showed that the proposed method could improve PD classification when using speech data and can be applied to future studies seeking to improve PD classification methods.

10 CFR 36.13 - Specific licenses for irradiators.

Code of Federal Regulations, 2010 CFR

2010-01-01

... the training provided to irradiator operators including— (1) Classroom training; (2) On-the-job or... analysis; and (3) Pertinent experience of the individual who analyzes the samples. (g) If licensee...

Experimenting with Electric Trains

ERIC Educational Resources Information Center

Wick, D. P.; Ramsdell, M. W.

2007-01-01

A simple experiment can be performed to characterize the relationship between applied voltage and velocity (steady state and transient) for an electric toy train. The results can be used by teams of students to solve a series of challenges in which they attempt to predict the performance of a particular train. Some sample challenges might include…

Computer Literacy of Turkish Preservice Teachers in Different Teacher Training Programs

ERIC Educational Resources Information Center

Ozsevgec, Tuncay

2011-01-01

This paper reports on an investigation into the sophomore and senior preservice teachers' computer literacy in different teacher training programs and to determine relationship between grades and the teacher training programs in terms of their computer literacy. The study used case study research methodology, and the sample consisted of 276…

Vocational Education and Training: A Review of World Bank Investment. World Bank Discussion Papers 51.

ERIC Educational Resources Information Center

Middleton, John; Demsky, Terry

A study of a representative sample of 121 World Bank-funded vocational education and training components suggests that the level of economic development and consequent size and dynamism of industrial employment powerfully influence the outcome of such education and training. Consequently, future investment strategies should differ among countries…

Training Matters: Vocational Education and Training in the Retail Sector.

ERIC Educational Resources Information Center

Forrester, K. P.; And Others

Available vocational education and training in the United Kingdom's retail sector were examined in an employee-centered study during which data were collected primarily from two sources: questionnaires completed by 1,974 from a random sample of approximately 6,000 British retail employees who were surveyed, and semistructured face-to-face…

Effects of Different Genres of Music on Stress Levels.

ERIC Educational Resources Information Center

Marshall, O. W.; Tomcala, Maryjane

The response of patients with stress problems to one of five music genres during biofeedback training is measured. Fifty male and female patients between the ages of 15 and 25 who were receiving psychotherapy, self-help counseling, and physical fitness training as well as biofeedback training comprised the sample. Using a Biofeedback Systems…

Rational-Emotive, Self-Instructional, and Behavioral Assertion Training: Enhancing the Generalization and Maintenance of Treatment Gains.

ERIC Educational Resources Information Center

Carmody, Timothy P.

A sample of 63 subassertive adults participated in four 90-minute sessions of group assertion training. The treatment components of challenging maladaptive cognitions and learning self-instructions were examined by comparing Rational-Emotive, Self-Instructional, and Behavioral Assertion Training. A delayed-treatment control group was also…

Training Practices and Organisational Learning Capability: Relationship and Implications

ERIC Educational Resources Information Center

Jerez Gomez, Pilar; Cespedes Lorente, Jose J.; Valle Cabrera, Ramon

2004-01-01

This paper provides an in-depth study of the relationship between the company's training strategy and its learning capability. On a sample of 111 Spanish companies from the chemical industry, tests a set of hypotheses which link four different training strategies with the learning capability dimensions. The results obtained from the regression…

Training of Home Health Aides and Nurse Aides: Findings from National Data

ERIC Educational Resources Information Center

Sengupta, Manisha; Ejaz, Farida K.; Harris-Kojetin, Lauren D.

2012-01-01

Training and satisfaction with training were examined using data from nationally representative samples of 2,897 certified nursing assistants (CNAs) from the National Nursing Assistant Survey and 3,377 home health aides (HHAs) from the National Home Health Aide Survey conducted in 2004 and 2007, respectively. This article focuses on the…

An Evaluation of a Parent Training Program

ERIC Educational Resources Information Center

Nguyen, Quynh T.

2013-01-01

This study examined the effectiveness of a parent training program whose children are diagnosed with autism. The sample consisted of families who are currently participating in a parent training program. The study examined the stress levels of parents utilizing the Questionnaire on Resources and Stress at the beginning of the study and then again…

The Effect of Anxiety Management Training on College Students' General, Overt, and Covert Anxiety.

ERIC Educational Resources Information Center

Vinson, Michael L.

The effect on anxiety of a behaviorally-oriented treatment, Anxiety Management Training (AMT), was investigated with a sample of college students (N=23). The treatment was based upon the techniques originally used by Richardson, Suinn, and Meichenbaum, and consisted of three principal elements: relaxation training, cognitive-restructuring, and…

40 CFR 745.225 - Accreditation of training programs: target housing and child-occupied facilities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... equipment to be used for lecture and hands-on training. (B) A copy of the course test blueprint for each..., the delivery of the lecture, course test, hands-on training, and assessment activities. This includes... containment and cleanup methods, and post-renovation cleaning verification. (vii) The dust sampling technician...

40 CFR 745.225 - Accreditation of training programs: target housing and child-occupied facilities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... equipment to be used for lecture and hands-on training. (B) A copy of the course test blueprint for each..., the delivery of the lecture, course test, hands-on training, and assessment activities. This includes... containment and cleanup methods, and post-renovation cleaning verification. (vii) The dust sampling technician...

Training in Psychiatric Genomics during Residency: A New Challenge

ERIC Educational Resources Information Center

Winner, Joel G.; Goebert, Deborah; Matsu, Courtenay; Mrazek, David A.

2010-01-01

Objective: The authors ascertained the amount of training in psychiatric genomics that is provided in North American psychiatric residency programs. Methods: A sample of 217 chief residents in psychiatric residency programs in the United States and Canada were identified by e-mail and surveyed to assess their training in psychiatric genetics and…

Acetylcholine Release in the Hippocampus and Striatum during Place and Response Training

ERIC Educational Resources Information Center

Pych, Jason C.; Chang, Qing; Colon-Rivera, Cynthia; Haag, Renee; Gold, Paul E.

2005-01-01

These experiments examined the release of acetylcholine in the hippocampus and striatum when rats were trained, within single sessions, on place or response versions of food-rewarded mazes. Microdialysis samples of extra-cellular fluid were collected from the hippocampus and striatum at 5-min increments before, during, and after training. These…

Australian Small Business Participation in Training Activities

ERIC Educational Resources Information Center

Webster, Beverley; Walker, Elizabeth; Brown, Alan

2005-01-01

Purpose: This purpose of this paper is to investigate the use of on-line training by small businesses in Australia. It explores the relationship between the owners acceptance and use of the Internet, and their current participation in training opportunities. Design/Methodology/Approach: A sample of small businesses which had participated in an…

Diversity Exiting the Academy: Influential Factors for the Career Choice of Well-Represented and Underrepresented Minority Scientists

ERIC Educational Resources Information Center

Layton, Rebekah L.; Brandt, Patrick D.; Freeman, Ashalla M.; Harrell, Jessica R.; Hall, Joshua D.; Sinche, Melanie

2016-01-01

A national sample of PhD-trained scientists completed training, accepted subsequent employment in academic and nonacademic positions, and were queried about their previous graduate training and current employment. Respondents indicated factors contributing to their employment decision (e.g., working conditions, salary, job security). The data…

Improving family medicine resident training in dementia care: an experiential learning opportunity in Primary Care Collaborative Memory Clinics.

PubMed

Lee, Linda; Weston, W Wayne; Hillier, Loretta; Archibald, Douglas; Lee, Joseph

2018-06-21

Family physicians often find themselves inadequately prepared to manage dementia. This article describes the curriculum for a resident training intervention in Primary Care Collaborative Memory Clinics (PCCMC), outlines its underlying educational principles, and examines its impact on residents' ability to provide dementia care. PCCMCs are family physician-led interprofessional clinic teams that provide evidence-informed comprehensive assessment and management of memory concerns. Within PCCMCs residents learn to apply a structured approach to assessment, diagnosis, and management; training consists of a tutorial covering various topics related to dementia followed by work-based learning within the clinic. Significantly more residents who trained in PCCMCs (sample = 98), as compared to those in usual training programs (sample = 35), reported positive changes in knowledge, ability, and confidence in ability to assess and manage memory problems. The PCCMC training intervention for family medicine residents provides a significant opportunity for residents to learn about best clinical practices and interprofessional care needed for optimal dementia care integrated within primary care practice.

Stimulus Equivalence, Generalization, and Contextual Stimulus Control in Verbal Classes

PubMed Central

Sigurðardóttir, Zuilma Gabriela; Mackay, Harry A; Green, Gina

2012-01-01

Stimulus generalization and contextual control affect the development of equivalence classes. Experiment 1 demonstrated primary stimulus generalization from the members of trained equivalence classes. Adults were taught to match six spoken Icelandic nouns and corresponding printed words and pictures to one another in computerized three-choice matching-to-sample tasks. Tests confirmed that six equivalence classes had formed. Without further training, plural forms of the stimuli were presented in tests for all matching performances. All participants demonstrated virtually errorless performances. In Experiment 2, classifications of the nouns used in Experiment 1 were brought under contextual control. Three nouns were feminine and three were masculine. The match-to-sample training taught participants to select a comparison of the same number as the sample (i.e., singular or plural) in the presence of contextual stimulus A regardless of noun gender. Concurrently, in the presence of contextual stimulus B, participants were taught to select a comparison of the same gender as the sample (i.e., feminine or masculine), regardless of number. Generalization was assessed using a card-sorting test. All participants eventually sorted the cards correctly into gender and number stimulus classes. When printed words used in training were replaced by their picture equivalents, participants demonstrated almost errorless performances. PMID:22754102

Randomized control trial of computer-based training targeting alertness in older adults: the ALERT trial protocol.

PubMed

VanVleet, Thomas; Voss, Michelle; Dabit, Sawsan; Mitko, Alex; DeGutis, Joseph

2018-05-03

Healthy aging is associated with a decline in multiple functional domains including perception, attention, short and long-term memory, reasoning, decision-making, as well as cognitive and motor control functions; all of which are significantly modulated by an individual's level of alertness. The control of alertness also significantly declines with age and contributes to increased lapses of attention in everyday life, ranging from minor memory slips to a lack of vigilance and increased risk of falls or motor-vehicle accidents. Several experimental behavioral therapies designed to remediate age-related cognitive decline have been developed, but differ widely in content, method and dose. Preliminary studies demonstrate that Tonic and Phasic Alertness Training (TAPAT) can improve executive functions in older adults and may be a useful adjunct treatment to enhance benefits gained in other clinically validated treatments. The purpose of the current trial (referred to as the Attention training for Learning Enhancement and Resilience Trial or ALERT) is to compare TAPAT to an active control training condition, include a larger sample of patients, and assess both cognitive and functional outcomes. We will employ a multi-site, longitudinal, blinded randomized controlled trial (RCT) design with a target sample of 120 patients with age-related cognitive decline. Patients will be asked to complete 36 training sessions remotely (30 min/day, 5 days a week, over 3 months) of either the experimental TAPAT training program or an active control computer games condition. Patients will be assessed on a battery of cognitive and functional outcomes at four time points, including: a) immediately before training, b) halfway through training, c) within forty-eight hours post completion of total training, and d) after a three-month no-contact period post completion of total training, to assess the longevity of potential training effects. The strengths of this protocol are that it tests an innovative, in-home administered treatment that targets a fundamental deficit in adults with age-related cognitive decline; employs highly sensitive computer-based assessments of cognition as well as functional abilities, and incorporates a large sample size in an RCT design. ClinicalTrials.gov identifier: NCT02416401.

A Functional Analytic Approach To Computer-Interactive Mathematics

PubMed Central

2005-01-01

Following a pretest, 11 participants who were naive with regard to various algebraic and trigonometric transformations received an introductory lecture regarding the fundamentals of the rectangular coordinate system. Following the lecture, they took part in a computer-interactive matching-to-sample procedure in which they received training on particular formula-to-formula and formula-to-graph relations as these formulas pertain to reflections and vertical and horizontal shifts. In training A-B, standard formulas served as samples and factored formulas served as comparisons. In training B-C, factored formulas served as samples and graphs served as comparisons. Subsequently, the program assessed for mutually entailed B-A and C-B relations as well as combinatorially entailed C-A and A-C relations. After all participants demonstrated mutual entailment and combinatorial entailment, we employed a test of novel relations to assess 40 different and complex variations of the original training formulas and their respective graphs. Six of 10 participants who completed training demonstrated perfect or near-perfect performance in identifying novel formula-to-graph relations. Three of the 4 participants who made more than three incorrect responses during the assessment of novel relations showed some commonality among their error patterns. Derived transfer of stimulus control using mathematical relations is discussed. PMID:15898471

A functional analytic approach to computer-interactive mathematics.

PubMed

Ninness, Chris; Rumph, Robin; McCuller, Glen; Harrison, Carol; Ford, Angela M; Ninness, Sharon K

2005-01-01

Following a pretest, 11 participants who were naive with regard to various algebraic and trigonometric transformations received an introductory lecture regarding the fundamentals of the rectangular coordinate system. Following the lecture, they took part in a computer-interactive matching-to-sample procedure in which they received training on particular formula-to-formula and formula-to-graph relations as these formulas pertain to reflections and vertical and horizontal shifts. In training A-B, standard formulas served as samples and factored formulas served as comparisons. In training B-C, factored formulas served as samples and graphs served as comparisons. Subsequently, the program assessed for mutually entailed B-A and C-B relations as well as combinatorially entailed C-A and A-C relations. After all participants demonstrated mutual entailment and combinatorial entailment, we employed a test of novel relations to assess 40 different and complex variations of the original training formulas and their respective graphs. Six of 10 participants who completed training demonstrated perfect or near-perfect performance in identifying novel formula-to-graph relations. Three of the 4 participants who made more than three incorrect responses during the assessment of novel relations showed some commonality among their error patterns. Derived transfer of stimulus control using mathematical relations is discussed.

General Conformity Training Modules: Appendix A Sample Emissions Calculations

EPA Pesticide Factsheets

Appendix A of the training modules gives example calculations for external and internal combustion sources, construction, fuel storage and transfer, on-road vehicles, aircraft operations, storage piles, and paved roads.

Using an external surrogate for predictor model training in real-time motion management of lung tumors.

PubMed

Rottmann, Joerg; Berbeco, Ross

2014-12-01

Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal-external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.

Factors associated with interest in subspecialty training among neurology residents.

PubMed

Teixeira-Poit, Stephanie M; Halpern, Michael T; Kane, Heather L; Frost, A Corey; Keating, Michael; Olmsted, Murrey

2015-01-01

PHENOMENON: Previous studies have not explored factors associated with decisions among neurology residents to pursue subspecialty training within neurology. Understanding career choices among neurology residents, particularly decisions regarding subspecialty training, is critical, as neurologists with specialized knowledge can help meet the needs of patients with specific disease conditions. This study addresses the knowledge gap about subspecialty training decisions by examining factors associated with neurology residents' interest in pursuing subspecialty training and the types of subspecialty training neurology residents consider. We surveyed a geographically stratified sample of neurology residents in U.S. training programs using a two-stage survey design. In Stage 1, we randomly sampled half of the accredited neurology residency programs stratified by U.S. census region; Stage 2 involved a survey of neurology residents within these programs. The majority (approximately 81%) of residents expressed interest in subspecialty training. Resident demographic characteristics and educational debt did not influence interest in pursuing subspecialty training. Residents were more likely to express interest in subspecialty training when they participated in any neurology research (odds ratio [OR] = 2.39), 95% confidence interval (CI) [1.13, 5.07], p = .02, and indicated more interest in careers involving teaching (OR = 8.33), 95% CI [1.64, 42.19], p = .01. Considering the "medical content of subspecialty" as a more important factor approached but did not reach statistical significance (OR = 3.12), 95% CI [0.97, 10.06], p = .06. Insights: Participation in any neurology research and interest in careers involving teaching are associated with interest in subspecialty training among neurology residents. Further research is needed to determine whether exposure to research and teaching stimulates interest in subspecialty training and whether residents believe that subspecialty training is instrumental in pursuing an academic career.

"Volunteering by chance" to promote civic responsibility and civic engagement: does it work?

PubMed

Santinello, Massimo; Cristini, Francesca; Vieno, Alessio; Scacchi, Luca

2012-01-01

This study investigated the effectiveness of a program to promote civic responsibility and prevent antisocial behavior in a sample of Italian adolescents. Participants were 83 Italian male adolescents, attending the second year of high school (Mean age = 15.79; SD = 0.87). In order to test the efficacy of different strategies (in-classroom training and service activity in a voluntary organization) we divided students into two experimental groups--one classroom of students participated in both strategies (training + volunteering group) and another classroom only participated in the training (training only group)--and one control group. Process and efficacy evaluations were completed. Data were collected before and following the intervention. The process evaluation revealed that the program was highly accepted and appreciated by students. The efficacy evaluation revealed no intervention effects on civic responsibility. However, the training + volunteering group reported a significant decrease in antisocial behavior after the program. Thus, the program was effective in preventing antisocial behavior but not in promoting civic responsibility in our sample.

Adaptive model predictive process control using neural networks

DOEpatents

Buescher, K.L.; Baum, C.C.; Jones, R.D.

1997-08-19

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

Adaptive model predictive process control using neural networks

DOEpatents

Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

1997-01-01

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

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

Jager, Yetta; Bevelhimer, Mark S; al., et.

Military landscapes represent a mixture of undisturbed natural ecosystems, developed areas, and lands that support different types and intensities of military training. Research to understand water-quality influences of military landscapes usually involves intensive sampling in a few watersheds. In this study, we developed a survey design of accessible headwater watersheds intended to improve our ability to distinguish land water relationships in general, and training influences, in particular, on Fort Stewart, GA. We sampled and analyzed water from watershed outlets. We successfully developed correlative models for total suspended solids (TSS), total nitrogen (TN), organic carbon (OC), and organic nitrogen (ON), whichmore » dominated in this blackwater ecosystem. TSS tended to be greater in samples after rainfall and during the growing season, and models that included %Wetland suggested a build-and-flush relationship. We also detected a positive association between TSS and tank-training, which suggests a need to intercept sediment-laden runoff from training areas. Models for OC showed a negative association with %Grassland. TN and ON both showed negative associations with %Grassland, %Wetland, and %Forest. Unexpected positive associations were observed between OC and equipmenttraining activity and between ON and %Bare ground ? Roads. Future studies that combine our survey-based approach with more intensive monitoring of the timing and intensity of training would be needed to better understand the mechanisms for these empirical relationships involving military training. Looking beyond local effects on Fort Stewart streams, we explore questions about how exports of OC and nitrogen from coastal military installations ultimately influence estuaries downstream.« less

Environmental effects of fog oil and CS usage at the Combat Maneuver Training Center, Hohenfels, Germany. [2-chlorophenylmethylene

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

Brubaker, K.L.; Rosenblatt, D.H.; Snyder, C.T.

1992-03-01

In response to environmental concerns at the Combat Maneuver Training Center (CMTC), Hohenfels, Germany, the US Army 7th Army Training Command commissioned a scientific study by Argonne National Laboratory to investigate specific issues. The study involved three parts: (1) a field study to determine if fog oil and CS (a compound named after its discoverers, B.B. Carson and R.W. Stoughton) were accumulating in the CMTC environment, (2) a screening of selected soil samples for the presence of US Environmental Protection Agency priority pollutants, and (3) a literature review of the health effects of fog oil and CS, as well asmore » a review of training practices at CMTC. No fog oil or fog oil degradation products were detected in any soil, sediment, or vegetation sample collected at CMTC. Trace quantities of one or more priority pollutants were tentatively detected in three of eight soil and sediment samples. However, the priority pollutant concentrations are so low that they pose no environmental or health hazards. No evidence of widespread or significant contamination in the training areas was found. Crucial data needed to fully evaluate both acute and chronic health effects of civilian exposures to CS at CMTC are not available. On the basis of the available literature, long-ten-n health effects in the civilian population near CMTC that could result from the use of fog oil and CS during training activities are believed to be negligible.« less

Environmental effects of fog oil and CS usage at the Combat Maneuver Training Center, Hohenfels, Germany

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

Brubaker, K.L.; Rosenblatt, D.H.; Snyder, C.T.

1992-03-01

In response to environmental concerns at the Combat Maneuver Training Center (CMTC), Hohenfels, Germany, the US Army 7th Army Training Command commissioned a scientific study by Argonne National Laboratory to investigate specific issues. The study involved three parts: (1) a field study to determine if fog oil and CS (a compound named after its discoverers, B.B. Carson and R.W. Stoughton) were accumulating in the CMTC environment, (2) a screening of selected soil samples for the presence of US Environmental Protection Agency priority pollutants, and (3) a literature review of the health effects of fog oil and CS, as well asmore » a review of training practices at CMTC. No fog oil or fog oil degradation products were detected in any soil, sediment, or vegetation sample collected at CMTC. Trace quantities of one or more priority pollutants were tentatively detected in three of eight soil and sediment samples. However, the priority pollutant concentrations are so low that they pose no environmental or health hazards. No evidence of widespread or significant contamination in the training areas was found. Crucial data needed to fully evaluate both acute and chronic health effects of civilian exposures to CS at CMTC are not available. On the basis of the available literature, long-ten-n health effects in the civilian population near CMTC that could result from the use of fog oil and CS during training activities are believed to be negligible.« less

Measurement of atmospheric mercury species with manual sampling and analysis methods in a case study in Indiana

USGS Publications Warehouse

Risch, M.R.; Prestbo, E.M.; Hawkins, L.

2007-01-01

Ground-level concentrations of three atmospheric mercury species were measured using manual sampling and analysis to provide data for estimates of mercury dry deposition. Three monitoring stations were operated simultaneously during winter, spring, and summer 2004, adjacent to three mercury wet-deposition monitoring stations in northern, central, and southern Indiana. The monitoring locations differed in land-use setting and annual mercury-emissions level from nearby sources. A timer-controlled air-sampling system that contained a three-part sampling train was used to isolate reactive gaseous mercury, particulate-bound mercury, and elemental mercury. The sampling trains were exchanged every 6 days, and the mercury species were quantified in a laboratory. A quality-assurance study indicated the sampling trains could be held at least 120 h without a significant change in reactive gaseous or particulate-bound mercury concentrations. The manual sampling method was able to provide valid mercury concentrations in 90 to 95% of samples. Statistical differences in mercury concentrations were observed during the project. Concentrations of reactive gaseous and elemental mercury were higher in the daytime samples than in the nighttime samples. Concentrations of reactive gaseous mercury were higher in winter than in summer and were highest at the urban monitoring location. The results of this case study indicated manual sampling and analysis could be a reliable method for measurement of atmospheric mercury species and has the capability for supplying representative concentrations in an effective manner from a long-term deposition-monitoring network. ?? 2007 Springer Science+Business Media B.V.

Preliminary results of investigations into the use of artificial neural networks for discriminating gas chromatograph mass spectra of remote samples

NASA Technical Reports Server (NTRS)

Geller, Harold A.; Norris, Eugene; Warnock, Archibald, III

1991-01-01

Neural networks trained using mass spectra data from the National Institute of Standards and Technology (NIST) are studied. The investigations also included sample data from the gas chromatograph mass spectrometer (GCMS) instrument aboard the Viking Lander, obtained from the National Space Science Data Center. The work performed to data and the preliminary results from the training and testing of neural networks are described. These preliminary results are presented for the purpose of determining the viability of applying artificial neural networks in discriminating mass spectra samples from remote instrumentation such as the Mars Rover Sample Return Mission and the Cassini Probe.

Bayes estimation on parameters of the single-class classifier. [for remotely sensed crop data

NASA Technical Reports Server (NTRS)

Lin, G. C.; Minter, T. C.

1976-01-01

Normal procedures used for designing a Bayes classifier to classify wheat as the major crop of interest require not only training samples of wheat but also those of nonwheat. Therefore, ground truth must be available for the class of interest plus all confusion classes. The single-class Bayes classifier classifies data into the class of interest or the class 'other' but requires training samples only from the class of interest. This paper will present a procedure for Bayes estimation on the mean vector, covariance matrix, and a priori probability of the single-class classifier using labeled samples from the class of interest and unlabeled samples drawn from the mixture density function.

Improved military air traffic controller selection methods as measured by subsequent training performance.

PubMed

Carretta, Thomas R; King, Raymond E

2008-01-01

Over the past decade, the U.S. military has conducted several studies to evaluate determinants of enlisted air traffic controller (ATC) performance. Research has focused on validation of the Armed Services Vocational Aptitude Battery (ASVAB) and has shown it to be a good predictor of training performance. Despite this, enlisted ATC training and post-training attrition is higher than desirable, prompting interest in alternate selection methods to augment current procedures. The current study examined the utility of the FAA Air Traffic Selection and Training (AT-SAT) battery for incrementing the predictiveness of the ASVAB versus several enlisted ATC training criteria. Subjects were 448 USAF enlisted ATC students who were administered the ASVAB and FAA AT-SAT subtests and subsequently graduated or were eliminated from apprentice-level training. Training criteria were a dichotomous graduation/elimination training score, average ATC fundamentals course score, and FAA certified tower operator test score. Results confirmed the predictive validity of the ASVAB and showed that one of the AT-SAT subtests resembling a low-fidelity ATC work sample significantly improved prediction of training performance beyond the ASVAB alone. Results suggested training attrition could be reduced by raising the current ASVAB minimum qualifying score. However, this approach may make it difficult to identify sufficient numbers of trainees and lead to adverse impact. Although the AT-SAT ATC work sample subtest showed incremental validity to the ASVAB, its length (95 min) may be problematic in operational testing. Recommendations are made for additional studies to address issues affecting operational implementation.

Applied Survey Sampling

ERIC Educational Resources Information Center

Blair, Edward; Blair, Johnny

2015-01-01

Written for students and researchers who wish to understand the conceptual and practical aspects of sampling, this book is designed to be accessible without requiring advanced statistical training. It covers a wide range of topics, from the basics of sampling to special topics such as sampling rare populations, sampling organizational populations,…

Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

PubMed Central

Thanh Noi, Phan; Kappas, Martin

2017-01-01

In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost classifiers at producing high accuracies. However, only a few studies have compared the performances of these classifiers with different training sample sizes for the same remote sensing images, particularly the Sentinel-2 Multispectral Imager (MSI). In this study, we examined and compared the performances of the RF, kNN, and SVM classifiers for land use/cover classification using Sentinel-2 image data. An area of 30 × 30 km2 within the Red River Delta of Vietnam with six land use/cover types was classified using 14 different training sample sizes, including balanced and imbalanced, from 50 to over 1250 pixels/class. All classification results showed a high overall accuracy (OA) ranging from 90% to 95%. Among the three classifiers and 14 sub-datasets, SVM produced the highest OA with the least sensitivity to the training sample sizes, followed consecutively by RF and kNN. In relation to the sample size, all three classifiers showed a similar and high OA (over 93.85%) when the training sample size was large enough, i.e., greater than 750 pixels/class or representing an area of approximately 0.25% of the total study area. The high accuracy was achieved with both imbalanced and balanced datasets. PMID:29271909

Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery.

PubMed

Thanh Noi, Phan; Kappas, Martin

2017-12-22

In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost classifiers at producing high accuracies. However, only a few studies have compared the performances of these classifiers with different training sample sizes for the same remote sensing images, particularly the Sentinel-2 Multispectral Imager (MSI). In this study, we examined and compared the performances of the RF, kNN, and SVM classifiers for land use/cover classification using Sentinel-2 image data. An area of 30 × 30 km² within the Red River Delta of Vietnam with six land use/cover types was classified using 14 different training sample sizes, including balanced and imbalanced, from 50 to over 1250 pixels/class. All classification results showed a high overall accuracy (OA) ranging from 90% to 95%. Among the three classifiers and 14 sub-datasets, SVM produced the highest OA with the least sensitivity to the training sample sizes, followed consecutively by RF and kNN. In relation to the sample size, all three classifiers showed a similar and high OA (over 93.85%) when the training sample size was large enough, i.e., greater than 750 pixels/class or representing an area of approximately 0.25% of the total study area. The high accuracy was achieved with both imbalanced and balanced datasets.

An Organization's Economic Return on Training Investment.

ERIC Educational Resources Information Center

Pucel, David J.; Lyau, Nyan-Myau

A study examined the relationship between investment in training and labor productivity in a sample of 237 large and medium-size Taiwanese firms producing auto parts. Of the 162 firms (68.4%) that returned usable questionnaires, 142 (59.9%) had training programs and 131 (55.3%) provided full cost data. The data were analyzed by multiple regression…

Evaluating Rater Responses to an Online Training Program for L2 Writing Assessment

ERIC Educational Resources Information Center

Elder, Catherine; Barkhuizen, Gary; Knoch, Ute; von Randow, Janet

2007-01-01

The use of online rater self-training is growing in popularity and has obvious practical benefits, facilitating access to training materials and rating samples and allowing raters to reorient themselves to the rating scale and self monitor their behaviour at their own convenience. However there has thus far been little research into rater…

The Perceived Relevance and Efficacy of a Graduate School Journal among Graduate Faculty and Training Directors

ERIC Educational Resources Information Center

Doran, Jennifer M.; Antonius, Daniel; Brown, Adam D.; Kriss, Alexander; Lehr, Evangeline Y. C.; Evans, Jason; Steele, Howard

2012-01-01

A total of 35 psychology department members from 21 universities assessed the relevance and efficacy of the "New School Psychology Bulletin" ("NSPB"), a graduate student journal, to training in psychology. Overall, a small sample of psychology department members viewed "NSPB" as an effective vehicle for student training. Perceptions among faculty…

Training Staff to Measure the Engagement of Children with Disabilities in Inclusive Childcare Centres

ERIC Educational Resources Information Center

Kishida, Yuriko; Kemp, Coral

2010-01-01

Practitioner use of the revised Individual Child Engagement Record--Revised (ICER-R) for observing children with disabilities in inclusive childcare is examined. Training in the use of the ICER-R, which includes both a momentary time sampling observation system and rating scales, was provided across two training phases with five to seven…

Designs for the Evaluation of Teacher Training Materials. Report No. 2.

ERIC Educational Resources Information Center

Okey, James R.; Ciesla, Jerome L.

This paper describes methods to assess the impact on students of a teacher using skills learned in a training program. Three designs for assessing the effects of teacher training materials are presented: time series design, equivalent time-samples design, and posttest-only control group design. Data obtained by classroom teachers while using the…

Multicultural Training in Doctoral School Psychology Programs: In Search of the Model Program?

ERIC Educational Resources Information Center

Kearns, Tori; Ford, Laurie; Brown, Kimberly

The multicultural training (MCT) of APA-accredited School Psychology programs was studied. The sample included faculty and students from five programs nominated for strong MCT and five comparison programs randomly selected from the list of remaining APA-accredited programs. Program training was evaluated using a survey based on APA guidelines for…

A National Overview of the Training Received by Certified Nursing Assistants Working in U.S. Nursing Homes

ERIC Educational Resources Information Center

Sengupta, Manisha; Harris-Kojetin, Lauren D.; Ejaz, Farida K.

2010-01-01

A few geographically limited studies have indicated that training of direct care workers may be insufficient. Using the first-ever nationally representative sample of certified nursing assistants (CNAs) from the 2004 National Nursing Assistant Survey (NNAS), this descriptive article provides an overview of the type of initial training and…

Training Opportunities and Employee Exhaustion in Call Centres: Mediation by Psychological Contract Fulfilment

ERIC Educational Resources Information Center

Chambel, Maria Jose; Castanheira, Filipa

2012-01-01

The aim of this study is to analyse psychological contract fulfilment as a mechanism through which training affects stress in call centres. The hypotheses were tested on a sample of 412 call centre operators, using structural equation modelling to analyse their survey responses. Our results demonstrated that training is negatively related to…

Race/Ethnicity, Color-Blind Racial Attitudes, and Multicultural Counseling Competence: The Moderating Effects of Multicultural Counseling Training

ERIC Educational Resources Information Center

Chao, Ruth Chu-Lien; Wei, Meifen; Good, Glenn E.; Flores, Lisa Y.

2011-01-01

Increasing trainees' multicultural counseling competence (MCC) has been a hot topic in counseling. Scholars have identified predictors (e.g., race/ethnicity, color-blindness) of MCC, and educators provide multicultural training for trainees. Using a sample of 370 psychology trainees, this study examined whether multicultural training (a) moderated…

Practising Mental Rotation Using Interactive Desktop Mental Rotation Trainer (iDeMRT)

ERIC Educational Resources Information Center

Rafi, Ahmad; Samsudin, Khairulanuar

2009-01-01

An experimental study involving 30 undergraduates (mean age = 20.5 years) in mental rotation (MR) training was conducted in an interactive Desktop Mental Rotation Trainer (iDeMRT). Stratified random sampling assigned students into one experimental group and one control group. The former trained in iDeMRT and the latter trained in conventional…

Effectiveness of the training material in drug-dose calculation skills.

PubMed

Basak, Tulay; Aslan, Ozlem; Unver, Vesile; Yildiz, Dilek

2016-07-01

The aim of study was to evaluate the effectiveness of the training material based on low-level environmental fidelity simulation in drug-dose calculation skills in senior nursing students. A quasi-experimental design with one group. The sample included senior nursing students attending a nursing school in Turkey in the period December 2012-January 2013. Eighty-two senior nursing students were included in the sample. Data were obtained using a data collection form which was developed by the researchers. A paired-sample t-test was used to compare the pretest and post-test scores. The difference between the mean pretest score and the mean post-test score was statistically significant (P < 0.05). This study revealed that the training material based on low-level environmental fidelity simulation positively impacted accurate drug-dose calculation skills in senior nursing students. © 2016 Japan Academy of Nursing Science.

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

PubMed Central

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

2015-01-01

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

The Influence of Cognitive Training on Older Adults’ Recall for Short Stories

PubMed Central

Sisco, S. M.; Marsiske, M; Gross, A. L.; Rebok, G. W.

2013-01-01

Objectives This paper investigated how a multi-component memory intervention affected memory for prose. We compared verbatim and paraphrased recall for short stories immediately and 1-, 2-, 3- and 5-years post-intervention in the ACTIVE (Advanced Cognitive Training for Independent and Vital Elderly) sample. Methods We studied 1,912 ACTIVE participants aged 65–91. Participants were randomized into one of three training arms (Memory, Reasoning, Speed of Processing) or a no-contact Control group; about half of the trained participants received additional booster training 1 and 3 years post-intervention. Results Memory-trained participants showed higher verbatim recall than non-memory-trained participants. Booster memory training led to higher verbatim recall. Memory training effects were evident immediately following training and not after one year following training. Discussion Results suggest that multi-factorial memory training can improve verbatim recall for prose, but the effect does not last without continued intervention. PMID:24385636

The influence of cognitive training on older adults' recall for short stories.

PubMed

Sisco, Shannon M; Marsiske, Michael; Gross, Alden L; Rebok, George W

2013-12-01

This article investigated how a multicomponent memory intervention affected memory for prose. We compared verbatim and paraphrased recall for short stories immediately and 1, 2, 3, and 5 years post-intervention in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) sample. We studied 1,912 ACTIVE participants aged 65 to 91. Participants were randomized into one of three training arms (Memory, Reasoning, Speed of Processing) or a no-contact Control group; about half of the trained participants received additional booster training 1 and 3 years post-intervention. Memory-trained participants showed higher verbatim recall than non-memory-trained participants. Booster-memory training led to higher verbatim recall. Memory training effects were evident immediately following training and not after 1 year following training. Results suggest that multifactorial memory training can improve verbatim recall for prose, but the effect does not last without continued intervention.

Geometrical features assessment of liver's tumor with application of artificial neural network evolved by imperialist competitive algorithm.

PubMed

Keshavarz, M; Mojra, A

2015-05-01

Geometrical features of a cancerous tumor embedded in biological soft tissue, including tumor size and depth, are a necessity in the follow-up procedure and making suitable therapeutic decisions. In this paper, a new socio-politically motivated global search strategy which is called imperialist competitive algorithm (ICA) is implemented to train a feed forward neural network (FFNN) to estimate the tumor's geometrical characteristics (FFNNICA). First, a viscoelastic model of liver tissue is constructed by using a series of in vitro uniaxial and relaxation test data. Then, 163 samples of the tissue including a tumor with different depths and diameters are generated by making use of PYTHON programming to link the ABAQUS and MATLAB together. Next, the samples are divided into 123 samples as training dataset and 40 samples as testing dataset. Training inputs of the network are mechanical parameters extracted from palpation of the tissue through a developing noninvasive technology called artificial tactile sensing (ATS). Last, to evaluate the FFNNICA performance, outputs of the network including tumor's depth and diameter are compared with desired values for both training and testing datasets. Deviations of the outputs from desired values are calculated by a regression analysis. Statistical analysis is also performed by measuring Root Mean Square Error (RMSE) and Efficiency (E). RMSE in diameter and depth estimations are 0.50 mm and 1.49, respectively, for the testing dataset. Results affirm that the proposed optimization algorithm for training neural network can be useful to characterize soft tissue tumors accurately by employing an artificial palpation approach. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of a segment-based LANDSAT full-frame approach to corp area estimation

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Hixson, M. M.; Davis, S. M.

1981-01-01

As the registration of LANDSAT full frames enters the realm of current technology, sampling methods should be examined which utilize other than the segment data used for LACIE. The effect of separating the functions of sampling for training and sampling for area estimation. The frame selected for analysis was acquired over north central Iowa on August 9, 1978. A stratification of he full-frame was defined. Training data came from segments within the frame. Two classification and estimation procedures were compared: statistics developed on one segment were used to classify that segment, and pooled statistics from the segments were used to classify a systematic sample of pixels. Comparisons to USDA/ESCS estimates illustrate that the full-frame sampling approach can provide accurate and precise area estimates.

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

Rottmann, Joerg; Berbeco, Ross

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable tomore » overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). Conclusions: A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.« less

A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis

NASA Astrophysics Data System (ADS)

An, Le; Adeli, Ehsan; Liu, Mingxia; Zhang, Jun; Lee, Seong-Whan; Shen, Dinggang

2017-03-01

Classification is one of the most important tasks in machine learning. Due to feature redundancy or outliers in samples, using all available data for training a classifier may be suboptimal. For example, the Alzheimer’s disease (AD) is correlated with certain brain regions or single nucleotide polymorphisms (SNPs), and identification of relevant features is critical for computer-aided diagnosis. Many existing methods first select features from structural magnetic resonance imaging (MRI) or SNPs and then use those features to build the classifier. However, with the presence of many redundant features, the most discriminative features are difficult to be identified in a single step. Thus, we formulate a hierarchical feature and sample selection framework to gradually select informative features and discard ambiguous samples in multiple steps for improved classifier learning. To positively guide the data manifold preservation process, we utilize both labeled and unlabeled data during training, making our method semi-supervised. For validation, we conduct experiments on AD diagnosis by selecting mutually informative features from both MRI and SNP, and using the most discriminative samples for training. The superior classification results demonstrate the effectiveness of our approach, as compared with the rivals.

Yoga Training in Junior Primary School-Aged Children Has an Impact on Physical Self-Perceptions and Problem-Related Behavior

PubMed Central

Richter, Stefanie; Tietjens, Maike; Ziereis, Susanne; Querfurth, Sydney; Jansen, Petra

2016-01-01

The present pilot study investigated the effects of yoga training, as compared to physical skill training, on motor and executive function, physical self-concept, and anxiety-related behavior in junior primary school-aged children. Twenty-four participants with a mean age of 8.4 (±1.4) years completed either yoga or physical skill training twice a week for 6 weeks outside of regular school class time. Both forms of training were delivered in an individualized and child-oriented manner. The type of training did not result in any significant differences in movement and executive function outcomes. In terms of physical self-concept, significant group differences were revealed only for perceived movement speed such that yoga training resulted in perceptions of being slower while physical skill training resulted in perceptions of moving faster. Analysis of anxiety related outcomes revealed significant group effects only for avoidance behavior and coping strategies. Avoidance behavior increased following yoga training, but decreased following physical skill training. In addition, following yoga training, children showed an increased use of divergent coping strategies when facing problematic situations while after physical skill training children demonstrated a decrease in use of divergent coping strategies. Changes in overall physical self-concept scores were not significantly correlated with changes in avoidance behavior following yoga training. In contrast, following physical skill training increased physical self-concept was significantly correlated with decreases in avoidance behavior. In sum, exposure to yoga or physical skill training appears to result in distinct effects for specific domains of physical self-concept and anxiety-related behavior. Further studies with larger samples and more rigorous methodologies are required to further investigate the effects reported here. With respect to future studies, we address potential research questions and specific features associated with the investigation of the effects of yoga in a sample of school-aged children. PMID:26941676

A Comparison of the Career Maturity, Self Concept and Academic Achievement of Female Cooperative Vocational Office Training Students, Intensive Business Training Students, and Regular Business Education Students in Selected High Schools in Mississippi.

ERIC Educational Resources Information Center

Seaward, Marty Robertson

The purpose of this study was to compare the career maturity, self concept, and academic achievement of female students enrolled in intensive business training (IBT), cooperative vocational office training (CVOT), and regular business education programs. A sample of 240 students, equalized into three groups on the basis of IQ scores, were given…

Feasibility of a Humor Training to Promote Humor and Decrease Stress in a Subclinical Sample: A Single-Arm Pilot Study

PubMed Central

Tagalidou, Nektaria; Loderer, Viola; Distlberger, Eva; Laireiter, Anton-Rupert

2018-01-01

The present study investigates the feasibility of a humor training for a subclinical sample suffering from increased stress, depressiveness, or anxiety. Based on diagnostic interviews, 35 people were invited to participate in a 7-week humor training. Evaluation measures were filled in prior training, after training, and at a 1-month follow-up including humor related outcomes (coping humor and cheerfulness) and mental health-related outcomes (perceived stress, depressiveness, anxiety, and well-being). Outcomes were analyzed using repeated-measures ANOVAs. Within-group comparisons of intention-to-treat analysis showed main effects of time with large effect sizes on all outcomes. Post hoc tests showed medium to large effect sizes on all outcomes from pre to post and results remained stable until follow-up. Satisfaction with the training was high, attrition rate low (17.1%), and participants would highly recommend the training. Summarizing the results, the pilot study showed promising effects for people suffering from subclinical symptoms. All outcomes were positively influenced and showed stability over time. Humor trainings could be integrated more into mental health care as an innovative program to reduce stress whilst promoting also positive emotions. However, as this study was a single-arm pilot study, further research (including also randomized controlled trials) is still needed to evaluate the effects more profoundly. PMID:29740368

Training in Tbilisi nuclear facility provides new sampling perspectives for IAEA inspectors

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

Brim, Cornelia P.

2016-06-08

Office of Nonproliferation and Arms Control- (NPAC-) sponsored training in a “cold” nuclear facility in Tbilisi, Georgia provides International Atomic Energy Agency (IAEA) inspectors with a new perspective on environmental sampling strategies. Sponsored by the Nuclear Safeguards program under the NPAC, Pacific Northwest National Laboratory (PNNL) experts have been conducting an annual weeklong class for IAEA inspectors in a closed nuclear facility since 2011. The Andronikashvili Institute of Physics and the Republic of Georgia collaborate with PNNL to provide the training, and the U.S. Department of State, the U.S. Embassy in Tbilisi and the U.S. Mission to International Organizations inmore » Vienna provide logistical support.« less

Strength training improves the tri-digit finger-pinch force control of older adults.

PubMed

Keogh, Justin W; Morrison, Steve; Barrett, Rod

2007-08-01

To investigate the effect of unilateral upper-limb strength training on the finger-pinch force control of older men. Pretest and post-test 6-week intervention study. Exercise science research laboratory. Eleven neurologically fit older men (age range, 70-80y). The strength training group (n=7) trained twice a week for 6 weeks, performing dumbbell bicep curls, wrist flexions, and wrists extensions, while the control group subjects (n=4) maintained their normal activities. Changes in force variability, targeting error, peak power frequency, proportional power, sample entropy, digit force sharing, and coupling relations were assessed during a series of finger-pinch tasks. These tasks involved maintaining a constant or sinusoidal force output at 20% and 40% of each subject's maximum voluntary contraction. All participants performed the finger-pinch tasks with both the preferred and nonpreferred limbs. Analysis of covariance for between-group change scores indicated that the strength training group (trained limb) experienced significantly greater reductions in finger-pinch force variability and targeting error, as well as significantly greater increases in finger-pinch force, sample entropy, bicep curl, and wrist flexion strength than did the control group. A nonspecific upper-limb strength-training program may improve the finger-pinch force control of older men.

Training for vigilance on the move: a video game-based paradigm for sustained attention.

PubMed

Szalma, J L; Daly, T N; Teo, G W L; Hancock, G M; Hancock, P A

2018-04-01

The capacity for superior vigilance can be trained by using knowledge of results (KR). Our present experiments demonstrate the efficacy of such training using a first-person perspective movement videogame-based platform in samples of students and Soldiers. Effectiveness was assessed by manipulating KR during a training phase and withdrawing it in a subsequent transfer phase. Relative to a no KR control condition, KR systematically improved performance for both Soldiers and students. These results build upon our previous findings that demonstrated that a video game-based platform can be used to create a movement-centred sustained attention task with important elements of traditional vigilance. The results indicate that KR effects in sustained attention extend to a first person perspective movement based paradigm, and that these effects occur in professional military as well as a more general population. Such sustained attention training can save lives and the present findings demonstrate one particular avenue to achieve this goal. Practitioner Summary: Sustained attention can be trained by means of knowledge of results using a videogame-based platform with samples of students and Soldiers. Four experiments demonstrate that a dynamic, first-person perspective video game environment can serve to support effective sustained attention training in professional military as well as a more general population.

Mindfulness meditation training alters stress-related amygdala resting state functional connectivity: a randomized controlled trial.

PubMed

Taren, Adrienne A; Gianaros, Peter J; Greco, Carol M; Lindsay, Emily K; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K; Ferris, Jennifer L; Julson, Erica; Marsland, Anna L; Bursley, James K; Ramsburg, Jared; Creswell, J David

2015-12-01

Recent studies indicate that mindfulness meditation training interventions reduce stress and improve stress-related health outcomes, but the neural pathways for these effects are unknown. The present research evaluates whether mindfulness meditation training alters resting state functional connectivity (rsFC) of the amygdala, a region known to coordinate stress processing and physiological stress responses. We show in an initial discovery study that higher perceived stress over the past month is associated with greater bilateral amygdala-subgenual anterior cingulate cortex (sgACC) rsFC in a sample of community adults (n = 130). A follow-up, single-blind randomized controlled trial shows that a 3-day intensive mindfulness meditation training intervention (relative to a well-matched 3-day relaxation training intervention without a mindfulness component) reduced right amygdala-sgACC rsFC in a sample of stressed unemployed community adults (n = 35). Although stress may increase amygdala-sgACC rsFC, brief training in mindfulness meditation could reverse these effects. This work provides an initial indication that mindfulness meditation training promotes functional neuroplastic changes, suggesting an amygdala-sgACC pathway for stress reduction effects. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Effects of consensus training on the reliability of auditory perceptual ratings of voice quality.

PubMed

Iwarsson, Jenny; Reinholt Petersen, Niels

2012-05-01

This study investigates the effect of consensus training of listeners on intrarater and interrater reliability and agreement of perceptual voice analysis. The use of such training, including a reference voice sample, could be assumed to make the internal standards held in memory common and more robust, which is of great importance to reduce the variability of auditory perceptual ratings. A prospective design with testing before and after training. Thirteen students of audiologopedics served as listening subjects. The ratings were made using a multidimensional protocol with four-point equal-appearing interval scales. The stimuli consisted of text reading by authentic dysphonic patients. The consensus training for each perceptual voice parameter included (1) definition, (2) underlying physiology, (3) presentation of carefully selected sound examples representing the parameter in three different grades followed by group discussions of perceived characteristics, and (4) practical exercises including imitation to make use of the listeners' proprioception. Intrarater reliability and agreement showed a marked improvement for intermittent aphonia but not for vocal fry. Interrater reliability was high for most parameters before training with a slight increase after training. Interrater agreement showed marked increases for most voice quality parameters as a result of the training. The results support the recommendation of specific consensus training, including use of a reference voice sample material, to calibrate, equalize, and stabilize the internal standards held in memory by the listeners. Copyright © 2012 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Systems and methods for selective detection and imaging in coherent Raman microscopy by spectral excitation shaping

DOEpatents

Xie, Xiaoliang Sunney; Freudiger, Christian; Min, Wei

2016-03-15

A microscopy imaging system is disclosed that includes a light source system, a spectral shaper, a modulator system, an optics system, an optical detector and a processor. The light source system is for providing a first train of pulses and a second train of pulses. The spectral shaper is for spectrally modifying an optical property of at least some frequency components of the broadband range of frequency components such that the broadband range of frequency components is shaped producing a shaped first train of pulses to specifically probe a spectral feature of interest from a sample, and to reduce information from features that are not of interest from the sample. The modulator system is for modulating a property of at least one of the shaped first train of pulses and the second train of pulses at a modulation frequency. The optical detector is for detecting an integrated intensity of substantially all optical frequency components of a train of pulses of interest transmitted or reflected through the common focal volume. The processor is for detecting a modulation at the modulation frequency of the integrated intensity of substantially all of the optical frequency components of the train of pulses of interest due to the non-linear interaction of the shaped first train of pulses with the second train of pulses as modulated in the common focal volume, and for providing an output signal for a pixel of an image for the microscopy imaging system.

Temporal Texture Profile and Identification of Glass Transition Temperature as an Instrumental Predictor of Stickiness in a Caramel System.

PubMed

Mayhew, Emily J; Schmidt, Shelly J; Schlich, Pascal; Lee, Soo-Yeun

2017-09-01

Stickiness is an important texture attribute in many food systems, but its meaning can vary by person, product, and throughout mastication. This variability and complexity makes it difficult to devise analytical tests that accurately and consistently predict sensory stickiness. Glass transition temperature (T g ) is a promising candidate for texture prediction. Our objective is to elucidate the temporal profile of stickiness in order to probe the relationship between T g and dynamic stickiness perception. Nine caramel samples with diverse texture and thermal profiles were produced for sensory testing and differential scanning calorimetry. Sixteen trained panelists generated stickiness-relevant terms to be used in a subsequent temporal dominance of sensation (TDS) test with the same panelists. Following the TDS study, these panelists also rated samples for overall tactile and oral stickiness. Stickiness ratings were then correlated to TDS dominance parameters across the full evaluation period and within the first, middle, and final thirds of the evaluation period. Samples with temporal texture profiles dominated by tacky, stringy, and enveloping attributes consistently received the highest stickiness scores, although the correlation strength varied by time period. T g was found to correlate well with trained panelist and consumer ratings of oral (R 2 trained = 0.85; R 2 consumer = 0.96) and tactile (R 2 trained = 0.78; R 2 consumer = 0.79) stickiness intensity, and stickiness intensity ratings decreased with T g of completely amorphous samples. Further, glassy samples followed a different texture trajectory (brittle-cohesive-toothpacking) than rubbery samples (deformable-tacky-enveloping). These results illuminate the dynamic perception of stickiness and support the potential of T g to predict both stickiness intensity and texture trajectory in caramel systems. © 2017 Institute of Food Technologists®.

Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis.

PubMed

Ozçift, Akin

2011-05-01

Supervised classification algorithms are commonly used in the designing of computer-aided diagnosis systems. In this study, we present a resampling strategy based Random Forests (RF) ensemble classifier to improve diagnosis of cardiac arrhythmia. Random forests is an ensemble classifier that consists of many decision trees and outputs the class that is the mode of the class's output by individual trees. In this way, an RF ensemble classifier performs better than a single tree from classification performance point of view. In general, multiclass datasets having unbalanced distribution of sample sizes are difficult to analyze in terms of class discrimination. Cardiac arrhythmia is such a dataset that has multiple classes with small sample sizes and it is therefore adequate to test our resampling based training strategy. The dataset contains 452 samples in fourteen types of arrhythmias and eleven of these classes have sample sizes less than 15. Our diagnosis strategy consists of two parts: (i) a correlation based feature selection algorithm is used to select relevant features from cardiac arrhythmia dataset. (ii) RF machine learning algorithm is used to evaluate the performance of selected features with and without simple random sampling to evaluate the efficiency of proposed training strategy. The resultant accuracy of the classifier is found to be 90.0% and this is a quite high diagnosis performance for cardiac arrhythmia. Furthermore, three case studies, i.e., thyroid, cardiotocography and audiology, are used to benchmark the effectiveness of the proposed method. The results of experiments demonstrated the efficiency of random sampling strategy in training RF ensemble classification algorithm. Copyright © 2011 Elsevier Ltd. All rights reserved.

Semi-Supervised Tripled Dictionary Learning for Standard-dose PET Image Prediction using Low-dose PET and Multimodal MRI

PubMed Central

Wang, Yan; Ma, Guangkai; An, Le; Shi, Feng; Zhang, Pei; Lalush, David S.; Wu, Xi; Pu, Yifei; Zhou, Jiliu; Shen, Dinggang

2017-01-01

Objective To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic resonance imaging (MRI). Methods It was achieved by patch-based sparse representation (SR), using the training samples with a complete set of MRI, L-PET and S-PET modalities for dictionary construction. However, the number of training samples with complete modalities is often limited. In practice, many samples generally have incomplete modalities (i.e., with one or two missing modalities) that thus cannot be used in the prediction process. In light of this, we develop a semi-supervised tripled dictionary learning (SSTDL) method for S-PET image prediction, which can utilize not only the samples with complete modalities (called complete samples) but also the samples with incomplete modalities (called incomplete samples), to take advantage of the large number of available training samples and thus further improve the prediction performance. Results Validation was done on a real human brain dataset consisting of 18 subjects, and the results show that our method is superior to the SR and other baseline methods. Conclusion This work proposed a new S-PET prediction method, which can significantly improve the PET image quality with low-dose injection. Significance The proposed method is favorable in clinical application since it can decrease the potential radiation risk for patients. PMID:27187939

Training and technical assistance for compliance with beverage and physical activity components of New York City's regulations for early child care centers.

PubMed

Kakietek, Jakub; Dunn, Lillian; O'Dell, Sarah Abood; Jernigan, Jan; Kettel Khan, Laura

2014-10-16

In 2006, the New York City Department of Health and Mental Hygiene (DOHMH) passed regulations for child care centers that established standards for beverages provided to children and set a minimum amount of time for daily physical activity. DOHMH offered several types of training and technical assistance to support compliance with the regulations. This article analyzes the association between training and technical assistance provided and compliance with the regulations in a sample of 174 group child care centers. Compliance was measured by using a site inventory of beverages stored on premises and a survey of centers' teachers regarding the amount of physical activity provided. Training and technical assistance measures were based on the DOHMH records of training and technical assistance provided to the centers in the sample and on a survey of center directors. Ordinal logistic regression was used to assess the association between training and technical assistance measures and compliance with the regulations. Measures of training related to physical activity the center received: the number of staff members who participated in Sport, Play and Active Recreation for Kids (SPARK) and other training programs in which a center participated were associated with better compliance with the physical activity regulations. Neither training nor technical assistance were associated with compliance with the regulations related to beverages. Increased compliance with regulations pertaining to physical activity was not related to compliance with beverage regulations. Future trainings should be targeted to the specific regulation requirements to increase compliance.

Method and system for laser-based formation of micro-shapes in surfaces of optical elements

DOEpatents

Bass, Isaac Louis; Guss, Gabriel Mark

2013-03-05

A method of forming a surface feature extending into a sample includes providing a laser operable to emit an output beam and modulating the output beam to form a pulse train having a plurality of pulses. The method also includes a) directing the pulse train along an optical path intersecting an exposed portion of the sample at a position i and b) focusing a first portion of the plurality of pulses to impinge on the sample at the position i. Each of the plurality of pulses is characterized by a spot size at the sample. The method further includes c) ablating at least a portion of the sample at the position i to form a portion of the surface feature and d) incrementing counter i. The method includes e) repeating steps a) through d) to form the surface feature. The sample is free of a rim surrounding the surface feature.

Scene recognition based on integrating active learning with dictionary learning

NASA Astrophysics Data System (ADS)

Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

2018-04-01

Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

NASA Astrophysics Data System (ADS)

Correa, R.; Chesta, M. A.; Morales, J. R.; Dinator, M. I.; Requena, I.; Vila, I.

2006-08-01

An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses.

Oregon Works: Assessing the Worker Training and Work Organization Practices of Oregon Employers.

ERIC Educational Resources Information Center

Oregon State Economic Development Dept., Salem.

In 1992, questionnaires regarding the training and work organization practices were mailed to a random sample of 4,000 Oregon employers, and focus groups were held with 100 Oregon managers/employers. The main findings from the completed questionnaires (43% response rate) were as follows: most Oregon employers do not plan for training or treat it…

Linking Rhetorical Sensitivity with the Ability of an Athletic Training Student to Successfully Perform a Patient Medical Interview

ERIC Educational Resources Information Center

Bertoncino, Thomas K.

2010-01-01

The purpose of this study was to investigate the extent to which the self-reported rhetorical sensitivity of a sample of athletic training students is positively related to successfully performing a patient medical interview. Particularly, the study focused on if athletic training students' reported communication behaviors is related to their…

Peer Deviancy Training and Peer Coercion: Dual Processes Associated with Early-Onset Conduct Problems

ERIC Educational Resources Information Center

Snyder, James; Schrepferman, Lynn; McEachern, Amber; Barner, Stacy; Johnson, Kassy; Provines, Jessica

2008-01-01

The prospective relationships of conduct problems and peer coercion and deviancy training during kindergarten (mean age = 5.3 years) to overt and covert conduct problems in third-fourth grade were examined in a sample of 267 boys and girls. Coercion and deviancy training were distinct peer processes. Both were associated with earlier child conduct…

Development of a Screening Methodology for Entry into Medical Technical Training Courses. Final Report for Period October 1975-April 1977.

ERIC Educational Resources Information Center

Leisey, Sandra A.; Guinn, Nancy

At the request of the Air Force School of Aviation Medicine, a project was initiated to evaluate the current screening process used for entry into three medical technical training courses: Aeromedical Specialist, Environmental Health Specialist, and Physiological Training Specialist. A sample of 1,003 students were administered the General…

Effects of Two Modes of Exercise Training on Physical Fitness of 10 Year-Old Children

ERIC Educational Resources Information Center

Ribeiro, Ligia G. dos Santos Chaves; Portal, Maria de Nazare Dias; da Silva, Joao Bittencourt; Saraiva, Alan; da Cruz Monte, Gerson, Jr.; Dantas, Estelio H. M.

2010-01-01

Study aim: To compare two exercise training modes on the physical fitness of 10 year-old children. Material and methods: A sample of 60 schoolboys aged 10 years were randomly divided into 3 groups: Traditional (TG), trained according to the Brazilian national curricular parameters, Maturational (MG), in which the degree of difficulty of the…

An Evaluation of the National Teachers' Institute's Manpower Training Program for Teaching Personnel in Mid-Western Nigeria

ERIC Educational Resources Information Center

Osunde, A. U.; Omoruyi, F. E. O.

2004-01-01

This study evaluated the manpower-training program for teaching personnel in mid-western Nigeria by the National Teachers' Institute. Overall, 240 participants involved in the training program who were randomly selected from the area constituted the sample for the study. A questionnaire designed by the authors was the major instrument used for…

Working Memory Training for Children with Cochlear Implants: A Pilot Study

ERIC Educational Resources Information Center

Kronenberger, William G.; Pisoni, David B.; Henning, Shirley C.; Colson, Bethany G.; Hazzard, Lindsey M.

2011-01-01

Purpose: This study investigated the feasibility and efficacy of a working memory training program for improving memory and language skills in a sample of 9 children who are deaf (age 7-15 years) with cochlear implants (CIs). Method: All children completed the Cogmed Working Memory Training program on a home computer over a 5-week period.…

Stress Prevention through a Time Management Training Intervention: An Experimental Study

ERIC Educational Resources Information Center

Häfner, Alexander; Stock, Armin; Pinneker, Lydia; Ströhle, Sabine

2014-01-01

The purpose of this study was to examine the effects of a short-term time management training programme on perceived control of time and perceived stress. The sample of 177 freshmen was randomly assigned to a time management training (n?=?89) and an active control group (CG) (n?=?88). We expected that an increase in external demands during the…

The effect of note-taking skills training on the achievement motivation in learning on B.A students in Shahid Bahonar University of Kerman and Kerman University of Medical Sciences (Iran).

PubMed

Sharifi, Parvane; Rahmati, Abbas; Saber, Maryam

2013-10-01

To evaluate the effect of note-taking skills training on the achievement motivation in learning. The experimental study comprised graduate students of the 2010-11 batch at Kerman's Bahonar University and Kerman's Medical Sciences University, Iran. The study sample included 110 people; 55 in the test group, and 55 in the control group. They were randomly selected and replaced through the single-stage cluster sampling. To collect the data, a questionnaire was used. Pre-test was performed before the training session in two groups. After training course, a post-test was taken. For data analysis, the independent t-test, was used. The average pre-test score of the test group was 182 +/- 34.15, while for the control group it was 191 +/- 30.37 (p < 0.089). After the training, the post-test showed statistically significant change. The test group scored 220 +/- 20.94 against the controls who scored 195 +/- 27.26 (p < 0.001). The findings showed that achievement motivation in learning increased significantly after imparting training in note-taking skills. Authorities in the educational system should invest more for promotion of such skills.

Police training in interviewing and interrogation methods: A comparison of techniques used with adult and juvenile suspects.

PubMed

Cleary, Hayley M D; Warner, Todd C

2016-06-01

Despite empirical progress in documenting and classifying various interrogation techniques, very little is known about how police are trained in interrogation methods, how frequently they use various techniques, and whether they employ techniques differentially with adult versus juvenile suspects. This study reports the nature and extent of formal (e.g., Reid Technique, PEACE, HUMINT) and informal interrogation training as well as self-reported technique usage in a diverse national sample (N = 340) of experienced American police officers. Officers were trained in a variety of different techniques ranging from comparatively benign pre-interrogation strategies (e.g., building rapport, observing body language or speech patterns) to more psychologically coercive techniques (e.g., blaming the victim, discouraging denials). Over half the sample reported being trained to use psychologically coercive techniques with both adults and juveniles. The majority (91%) receive informal, "on the job" interrogation training. Technique usage patterns indicate a spectrum of psychological intensity where information-gathering approaches were used most frequently and high-pressure tactics less frequently. Reid-trained officers (56%) were significantly more likely than officers without Reid training to use pre-interrogation and manipulation techniques. Across all analyses and techniques, usage patterns were identical for adult and juvenile suspects, suggesting that police interrogate youth in the same manner as adults. Overall, results suggest that training in specific interrogation methods is strongly associated with usage. Findings underscore the need for more law enforcement interrogation training in general, especially with juvenile suspects, and highlight the value of training as an avenue for reducing interrogation-induced miscarriages of justice. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The customer satisfaction towards the service quality of Tawang Alun Malang-Banyuwangi Train

NASA Astrophysics Data System (ADS)

Permatasari, D.

2017-06-01

Service sector which has quiet vital role in supporting people’s daily activities is transportation service. Transportation is one of the important and strategic developments in improving economy sector. One of the alternative ways to overcome people’s need of transportation is by providing trains. This research was conducted on the weekend that has objectives to analyze the work performance of Indonesian Railway Company towards the service quality that can determine the customers’ satisfaction of TawangAlun Malang-Banyuwangi train and to analyze the customers’ satisfaction itself towards the service quality of TawangAlun Malang-Banyuwangi train. This research used quantitative descriptive as the research method. There are two kinds of data that were used in this research; the first one is the primary data taken from questionnaire’s results and interview meanwhile the second one is the secondary data taken from literature and internet. The sample used in this research is nonprobability sampling using convenience sampling technique. Data analysis used in this research is Importance Performance Analysis (IPA) and Customer Satisfaction index (CSI). The results are the Indonesian Railway Company should make a new innovation to buy the ticket from the ticket machine and add more exhausts in every railway coach.

Using Opinions and Knowledge to Identify Natural Groups of Gambling Employees.

PubMed

Gray, Heather M; Tom, Matthew A; LaPlante, Debi A; Shaffer, Howard J

2015-12-01

Gaming industry employees are at higher risk than the general population for health conditions including gambling disorder. Responsible gambling training programs, which train employees about gambling and gambling-related problems, might be a point of intervention. However, such programs tend to use a "one-size-fits-all" approach rather than multiple tiers of instruction. We surveyed employees of one Las Vegas casino (n = 217) and one online gambling operator (n = 178) regarding their gambling-related knowledge and opinions prior to responsible gambling training, to examine the presence of natural knowledge groups among recently hired employees. Using k-means cluster analysis, we observed four natural groups within the Las Vegas casino sample and two natural groups within the online operator sample. We describe these natural groups in terms of opinion/knowledge differences as well as distributions of demographic/occupational characteristics. Gender and language spoken at home were correlates of cluster group membership among the sample of Las Vegas casino employees, but we did not identify demographic or occupational correlates of cluster group membership among the online gambling operator employees. Gambling operators should develop more sophisticated training programs that include instruction that targets different natural knowledge groups.

A behavior analytic analogue of learning to use synonyms, syntax, and parts of speech.

PubMed

Chase, Philip N; Ellenwood, David W; Madden, Gregory

2008-01-01

Matching-to-sample and sequence training procedures were used to develop responding to stimulus classes that were considered analogous to 3 aspects of verbal behavior: identifying synonyms and parts of speech, and using syntax. Matching-to-sample procedures were used to train 12 paired associates from among 24 stimuli. These pairs were analogous to synonyms. Then, sequence characteristics were trained to 6 of the stimuli. The result was the formation of 3 classes of 4 stimuli, with the classes controlling a sequence response analogous to a simple ordering syntax: first, second, and third. Matching-to-sample procedures were then used to add 4 stimuli to each class. These stimuli, without explicit sequence training, also began to control the same sequence responding as the other members of their class. Thus, three 8-member functionally equivalent sequence classes were formed. These classes were considered to be analogous to parts of speech. Further testing revealed three 8-member equivalence classes and 512 different sequences of first, second, and third. The study indicated that behavior analytic procedures may be used to produce some generative aspects of verbal behavior related to simple syntax and semantics.

NASA Sample Return Missions: Recovery Operations

NASA Technical Reports Server (NTRS)

Pace, L. F.; Cannon, R. E.

2017-01-01

The Utah Test and Training Range (UTTR), southwest of Salt Lake City, Utah, is the site of all NASA unmanned sample return missions. To date these missions include the Genesis solar wind samples (2004) and Stardust cometary and interstellar dust samples (2006). NASA’s OSIRIS-REx Mission will return its first asteroid sample at UTTR in 2023.

Retraumatization Mediates the Effect of Adverse Childhood Experiences on Clinical Training-Related Secondary Traumatic Stress Symptoms.

PubMed

Butler, Lisa D; Maguin, Eugene; Carello, Janice

2018-01-01

Previous research (Butler, Carello, & Maguin, 2016) has found that exposure to trauma-related material in graduate clinical coursework and field training can put students at risk for reactivations of feelings/memories from negative past experiences (retraumatization) and for secondary traumatic stress (STS) symptoms. The present report sought to examine the role, if any, of adverse childhood experiences (ACEs) in these outcomes. Using the Butler et al. (2016) sample, we examined: (1) rates of ACEs in 195 graduate social work students, (2) whether the total number of ACEs was associated with training-related retraumatization (TRT) and/or STS symptoms, and (3) if TRT mediated the relationship between ACEs and STS symptoms. The results indicate that more than three quarters of the sample had experienced one or more ACEs before age 18 and almost one third endorsed 4 or more. The most commonly reported ACEs were household mental illness, parental separation/divorce, household alcohol/substance abuse, and emotional abuse or neglect by a parent or household member. Higher ACE scores were associated with increased likelihood of TRT experiences and STS symptoms during training. A mediation analysis confirmed that TRT mediated the effect of ACE scores on STS symptoms; this finding also provides support for the role of proximal emotional reactions in mediating the effects of distal adverse experiences on the development of trauma symptoms. In summary, despite the evident resilience of this graduate student sample, those with ACE histories were at heightened risk for training-related distress. These results underscore the need for a trauma-informed approach to clinical training.

The state of chronic pain education in geriatric medicine fellowship training programs: results of a national survey.

PubMed

Weiner, Debra K; Turner, Gregory H; Hennon, John G; Perera, Subashan; Hartmann, Susanne

2005-10-01

A survey of U.S. geriatric medicine fellowship training programs was performed to assess the status of teaching about chronic pain evaluation and management and identify opportunities for improvement. After an initial e-mail query, 43 of 96 programs agreed to participate. A self-administered questionnaire, with items adapted from a 2002 consensus panel statement, was mailed to their 171 fellows-in-training and 43 fellowship directors. Thirty-two programs (33% of nationwide sample) including 79 fellows (30% of nationwide sample) and 25 directors (26% of nationwide sample) returned surveys; 21 institutions returned both faculty and fellow surveys. Overall, directors endorsed the 19 items identified by the consensus panel as essential components of fellowship training, but fellows identified deficiencies, both before and during fellowship training. Specific areas of undereducation included comprehensive musculoskeletal assessment, neuropathic pain evaluation, indications for low back pain imaging, the role of multidisciplinary pain clinics and nonpharmacological modalities, the effect of physical and psychosocial comorbidities in formulating treatment goals, and the effect of aging on analgesic metabolism and prescription. Both groups were generally positive about fellows' abilities to implement pain-related clinical skills. Discrepancies existed between fellowship directors' ratings of importance of teaching individual items and the degree to which teaching was actually done, as well as faculty versus fellow assessments of whether some of the 19 items were taught. Primary care training programs (e.g., internal medicine, family medicine, geriatric medicine) should pay more systematic attention to educating trainees about chronic pain to optimize patient care, decrease suffering, and diminish healthcare expenditures.

A non-invasive tool for detecting cervical cancer odor by trained scent dogs.

PubMed

Guerrero-Flores, Héctor; Apresa-García, Teresa; Garay-Villar, Ónix; Sánchez-Pérez, Alejandro; Flores-Villegas, David; Bandera-Calderón, Artfy; García-Palacios, Raúl; Rojas-Sánchez, Teresita; Romero-Morelos, Pablo; Sánchez-Albor, Verónica; Mata, Osvaldo; Arana-Conejo, Víctor; Badillo-Romero, Jesús; Taniguchi, Keiko; Marrero-Rodríguez, Daniel; Mendoza-Rodríguez, Mónica; Rodríguez-Esquivel, Miriam; Huerta-Padilla, Víctor; Martínez-Castillo, Andrea; Hernández-Gallardo, Irma; López-Romero, Ricardo; Bandala, Cindy; Rosales-Guevara, Juan; Salcedo, Mauricio

2017-01-26

Cervical Cancer (CC) has become a public health concern of alarming proportions in many developing countries such as Mexico, particularly in low income sectors and marginalized regions. As such, an early detection is a key medical factor in improving not only their population's quality of life but also its life expectancy. Interestingly, there has been an increase in the number of reports describing successful attempts at detecting cancer cells in human tissues or fluids using trained (sniffer) dogs. The great odor detection threshold exhibited by dogs is not unheard of. However, this represented a potential opportunity to develop an affordable, accessible, and non-invasive method for detection of CC. Using clicker training, a male beagle was trained to recognize CC odor. During training, fresh CC biopsies were used as a reference point. Other samples used included cervical smears on glass slides and medical surgical bandages used as intimate sanitary pads by CC patients. A double-blind procedure was exercised when testing the beagle's ability to discriminate CC from control samples. The beagle was proven able to detect CC-specific volatile organic compounds (VOC) contained in both fresh cervical smear samples and adsorbent material samples. Beagle's success rate at detecting and discriminating CC and non-CC odors, as indicated by specificity and sensitivity values recorded during the experiment, stood at an overall high (>90%). CC-related VOC in adsorbent materials were detectable after only eight hours of use by CC patients. Present data suggests different applications for VOC from the uterine cervix to be used in the detection and diagnosis of CC. Furthermore, data supports the use of trained dogs as a viable, affordable, non-invasive and, therefore, highly relevant alternative method for detection of CC lesions. Additional benefits of this method include its quick turnaround time and ease of use while remaining highly accurate and robust.

Disaster response team FAST skills training with a portable ultrasound simulator compared to traditional training: pilot study.

PubMed

Paddock, Michael T; Bailitz, John; Horowitz, Russ; Khishfe, Basem; Cosby, Karen; Sergel, Michelle J

2015-03-01

Pre-hospital focused assessment with sonography in trauma (FAST) has been effectively used to improve patient care in multiple mass casualty events throughout the world. Although requisite FAST knowledge may now be learned remotely by disaster response team members, traditional live instructor and model hands-on FAST skills training remains logistically challenging. The objective of this pilot study was to compare the effectiveness of a novel portable ultrasound (US) simulator with traditional FAST skills training for a deployed mixed provider disaster response team. We randomized participants into one of three training groups stratified by provider role: Group A. Traditional Skills Training, Group B. US Simulator Skills Training, and Group C. Traditional Skills Training Plus US Simulator Skills Training. After skills training, we measured participants' FAST image acquisition and interpretation skills using a standardized direct observation tool (SDOT) with healthy models and review of FAST patient images. Pre- and post-course US and FAST knowledge were also assessed using a previously validated multiple-choice evaluation. We used the ANOVA procedure to determine the statistical significance of differences between the means of each group's skills scores. Paired sample t-tests were used to determine the statistical significance of pre- and post-course mean knowledge scores within groups. We enrolled 36 participants, 12 randomized to each training group. Randomization resulted in similar distribution of participants between training groups with respect to provider role, age, sex, and prior US training. For the FAST SDOT image acquisition and interpretation mean skills scores, there was no statistically significant difference between training groups. For US and FAST mean knowledge scores, there was a statistically significant improvement between pre- and post-course scores within each group, but again there was not a statistically significant difference between training groups. This pilot study of a deployed mixed-provider disaster response team suggests that a novel portable US simulator may provide equivalent skills training in comparison to traditional live instructor and model training. Further studies with a larger sample size and other measures of short- and long-term clinical performance are warranted.

Effectiveness of training in organizations: a meta-analysis of design and evaluation features.

PubMed

Arthur, Winfred; Bennett, Winston; Edens, Pamela S; Bell, Suzanne T

2003-04-01

The authors used meta-analytic procedures to examine the relationship between specified training design and evaluation features and the effectiveness of training in organizations. Results of the meta-analysis revealed training effectiveness sample-weighted mean ds of 0.60 (k = 15, N = 936) for reaction criteria, 0.63 (k = 234, N = 15,014) for learning criteria, 0.62 (k = 122, N = 15,627) for behavioral criteria, and 0.62 (k = 26, N = 1,748) for results criteria. These results suggest a medium to large effect size for organizational training. In addition, the training method used, the skill or task characteristic trained, and the choice of evaluation criteria were related to the effectiveness of training programs. Limitations of the study along with suggestions for future research are discussed.

Mercury Deposition Network Site Operator Training for the System Blank and Blind Audit Programs

USGS Publications Warehouse

Wetherbee, Gregory A.; Lehmann, Christopher M.B.

2008-01-01

The U.S. Geological Survey operates the external quality assurance project for the National Atmospheric Deposition Program/Mercury Deposition Network. The project includes the system blank and blind audit programs for assessment of total mercury concentration data quality for wet-deposition samples. This presentation was prepared to train new site operators and to refresh experienced site operators to successfully process and submit system blank and blind audit samples for chemical analysis. Analytical results are used to estimate chemical stability and contamination levels of National Atmospheric Deposition Program/Mercury Deposition Network samples and to evaluate laboratory variability and bias.

Toward accelerating landslide mapping with interactive machine learning techniques

NASA Astrophysics Data System (ADS)

Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

2013-04-01

Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also included an experimental evaluation of the uncertainties of manual mappings from multiple experts and demonstrated strong relationships between the uncertainty of the experts and the machine learning model.

Generating Seismograms with Deep Neural Networks

NASA Astrophysics Data System (ADS)

Krischer, L.; Fichtner, A.

2017-12-01

The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of neural networks by estimating the quality and uncertainties of the generated seismograms.

Training providers on issues of race and racism improve health care equity.

PubMed

Nelson, Stephen C; Prasad, Shailendra; Hackman, Heather W

2015-05-01

Race is an independent factor in health disparity. We developed a training module to address race, racism, and health care. A group of 19 physicians participated in our training module. Anonymous survey results before and after the training were compared using a two-sample t-test. The awareness of racism and its impact on care increased in all participants. White participants showed a decrease in self-efficacy in caring for patients of color when compared to white patients. This training was successful in deconstructing white providers' previously held beliefs about race and racism. © 2015 Wiley Periodicals, Inc.

An exploratory study of a text classification framework for Internet-based surveillance of emerging epidemics

PubMed Central

Torii, Manabu; Yin, Lanlan; Nguyen, Thang; Mazumdar, Chand T.; Liu, Hongfang; Hartley, David M.; Nelson, Noele P.

2014-01-01

Purpose Early detection of infectious disease outbreaks is crucial to protecting the public health of a society. Online news articles provide timely information on disease outbreaks worldwide. In this study, we investigated automated detection of articles relevant to disease outbreaks using machine learning classifiers. In a real-life setting, it is expensive to prepare a training data set for classifiers, which usually consists of manually labeled relevant and irrelevant articles. To mitigate this challenge, we examined the use of randomly sampled unlabeled articles as well as labeled relevant articles. Methods Naïve Bayes and Support Vector Machine (SVM) classifiers were trained on 149 relevant and 149 or more randomly sampled unlabeled articles. Diverse classifiers were trained by varying the number of sampled unlabeled articles and also the number of word features. The trained classifiers were applied to 15 thousand articles published over 15 days. Top-ranked articles from each classifier were pooled and the resulting set of 1337 articles was reviewed by an expert analyst to evaluate the classifiers. Results Daily averages of areas under ROC curves (AUCs) over the 15-day evaluation period were 0.841 and 0.836, respectively, for the naïve Bayes and SVM classifier. We referenced a database of disease outbreak reports to confirm that this evaluation data set resulted from the pooling method indeed covered incidents recorded in the database during the evaluation period. Conclusions The proposed text classification framework utilizing randomly sampled unlabeled articles can facilitate a cost-effective approach to training machine learning classifiers in a real-life Internet-based biosurveillance project. We plan to examine this framework further using larger data sets and using articles in non-English languages. PMID:21134784

Temporal Correlations and Neural Spike Train Entropy

NASA Astrophysics Data System (ADS)

Schultz, Simon R.; Panzeri, Stefano

2001-06-01

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a ``brute force'' approach.

Factors Affecting the Transfer of Basic Combat Skills Training in the Air Force

DTIC Science & Technology

2006-03-01

Kaiser - Meyer - Olkin Measure of Sampling Adequacy (KMO) and Bartlett’s test of Sphericity. The items reported a KMO=.87 and χ2 = 5,158.57, p < .01...Results Factor Analysis Table E1 Kaiser - Meyer - Olkin (KMO) and Bartlett’s Test of Sphericity for Perceived Training Transfer and Transfer Enhancing...Activities KMO Χ2 df Sig. Kaiser - Meyer - Olkin Measure of Sampling Adequacy .87 Bartletts Test of Sphericity 5,158.57 66 .000 100

Transfer Effects to a Multimodal Dual-Task after Working Memory Training and Associated Neural Correlates in Older Adults - A Pilot Study.

PubMed

Heinzel, Stephan; Rimpel, Jérôme; Stelzel, Christine; Rapp, Michael A

2017-01-01

Working memory (WM) performance declines with age. However, several studies have shown that WM training may lead to performance increases not only in the trained task, but also in untrained cognitive transfer tasks. It has been suggested that transfer effects occur if training task and transfer task share specific processing components that are supposedly processed in the same brain areas. In the current study, we investigated whether single-task WM training and training-related alterations in neural activity might support performance in a dual-task setting, thus assessing transfer effects to higher-order control processes in the context of dual-task coordination. A sample of older adults (age 60-72) was assigned to either a training or control group. The training group participated in 12 sessions of an adaptive n-back training. At pre and post-measurement, a multimodal dual-task was performed in all participants to assess transfer effects. This task consisted of two simultaneous delayed match to sample WM tasks using two different stimulus modalities (visual and auditory) that were performed either in isolation (single-task) or in conjunction (dual-task). A subgroup also participated in functional magnetic resonance imaging (fMRI) during the performance of the n-back task before and after training. While no transfer to single-task performance was found, dual-task costs in both the visual modality ( p < 0.05) and the auditory modality ( p < 0.05) decreased at post-measurement in the training but not in the control group. In the fMRI subgroup of the training participants, neural activity changes in left dorsolateral prefrontal cortex (DLPFC) during one-back predicted post-training auditory dual-task costs, while neural activity changes in right DLPFC during three-back predicted visual dual-task costs. Results might indicate an improvement in central executive processing that could facilitate both WM and dual-task coordination.

Transfer Effects to a Multimodal Dual-Task after Working Memory Training and Associated Neural Correlates in Older Adults – A Pilot Study

PubMed Central

Heinzel, Stephan; Rimpel, Jérôme; Stelzel, Christine; Rapp, Michael A.

2017-01-01

Working memory (WM) performance declines with age. However, several studies have shown that WM training may lead to performance increases not only in the trained task, but also in untrained cognitive transfer tasks. It has been suggested that transfer effects occur if training task and transfer task share specific processing components that are supposedly processed in the same brain areas. In the current study, we investigated whether single-task WM training and training-related alterations in neural activity might support performance in a dual-task setting, thus assessing transfer effects to higher-order control processes in the context of dual-task coordination. A sample of older adults (age 60–72) was assigned to either a training or control group. The training group participated in 12 sessions of an adaptive n-back training. At pre and post-measurement, a multimodal dual-task was performed in all participants to assess transfer effects. This task consisted of two simultaneous delayed match to sample WM tasks using two different stimulus modalities (visual and auditory) that were performed either in isolation (single-task) or in conjunction (dual-task). A subgroup also participated in functional magnetic resonance imaging (fMRI) during the performance of the n-back task before and after training. While no transfer to single-task performance was found, dual-task costs in both the visual modality (p < 0.05) and the auditory modality (p < 0.05) decreased at post-measurement in the training but not in the control group. In the fMRI subgroup of the training participants, neural activity changes in left dorsolateral prefrontal cortex (DLPFC) during one-back predicted post-training auditory dual-task costs, while neural activity changes in right DLPFC during three-back predicted visual dual-task costs. Results might indicate an improvement in central executive processing that could facilitate both WM and dual-task coordination. PMID:28286477

Employer Training of Work-Bound Youth: An Historical Review and New Results. Background Paper No. 43.

ERIC Educational Resources Information Center

Alsalam, Nabeel; Stacey, Nevzer

A study of the training opportunities of high school graduates (about 825,000 in 1988) who work immediately after leaving school identified which members of that group get trained, by whom, and with what earnings consequences, based on the experiences of a sample of graduates from their graduation in 1972 until 1986. The following are among the…

The Importance of Ethical Training for the Improvement of Ethical Decision-Making: Evidence from Germany and the United States

ERIC Educational Resources Information Center

Rottig, Daniel; Heischmidt, Kenneth A.

2007-01-01

Based on three independent samples from Germany and the United States, this exploratory, cross-cultural study examines empirically the importance of ethical training for the improvement of ethical decision-making. The results of the study reveal a significant difference in the use of corporate codes of conduct and ethical training, as well as…

TMOC: A Model for Lecturers' Training to Management of Online Courses in Higher-Education

ERIC Educational Resources Information Center

Ghilay, Yaron; Ghilay, Ruth

2014-01-01

The study examined a new model called TMOC: Training to Management of Online Courses. The model is designed to train lecturers in higher-education to successfully create, deliver and develop online courses. The research was based on a sample of lecturers, who studied in a course based on the new model at the Mofet Institute in Tel-Aviv (n = 20).…

Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

NASA Astrophysics Data System (ADS)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2018-05-01

The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image classification of building damages.

Field validation of the dnph method for aldehydes and ketones. Final report

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

Workman, G.S.; Steger, J.L.

1996-04-01

A stationary source emission test method for selected aldehydes and ketones has been validated. The method employs a sampling train with impingers containing 2,4-dinitrophenylhydrazine (DNPH) to derivatize the analytes. The resulting hydrazones are recovered and analyzed by high performance liquid chromatography. Nine analytes were studied; the method was validated for formaldehyde, acetaldehyde, propionaldehyde, acetophenone and isophorone. Acrolein, menthyl ethyl ketone, menthyl isobutyl ketone, and quinone did not meet the validation criteria. The study employed the validation techniques described in EPA method 301, which uses train spiking to determine bias, and collocated sampling trains to determine precision. The studies were carriedmore » out at a plywood veneer dryer and a polyester manufacturing plant.« less

Computerized cognitive training in survivors of childhood cancer: a pilot study.

PubMed

Hardy, Kristina K; Willard, Victoria W; Bonner, Melanie J

2011-01-01

The objective of the current study was to pilot a computerized cognitive training program, Captain's Log, in a small sample of survivors of childhood cancer. A total of 9 survivors of acute lymphoblastic leukemia and brain tumors with attention and working memory deficits were enrolled in a home-based 12-week cognitive training program. Survivors returned for follow-up assessments postintervention and 3 months later. The intervention was associated with good feasibility and acceptability. Participants exhibited significant increases in working memory and decreases in parent-rated attention problems following the intervention. Findings indicate that home-based, computerized cognitive intervention is a promising intervention for survivors with cognitive late effects; however, further study is warranted with a larger sample.

Carpentry Performance Objectives.

ERIC Educational Resources Information Center

Day, Gerald F.; Tucker, John

The guidelines for carpentry performance objectives were written for vocational educators in order to insure that their programs are fulfilling the training requirements of today's job market. The document outlines eight uses of performance objectives and provides sample employability profiles, training achievement records, and a carpentry…

HINTS Puerto Rico: Final Report

Cancer.gov

This final report describes HINTS implementation in Puerto Rico. The report addresses sampling; staffing, training and management of data collection; calling protocol; findings from the CATI Operations, and sample weights.

Rape Aggression Defense: Unique Self-Efficacy Benefits for Survivors of Sexual Trauma.

PubMed

Pinciotti, Caitlin M; Orcutt, Holly K

2018-04-01

Self-defense training is consistently linked to psychological benefits for survivors of sexual trauma, yet little is known about how training may uniquely benefit survivors compared with their nonsurvivor peers enrolled in the same course. Path analysis was used to examine how history of sexual trauma impacts pre- and post-training scores on three domains of self-efficacy using a national sample of Rape Aggression Defense (RAD) participants. All participants reported significant increases in self-efficacy domains, and sexual trauma history significantly predicted pre-training interpersonal self-efficacy and post-training self-defense self-efficacy, suggesting that self-defense training confers benefits for survivors above and beyond benefits for other participants.

The impact of group therapy training on social communications of Afghan immigrants

PubMed Central

Mehrabi, Tayebeh; Musavi, Tayebeh; Ghazavi, Zahra; Zandieh, Zahra; Zamani, Ahmadreza

2011-01-01

BACKGROUND: Mental training considers sharing of mental health care information as the primary objective. The secondary objectives include facilitating dialogue about feelings such as isolation, sadness, labeling, loneliness and possible strategies for confronting with these feelings. Group therapy trainings have supportive functioning in accepting the environment so that the members are able to be part of the indigenous groups. However, no study has been ever done on the impact of this educational method on the communication problems of this group. This study aimed to determine the impact of group therapy training on the communication problems of Afghan immigrants. METHODS: This was a clinical trial study. Eighty-eight Afghan men were investigated. Sampling method was simple sampling method. Thereafter, the study subjects were divided randomly into two groups of test and control based on the inclusion criteria. Data collection tool was a self-made questionnaire about the social problems. For analyzing the data, software SPSS, independent t-test and paired t-test were used. RESULTS: Reviewing the data indicated lower mean score of the social problems after implementing the group therapy training in social communication compared with before implementing the group therapy training. Paired t-test showed a significant difference between mean scores of the social communication problems before and after the implementation of group therapy training. CONCLUSIONS: Given the effectiveness of the intervention, group therapy training on social problems in social communication of Afghan immigrants is recommended. This program should be part of continuous education and training of the Afghan immigrants. PMID:22224098

Prevalence and correlates of resistance training in a regional Australian population.

PubMed

Humphries, B; Duncan, M J; Mummery, W K

2010-07-01

The core components of physical activity, cardiovascular endurance, muscular strength, balance and flexibility can provide many health benefits and potentially slow declines associated with aging. Aerobic exercise message to the public has been widely promoted by national health authorities, although the promotion of resistance training has received far less attention. In this research, the prevalence of resistance training in a sample of adults living in regional Australia was primarily assessed. A computer-assisted telephone interview survey (n=1230) was conducted by the Population Research Laboratory at Central Queensland University on Queensland adults in October to November 2006. Respondents were asked to report the frequency with which they engaged in resistance training. Respondents were 18 years or older that could be contacted by direct-dialled, land-based telephone service. A telephone database using a computer program to select, with replacement, a simple random sample of phone numbers selected respondents. Almost 14% of the population did some form of gym-based resistance training in the week before the survey. There was a significant (p<0.05) reduction in participation levels with age. Participation was highest amongst the youngest 18-34-year-olds (23.8%), steadily declining with age to a low of 7% in the 55 years and older age group. There was no significant association between sexes and participation in resistance training. The findings underscore the need to increase overall education on the benefits of resistance training with an emphasis among targeted adult populations to increase participation in resistance training.

[Empathy, inter-professional collaboration, and lifelong medical learning in Spanish and Latin-American physicians-in-training who start their postgraduate training in hospitals in Spain. Preliminary outcomes].

PubMed

San-Martín, Montserrat; Roig-Carrera, Helena; Villalonga-Vadell, Rosa M; Benito-Sevillano, Carmen; Torres-Salinas, Miquel; Claret-Teruel, Gemma; Robles, Bernabé; Sans-Boix, Antonia; Alcorta-Garza, Adelina; Vivanco, Luis

2017-01-01

To identify similarities and differences in empathy, abilities toward inter-professional collaboration, and lifelong medical learning, between Spanish and Latin-American physicians-in-training who start their posgraduate training in teaching hospitals in Spain. Observational study using self-administered questionnaires. Five teaching hospitals in the province of Barcelona, Spain. Spanish and Latin-American physicians-in-training who started their first year of post-graduate medical training. Empathy was measured using the Jefferson scale of empathy. Abilities for inter-professional collaboration were measured using the Jefferson scale attitudes towards nurse-physician collaboration. Learning was measured using the Jefferson scale of medical lifelong learning scale. From a sample of 156 physicians-in-training, 110 from Spain and 40 from Latin America, the Spanish group showed the highest empathy (p<.05). On the other hand, Latin-American physicians had the highest scores in lifelong learning abilities (p<.001). A positive relationship was found between empathy and inter-professional collaboration for the whole sample (r=+0.34; p<.05). These results confirm previous preliminary data and underline the positive influence of empathy in the development of inter-professional collaboration abilities. In Latin-American physicians who start posgraduate training programs, lifelong learning abilities have a positive influence on the development of other professional competencies. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Distribution-Preserving Stratified Sampling for Learning Problems.

PubMed

Cervellera, Cristiano; Maccio, Danilo

2017-06-09

The need for extracting a small sample from a large amount of real data, possibly streaming, arises routinely in learning problems, e.g., for storage, to cope with computational limitations, obtain good training/test/validation sets, and select minibatches for stochastic gradient neural network training. Unless we have reasons to select the samples in an active way dictated by the specific task and/or model at hand, it is important that the distribution of the selected points is as similar as possible to the original data. This is obvious for unsupervised learning problems, where the goal is to gain insights on the distribution of the data, but it is also relevant for supervised problems, where the theory explains how the training set distribution influences the generalization error. In this paper, we analyze the technique of stratified sampling from the point of view of distances between probabilities. This allows us to introduce an algorithm, based on recursive binary partition of the input space, aimed at obtaining samples that are distributed as much as possible as the original data. A theoretical analysis is proposed, proving the (greedy) optimality of the procedure together with explicit error bounds. An adaptive version of the algorithm is also introduced to cope with streaming data. Simulation tests on various data sets and different learning tasks are also provided.

GIS-based support vector machine modeling of earthquake-triggered landslide susceptibility in the Jianjiang River watershed, China

NASA Astrophysics Data System (ADS)

Xu, Chong; Dai, Fuchu; Xu, Xiwei; Lee, Yuan Hsi

2012-04-01

Support vector machine (SVM) modeling is based on statistical learning theory. It involves a training phase with associated input and target output values. In recent years, the method has become increasingly popular. The main purpose of this study is to evaluate the mapping power of SVM modeling in earthquake triggered landslide-susceptibility mapping for a section of the Jianjiang River watershed using a Geographic Information System (GIS) software. The river was affected by the Wenchuan earthquake of May 12, 2008. Visual interpretation of colored aerial photographs of 1-m resolution and extensive field surveys provided a detailed landslide inventory map containing 3147 landslides related to the 2008 Wenchuan earthquake. Elevation, slope angle, slope aspect, distance from seismogenic faults, distance from drainages, and lithology were used as the controlling parameters. For modeling, three groups of positive and negative training samples were used in concert with four different kernel functions. Positive training samples include the centroids of 500 large landslides, those of all 3147 landslides, and 5000 randomly selected points in landslide polygons. Negative training samples include 500, 3147, and 5000 randomly selected points on slopes that remained stable during the Wenchuan earthquake. The four kernel functions are linear, polynomial, radial basis, and sigmoid. In total, 12 cases of landslide susceptibility were mapped. Comparative analyses of landslide-susceptibility probability and area relation curves show that both the polynomial and radial basis functions suitably classified the input data as either landslide positive or negative though the radial basis function was more successful. The 12 generated landslide-susceptibility maps were compared with known landslide centroid locations and landslide polygons to verify the success rate and predictive accuracy of each model. The 12 results were further validated using area-under-curve analysis. Group 3 with 5000 randomly selected points on the landslide polygons, and 5000 randomly selected points along stable slopes gave the best results with a success rate of 79.20% and predictive accuracy of 79.13% under the radial basis function. Of all the results, the sigmoid kernel function was the least skillful when used in concert with the centroid data of all 3147 landslides as positive training samples, and the negative training samples of 3147 randomly selected points in regions of stable slope (success rate = 54.95%; predictive accuracy = 61.85%). This paper also provides suggestions and reference data for selecting appropriate training samples and kernel function types for earthquake triggered landslide-susceptibility mapping using SVM modeling. Predictive landslide-susceptibility maps could be useful in hazard mitigation by helping planners understand the probability of landslides in different regions.

Statistical generation of training sets for measuring NO3(-), NH4(+) and major ions in natural waters using an ion selective electrode array.

PubMed

Mueller, Amy V; Hemond, Harold F

2016-05-18

Knowledge of ionic concentrations in natural waters is essential to understand watershed processes. Inorganic nitrogen, in the form of nitrate and ammonium ions, is a key nutrient as well as a participant in redox, acid-base, and photochemical processes of natural waters, leading to spatiotemporal patterns of ion concentrations at scales as small as meters or hours. Current options for measurement in situ are costly, relying primarily on instruments adapted from laboratory methods (e.g., colorimetric, UV absorption); free-standing and inexpensive ISE sensors for NO3(-) and NH4(+) could be attractive alternatives if interferences from other constituents were overcome. Multi-sensor arrays, coupled with appropriate non-linear signal processing, offer promise in this capacity but have not yet successfully achieved signal separation for NO3(-) and NH4(+)in situ at naturally occurring levels in unprocessed water samples. A novel signal processor, underpinned by an appropriate sensor array, is proposed that overcomes previous limitations by explicitly integrating basic chemical constraints (e.g., charge balance). This work further presents a rationalized process for the development of such in situ instrumentation for NO3(-) and NH4(+), including a statistical-modeling strategy for instrument design, training/calibration, and validation. Statistical analysis reveals that historical concentrations of major ionic constituents in natural waters across New England strongly covary and are multi-modal. This informs the design of a statistically appropriate training set, suggesting that the strong covariance of constituents across environmental samples can be exploited through appropriate signal processing mechanisms to further improve estimates of minor constituents. Two artificial neural network architectures, one expanded to incorporate knowledge of basic chemical constraints, were tested to process outputs of a multi-sensor array, trained using datasets of varying degrees of statistical representativeness to natural water samples. The accuracy of ANN results improves monotonically with the statistical representativeness of the training set (error decreases by ∼5×), while the expanded neural network architecture contributes a further factor of 2-3.5 decrease in error when trained with the most representative sample set. Results using the most statistically accurate set of training samples (which retain environmentally relevant ion concentrations but avoid the potential interference of humic acids) demonstrated accurate, unbiased quantification of nitrate and ammonium at natural environmental levels (±20% down to <10 μM), as well as the major ions Na(+), K(+), Ca(2+), Mg(2+), Cl(-), and SO4(2-), in unprocessed samples. These results show promise for the development of new in situ instrumentation for the support of scientific field work.

Assessing Generative Braille Responding Following Training in a Matching-to-Sample Format

ERIC Educational Resources Information Center

Putnam, Brittany C.; Tiger, Jeffrey H.

2016-01-01

We evaluated the effects of teaching sighted college students to select printed text letters given a braille sample stimulus in a matching-to-sample (MTS) format on the emergence of untrained (a) construction of print characters given braille samples, (b) construction of braille characters given print samples, (c) transcription of print characters…

Salivary Biomarkers and Training Load during Training and Competition in Paralympic Swimmers.

PubMed

Sinnott-O'Connor, Ciara; Comyns, Tom; Nevill, Alan M; Warrington, Giles

2017-11-28

Stress responses in athletes can be attributed to training and also competition, where increased physiological and psychological stress may negatively impact on performance and recovery. The aim of this study was to examine the relationship between training load and salivary biomarkers IgA, alpha-amylase (AA) and cortisol across a 16-week preparation phase and 10-day competition phase in Paralympic swimmers. Four Paralympic swimmers provided bi-weekly saliva samples during three training phases - 1) normal training, 2) intensified training and 3) taper as well as daily saliva samples in the 10 day Paralympic competition (2016 Paralympic Games). Training load (TL) was measured using session-RPE. Multi-level analysis identified a significant increase in sIgA (94.98 (27.69) μg.ml -1 ), sAA (45.78 (19.07) μg.ml -1 ) and salivary cortisol (7.92 (2.17) ng.ml) during intensified training concurrent with a 38.3% increase in TL. During taper phase, a 49.5% decrease in TL from the intensified training phase resulted in decrease in sIgA, sAA and salivary cortisol; however, all three remained higher than baseline levels. A further significant increase was observed during competition in sIgA (168.69(24.19) μg.ml -1 ), sAA (35.86(16.67) μg.ml -1 ) and salivary cortisol (10.49(1.89) ng.ml) despite a continued decrease (77.8%) in TL from taper phase. Results demonstrate performance in major competition such as Paralympic Games despite a noticeable reduction in TL induces a stress response in athletes. Due to elevated stress response observed, modifications to individual post-race recovery protocols may be required to enable athletes to maximise performance across all ten days of competition.

Exercise training does not increase muscle FNDC5 protein or mRNA expression in pigs

PubMed Central

Fain, John N.; Company, Joseph M.; Booth, Frank W.; Laughlin, M. Harold; Padilla, Jaume; Jenkins, Nathan T.; Bahouth, Suleiman W.; Sacks, Harold S.

2013-01-01

Background Exercise training elevates circulating irisin and induces the expression of the FNDC5 gene in skeletal muscles of mice. Our objective was to determine whether exercise training also increases FNDC5 protein or mRNA expression in the skeletal muscles of pigs as well as plasma irisin. Methods Castrated male pigs of the Rapacz familial hypercholesterolemic (FHM) strain and normal (Yucatan miniature) pigs were sacrificed after 16–20 weeks of exercise training. Samples of cardiac muscle, deltoid and triceps brachii muscle, subcutaneous and epicardial fat were obtained and FNDC5 mRNA, along with that of 6 other genes, was measured in all tissues of FHM pigs by reverse transcription polymerase chain reaction. FNDC protein in deltoid and triceps brachii was determined by Western blotting in both FHM and normal pigs. Citrate synthase activity was measured in the muscle samples of all pigs as an index of exercise training. Irisin was measured by an ELISA assay. Results There was no statistically significant effect of exercise training on FNDC5 gene expression in epicardial or subcutaneous fat, deltoid muscle, triceps brachii muscle or heart muscle. Exercise-training elevated circulating levels of irisin in the FHM pigs and citrate synthase activity in deltoid and triceps brachii muscle. A similar increase in citrate synthase activity was seen in muscle extracts of exercise-trained normal pigs but there was no alteration in circulating irisin. Conclusion Exercise training in pigs does not increase FNDC5 mRNA or protein in the deltoid or triceps brachii of FHM or normal pigs while increasing circulating irisin only in the FHM pigs. These data indicate that the response to exercise training in normal pigs is not comparable to that seen in mice. PMID:23831442

Alpha/Theta Neurofeedback Increases Mentalization and Default Mode Network Connectivity in a Non-Clinical Sample.

PubMed

Imperatori, Claudio; Della Marca, Giacomo; Amoroso, Noemi; Maestoso, Giulia; Valenti, Enrico Maria; Massullo, Chiara; Carbone, Giuseppe Alessio; Contardi, Anna; Farina, Benedetto

2017-11-01

Several studies showed the effectiveness of alpha/theta (A/T) neurofeedback training in treating some psychiatric conditions. Despite the evidence of A/T effectiveness, the psychological and neurobiological bases of its effects is still unclear. The aim of the present study was to explore the usefulness of the A/T training in increasing mentalization in a non-clinical sample. The modifications of electroencephalographic (EEG) functional connectivity in Default Mode Network (DMN) associated with A/T training were also investigated. Forty-four subjects were enrolled in the study and randomly assigned to receive ten sessions of A/T training [neurofeedback group (NFG) = 22], or to act as controls [waiting list group (WLG) = 22]. All participants were administered the mentalization questionnaire (MZQ) and the Symptom Checklist-90-Revised (SCL-90-R). In the post training assessment, compared to WLG, NFG showed a significant increase of MZQ total scores (3.94 ± 0.73 vs. 3.53 ± 0.77; F 1;43 = 8.19; p = 0.007; d = 0.863). Furthermore, A/T training was also associated with a significant increase of EEG functional connectivity in several DMN brain areas (e.g. Posterior Cingulate Cortex). Taken together our results support the usefulness of the A/T training in enhancing mentalization and DMN connectivity.

Effects of interpretation training on hostile attribution bias and reactivity to interpersonal insult.

PubMed

Hawkins, Kirsten A; Cougle, Jesse R

2013-09-01

Research suggests that individuals high in anger have a bias for attributing hostile intentions to ambiguous situations. The current study tested whether this interpretation bias can be altered to influence anger reactivity to an interpersonal insult using a single-session cognitive bias modification program. One hundred thirty-five undergraduate students were randomized to receive positive training, negative training, or a control condition. Anger reactivity to insult was then assessed. Positive training led to significantly greater increases in positive interpretation bias relative to the negative group, though these increases were only marginally greater than the control group. Negative training led to increased negative interpretation bias relative to other groups. During the insult, participants in the positive condition reported less anger than those in the control condition. Observers rated participants in the positive condition as less irritated than those in the negative condition and more amused than the other two conditions. Though mediation of effects via bias modification was not demonstrated, among the positive condition posttraining interpretation bias was correlated with self-reported anger, suggesting that positive training reduced anger reactivity by influencing interpretation biases. Findings suggest that positive interpretation training may be a promising treatment for reducing anger. However, the current study was conducted with a non-treatment-seeking student sample; further research with a treatment-seeking sample with problematic anger is necessary. Copyright © 2013. Published by Elsevier Ltd.

Assessment of a prevention program for work-related stress among urban police officers

PubMed Central

Arnetz, Bengt B.; Backman, Lena; Lynch, Adam; Lublin, Ake

2013-01-01

Objective To determine the efficacy of a primary prevention program designed to improve psychobiological responses to stress among urban police officers. Methods A random sample of 37 police cadets received complementary training in psychological and technical techniques to reduce anxiety and enhance performance when facing a series of police critical incidents. Training was done by Special Forces officers, trained by the authors in imaging. A random sample of 38 cadets, receiving training as usual, was followed in parallel. Assessment of somatic and psychological health, and stress biomarkers, was done at baseline, immediately following training, and after 18 months as regular police officers. Comparison was done using two-way repeated analysis of variance (ANOVA) and logistic regression. Results The intervention group improved their general health and problem-based coping as compared to the control group. They also demonstrated lower levels of stomach problems, sleep difficulties, and exhaustion. Training was associated with an OR of 4.1 (95% CI, 1.3–13.7; p < 0.05) for improved GHQ scores during the study as compared to no changes or worsening score. Conclusions This first primary prevention study of high-risk professions demonstrates the validity and functional utility of the intervention. Beneficial effects lasted at least during the first 2 years on the police force. It is suggested that preventive imagery training in first responders might contribute to enhanced resiliency. PMID:22366986

Comparative Initial and Sustained Engagement in Web-based Training by Behavioral Healthcare Providers in New York State.

PubMed

Talley, Rachel; Chiang, I-Chin; Covell, Nancy H; Dixon, Lisa

2018-06-01

Improved dissemination is critical to implementation of evidence-based practice in community behavioral healthcare settings. Web-based training modalities are a promising strategy for dissemination of evidence-based practice in community behavioral health settings. Initial and sustained engagement of these modalities in large, multidisciplinary community provider samples is not well understood. This study evaluates comparative engagement and user preferences by provider type in a web-based training platform in a large, multidisciplinary community sample of behavioral health staff in New York State. Workforce make-up among platform registrants was compared to the general NYS behavioral health workforce. Training completion by functional job type was compared to characterize user engagement and preferences. Frequently completed modules were classified by credit and requirement incentives. High initial training engagement across professional role was demonstrated, with significant differences in initial and sustained engagement by professional role. The most frequently completed modules across functional job types contained credit or requirement incentives. The analysis demonstrated that high engagement of a web-based training in a multidisciplinary provider audience can be achieved without tailoring content to specific professional roles. Overlap between frequently completed modules and incentives suggests a role for incentives in promoting engagement of web-based training. These findings further the understanding of strategies to promote large-scale dissemination of evidence-based practice in community behavioral health settings.

Suicide Risk Assessment Training for Psychology Doctoral Programs: Core Competencies and a Framework for Training

PubMed Central

Cramer, Robert J.; Johnson, Shara M.; McLaughlin, Jennifer; Rausch, Emilie M.; Conroy, Mary Alice

2014-01-01

Clinical and counseling psychology programs currently lack adequate evidence-based competency goals and training in suicide risk assessment. To begin to address this problem, this article proposes core competencies and an integrated training framework that can form the basis for training and research in this area. First, we evaluate the extent to which current training is effective in preparing trainees for suicide risk assessment. Within this discussion, sample and methodological issues are reviewed. Second, as an extension of these methodological training issues, we integrate empirically- and expert-derived suicide risk assessment competencies from several sources with the goal of streamlining core competencies for training purposes. Finally, a framework for suicide risk assessment training is outlined. The approach employs Objective Structured Clinical Examination (OSCE) methodology, an approach commonly utilized in medical competency training. The training modality also proposes the Suicide Competency Assessment Form (SCAF), a training tool evaluating self- and observer-ratings of trainee core competencies. The training framework and SCAF are ripe for empirical evaluation and potential training implementation. PMID:24672588

Suicide Risk Assessment Training for Psychology Doctoral Programs: Core Competencies and a Framework for Training.

PubMed

Cramer, Robert J; Johnson, Shara M; McLaughlin, Jennifer; Rausch, Emilie M; Conroy, Mary Alice

2013-02-01

Clinical and counseling psychology programs currently lack adequate evidence-based competency goals and training in suicide risk assessment. To begin to address this problem, this article proposes core competencies and an integrated training framework that can form the basis for training and research in this area. First, we evaluate the extent to which current training is effective in preparing trainees for suicide risk assessment. Within this discussion, sample and methodological issues are reviewed. Second, as an extension of these methodological training issues, we integrate empirically- and expert-derived suicide risk assessment competencies from several sources with the goal of streamlining core competencies for training purposes. Finally, a framework for suicide risk assessment training is outlined. The approach employs Objective Structured Clinical Examination (OSCE) methodology, an approach commonly utilized in medical competency training. The training modality also proposes the Suicide Competency Assessment Form (SCAF), a training tool evaluating self- and observer-ratings of trainee core competencies. The training framework and SCAF are ripe for empirical evaluation and potential training implementation.

Confidence Preserving Machine for Facial Action Unit Detection

PubMed Central

Zeng, Jiabei; Chu, Wen-Sheng; De la Torre, Fernando; Cohn, Jeffrey F.; Xiong, Zhang

2016-01-01

Facial action unit (AU) detection from video has been a long-standing problem in automated facial expression analysis. While progress has been made, accurate detection of facial AUs remains challenging due to ubiquitous sources of errors, such as inter-personal variability, pose, and low-intensity AUs. In this paper, we refer to samples causing such errors as hard samples, and the remaining as easy samples. To address learning with the hard samples, we propose the Confidence Preserving Machine (CPM), a novel two-stage learning framework that combines multiple classifiers following an “easy-to-hard” strategy. During the training stage, CPM learns two confident classifiers. Each classifier focuses on separating easy samples of one class from all else, and thus preserves confidence on predicting each class. During the testing stage, the confident classifiers provide “virtual labels” for easy test samples. Given the virtual labels, we propose a quasi-semi-supervised (QSS) learning strategy to learn a person-specific (PS) classifier. The QSS strategy employs a spatio-temporal smoothness that encourages similar predictions for samples within a spatio-temporal neighborhood. In addition, to further improve detection performance, we introduce two CPM extensions: iCPM that iteratively augments training samples to train the confident classifiers, and kCPM that kernelizes the original CPM model to promote nonlinearity. Experiments on four spontaneous datasets GFT [15], BP4D [56], DISFA [42], and RU-FACS [3] illustrate the benefits of the proposed CPM models over baseline methods and state-of-the-art semisupervised learning and transfer learning methods. PMID:27479964

Evaluation of Training Samples Manually Welded With the Universal Handtool in a Space Simulation Chamber

NASA Technical Reports Server (NTRS)

Russell, C. K.; Malone, T. W.; Cato, S. N.

2004-01-01

The international space welding experiment was designed to evaluate the universal handtool (UHT) functions as a welding, brazing, coating, and cutting tool for in-space operations. The UHT is an electron beam welding system developed by the Paton Welding Institute (PWI), Kiev, Ukraine, and operated a 8 kV with up to 1 kW of power. In preparation for conducting the space welding experiment, cosmonauts were trained to properly operate the UHT and correctly process samples. This Technical Memorandum presents the results of the destructive and nondestructive evaluation of the training samples made in Russia in 1998. It was concluded that acceptable welds can be made with the UHT despite the constraints imposed by a space suit. The lap joint fillet weld configuration was more suitable than the butt joint configuration for operators with limited welding experience. The tube braze joint configuration designed by the PWI was easily brazed in a repeatable manner.

A Sensemaking Approach to Ethics Training for Scientists: Preliminary Evidence of Training Effectiveness.

PubMed

Mumford, Michael D; Connelly, Shane; Brown, Ryan P; Murphy, Stephen T; Hill, Jason H; Antes, Alison L; Waples, Ethan P; Devenport, Lynn D

2008-10-01

In recent years, we have seen a new concern with ethics training for research and development professionals. Although ethics training has become more common, the effectiveness of the training being provided is open to question. In the present effort, a new ethics training course was developed that stresses the importance of the strategies people apply to make sense of ethical problems. The effectiveness of this training was assessed in a sample of 59 doctoral students working in the biological and social sciences using a pre-post design with follow-up, and a series of ethical decision-making measures serving as the outcome variable. Results showed that this training not only led to sizable gains in ethical decision-making, but that these gains were maintained over time. The implications of these findings for ethics training in the sciences are discussed.

A Sensemaking Approach to Ethics Training for Scientists: Preliminary Evidence of Training Effectiveness

PubMed Central

Mumford, Michael D.; Connelly, Shane; Brown, Ryan P.; Murphy, Stephen T.; Hill, Jason H.; Antes, Alison L.; Waples, Ethan P.; Devenport, Lynn D.

2009-01-01

In recent years, we have seen a new concern with ethics training for research and development professionals. Although ethics training has become more common, the effectiveness of the training being provided is open to question. In the present effort, a new ethics training course was developed that stresses the importance of the strategies people apply to make sense of ethical problems. The effectiveness of this training was assessed in a sample of 59 doctoral students working in the biological and social sciences using a pre-post design with follow-up, and a series of ethical decision-making measures serving as the outcome variable. Results showed that this training not only led to sizable gains in ethical decision-making, but that these gains were maintained over time. The implications of these findings for ethics training in the sciences are discussed. PMID:19578559

An empirical identification and categorisation of training best practices for ERP implementation projects

NASA Astrophysics Data System (ADS)

Esteves, Jose Manuel

2014-11-01

Although training is one of the most cited critical success factors in Enterprise Resource Planning (ERP) systems implementations, few empirical studies have attempted to examine the characteristics of management of the training process within ERP implementation projects. Based on the data gathered from a sample of 158 respondents across four stakeholder groups involved in ERP implementation projects, and using a mixed method design, we have assembled a derived set of training best practices. Results suggest that the categorised list of ERP training best practices can be used to better understand training activities in ERP implementation projects. Furthermore, the results reveal that the company size and location have an impact on the relevance of training best practices. This empirical study also highlights the need to investigate the role of informal workplace trainers in ERP training activities.

Persistent Classroom Management Training Needs of Experienced Teachers

ERIC Educational Resources Information Center

Stough, Laura M.; Montague, Marcia L.; Landmark, Leena Jo; Williams-Diehm, Kendra

2015-01-01

Experienced special education teachers (n = 62) were surveyed on their professional preparation to become effective classroom managers. Despite having received extensive preservice training, over 83% of the sample reported being underprepared in classroom management and behavioral interventions. No statistically significant difference was found…

Survey of training and education of cytotechnologists in Europe.

PubMed

Anic, V; Eide, M L

2014-10-01

This report presents the results of a survey of the training and education of cytotechnologists (CTs) in 15 European countries and suggests guidelines on which future education should be developed. A questionnaire was sent to 25 countries in 2011: 14 with and 11 without a European Advisory Committee of Cytotechnology (EACC) member or representative. We received responses from 18 countries, among which three were excluded from the survey because they did not have CTs in training. The number of fully trained and employed CTs in these 15 European countries varied from 35 to 2600. The level of responsibility for most CTs in 14 of these countries was intermediate (signing out negative and inadequate gynaecological samples), whereas seven also had a minority of CTs at an advanced level (signing out abnormal gynaecological samples). Basic education was equally divided (7/8) between countries requiring a bachelor degree or training in medical technology before entry into cytology training. The training in cytology was given as a separate course/education or a combination of separate courses and in-house training, but was often confined to gynaecological cytology. It was recognized that CTs should extend their activities with the advent of human papillomavirus (HPV) testing and vaccination. The training requirement for CTs was usually decided by the national professional society. Most cytology training programmes were accredited by academic institutions at university level and were recognized nationally in almost all of the countries. For most of the countries, the optimal education in the future should be at university level with a diploma in cytotechnology certified or accredited by the European Federation of Cytology Societies. The survey showed variation in basic education and cytology training, especially with respect to non-gynaecological cytology, although graduate entry was favoured. The role of CTs is changing and the education and training programmes need to adapt to these changes. © 2014 John Wiley & Sons Ltd.

Family physicians' approach to psychotherapy and counseling. Perceptions and practices.

PubMed Central

Swanson, J. G.

1994-01-01

To determine how family physicians perceive the support they get for psychotherapy and counseling, we surveyed a random sample of Ontario College of Family Physicians members. Of 100 physicians who had family medicine residency training with psychotherapy experience, 43% indicated that such training was inadequate for their current needs. Because family physicians often provide psychotherapy and counseling, their training should reflect the needs found in practice. PMID:8080505

Does Teaching Problem-Solving Skills Matter? An Evaluation of Problem-Solving Skills Training for the Treatment of Social and Behavioral Problems in Children

ERIC Educational Resources Information Center

Bushman, Bryan B.; Peacock, Gretchen Gimpel

2010-01-01

Problem-solving skills training (PSST) has been proposed as a potentially effective addition to behavioral parent training (PT). However, it is not clear whether PSST specifically increases the benefits provided by PT. In this study, PT + PSST was compared to PT + nondirective therapy in a sample of 26 families. All parents received PT. Following…

Firm-Based Training for Young Australians: Changes from the 1980s to the 1990s. Research Report.

ERIC Educational Resources Information Center

Long, Michael; Lamb, Stephen

Changes in the extent, pattern, and outcomes of young Australians' participation in firm-based training from the 1980s to the 1990s were analyzed by comparing data from the Australian Youth Survey (AYS) and the Australian Longitudinal Survey (ALS). In 1994, 46% of those in the AYS sample participated in formal training (at age 16-24 years) and…

Pesticide Applicator Training Manual, Category 8B: Mosquito Control for New Jersey. A Training Program for the Certification of Commercial Pesticide Applicators, and Study Questions.

ERIC Educational Resources Information Center

Schulze, Terry L., Ed.; Kriner, Ray R., Ed.

This training manual provides information needed to meet the mimimum EPA standards for certification as a commercial applicator of pesticides in the mosquito control category. The text discusses the aspects of mosquito biology and control by biological, mechanical, and integrated measures. A study guide with sample and study questions is included.…

Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network

NASA Astrophysics Data System (ADS)

Zhang, J.; Zhang, J.; Zhao, Z.

2018-04-01

Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey

USGS Publications Warehouse

Pengra, Bruce; Gallant, Alisa L.; Zhu, Zhe; Dahal, Devendra

2016-01-01

The U.S. Geological Survey (USGS) has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC) algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends) project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.

Naming and Categorization in Young Children: IV: Listener Behavior Training and Transfer of Function

PubMed Central

Horne, Pauline J; Hughes, J. Carl; Lowe, C. Fergus

2006-01-01

Following pretraining with everyday objects, 14 children aged from 1 to 4 years were trained, for each of three pairs of different arbitrary wooden shapes (Set 1), to select one stimulus in response to the spoken word /zog/, and the other to /vek/. When given a test for the corresponding tacts (“zog” and “vek”), 10 children passed, showing that they had learned common names for the stimuli, and 4 failed. All children were trained to clap to one stimulus of Pair 1 and wave to the other. All those who named showed either transfer of the novel functions to the remaining two pairs of stimuli in Test 1, or novel function comprehension for all three pairs in Test 2, or both. Three of these children next participated in, and passed, category match-to-sample tests. In contrast, all 4 children who had learned only listener behavior failed both the category transfer and category match-to-sample tests. When 3 of them were next trained to name the stimuli, they passed the category transfer and (for the 2 subjects tested) category match-to-sample tests. Three children were next trained on the common listener relations with another set of arbitrary stimuli (Set 2); all succeeded on the tact and category tests with the Set 2 stimuli. Taken together with the findings from the other studies in the series, the present experiment shows that (a) common listener training also establishes the corresponding names in some but not all children, and (b) only children who learn common names categorize; all those who learn only listener behavior fail. This is good evidence in support of the naming account of categorization. PMID:16673828

A comparison of machine learning and Bayesian modelling for molecular serotyping.

PubMed

Newton, Richard; Wernisch, Lorenz

2017-08-11

Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological insights, which we illustrate with an example.

Working memory training in older adults: Bayesian evidence supporting the absence of transfer.

PubMed

Guye, Sabrina; von Bastian, Claudia C

2017-12-01

The question of whether working memory training leads to generalized improvements in untrained cognitive abilities is a longstanding and heatedly debated one. Previous research provides mostly ambiguous evidence regarding the presence or absence of transfer effects in older adults. Thus, to draw decisive conclusions regarding the effectiveness of working memory training interventions, methodologically sound studies with larger sample sizes are needed. In this study, we investigated whether or not a computer-based working memory training intervention induced near and far transfer in a large sample of 142 healthy older adults (65 to 80 years). Therefore, we randomly assigned participants to either the experimental group, which completed 25 sessions of adaptive, process-based working memory training, or to the active, adaptive visual search control group. Bayesian linear mixed-effects models were used to estimate performance improvements on the level of abilities, using multiple indicator tasks for near (working memory) and far transfer (fluid intelligence, shifting, and inhibition). Our data provided consistent evidence supporting the absence of near transfer to untrained working memory tasks and the absence of far transfer effects to all of the assessed abilities. Our results suggest that working memory training is not an effective way to improve general cognitive functioning in old age. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Chemical and biological quality of surface water at the U.S. Army Atterbury Reserve Forces Training Area near Edinburgh, Indiana, September 2000 through July 2001

USGS Publications Warehouse

Risch, Martin R.

2004-01-01

A base-wide assessment of surface-water quality at the U.S. Army Atterbury Reserve Forces Training Area near Edinburgh, Indiana, examined short-term and long-term quality of surface water flowing into, across, and out of a 33,760-acre study area. The 30-day geometric-mean concentrations of fecal-indicator bacteria (Escherichia coli) in water samples from all 16 monitoring sites on streams in the study area were greater than the Indiana recreational water-quality standard. None of the bacteria concentrations in samples from four lakes exceeded the standard. Half the samples with bacteria concentrations greater than the single-sample standard contained chemical tracers potentially associated with human sewage. Increased turbidity of water samples was related statistically to increased bacteria concentration. Lead concentrations ranging from 0.5 to 2.0 micrograms per liter were detected in water samples at seven monitoring sites. Lead in one sample collected during high-streamflow conditions was greater than the calculated Indiana water-quality standard. With the exception of Escherichia coli and lead, 211 of 213 chemical constituents analyzed in water samples did not exceed Indiana water-quality standards. Out of 131 constituents analyzed in streambed-sediment and fish-tissue samples from three sites in the Common Impact Area for weapons training, the largest concentrations overall were detected for copper, lead, manganese, strontium, and zinc. Fish-community integrity, based on diversity and pollution tolerance, was rated poor at one of those three sites. Compared with State criteria, the fish-community data indicated 8 of 10 stream reaches in the study area could be categorized as "fully supporting" aquatic-life uses.

Domain Regeneration for Cross-Database Micro-Expression Recognition

NASA Astrophysics Data System (ADS)

Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

2018-05-01

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

A-Train Data Depot - Bringing Atmospheric Measurements Together

NASA Technical Reports Server (NTRS)

Savtchenko, Andrey; Kummerer, Robert; Smith, Peter; Gopalan, Arun; Kempler, Steven; Leptoukh, Gregory

2007-01-01

This paper describes the satellite data processing and services that constitute current functionalities of the A-Train Data Depot. We first provide a brief introduction to the original geometrical intricacies of the platforms and instruments of the A-Train constellation, and then proceed with description of our ATrain collocation processing algorithm that provides subsets that facilitate synergistic use of the various instruments. Finally, we present some sample image products from our web-based Giovanni tool which allows users to display, compare and download coregistered A-Train related data.

Jaccard distance based weighted sparse representation for coarse-to-fine plant species recognition.

PubMed

Zhang, Shanwen; Wu, Xiaowei; You, Zhuhong

2017-01-01

Leaf based plant species recognition plays an important role in ecological protection, however its application to large and modern leaf databases has been a long-standing obstacle due to the computational cost and feasibility. Recognizing such limitations, we propose a Jaccard distance based sparse representation (JDSR) method which adopts a two-stage, coarse to fine strategy for plant species recognition. In the first stage, we use the Jaccard distance between the test sample and each training sample to coarsely determine the candidate classes of the test sample. The second stage includes a Jaccard distance based weighted sparse representation based classification(WSRC), which aims to approximately represent the test sample in the training space, and classify it by the approximation residuals. Since the training model of our JDSR method involves much fewer but more informative representatives, this method is expected to overcome the limitation of high computational and memory costs in traditional sparse representation based classification. Comparative experimental results on a public leaf image database demonstrate that the proposed method outperforms other existing feature extraction and SRC based plant recognition methods in terms of both accuracy and computational speed.

[Generalization of money-handling though training in equivalence relationships].

PubMed

Vives-Montero, Carmen; Valero-Aguayo, Luis; Ascanio, Lourdes

2011-02-01

This research used a matching-to-sample procedure and equivalence learning process with language and verbal tasks. In the study, an application of the equivalence relationship of money was used with several kinds of euro coins presented. The sample consisted of 16 children (8 in the experimental group and 8 in the control group) aged 5 years. The prerequisite behaviors, the identification of coins and the practical use of different euro coins, were assessed in the pre and post phases for both groups. The children in the experimental group performed an equivalence task using the matching-to-sample procedure. This consisted of a stimulus sample and four matching stimuli, using a series of euro coins with equivalent value in each set. The children in the control group did not undergo this training process. The results showed a large variability in the children's data of the equivalence tests. The experimental group showed the greatest pre and post changes in the statistically significant data. They also showed a greater generalization in the identification of money and in the use of euro coins than the control group. The implications for educational training and the characteristics of the procedure used here for coin equivalence are discussed.

Monitoring water quality in Toronto's urban stormwater ponds: Assessing participation rates and data quality of water sampling by citizen scientists in the FreshWater Watch.

PubMed

Scott, Andrew B; Frost, Paul C

2017-08-15

From 2013 to 2015, citizen scientist volunteers in Toronto, Canada were trained to collect and analyze water quality in urban stormwater ponds. This volunteer sampling was part of the research program, FreshWater Watch (FWW), which aimed to standardize urban water sampling efforts from around the globe. We held training sessions for new volunteers twice yearly and trained a total of 111 volunteers. Over the course of project, ~30% of volunteers participated by collecting water quality data after the training session with 124 individual sampling events at 29 unique locations in Toronto, Canada. A few highly engaged volunteers were most active, with 50% of the samples collected by 5% of trainees. Stormwater ponds generally have poor water quality demonstrated by elevated phosphate concentrations (~30μg/L), nitrate (~427μg/L), and turbidity relative to Canadian water quality standards. Compared to other urban waterbodies in the global program, nutrient concentrations in Toronto's urban stormwater ponds were lower, while turbidity was not markedly different. Toronto FWW (FWW-TO) data was comparable to that measured by standard lab analyses and matched results from previous studies of stormwater ponds in Toronto. Combining observational and chemical data acquired by citizen scientists, macrophyte dominated ponds had lower phosphate concentrations while phytoplankton dominated ponds had lower nitrate concentrations, which indicates a potentially important and unstudied role of internal biogeochemical processes on pond nutrient dynamics. This experience in the FWW demonstrates the capabilities and constraints of citizen science when applied to water quality sampling. While analytical limits on in-field analyses produce higher uncertainty in water quality measurements of individual sites, rapid data collection is possible but depends on the motivation and engagement of the group of volunteers. Ongoing efforts in citizen science will thus need to address sampling effort and analytical limits to fully realize the potential value of engaging citizen scientists in water quality sampling. Copyright © 2017 Elsevier B.V. All rights reserved.

Trauma Training for School Counselors: How Well Do Programs Prepare?

ERIC Educational Resources Information Center

Lokeman, Kimberly Shawnte

2011-01-01

This study investigates the availability and perceived importance of trauma response training in school counseling preparatory programs. Using two population samples, 101 counselor educators of institutions with CACREP-accredited school counseling programs and 803 practicing school counselors, questionnaires assessed the extent to which…

The International Mathematical Olympiad Training Session.

ERIC Educational Resources Information Center

Rousseau, Cecil; Patruno, Gregg

1985-01-01

The Mathematical Olympiad Training Session is designed to give United States students a problem-oriented exposure to subject areas (algebra, geometry, number theory, combinatorics, and inequalities) through an intensive three-week course. Techniques used during the session, with three sample problems and their solutions, are presented. (JN)

Protecting the Voc Ed Consumer.

ERIC Educational Resources Information Center

Wilms, Wellford W.

To test the differences in effect of postsecondary vocational training offered by public schools and by proprietary schools, a study based on a sample of 4,8000 students and graduates in the accounting, programing, electronic technician training, dental assisting, secretarial, and cosmetology occupations was designed. Even though vocational…

ISSUES RELATED TO SOLUTION CHEMISTRY IN MERCURY SAMPLING IMPINGERS

EPA Science Inventory

Analysis of mercury (Hg) speciation in combustion flue gases is often accomplished in standardized sampling trains in which the sample is passed sequentially through a series of aqueous solutions to capture and separate oxidized Hg (Hg2+) and elemental Hg (Hgo). Such methods incl...

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research.

PubMed

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-Etriby, Sherif

2016-03-11

Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers-that we proposed earlier-improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research

PubMed Central

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-etriby, Sherif

2016-01-01

Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers—that we proposed earlier—improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction. PMID:26978368

Repeated Low-Level Blast Exposure: A Descriptive Human Subjects Study.

PubMed

Carr, Walter; Stone, James R; Walilko, Tim; Young, Lee Ann; Snook, Tianlu Li; Paggi, Michelle E; Tsao, Jack W; Jankosky, Christopher J; Parish, Robert V; Ahlers, Stephen T

2016-05-01

The relationship between repeated exposure to blast overpressure and neurological function was examined in the context of breacher training at the U.S. Marine Corps Weapons Training Battalion Dynamic Entry School. During this training, Students are taught to apply explosive charges to achieve rapid ingress into secured buildings. For this study, both Students and Instructors participated in neurobehavioral testing, blood toxin screening, vestibular/auditory testing, and neuroimaging. Volunteers wore instrumentation during training to allow correlation of human response measurements and blast overpressure exposure. The key findings of this study were from high-memory demand tasks and were limited to the Instructors. Specific tests showing blast-related mean differences were California Verbal Learning Test II, Automated Neuropsychological Assessment Metrics subtests (Match-to-Sample, Code Substitution Delayed), and Delayed Matching-to-Sample 10-second delay condition. Importantly, apparent deficits were paralleled with functional magnetic resonance imaging using the n-back task. The findings of this study are suggestive, but not conclusive, owing to small sample size and effect. The observed changes yield descriptive evidence for potential neurological alterations in the subset of individuals with occupational history of repetitive blast exposure. This is the first study to integrate subject instrumentation for measurement of individual blast pressure exposure, neurocognitive testing, and neuroimaging. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

A Sequential Monte Carlo Approach for Streamflow Forecasting

NASA Astrophysics Data System (ADS)

Hsu, K.; Sorooshian, S.

2008-12-01

As alternatives to traditional physically-based models, Artificial Neural Network (ANN) models offer some advantages with respect to the flexibility of not requiring the precise quantitative mechanism of the process and the ability to train themselves from the data directly. In this study, an ANN model was used to generate one-day-ahead streamflow forecasts from the precipitation input over a catchment. Meanwhile, the ANN model parameters were trained using a Sequential Monte Carlo (SMC) approach, namely Regularized Particle Filter (RPF). The SMC approaches are known for their capabilities in tracking the states and parameters of a nonlinear dynamic process based on the Baye's rule and the proposed effective sampling and resampling strategies. In this study, five years of daily rainfall and streamflow measurement were used for model training. Variable sample sizes of RPF, from 200 to 2000, were tested. The results show that, after 1000 RPF samples, the simulation statistics, in terms of correlation coefficient, root mean square error, and bias, were stabilized. It is also shown that the forecasted daily flows fit the observations very well, with the correlation coefficient of higher than 0.95. The results of RPF simulations were also compared with those from the popular back-propagation ANN training approach. The pros and cons of using SMC approach and the traditional back-propagation approach will be discussed.

The role of legitimation in the professional socialization of second-year undergraduate athletic training students.

PubMed

Klossner, Joanne

2008-01-01

Professional socialization during formal educational preparation can help students learn professional roles and can lead to improved organizational socialization as students emerge as members of the occupation's culture. Professional socialization research in athletic training is limited. To present the role of legitimation and how it influences the professional socialization of second-year athletic training students. Modified constructivist grounded theory and case study methods were used for this qualitative study. An accredited undergraduate athletic training education program. Twelve second-year students were selected purposively. The primary sample group (n = 4) was selected according to theoretical sampling guidelines. The remaining students made up the cohort sample (n = 8). Theoretically relevant data were gathered from 14 clinical instructors to clarify emergent student data. Data collection included document examination, observations, and interviews during 1 academic semester. Data were collected and analyzed through constant comparative analysis. Data triangulation, member checking, and peer-review strategies were used to ensure trustworthiness. Legitimation from various socializing agents initiated professional socialization. Students viewed trust and team membership as rewards for role fulfillment. My findings are consistent with the socialization literature that shows how learning a social or professional role, using rewards to facilitate role performance, and building trusting relationships with socializing agents are important aspects of legitimation and, ultimately, professional socialization.

The hidden curriculum in undergraduate medical education: qualitative study of medical students' perceptions of teaching.

PubMed

Lempp, Heidi; Seale, Clive

2004-10-02

To study medical students' views about the quality of the teaching they receive during their undergraduate training, especially in terms of the hidden curriculum. Semistructured interviews with individual students. One medical school in the United Kingdom. 36 undergraduate medical students, across all stages of their training, selected by random and quota sampling, stratified by sex and ethnicity, with the whole medical school population as a sampling frame. Medical students' experiences and perceptions of the quality of teaching received during their undergraduate training. Students reported many examples of positive role models and effective, approachable teachers, with valued characteristics perceived according to traditional gendered stereotypes. They also described a hierarchical and competitive atmosphere in the medical school, in which haphazard instruction and teaching by humiliation occur, especially during the clinical training years. Following on from the recent reforms of the manifest curriculum, the hidden curriculum now needs attention to produce the necessary fundamental changes in the culture of undergraduate medical education.

Assertiveness levels of nursing students who experience verbal violence during practical training.

PubMed

Unal, Sati; Hisar, Filiz; Görgülü, Ulkü

2012-08-01

The aim of the study was to investigate students' verbal violence experiences, the effect of assertiveness on being subjected to violence, the behaviour of students after the violence and the experience of psychological distress during practical training. The study sample consisted of 274 students attending a school of nursing. A questionnaire form and the Rathus Assertiveness Schedule (RAS) were used for data collection. Percentages, means and the independent samples t-test were used for the evaluation of data. During practical training, the students suffered verbal violence from teachers, department nurses and doctors. The students had higher mean scores of RAS for most types of violence committed by the teachers and being reprimanded by the nurses and 69.3% had not responded to the violence. Students with a high level of assertiveness are subjected to violence more frequently. Being subjected to verbal violence and feeling psychological distress during practical training are a major problem among nursing students. Students should be supported in terms of assertiveness and dealing with violence effectively.

SELDI-TOF-MS proteomic profiling of serum, urine, and amniotic fluid in neural tube defects.

PubMed

Liu, Zhenjiang; Yuan, Zhengwei; Zhao, Qun

2014-01-01

Neural tube defects (NTDs) are common birth defects, whose specific biomarkers are needed. The purpose of this pilot study is to determine whether protein profiling in NTD-mothers differ from normal controls using SELDI-TOF-MS. ProteinChip Biomarker System was used to evaluate 82 maternal serum samples, 78 urine samples and 76 amniotic fluid samples. The validity of classification tree was then challenged with a blind test set including another 20 NTD-mothers and 18 controls in serum samples, and another 19 NTD-mothers and 17 controls in urine samples, and another 20 NTD-mothers and 17 controls in amniotic fluid samples. Eight proteins detected in serum samples were up-regulated and four proteins were down-regulated in the NTD group. Four proteins detected in urine samples were up-regulated and one protein was down-regulated in the NTD group. Six proteins detected in amniotic fluid samples were up-regulated and one protein was down-regulated in the NTD group. The classification tree for serum samples separated NTDs from healthy individuals, achieving a sensitivity of 91% and a specificity of 97% in the training set, and achieving a sensitivity of 90% and a specificity of 97% and a positive predictive value of 95% in the test set. The classification tree for urine samples separated NTDs from controls, achieving a sensitivity of 95% and a specificity of 94% in the training set, and achieving a sensitivity of 89% and a specificity of 82% and a positive predictive value of 85% in the test set. The classification tree for amniotic fluid samples separated NTDs from controls, achieving a sensitivity of 93% and a specificity of 89% in the training set, and achieving a sensitivity of 90% and a specificity of 88% and a positive predictive value of 90% in the test set. These suggest that SELDI-TOF-MS is an additional method for NTDs pregnancies detection.

Compliance Testing of Grissom AFB Central Heating Plant Coal-Fired Boilers 3, 4, and 5, Grissom AFB, Indiana

DTIC Science & Technology

1989-06-01

to a common breeching and can be routed to the wet -scrubber or to a bypass stack. The scrubber is a double-alkali flue - gas desulfurization system...the ambient air Bw. = proportion by volume of water vapor in F, = a factor representing a ratio of the vol. the stack gas . ume of wet flue gases...Scrubbers and Bypass Stacks 4 3 Flue Gas Flow Diagram 5 4 ORSAT Sampling Train 8 5 ORSAT Apparatus 8 6 Particulate Sampling Train 9 Table 1 Emission

Hematological and metabolic responses to training in racing sled dogs fed diets containing medium, low, or zero carbohydrate.

PubMed

Kronfeld, D S; Hammel, E P; Ramberg, C F; Dunlap, H L

1977-03-01

In a 28 week study, 18 racing sled dogs were trained to maximal fitness in 12 weeks, sustained through a racing season of 12 weeks, followed by gradual of training of 4 weeks. The dogs were fed a predominantly cereal diet prior to the study; experimental diets containing more chicken and meat by products were introduced from the 2nd to the 4th week of training. On an energy basis, the diets contained protein, fat, and carbohydrate in the proportions of 39:61:0 (diet A), 32:45:23 (diet B), and 28:34:38 (diet C). Blood samples were taken at rest just before the start of training, at 6, 12,24 and 28 weeks; 33 variables were measured on most samples. The results were subjected to analysis of variance. No adverse effects were observed in dogs fed the extreme diet A. Significant relationships to training were shown by serum glutamic oxaloacetic transaminase, creatinine, packed cell volume, calcium, hemoglobin, and globulin. Serum cholesterol concentration increased with the introduction of the higher protein-fat diets; the high concentrations attenuated with time but rose again when training was abated. Dogs on diet A maintained higher serum concentrations of albumin, calcium, magnesium, and free fatty acids during the racing season than did dogs fed diets B or C. They also exhibited the greatest increases in red cell count, hemoglobin concentration, and packed cell volume during training. High values of red cell indices were not sustained through the racing season in dogs fed diet C. In addition to attributes already widely appreciated, viz. a higher energy density an digestibility, the carbohydrate-free, high-fat diet A appeared to confer advantages for prolonged strenuous running in terms of certain metabolic responses to training.

Training attentional control in older adults

PubMed Central

MacKay-Brandt, Anna

2013-01-01

Recent research has demonstrated benefits for older adults from training attentional control using a variable priority strategy, but the construct validity of the training task and the degree to which benefits of training transfer to other contexts are unclear. The goal of this study was to characterize baseline performance on the training task in a sample of 105 healthy older adults and to test for transfer of training in a subset (n = 21). Training gains after 5 days and extent of transfer was compared to another subset (n = 20) that served as a control group. Baseline performance on the training task was characterized by a two-factor model of working memory and processing speed. Processing speed correlated with the training task. Training gains in speed and accuracy were reliable and robust (ps <.001, η2 = .57 to .90). Transfer to an analogous task was observed (ps <.05, η2 = .10 to .17). The beneficial effect of training did not translate to improved performance on related measures of processing speed. This study highlights the robust effect of training and transfer to a similar context using a variable priority training task. Although processing speed is an important aspect of the training task, training benefit is either related to an untested aspect of the training task or transfer of training is limited to the training context. PMID:21728889

Pharmacist supply of sildenafil: pharmacists' experiences and perceptions on training and tools for supply.

PubMed

Braund, Rhiannon; Ratnayake, Kaushalya; Tong, Katie; Song, Jackie; Chai, Stephen; Gauld, Natalie

2018-06-01

Background In 2014, New Zealand reclassified sildenafil (for erectile dysfunction) to allow supply by specially trained pharmacists under strict criteria. Objective The study aimed to determine pharmacists' experiences and perspectives on the training for, and supply of sildenafil under this model. Setting New Zealand community pharmacy. Method This qualitative study captured data with a semi-structured interview used with purposively-sampled participants. A maximum variation sample was used to select a wide range of pharmacists working in various pharmacies, including pharmacists who were trained to provide sildenafil and those not trained to supply sildenafil. Consenting pharmacists were interviewed, with interviews audio-recorded and transcribed. Analysis used a framework approach. Main outcome measures Topics explored included: satisfaction and experience of the training; suitability and usability of the screening tools; experiences of the supply process and why some pharmacists chose not to become trained. Results Thirty-five pharmacists were interviewed. Training was seen as uncomplicated and the screening tools provided confidence that key consultation areas were covered. Most consultations reportedly took 15-20 min, some up to 60 min. Pharmacists reported being comfortable with the consultations. Many men requesting supply fell outside of the parameters, resulting in medical referral. This new model of supply was seen as a positive for pharmacists and their patients. Unaccredited pharmacists reported a perceived lack of interest from men, or ability to provide the service as reasons for not seeking accreditation. Conclusion New Zealand's model of pharmacist supply of sildenafil appears workable with some areas for improvement identified.

The influence of listener training on the perceptual assessment of hypernasality.

PubMed

Oliveira, Adriana Cristina de Almeida Santos Furlan de; Scarmagnani, Rafaeli Higa; Fukushiro, Ana Paula; Yamashita, Renata Paciello

2016-04-01

Introduction A high agreement in the perceptual assessment of hypernasality among different listeners is difficult to achieve. Prior listener training and the standardization of analysis criteria may be effective strategies to decrease the effect of perceptual assessment subjectivity and increase the agreement among listeners. Objective To investigate the influence of prior training on agreement among different listeners in the perceptual assessment of hypernasality. Methods Three experienced speech-language pathologists analyzed 77 audio-recorded speech samples of individuals with repaired cleft palate. During the first phase, the listeners classified hypernasality according to their own criteria, using a 4-point scale. Seventy days later, they were required to complete the training to define the stimuli to be used as anchors for the assessment in the following phase. During the second phase, the listeners analyzed the same samples and rated hypernasality in a 4-point scale, using the anchors defined during training as the criteria. Intra- and interrater agreement in both the phases were calculated by the kappa coefficient. These values were statistically compared using the Z-test. Results The intrarater agreement obtained between the two phases of the study ranged from 0.38 to 0.92, with a statistically significant difference for one of the listeners (p=0.004). The agreement for the hypernasality degree obtained among the three listeners after training (0.54) was significantly higher than that obtained before training (0.37; p=0.044). Conclusion Listener training and the definition of criteria to rate hypernasality lead to the increase of intra- and interrater agreement.

Image Augmentation for Object Image Classification Based On Combination of Pre-Trained CNN and SVM

NASA Astrophysics Data System (ADS)

Shima, Yoshihiro

2018-04-01

Neural networks are a powerful means of classifying object images. The proposed image category classification method for object images combines convolutional neural networks (CNNs) and support vector machines (SVMs). A pre-trained CNN, called Alex-Net, is used as a pattern-feature extractor. Alex-Net is pre-trained for the large-scale object-image dataset ImageNet. Instead of training, Alex-Net, pre-trained for ImageNet is used. An SVM is used as trainable classifier. The feature vectors are passed to the SVM from Alex-Net. The STL-10 dataset are used as object images. The number of classes is ten. Training and test samples are clearly split. STL-10 object images are trained by the SVM with data augmentation. We use the pattern transformation method with the cosine function. We also apply some augmentation method such as rotation, skewing and elastic distortion. By using the cosine function, the original patterns were left-justified, right-justified, top-justified, or bottom-justified. Patterns were also center-justified and enlarged. Test error rate is decreased by 0.435 percentage points from 16.055% by augmentation with cosine transformation. Error rates are increased by other augmentation method such as rotation, skewing and elastic distortion, compared without augmentation. Number of augmented data is 30 times that of the original STL-10 5K training samples. Experimental test error rate for the test 8k STL-10 object images was 15.620%, which shows that image augmentation is effective for image category classification.

Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia

PubMed Central

LI, CHENGLONG; ZHU, BIAO; CHEN, JIAO; HUANG, XIAOBING

2016-01-01

In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation-positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the micro-array data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML. PMID:27177049

Analysis of training sample selection strategies for regression-based quantitative landslide susceptibility mapping methods

NASA Astrophysics Data System (ADS)

Erener, Arzu; Sivas, A. Abdullah; Selcuk-Kestel, A. Sevtap; Düzgün, H. Sebnem

2017-07-01

All of the quantitative landslide susceptibility mapping (QLSM) methods requires two basic data types, namely, landslide inventory and factors that influence landslide occurrence (landslide influencing factors, LIF). Depending on type of landslides, nature of triggers and LIF, accuracy of the QLSM methods differs. Moreover, how to balance the number of 0 (nonoccurrence) and 1 (occurrence) in the training set obtained from the landslide inventory and how to select which one of the 1's and 0's to be included in QLSM models play critical role in the accuracy of the QLSM. Although performance of various QLSM methods is largely investigated in the literature, the challenge of training set construction is not adequately investigated for the QLSM methods. In order to tackle this challenge, in this study three different training set selection strategies along with the original data set is used for testing the performance of three different regression methods namely Logistic Regression (LR), Bayesian Logistic Regression (BLR) and Fuzzy Logistic Regression (FLR). The first sampling strategy is proportional random sampling (PRS), which takes into account a weighted selection of landslide occurrences in the sample set. The second method, namely non-selective nearby sampling (NNS), includes randomly selected sites and their surrounding neighboring points at certain preselected distances to include the impact of clustering. Selective nearby sampling (SNS) is the third method, which concentrates on the group of 1's and their surrounding neighborhood. A randomly selected group of landslide sites and their neighborhood are considered in the analyses similar to NNS parameters. It is found that LR-PRS, FLR-PRS and BLR-Whole Data set-ups, with order, yield the best fits among the other alternatives. The results indicate that in QLSM based on regression models, avoidance of spatial correlation in the data set is critical for the model's performance.

Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia.

PubMed

Li, Chenglong; Zhu, Biao; Chen, Jiao; Huang, Xiaobing

2016-07-01

In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation‑positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the microarray data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML.

Cleft audit protocol for speech (CAPS-A): a comprehensive training package for speech analysis.

PubMed

Sell, D; John, A; Harding-Bell, A; Sweeney, T; Hegarty, F; Freeman, J

2009-01-01

The previous literature has largely focused on speech analysis systems and ignored process issues, such as the nature of adequate speech samples, data acquisition, recording and playback. Although there has been recognition of the need for training on tools used in speech analysis associated with cleft palate, little attention has been paid to this issue. To design, execute, and evaluate a training programme for speech and language therapists on the systematic and reliable use of the Cleft Audit Protocol for Speech-Augmented (CAPS-A), addressing issues of standardized speech samples, data acquisition, recording, playback, and listening guidelines. Thirty-six specialist speech and language therapists undertook the training programme over four days. This consisted of two days' training on the CAPS-A tool followed by a third day, making independent ratings and transcriptions on ten new cases which had been previously recorded during routine audit data collection. This task was repeated on day 4, a minimum of one month later. Ratings were made using the CAPS-A record form with the CAPS-A definition table. An analysis was made of the speech and language therapists' CAPS-A ratings at occasion 1 and occasion 2 and the intra- and inter-rater reliability calculated. Trained therapists showed consistency in individual judgements on specific sections of the tool. Intraclass correlation coefficients were calculated for each section with good agreement on eight of 13 sections. There were only fair levels of agreement on anterior oral cleft speech characteristics, non-cleft errors/immaturities and voice. This was explained, at least in part, by their low prevalence which affects the calculation of the intraclass correlation coefficient statistic. Speech and language therapists benefited from training on the CAPS-A, focusing on specific aspects of speech using definitions of parameters and scalar points, in order to apply the tool systematically and reliably. Ratings are enhanced by ensuring a high degree of attention to the nature of the data, standardizing the speech sample, data acquisition, the listening process together with the use of high-quality recording and playback equipment. In addition, a method is proposed for maintaining listening skills following training as part of an individual's continuing education.

Recognition Using Hybrid Classifiers.

PubMed

Osadchy, Margarita; Keren, Daniel; Raviv, Dolev

2016-04-01

A canonical problem in computer vision is category recognition (e.g., find all instances of human faces, cars etc., in an image). Typically, the input for training a binary classifier is a relatively small sample of positive examples, and a huge sample of negative examples, which can be very diverse, consisting of images from a large number of categories. The difficulty of the problem sharply increases with the dimension and size of the negative example set. We propose to alleviate this problem by applying a "hybrid" classifier, which replaces the negative samples by a prior, and then finds a hyperplane which separates the positive samples from this prior. The method is extended to kernel space and to an ensemble-based approach. The resulting binary classifiers achieve an identical or better classification rate than SVM, while requiring far smaller memory and lower computational complexity to train and apply.

A Descriptive Study of Military Nurse Practitioners’ Practice Settings and Clinical Practice Activities

DTIC Science & Technology

1996-05-01

experience and/or education, patient appreciation, administrative support and trained co-workers. Prescott (1994) states that there is "substantial evidence...role changing by stating that roles involve more than training a person to follow expectations, that the person takes on an active mode of...he sample had 110 respondents. A significant limitation to the study however, is that the responding NPs received training through continuing

Effectiveness of Training Sessions on a Measure of Optimism and Pessimism Concepts among the Kindergarten Children in the District of Al-Shobak in Jordan

ERIC Educational Resources Information Center

Al-Mohtadi, Reham Mohammad; ALdarab'h, Intisar Turki; Gasaymeh, Al-Mothana Moustafa

2015-01-01

The current study aimed to examine the effects of training sessions on children's levels of optimism versus pessimism among the kindergarten children in the district of Shobak in Jordan. The sample of the study consisted 21 children whom their ages were between 5 to 6 years old. A training program was applied. The level of optimism and pessimism…

What's in a name? Inflammatory airway disease in racehorses in training.

PubMed

Cardwell, J M; Christley, R M; Gerber, V; Malikides, N; Wood, J L N; Newton, J R; Hodgson, J L

2011-11-01

The term 'inflammatory airway disease' (IAD) is often used to describe the syndrome of lower airway inflammation that frequently affects young racehorses in training around the world. In practice, this inflammation is generally diagnosed using a combination of endoscopic tracheal examination, including grading of amounts of mucus present and tracheal wash sampling. However, a recent consensus statement from the American College of Veterinary Internal Medicine concluded that bronchoalveolar lavage (BAL) sampling, rather than tracheal wash (TW) sampling, is required for cytological diagnosis of IAD and that tracheal mucus is not an essential criterion. However, as BAL is a relatively invasive procedure that is not commonly used on racing yards, this definition can only be applied routinely to a biased referral population. In contrast, many practitioners continue to diagnose IAD using endoscopic tracheal examination and sampling. We argue that, rather than restricting the use of the term IAD to phenotypes diagnosed by BAL, it is important to distinguish in the literature between airway inflammation diagnosed by BAL and that identified in the field using TW sampling. We suggest the use of the term brIAD for the former and trIAD for the latter. It is essential that we continue to endeavour to improve our understanding of the aetiology, pathogenesis and clinical relevance of airway inflammation identified in racehorses in training using tracheal examination and sampling. Future studies should focus on investigations of the component signs of airway inflammation. © 2011 EVJ Ltd.

Crows spontaneously exhibit analogical reasoning.

PubMed

Smirnova, Anna; Zorina, Zoya; Obozova, Tanya; Wasserman, Edward

2015-01-19

Analogical reasoning is vital to advanced cognition and behavioral adaptation. Many theorists deem analogical thinking to be uniquely human and to be foundational to categorization, creative problem solving, and scientific discovery. Comparative psychologists have long been interested in the species generality of analogical reasoning, but they initially found it difficult to obtain empirical support for such thinking in nonhuman animals (for pioneering efforts, see [2, 3]). Researchers have since mustered considerable evidence and argument that relational matching-to-sample (RMTS) effectively captures the essence of analogy, in which the relevant logical arguments are presented visually. In RMTS, choice of test pair BB would be correct if the sample pair were AA, whereas choice of test pair EF would be correct if the sample pair were CD. Critically, no items in the correct test pair physically match items in the sample pair, thus demanding that only relational sameness or differentness is available to support accurate choice responding. Initial evidence suggested that only humans and apes can successfully learn RMTS with pairs of sample and test items; however, monkeys have subsequently done so. Here, we report that crows too exhibit relational matching behavior. Even more importantly, crows spontaneously display relational responding without ever having been trained on RMTS; they had only been trained on identity matching-to-sample (IMTS). Such robust and uninstructed relational matching behavior represents the most convincing evidence yet of analogical reasoning in a nonprimate species, as apes alone have spontaneously exhibited RMTS behavior after only IMTS training. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification.

PubMed

Vrooman, Henri A; Cocosco, Chris A; van der Lijn, Fedde; Stokking, Rik; Ikram, M Arfan; Vernooij, Meike W; Breteler, Monique M B; Niessen, Wiro J

2007-08-01

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.

Problems in air traffic management. III., Implications of age for training and job performance of air traffic controllers.

DOT National Transportation Integrated Search

1962-02-01

The relationships between chronological age upon entry into ATC training and school and job performance were examined in five samples of air traffic controller trainees. The data confirm conclusively the existence of an inverse relationship such that...

Teaching Teachers to Search Electronically.

ERIC Educational Resources Information Center

Smith, Nancy H. G.

1992-01-01

Describes an inservice teacher training program developed to teach secondary school teachers how to search CD-ROMs, laser disks, and automated catalogs. Training sessions held during faculty meetings are described, computer activities are explained, a sample worksheet for searching an electronic encyclopedia is included, and sources for CD-ROMs…

State of Alaska Fire Service Training. Instructor Certification Standards.

ERIC Educational Resources Information Center

Hagevig, William

Designed for local Alaskan fire departments, this pamphlet provides the criteria and qualifications for certificates of firefighter instructors (basic, advanced, master), a list of approved subject categories for each level of certification, sample certification applications, a list of resource publications, and a training course outline (basic…

Organizational Correlates of Management Training Interests.

ERIC Educational Resources Information Center

Tills, Marvin

A study was made of a sample of Wisconsin manufacturing firms and a subsample of firms in different size categories to determine organizational correlates of management training interests. Correlations were sought between characteristics of firms (ownership, relationship to parent company, size of employment, market orientation, growth trends,…

Training Parents with Videotapes: Recognizing Limitations

ERIC Educational Resources Information Center

Foster, Brandon W.; Roberts, Mark W.

2007-01-01

Among the many methods of teaching skills to parents of disruptive children, videotape modeling of specific parent-child interaction sequences has been particularly effective. Given the likelihood of timeout resistance in defiant children, the authors tested the effectiveness of videotape parent training with a sample of clinic referred,…

Plyometrics: A Legitimate Form of Power Training?

ERIC Educational Resources Information Center

Duda, Marty

1988-01-01

Plyometric exercises or drills combine speed and strength to produce an explosive-reactive movement or increased power. Some world-class athletes have used plyometric-training in sports such as high-jumping, hurdles, football, baseball, and hockey. The method is still considered experimental. Sample exercises are described. (JL)

Water Quality & Pollutant Source Monitoring: Field and Laboratory Procedures. Training Manual.

ERIC Educational Resources Information Center

Office of Water Program Operations (EPA), Cincinnati, OH. National Training and Operational Technology Center.

This training manual presents material on techniques and instrumentation used to develop data in field monitoring programs and related laboratory operations concerned with water quality and pollution monitoring. Topics include: collection and handling of samples; bacteriological, biological, and chemical field and laboratory methods; field…

A school mental health literacy curriculum resource training approach: effects on Tanzanian teachers' mental health knowledge, stigma and help-seeking efficacy.

PubMed

Kutcher, Stan; Wei, Yifeng; Gilberds, Heather; Ubuguyu, Omary; Njau, Tasiana; Brown, Adena; Sabuni, Norman; Magimba, Ayoub; Perkins, Kevin

2016-01-01

Mental health literacy (MHL) is foundational for mental health promotion, prevention, stigma reduction, and care; School supported information pertaining to MHL in sub-Saharan Africa is extremely limited, including in Tanzania. Successful application of a school MHL curriculum resource may be an effective way to increase teacher MHL and therefore help to improve mental health outcomes for students. Secondary school teachers in Tanzania were trained on the African Guide (AG) a school MHL curriculum resource culturally adapted from a Canadian MHL resource (The Guide) for use in Africa. Teacher training workshops on the classroom application of the AG were used to evaluate its impact on mental health literacy in a sample of Tanzanian Secondary school teachers. Pre-post training assessment of participant knowledge and attitudes was conducted. Help-seeking efficacy for teachers themselves and their interventions for students, friends, family members and peers were determined. Paired t test (n = 37) results demonstrate highly significant improvements in teacher's overall knowledge (p < 0.001; d = 1.14), including mental health knowledge, (p < 0.001; d = 1.14) and curriculum specific knowledge (p < 0.01; d = 0.63). Teachers' stigma against mental illness decreased significantly following the training (p < 0.001; d = 0.61). Independent t tests comparing the paired sample against unpaired sample also demonstrated significant differences between the groups for teacher's overall knowledge (p < 0.001). Teachers also reported high rates (greater than ¾ of the sample) of positive help-seeking efficacy for themselves as well as for their students, friends, family members and peers. As a result of the training, the number of students teachers identified for potential mental health care totaled over 200. These positive results, when taken together with other research, suggest that the use of a classroom-based resource (the AG) that integrates MHL into existing school curriculum through training teachers may be an effective and sustainable way to increase the MHL (improved knowledge, decreased stigma and positive help-seeking efficacy) of teachers in Tanzania. As this study replicated the results of a previous intervention in Malawi, consideration could be given to scaling up this intervention in both countries and applying this resource and approach in other countries in East Africa.

Biodynamic feedback training to assure learning partial load bearing on forearm crutches.

PubMed

Krause, Daniel; Wünnemann, Martin; Erlmann, Andre; Hölzchen, Timo; Mull, Melanie; Olivier, Norbert; Jöllenbeck, Thomas

2007-07-01

To examine how biodynamic feedback training affects the learning of prescribed partial load bearing (200N). Three pre-post experiments. Biomechanics laboratory in a German university. A volunteer sample of 98 uninjured subjects who had not used crutches recently. There were 24 subjects in experiment 1 (mean age, 23.2y); 64 in experiment 2 (mean age, 43.6y); and 10 in experiment 3 (mean age, 40.3y), parallelized by arm force. Video instruction and feedback training: In experiment 1, 2 varied instruction videos and reduced feedback frequency; in experiment 2, varied frequencies of changing tasks (contextual interference); and in experiment 3, feedback training (walking) and transfer (stair tasks). Vertical ground reaction force. Absolute error of practiced tasks was significantly reduced for all samples (P<.050). Varied contextual interference conditions did not significantly affect retention (P=.798) or transfer (P=.897). Positive transfer between tasks was significant in experiment 2 (P<.001) and was contrary to findings in experiment 3 (P=.071). Biodynamic feedback training is applicable for learning prescribed partial load bearing. The frequency of changing tasks is irrelevant. Despite some support for transfer effects, additional practice in climbing and descending stairs might be beneficial.

Transfer Learning for Class Imbalance Problems with Inadequate Data.

PubMed

Al-Stouhi, Samir; Reddy, Chandan K

2016-07-01

A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

PubMed

Zwartjes, Ardjan; Havinga, Paul J M; Smit, Gerard J M; Hurink, Johann L

2016-10-01

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

Emergent, untrained stimulus relations in many-to-one matching-to-sample discriminations in rats.

PubMed

Nakagawa, Esho

2005-03-01

The present experiment investigated whether rats formed emergent, untrained stimulus relations in many-to-one matching-to-sample discriminations. In Phase 1, rats were trained to match two samples (triangle and horizontal stripes) to a common comparison (horizontal stripes) and two additional samples (circle or vertical stripes) to another comparison (vertical stripes). Then, in Phase 2, the rats were trained to match the one sample (triangle) to a new comparison (black) and the other sample (circle) to another comparison (white). In the Phase 3 test, half the rats (consistent group) were given two new tasks in which the sample-correct comparison relation was consistent with any emergent stimulus relations that previously may have been learned. The remaining 6 rats (inconsistent group) were given two new tasks in which the sample-correct comparison relation was not consistent with any previously learned emergent stimulus relations. Rats in the consistent group showed more accurate performance at the start of Phase 3, and faster learning to criterion in this phase, as compared with rats in the inconsistent group. This finding suggests that rats may form emergent, untrained stimulus relations between the discriminative stimuli in many-to-one matching-to-sample discriminations.

Metadynamics for training neural network model chemistries: A competitive assessment

NASA Astrophysics Data System (ADS)

Herr, John E.; Yao, Kun; McIntyre, Ryker; Toth, David W.; Parkhill, John

2018-06-01

Neural network model chemistries (NNMCs) promise to facilitate the accurate exploration of chemical space and simulation of large reactive systems. One important path to improving these models is to add layers of physical detail, especially long-range forces. At short range, however, these models are data driven and data limited. Little is systematically known about how data should be sampled, and "test data" chosen randomly from some sampling techniques can provide poor information about generality. If the sampling method is narrow, "test error" can appear encouragingly tiny while the model fails catastrophically elsewhere. In this manuscript, we competitively evaluate two common sampling methods: molecular dynamics (MD), normal-mode sampling, and one uncommon alternative, Metadynamics (MetaMD), for preparing training geometries. We show that MD is an inefficient sampling method in the sense that additional samples do not improve generality. We also show that MetaMD is easily implemented in any NNMC software package with cost that scales linearly with the number of atoms in a sample molecule. MetaMD is a black-box way to ensure samples always reach out to new regions of chemical space, while remaining relevant to chemistry near kbT. It is a cheap tool to address the issue of generalization.

Degradation analysis in the estimation of photometric redshifts from non-representative training sets

NASA Astrophysics Data System (ADS)

Rivera, J. D.; Moraes, B.; Merson, A. I.; Jouvel, S.; Abdalla, F. B.; Abdalla, M. C. B.

2018-07-01

We perform an analysis of photometric redshifts estimated by using a non-representative training sets in magnitude space. We use the ANNz2 and GPz algorithms to estimate the photometric redshift both in simulations and in real data from the Sloan Digital Sky Survey (DR12). We show that for the representative case, the results obtained by using both algorithms have the same quality, using either magnitudes or colours as input. In order to reduce the errors when estimating the redshifts with a non-representative training set, we perform the training in colour space. We estimate the quality of our results by using a mock catalogue which is split samples cuts in the r band between 19.4 < r < 20.8. We obtain slightly better results with GPz on single point z-phot estimates in the complete training set case, however the photometric redshifts estimated with ANNz2 algorithm allows us to obtain mildly better results in deeper r-band cuts when estimating the full redshift distribution of the sample in the incomplete training set case. By using a cumulative distribution function and a Monte Carlo process, we manage to define a photometric estimator which fits well the spectroscopic distribution of galaxies in the mock testing set, but with a larger scatter. To complete this work, we perform an analysis of the impact on the detection of clusters via density of galaxies in a field by using the photometric redshifts obtained with a non-representative training set.

Pelvic floor muscle training protocol for stress urinary incontinence in women: A systematic review.

PubMed

Oliveira, Marlene; Ferreira, Margarida; Azevedo, Maria João; Firmino-Machado, João; Santos, Paula Clara

2017-07-01

Strengthening exercises for pelvic floor muscles (SEPFM) are considered the first approach in the treatment of stress urinary incontinence (SUI). Nevertheless, there is no evidence about training parameters. To identify the protocol and/or most effective training parameters in the treatment of female SUI. A literature research was conducted in the PubMed, Cochrane Library, PEDro, Web of Science and Lilacs databases, with publishing dates ranging from January 1992 to March 2014. The articles included consisted of English-speaking experimental studies in which SEPFM were compared with placebo treatment (usual or untreated). The sample had a diagnosis of SUI and their age ranged between 18 and 65 years. The assessment of methodological quality was performed based on the PEDro scale. Seven high methodological quality articles were included in this review. The sample consisted of 331 women, mean age 44.4±5.51 years, average duration of urinary loss of 64±5.66 months and severity of SUI ranging from mild to severe. SEPFM programs included different training parameters concerning the PFM. Some studies have applied abdominal training and adjuvant techniques. Urine leakage cure rates varied from 28.6 to 80%, while the strength increase of PFM varied from 15.6 to 161.7%. The most effective training protocol consists of SEPFM by digital palpation combined with biofeedback monitoring and vaginal cones, including 12 week training parameters, and ten repetitions per series in different positions compared with SEPFM alone or a lack of treatment.

Degradation analysis in the estimation of photometric redshifts from non-representative training sets

NASA Astrophysics Data System (ADS)

Rivera, J. D.; Moraes, B.; Merson, A. I.; Jouvel, S.; Abdalla, F. B.; Abdalla, M. C. B.

2018-04-01

We perform an analysis of photometric redshifts estimated by using a non-representative training sets in magnitude space. We use the ANNz2 and GPz algorithms to estimate the photometric redshift both in simulations as well as in real data from the Sloan Digital Sky Survey (DR12). We show that for the representative case, the results obtained by using both algorithms have the same quality, either using magnitudes or colours as input. In order to reduce the errors when estimating the redshifts with a non-representative training set, we perform the training in colour space. We estimate the quality of our results by using a mock catalogue which is split samples cuts in the r-band between 19.4 < r < 20.8. We obtain slightly better results with GPz on single point z-phot estimates in the complete training set case, however the photometric redshifts estimated with ANNz2 algorithm allows us to obtain mildly better results in deeper r-band cuts when estimating the full redshift distribution of the sample in the incomplete training set case. By using a cumulative distribution function and a Monte-Carlo process, we manage to define a photometric estimator which fits well the spectroscopic distribution of galaxies in the mock testing set, but with a larger scatter. To complete this work, we perform an analysis of the impact on the detection of clusters via density of galaxies in a field by using the photometric redshifts obtained with a non-representative training set.

Occupational exposure to airborne lead in Brazilian police officers.

PubMed

Rocha, Ernesto Díaz; Sarkis, Jorge E Souza; Carvalho, Maria de Fátima H; Santos, Gerson Vechio Dos; Canesso, Claudemir

2014-07-01

Shooting with lead-containing ammunition in indoor firing ranges is a known source of lead exposure in adults. Police officers may be at risk of lead intoxication when regular training shooting exercises are yearly mandatory to law enforcement officers. Effects on health must be documented, even when low-level elemental (inorganic) lead exposure is detected. Forty police officers (nineteen cadets and twenty-one instructors) responded to a questionnaire about health, shooting habits, and potential lead exposure before a training curse. Blood samples were collected and analyzed for blood lead level (BLL) before and after a three days training curse. The mean BLL for the instructors' group was 5.5 μg/dL ± 0.6. The mean BLL for the cadets' group before the training was 3.3 μg/dL ± 0.15 and after the training the main BLL was 18.2 μg/d L± 1.5. Samples were analyzed by Inductively Coupled Plasma Mass Spectrometer (ICP-MS). All the participants in the training curse had significantly increased BLL (mean increment about 15 μg/dL) after the three days indoor shooting season. In conclusion, occupational lead exposure in indoor firing ranges is a source of lead exposure in Brazilian police officers, and appears to be a health risk, especially when heavy weapons with lead-containing ammunition are used in indoor environments during the firing training seasons. Copyright © 2013 Elsevier GmbH. All rights reserved.

Stochastic subset selection for learning with kernel machines.

PubMed

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Unsupervised Ensemble Anomaly Detection Using Time-Periodic Packet Sampling

NASA Astrophysics Data System (ADS)

Uchida, Masato; Nawata, Shuichi; Gu, Yu; Tsuru, Masato; Oie, Yuji

We propose an anomaly detection method for finding patterns in network traffic that do not conform to legitimate (i.e., normal) behavior. The proposed method trains a baseline model describing the normal behavior of network traffic without using manually labeled traffic data. The trained baseline model is used as the basis for comparison with the audit network traffic. This anomaly detection works in an unsupervised manner through the use of time-periodic packet sampling, which is used in a manner that differs from its intended purpose — the lossy nature of packet sampling is used to extract normal packets from the unlabeled original traffic data. Evaluation using actual traffic traces showed that the proposed method has false positive and false negative rates in the detection of anomalies regarding TCP SYN packets comparable to those of a conventional method that uses manually labeled traffic data to train the baseline model. Performance variation due to the probabilistic nature of sampled traffic data is mitigated by using ensemble anomaly detection that collectively exploits multiple baseline models in parallel. Alarm sensitivity is adjusted for the intended use by using maximum- and minimum-based anomaly detection that effectively take advantage of the performance variations among the multiple baseline models. Testing using actual traffic traces showed that the proposed anomaly detection method performs as well as one using manually labeled traffic data and better than one using randomly sampled (unlabeled) traffic data.

Mark 4A project training evaluation

NASA Technical Reports Server (NTRS)

Stephenson, S. N.

1985-01-01

A participant evaluation of a Deep Space Network (DSN) is described. The Mark IVA project is an implementation to upgrade the tracking and data acquisition systems of the dSN. Approximately six hundred DSN operations and engineering maintenance personnel were surveyed. The survey obtained a convenience sample including trained people within the population in order to learn what training had taken place and to what effect. The survey questionnaire used modifications of standard rating scales to evaluate over one hundred items in four training dimensions. The scope of the evaluation included Mark IVA vendor training, a systems familiarization training seminar, engineering training classes, a on-the-job training. Measures of central tendency were made from participant rating responses. Chi square tests of statistical significance were performed on the data. The evaluation results indicated that the effects of different Mark INA training methods could be measured according to certain ratings of technical training effectiveness, and that the Mark IVA technical training has exhibited positive effects on the abilities of DSN personnel to operate and maintain new Mark IVA equipment systems.

Sibling Conflict Resolution Skills: Assessment and Training

ERIC Educational Resources Information Center

Thomas, Brett W.; Roberts, Mark W.

2009-01-01

Sibling conflict can rise to the level of a clinical problem. In Phase 1 a lengthy behavioral role-play analog sampling child reactions to normal sibling conflicts was successfully shortened. In Phase 2 normal children who lacked sibling conflict resolution skills were randomly assigned to a Training or Measurement Only condition. Training…

Structural Precursors to Identity Processes: The Role of Proximate Social Structures

ERIC Educational Resources Information Center

Merolla, David M.; Serpe, Richard T.; Stryker, Sheldon; Schultz, P. Wesley

2012-01-01

This research investigates how participation in college-based science-training programs increases student intention to pursue a scientific career. Using identity theory, we delineate three levels of social structure and conceptualize science-training programs as proximate social structures. Results from a sample of 892 undergraduate science…

Entrepreneur Training Program. Getting Started.

ERIC Educational Resources Information Center

De Maria, Richard

This student workbook on starting a small business is part of the entrepreneur training program at Ocean County (New Jersey) Vocational-Technical Schools. The workbook consists of 16 units containing goals and objectives, study questions, exercises, sample materials, and information sheets. Unit topics are as follows: being a small business owner;…

Training in Japan: The Use of Instructional Systems Design.

ERIC Educational Resources Information Center

Taguchi, Mina; Keller, John M.

This study investigated the kinds of training conducted in Japanese companies and the degree to which instructional systems design (ISD) is implemented. A random sample of 12 Japanese companies in the banking, automobile manufacturing, electrical machinery, wholesale stores, insurance and securities, and transportation industries were surveyed; a…

The Rise and Fall of Diversity Training.

ERIC Educational Resources Information Center

Easter, Marilyn

The effectiveness of diversity training in eliminating racial stereotypes in the workplace and modifying employees' negative attitudes toward diversity was examined in a study conducted at a private nonprofit college in the San Francisco Bay area. The study sample consisted of 80 nontraditional students from 4 sections of a course titled Managing…

10 CFR 39.13 - Specific licenses for well logging.

Code of Federal Regulations, 2010 CFR

2010-01-01

... training; (2) On-the-job training; (3) Annual safety reviews provided by the licensee; (4) Means the... annual inspections of the job performance of each logging supervisor to ensure that the Commission's... performing the analysis; and (3) Pertinent experience of the person who will analyze the wipe samples. ...

Multiple Effects of Human Resource Development Interventions

ERIC Educational Resources Information Center

Rowold, Jens

2008-01-01

Purpose: This study aims to explore the simultaneous impact of employees participation in non-technical training, technical training, and coaching on subsequent job performance, job involvement, and job satisfaction. Design/methodology/approach: The present study was based on a sample of German call center employees and on a longitudinal,…

Factors Influencing the Implementation of Training and Learning in the Workplace.

ERIC Educational Resources Information Center

Ridoutt, Lee; Dutneall, Ralph; Hummel, Kevin; Smith, Chris Selby

The quantitative relationship between factors previously identified as affecting the extent and intensity of training within organizations was explored through a survey of companies in Australia's entertainment and process manufacturing sectors. A self-completion questionnaire was mailed first to a sample of 446 companies across Australia (112 of…

The Complete Guide to Training Delivery: A Competency-Based Approach.

ERIC Educational Resources Information Center

King, Stephen B.; King, Marsha; Rothwell, William J.

This guide focuses on 14 instructor competencies identified by the International Board of Standards for Training, Performance, and Instruction. It provides examples, job aids, worksheets, case studies, and sample dialogs and contains actual experiences and critical incidents faced by trainers who participated in the survey study. Strategies to…

Lead Sampling Technician Training Course. Trainer Manual.

ERIC Educational Resources Information Center

ICF, Inc., Washington, DC.

This document presents a model curriculum for use by trainers presenting training course in assessing and reporting dust and debris from deteriorated lead-based paint. The course, which was developed by the U.S. Environmental Protection Agency, is intended for use with housing quality standard inspectors, rehabilitation specialists, home…

O'Neal Training Manual.

ERIC Educational Resources Information Center

Alabama State Dept. of Education, Montgomery.

This training manual provides 42 lessons developed for a workplace literacy program at O'Neal Steel. Each lesson consists of a summary sheet with activities and corresponding materials and time; handout(s); pretest; instructor materials and samples; and worksheet(s). Activities in each lesson are set induction, guided practice, applied practice,…

Exploring the Relationships among Multicultural Training Experiences and Attitudes toward Diversity among Counseling Students

ERIC Educational Resources Information Center

Dickson, Ginger L.; Jepsen, David A.; Barbee, Phillip W.

2008-01-01

The authors surveyed a national sample of master's-level counseling students regarding their multicultural training experiences and their attitudes toward racial diversity and gender equity. Hierarchical regression models showed that student perceptions of program cultural ambience predicted positive cognitive attitudes toward racial diversity.…

NHEXAS PHASE I MARYLAND STUDY--STANDARD OPERATING PROCEDURE FOR TRAINING OF PHLEBOTOMISTS (G10)

EPA Science Inventory

The purpose of this SOP is to outline the responsibilities of the phlebotomist before, during, and after sampling at residences; and the training system that teaches phlebotomists what they need to know to handle these responsibilities. The overall responsibilities are to collec...

English Preservice Teaching: Problems and Suggested Solutions

ERIC Educational Resources Information Center

Naeem, Marwa Ahmed Refat

2014-01-01

The present study investigated the problems faced by Egyptian EFL prospective teachers during their first encounter with preservice teaching. The sample for the study included 135 prospective EFL teachers trained in five preparatory (middle) schools in Kafr El-Sheikh city, Egypt. At the end of their first year training course, the prospective…

The Role of Anonymity in Peer Assessment

ERIC Educational Resources Information Center

Li, Lan

2017-01-01

This quasi-experimental study aimed to examine the impact of anonymity and training (an alternative strategy when anonymity was unattainable) on students' performance and perceptions in formative peer assessment. The training in this study focused on educating students to understand and appreciate formative peer assessment. A sample of 77 students…

Training Neighborhood Residents to Conduct a Survey

ERIC Educational Resources Information Center

Back, Susan Malone; Tseng, Wan-Chun; Li, Jiaqi; Wang, Yuanhua; Phan, Van Thanh; Yeter, Ibrahim Halil

2015-01-01

As a requirement for a federal neighborhood revitalization grant, the authors trained resident interviewers and coordinated the conduct of more than 1000 door-to-door interviews of a stratified random sample. The targeted area was a multiethnic, lower income neighborhood that continues to experience the effects of past segregation. Monitoring and…

The Jump Training Program. In Season Conditioning for Women's Basketball.

ERIC Educational Resources Information Center

Hannam, Sue; And Others

1988-01-01

Women athletes have been successful in maintaining and/or increasing their conditioning and vertical jump levels when they participate in the in-season circuit training program described in this article. An exercise guide, sample individual score card, and photos of women practicing the exercises are included. (IAH)

The Value of LIS Schools' Research Topics to Library Authors' Professional Work

ERIC Educational Resources Information Center

Perkins, Gay Helen; Helbig, Tuesdi L.

2008-01-01

Stoan's distinction between library skills and research skills based on different philosophies of information seeking suggests the value of training in research methodology for the librarian. Such training could lead to more effective patron consultations, committee/administrative work, and personal research. Thus, a convenience sample of…

Cost Control. Michigan School Food Service Training Manual.

ERIC Educational Resources Information Center

Michigan State Univ., East Lansing. Cooperative Extension Service.

Cost control is the subject of this eight-lesson, three-test food service training manual. Lesson 1 deals with financial accountability and includes 17 handouts, ranging from sample balance to quarterly report sheets. Lesson 2 focuses on budgeting principles, and lesson 3 on labor controls. Professional purchasing, receiving, and inventorying…

Taking the Pulse of Training Transfer: Instructor Quality and EMT Certification Examination Results

ERIC Educational Resources Information Center

Russ-Eft, Darlene F.; Dickison, Phil; Levine, Roger

2010-01-01

The Longitudinal Emergency Medical Technician Attributes and Demographics Study (LEADS) provides a representative sampling of EMTs throughout the United States. The present study adds to the transfer of training literature by examining the relationship between instructor quality and National Registry of Emergency Medical Technicians certification…

Associative Symmetry by Pigeons after Few-Exemplar Training

ERIC Educational Resources Information Center

Velasco, Saulo M.; Huziwara, Edson M.; Machado, Armando; Tomanari, Gerson Y.

2010-01-01

The present experiment investigated whether pigeons can show associative symmetry on a two-alternative matching-to-sample procedure. The procedure consisted of a within-subject sequence of training and testing with reinforcement, and it provided (a) exemplars of symmetrical responding, and (b) all prerequisite discriminations among test samples…

Training of Existing Workers: Issues, Incentives and Models

ERIC Educational Resources Information Center

Mawer, Giselle; Jackson, Elaine

2005-01-01

This report presents issues associated with incentives for training existing workers in small to medium-sized firms, identified through a small sample of case studies from the retail, manufacturing, and building and construction industries. While the majority of employers recognise workforce skill levels are fundamental to the success of the…

The Practice of Psychotherapy in Mexico: Past and Present

ERIC Educational Resources Information Center

Stark, Marcella D.; Frels, Rebecca K.; Chavez, Rafael Reyes; Sharma, Bipin

2010-01-01

This article explores the history of psychotherapy in Mexico and describes past and current practices of psychological services, training, and supervision for Mexican international students in the United States. Sample curricula, texts, and universities in Mexico are listed. Implications for training underscore the importance of collaboration and…

Variables Related to MDTA Trainee Employment Success in Minnesota.

ERIC Educational Resources Information Center

Pucel, David J.

To predict a person's use of his Manpower Development and Training Act (MDTA) training, this study attempted to supplement existing methods of evaluation, using personal descriptive data about trainees and General Aptitude Test Battery Scores. The sample under study included all students enrolled in ten MDTA projects, representing a geographical…

Desarrollo de un instrumento para medir percepciones sobre el contexto de construccion del conocimiento cientifico de estudiantes universitarios de nuevo ingreso

NASA Astrophysics Data System (ADS)

Garcia-Ramirez, Jaime Antonio

En esta investigacion, se desarrollo un instrumento que permite medir percepciones relacionadas al contexto de constriccion del conocimiento cientifico. Se examinaron instrumentos existentes y se encontro que el VOSTS (Views on science, technology, and society), instrumento desarrollado empiricamente en Canada por Aikenhead, Ryan y Fleming, podia traducirse y validarse en el contexto cultural puertorriqueno. El instrumento es extenso, consta de 113 reactivos, cada uno con una premisa basica relacionada a la tematica ciencia, tecnologia y sociedad y un numero de alternativas relacionadas a la premisa que oscila entre siete y trece. Se delimito su utilizacion a los quince reactivos identificados por los autores como relacionados a la construccion social del conocimiento cientifico. Metodologicamente, se procedio a utilizar el modelo de adaptacion intercultural, que permite que el instrumento desarrollado satisfaga las dimensiones de equivalencia semantica, de contenido, tecnica, de criterio y conceptual, atemperado asi al instrumento original. Se cumplio con este proposito mediante la traduccion de la version original en ingles al espanol y viceversa. Se utilizaron comites para examinar la traduccion y la retro-traduccion del instrumento. Se realizo una prueba piloto con estudiantes universitarios de nuevo ingreso, utilizando el instrumento traducido para asegurar su intelegibilidad. La confiabilidad del instrumento se determino mediante la intervencion de un panel de expertos quienes clasificaron las distintas posiciones dentro de cada reactivo en: realista, con merito e ingenua; se transformaron estas opciones en valores numericos lo que permitio establecer una escala Likert para cada una. Se suministro el instrumento a una muestra de estudiantes universitarios de nuevo ingreso con caracteristicas similares a las de la poblacion puertorriquena en cuanto a ejecucion en las pruebas de aptitud verbal y matematica del College Board. Los resultados de sus contestaciones fueron transformados numericamente para poder obtener el coeficiente de correlacion de Spearman-Brown para el instrumento (0.661, p < 0.01). El analisis de las contestaciones de los estudiantes refleja percepciones diversas y, en algunos casos, contradictorias con respecto al contexto de construccion del conocimiento cientifico.

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M.

2014-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.1 PMID:25395692

Teaching Manual Signs to Adults With Mental Retardation Using Matching-to-Sample Procedures and Stimulus Equivalence

PubMed Central

Elias, Nassim Chamel; Goyos, Celso; Saunders, Muriel; Saunders, Richard

2008-01-01

The objective of this study was to teach manual signs through an automated matching-to-sample procedure and to test for the emergence of new conditional relations and imitative behaviors. Seven adults with mild to severe mental retardation participated. Four were also hearing impaired. Relations between manual signs (set A) and pictures (set B) were initially taught, followed by the training of corresponding printed words (set C) and pictures (set B). Further presentations of conditional discriminations tested for the emergence of AC, followed by tests for the emergence of imitative signing behavior (D) in the presence of either pictures (B) or printed words (C). Each stimulus set was comprised of 9 elements. The stimuli were still pictures, printed words, and dynamic presentations of manual signs. A pretest was conducted to determine which signs the participants could make pre-experimentally. Teaching was arranged in a multiple baseline design across 3 groups of 3 words each. The purpose of the present study was to determine whether participants would emit manual signs in expressive signs tests as a result of observation (video modeling) during match-to-sample training in the absence of explicit training. Five of the 7 subjects passed tests of emergence and emitted at least 50% of the signs. Two were hearing impaired with signing experience, and 3 were not hearing impaired and had no signing experience. Thus, observation of video recorded manual signs in a matching-to-sample training procedure was effective at establishing some signs by adults with mental retardation. PMID:22477400

Optimizing area under the ROC curve using semi-supervised learning.

PubMed

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Smartphone-Based Patients' Activity Recognition by Using a Self-Learning Scheme for Medical Monitoring.

PubMed

Guo, Junqi; Zhou, Xi; Sun, Yunchuan; Ping, Gong; Zhao, Guoxing; Li, Zhuorong

2016-06-01

Smartphone based activity recognition has recently received remarkable attention in various applications of mobile health such as safety monitoring, fitness tracking, and disease prediction. To achieve more accurate and simplified medical monitoring, this paper proposes a self-learning scheme for patients' activity recognition, in which a patient only needs to carry an ordinary smartphone that contains common motion sensors. After the real-time data collection though this smartphone, we preprocess the data using coordinate system transformation to eliminate phone orientation influence. A set of robust and effective features are then extracted from the preprocessed data. Because a patient may inevitably perform various unpredictable activities that have no apriori knowledge in the training dataset, we propose a self-learning activity recognition scheme. The scheme determines whether there are apriori training samples and labeled categories in training pools that well match with unpredictable activity data. If not, it automatically assembles these unpredictable samples into different clusters and gives them new category labels. These clustered samples combined with the acquired new category labels are then merged into the training dataset to reinforce recognition ability of the self-learning model. In experiments, we evaluate our scheme using the data collected from two postoperative patient volunteers, including six labeled daily activities as the initial apriori categories in the training pool. Experimental results demonstrate that the proposed self-learning scheme for activity recognition works very well for most cases. When there exist several types of unseen activities without any apriori information, the accuracy reaches above 80 % after the self-learning process converges.

The Efficacy of Stuttering Measurement Training: Evaluating Two Training Programs

PubMed Central

Bainbridge, Lauren A.; Stavros, Candace; Ebrahimian, Mineh; Wang, Yuedong

2015-01-01

Purpose Two stuttering measurement training programs currently used for training clinicians were evaluated for their efficacy in improving the accuracy of total stuttering event counting. Method Four groups, each with 12 randomly allocated participants, completed a pretest–posttest design training study. They were evaluated by their counts of stuttering events on eight 3-min audiovisual speech samples from adults and children who stutter. Stuttering judgment training involved use of either the Stuttering Measurement System (SMS), Stuttering Measurement Assessment and Training (SMAAT) programs, or no training. To test for the reliability of any training effect, SMS training was repeated with the 4th group. Results Both SMS-trained groups produced approximately 34% improvement, significantly better than no training or the SMAAT program. The SMAAT program produced a mixed result. Conclusions The SMS program was shown to produce a “medium” effect size improvement in the accuracy of stuttering event counts, and this improvement was almost perfectly replicated in a 2nd group. Half of the SMAAT judges produced a 36% improvement in accuracy, but the other half showed no improvement. Additional studies are needed to demonstrate the durability of the reported improvements, but these positive effects justify the importance of stuttering measurement training. PMID:25629956

The efficacy of stuttering measurement training: evaluating two training programs.

PubMed

Bainbridge, Lauren A; Stavros, Candace; Ebrahimian, Mineh; Wang, Yuedong; Ingham, Roger J

2015-04-01

Two stuttering measurement training programs currently used for training clinicians were evaluated for their efficacy in improving the accuracy of total stuttering event counting. Four groups, each with 12 randomly allocated participants, completed a pretest-posttest design training study. They were evaluated by their counts of stuttering events on eight 3-min audiovisual speech samples from adults and children who stutter. Stuttering judgment training involved use of either the Stuttering Measurement System (SMS), Stuttering Measurement Assessment and Training (SMAAT) programs, or no training. To test for the reliability of any training effect, SMS training was repeated with the 4th group. Both SMS-trained groups produced approximately 34% improvement, significantly better than no training or the SMAAT program. The SMAAT program produced a mixed result. The SMS program was shown to produce a "medium" effect size improvement in the accuracy of stuttering event counts, and this improvement was almost perfectly replicated in a 2nd group. Half of the SMAAT judges produced a 36% improvement in accuracy, but the other half showed no improvement. Additional studies are needed to demonstrate the durability of the reported improvements, but these positive effects justify the importance of stuttering measurement training.

High School CPR/AED Training in Washington State.

PubMed

Salvatierra, Gail G; Palazzo, Steven J; Emery, Allison

2017-05-01

Describe the rates of CPR/AED training in high schools in the state of Washington after passage of legislation mandating CPR/AED training. A web-based survey was sent to administrators at 660 public and private high schools in the state of Washington. The survey was completed by 148 schools (22%); 64% reported providing CPR training and 54% provided AED training. Reported barriers to implementation included instructor availability, cost, and a lack of equipment. Descriptive statistics were used to describe the sample characteristics and implementation rates. Mandates without resources and support do not ensure implementation of CPR/AED training in high schools. Full public health benefits of a CPR mandate will not be realized until barriers to implementation are identified and eliminated through use of available, accessible public health resources. © 2016 Wiley Periodicals, Inc.

A sampling approach for predicting the eating quality of apples using visible-near infrared spectroscopy.

PubMed

Martínez Vega, Mabel V; Sharifzadeh, Sara; Wulfsohn, Dvoralai; Skov, Thomas; Clemmensen, Line Harder; Toldam-Andersen, Torben B

2013-12-01

Visible-near infrared spectroscopy remains a method of increasing interest as a fast alternative for the evaluation of fruit quality. The success of the method is assumed to be achieved by using large sets of samples to produce robust calibration models. In this study we used representative samples of an early and a late season apple cultivar to evaluate model robustness (in terms of prediction ability and error) on the soluble solids content (SSC) and acidity prediction, in the wavelength range 400-1100 nm. A total of 196 middle-early season and 219 late season apples (Malus domestica Borkh.) cvs 'Aroma' and 'Holsteiner Cox' samples were used to construct spectral models for SSC and acidity. Partial least squares (PLS), ridge regression (RR) and elastic net (EN) models were used to build prediction models. Furthermore, we compared three sub-sample arrangements for forming training and test sets ('smooth fractionator', by date of measurement after harvest and random). Using the 'smooth fractionator' sampling method, fewer spectral bands (26) and elastic net resulted in improved performance for SSC models of 'Aroma' apples, with a coefficient of variation CVSSC = 13%. The model showed consistently low errors and bias (PLS/EN: R(2) cal = 0.60/0.60; SEC = 0.88/0.88°Brix; Biascal = 0.00/0.00; R(2) val = 0.33/0.44; SEP = 1.14/1.03; Biasval = 0.04/0.03). However, the prediction acidity and for SSC (CV = 5%) of the late cultivar 'Holsteiner Cox' produced inferior results as compared with 'Aroma'. It was possible to construct local SSC and acidity calibration models for early season apple cultivars with CVs of SSC and acidity around 10%. The overall model performance of these data sets also depend on the proper selection of training and test sets. The 'smooth fractionator' protocol provided an objective method for obtaining training and test sets that capture the existing variability of the fruit samples for construction of visible-NIR prediction models. The implication is that by using such 'efficient' sampling methods for obtaining an initial sample of fruit that represents the variability of the population and for sub-sampling to form training and test sets it should be possible to use relatively small sample sizes to develop spectral predictions of fruit quality. Using feature selection and elastic net appears to improve the SSC model performance in terms of R(2), RMSECV and RMSEP for 'Aroma' apples. © 2013 Society of Chemical Industry.

The Impact of NIH Postdoctoral Training Grants on Scientific Productivity

PubMed Central

Jacob, Brian A.; Lefgren, Lars

2011-01-01

In this paper, we estimate the impact of receiving an NIH postdoctoral training grant on subsequent publications and citations. Our sample consists of all applications for NIH postdoctoral training grants (unsuccessful as well as successful) from 1980 to 2000. Both ordinary least squares and regression discontinuity estimates show that receipt of an NIH postdoctoral fellowship leads to about one additional publication over the next five years, which reflects a 20 percent increase in research productivity. PMID:21860538

Social Awareness and Action Training (SAAT)

DTIC Science & Technology

2015-06-01

scheduled for September, 2013, and the one -year follow-in June, 2014. o Preliminary analyses of the pretest - posttest data from Fort Sill and JBLM...training session ( pretest , Time 1) and immediately after the last training session ( posttest , Time 2). The sample size was estimated based on an expected...reverse worded items. As noted in Figure 1, data from 20 soldiers on the pretest or posttest (11 from the SRT, 9 from the CAT) were judged to be of

The Impact of NIH Postdoctoral Training Grants on Scientific Productivity.

PubMed

Jacob, Brian A; Lefgren, Lars

2011-07-01

In this paper, we estimate the impact of receiving an NIH postdoctoral training grant on subsequent publications and citations. Our sample consists of all applications for NIH postdoctoral training grants (unsuccessful as well as successful) from 1980 to 2000. Both ordinary least squares and regression discontinuity estimates show that receipt of an NIH postdoctoral fellowship leads to about one additional publication over the next five years, which reflects a 20 percent increase in research productivity.

Acute exercise and periodized training in different environments affect histone deacetylase activity and interleukin-10 levels in peripheral blood of patients with type 2 diabetes.

PubMed

Korb, Arthiese; Bertoldi, Karine; Agustini Lovatel, Gisele; Sudatti Dellevatti, Rodrigo; Rostirola Elsner, Viviane; Carolina Ferreira Meireles, Louisiana; Fernando Martins Kruel, Luiz; Rodrigues Siqueira, Ionara

2018-05-02

Our purpose was to investigate the effects of aerobic periodized training in aquatic and land environments on plasma histone deacetylase (HDAC) activity and cytokines levels in peripheral blood of diabetes mellitus type 2 (T2DM) patients. The patients underwent 12 weeks of periodized training programs that including walking or running in a swimming pool (aquatic group) or in a track (dry land group). Blood samples were collected immediately before and after both first and last sessions. Plasma cytokine levels and HDAC activity in peripheral blood mononuclear cell (PBMC) was measured. The exercise performed in both environments similarly modulated the evaluated acetylation mark, global HDAC activity. However, a differential profile depending on the evaluated moments was detected, since exercise increased acutely HDAC activity in sedentary and after 12 weeks of training period, while a reduced HDAC activity was observed following periodized training (samples collected before the last session). Additionally, the 12 weeks of periodized exercise in both environments increased IL-10 levels. Our data support the hypothesis that the modulation of HDAC activity and inflammatory status might be at least partially related to the effects of exercise effects on T2DM. The periodized training performed in both aquatic and land environments impacts similarly epigenetic and inflammatory status. Copyright © 2018 Elsevier B.V. All rights reserved.

HLA imputation in an admixed population: An assessment of the 1000 Genomes data as a training set.

PubMed

Nunes, Kelly; Zheng, Xiuwen; Torres, Margareth; Moraes, Maria Elisa; Piovezan, Bruno Z; Pontes, Gerlandia N; Kimura, Lilian; Carnavalli, Juliana E P; Mingroni Netto, Regina C; Meyer, Diogo

2016-03-01

Methods to impute HLA alleles based on dense single nucleotide polymorphism (SNP) data provide a valuable resource to association studies and evolutionary investigation of the MHC region. The availability of appropriate training sets is critical to the accuracy of HLA imputation, and the inclusion of samples with various ancestries is an important pre-requisite in studies of admixed populations. We assess the accuracy of HLA imputation using 1000 Genomes Project data as a training set, applying it to a highly admixed Brazilian population, the Quilombos from the state of São Paulo. To assess accuracy, we compared imputed and experimentally determined genotypes for 146 samples at 4 HLA classical loci. We found imputation accuracies of 82.9%, 81.8%, 94.8% and 86.6% for HLA-A, -B, -C and -DRB1 respectively (two-field resolution). Accuracies were improved when we included a subset of Quilombo individuals in the training set. We conclude that the 1000 Genomes data is a valuable resource for construction of training sets due to the diversity of ancestries and the potential for a large overlap of SNPs with the target population. We also show that tailoring training sets to features of the target population substantially enhances imputation accuracy. Copyright © 2016 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Effects of computerized match-to-sample training on emergent fraction-decimal relations in individuals with fragile X syndrome.

PubMed

Hammond, Jennifer L; Hirt, Melissa; Hall, Scott S

2012-01-01

Individuals diagnosed with fragile X syndrome (FXS), the most common known form of inherited intellectual disability, are reported to exhibit considerable deficits in mathematical skills that are often attributed to brain-based abnormalities associated with the syndrome. We examined whether participants with FXS would display emergent fraction-decimal relations following brief, intensive match-to-sample training on baseline relations. The performance profiles on tests of symmetry and transitivity/equivalence of 11 participants with FXS, aged 10-23 years, following baseline match-to-sample training were compared to those of 11 age- and IQ-matched controls with idiopathic developmental disability. The results showed that both groups of participants showed significant improvements in the baseline (trained) relations, as expected. However, participants with FXS failed to show significant improvements in the (untrained) symmetry and transitivity/equivalence relations compared to those in the control group. A categorical analysis of the data indicated that five participants with FXS and eight controls showed at least "intermediate" emergence of symmetry relations, whereas one individual with FXS and three controls showed at least intermediate emergence of transitivity/equivalence relations. A correlation analysis of the data indicated that improvements in the symmetry relations were significantly associated with improvements in the transitivity/equivalence relations in the control group (r=.69, p=.018), but this was not the case in the FXS group (r=.34, p>.05). Participant IQ was significantly associated with improvements in the symmetry relations in individuals with FXS (r=.60, p=.049), but not in controls (r=.21, p>.05). Taken together, these results suggest that brief, computerized match-to-sample training may produce emergent mathematical relations for a subset of children with FXS and developmental disabilities. However, the ability of individuals with FXS to form transitivity/equivalence relations may be impaired relative to those with idiopathic developmental disabilities, which may be attributed to neurodevelopmental variables associated with the syndrome. Copyright © 2011 Elsevier Ltd. All rights reserved.

Firefighter noise exposure during training activities and general equipment use.

PubMed

Root, Kyle S; Schwennker, Catherine; Autenrieth, Daniel; Sandfort, Delvin R; Lipsey, Tiffany; Brazile, William J

2013-01-01

Multiple noise measurements were taken on 6 types of fire station equipment and 15 types of emergency response vehicle-related equipment used by firefighters during routine and emergency operations at 10 fire stations. Five of the six types of fire station equipment, when measured at a distance of one meter and ear level, emitted noise equal to or greater than 85 dBA, including lawn maintenance equipment, snow blowers, compressors, and emergency alarms. Thirteen of 15 types of equipment located on the fire engines emitted noise levels equal to or greater than 85 dBA, including fans, saws, alarms, and extrication equipment. In addition, noise measurements were taken during fire engine operations, including the idling vehicle, vehicle sirens, and water pumps. Results indicated that idling fire-engine noise levels were below 85 dBA; however, during water pump and siren use, noise levels exceeded 85 dBA, in some instances, at different locations around the trucks where firefighters would be stationed during emergency operations. To determine if the duration and use of fire fighting equipment was sufficient to result in overexposures to noise during routine training activities, 93 firefighter personal noise dosimetry samples were taken during 10 firefighter training activities. Two training activities per sampling day were monitored during each sampling event, for a mean exposure time of 70 min per day. The noise dosimetry samples were grouped based on job description to compare noise exposures between the different categories of job tasks commonly associated with fire fighting. The three job categories were interior, exterior, and engineering. Mean personal dosimetry results indicated that the average noise exposure was 78 dBA during the training activities that lasted 70 min on average. There was no significant difference in noise exposure between each of the three job categories. Although firefighters routinely use equipment and emergency response vehicles that can produce hazardous levels of noise, this study showed that the average noise levels experienced by firefighters was below generally accepted guidelines.

Less is more: Sampling chemical space with active learning

NASA Astrophysics Data System (ADS)

Smith, Justin S.; Nebgen, Ben; Lubbers, Nicholas; Isayev, Olexandr; Roitberg, Adrian E.

2018-06-01

The development of accurate and transferable machine learning (ML) potentials for predicting molecular energetics is a challenging task. The process of data generation to train such ML potentials is a task neither well understood nor researched in detail. In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials. It is based on the concept of active learning (AL) via Query by Committee (QBC), which uses the disagreement between an ensemble of ML potentials to infer the reliability of the ensemble's prediction. QBC allows the presented AL algorithm to automatically sample regions of chemical space where the ML potential fails to accurately predict the potential energy. AL improves the overall fitness of ANAKIN-ME (ANI) deep learning potentials in rigorous test cases by mitigating human biases in deciding what new training data to use. AL also reduces the training set size to a fraction of the data required when using naive random sampling techniques. To provide validation of our AL approach, we develop the COmprehensive Machine-learning Potential (COMP6) benchmark (publicly available on GitHub) which contains a diverse set of organic molecules. Active learning-based ANI potentials outperform the original random sampled ANI-1 potential with only 10% of the data, while the final active learning-based model vastly outperforms ANI-1 on the COMP6 benchmark after training to only 25% of the data. Finally, we show that our proposed AL technique develops a universal ANI potential (ANI-1x) that provides accurate energy and force predictions on the entire COMP6 benchmark. This universal ML potential achieves a level of accuracy on par with the best ML potentials for single molecules or materials, while remaining applicable to the general class of organic molecules composed of the elements CHNO.

Dog and human inflammatory bowel disease rely on overlapping yet distinct dysbiosis networks.

PubMed

Vázquez-Baeza, Yoshiki; Hyde, Embriette R; Suchodolski, Jan S; Knight, Rob

2016-10-03

Inflammatory bowel disease (IBD) is an autoimmune condition that is difficult to diagnose, and animal models of this disease have questionable human relevance 1 . Here, we show that the dysbiosis network underlying IBD in dogs differs from that in humans, with some bacteria such as Fusobacterium switching roles between the two species (as Bacteroides fragilis switches roles between humans and mice) 2 . For example, a dysbiosis index trained on humans fails when applied to dogs, but a dog-specific dysbiosis index achieves high correlations with the overall dog microbial community diversity patterns. In addition, a random forest classifier trained on dog-specific samples achieves high discriminatory power, even when using stool samples rather than the mucosal biopsies required for high discriminatory power in humans 2 . These relationships were not detected in previously published dog IBD data sets due to their limited sample size and statistical power 3 . Taken together, these results reveal the need to train host-specific dysbiosis networks and point the way towards a generalized understanding of IBD across different mammalian models.

Effect of balance training in older adults using Wii fit plus.

PubMed

Afridi, Ayesha; Malik, Arshad Nawaz; Ali, Shaukat; Amjad, Imran

2018-03-01

The Nintendo Wii-fit plus is a type of Virtual Reality exer-gaming with graphical and auditory response system. A case series was conducted at Shifa Tamer-e-Millat University Islamabad from January-July 2016. Sixteen adults more than 60 years age (07 males and 09 females) were recruited through convenient sampling. The specified Wii fit plus training was provided to all patients and the games included the Soccer heading, Ski slalom, table tilt and yoga. Berg balance test, time up and go and functional reach test were used before and after 06 weeks of treatment (4 days / week). Data was analysed by SPSS V-20. The mean age of the sample was 67.56±7.29 years, with 56% female and 44% males were in sample. There was a statistically significant difference in pre and post Berg Balance Score, time up and go test and functional reach. In this case series Wii-fit plus training was effective in improving dynamic balance and mobility in older adults. This should be explored further in large trials.

Sensitivity of the central visual field in 70- to 81-year-old male athletes and in a population sample.

PubMed

Era, P; Pärssinen, O; Pykälä, P; Jokela, J; Suominen, H

1994-10-01

The sensitivity of the central visual field (0 degree-30 degrees) was studied using an automatic Octopus 500E perimeter in elderly male athletes and in a population sample of men of corresponding age. The athletes (N = 96) were endurance and power athletes, who were still active in competitive sports with training histories spanning tens of years. The athletes' results were compared with those of a sample of men of the same age (70-81 years, N = 41) randomly selected from the local population register. The sensitivity values of the athletes, and the endurance athletes in particular, were significantly better than those of the controls, with differences varying from 1 to 2.5 dB in the different areas of the central visual field. Multivariate analyses of the background factors of visual field sensitivity showed that the most important were age, amount of annual training, number of chronic diseases, HDL-cholesterol level, and vital capacity. The results suggest that a long training history, especially of the aerobic type, may be beneficial with respect to the sensitivity of the visual system.

The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

PubMed

Syfert, Mindy M; Smith, Matthew J; Coomes, David A

2013-01-01

Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

Hot flue-gas spiking and recovery study for tetrachlorodibenzodioxins (TCDD) using Modified Method 5 and SASS (Source Assessment Sampling System) sampling with a simulated incinerator. Final report, May 1981-February 1982

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

Cooke, M.; DeRoos, F.; Rising, B.

1984-10-01

The report gives results of an evaluation of the sampling and analysis of ultratrace levels of dibenzodioxins using EPA's recommended source sampling procedures (Modified Method 5 (MM5) train and the Source Assessment Sampling System--SASS). A gas-fired combustion system was used to simulate incineration flue gas, and a precision liquid injection system was designed for the program. The precision liquid injector was used to administer dilute solutions of 1,2,3,4-tetrachlorodibenzo-p-dioxin (1,2,3,4-TCDD) directly into a hot--260C (500F)--flue gas stream. Injections occurred continuously during the sampling episode so that very low gas-phase concentrations of 1,2,3,4-TCDD were continuously mixed with the flue gases. Recoveries weremore » measured for eight burn experiments. For all but one, the recoveries could be considered quantitative, demonstrating efficient collection by the EPA sampling systems. In one study, the components and connecting lines from a sampling device were analyzed separately to show where the 1,2,3,4-TCDD deposited in the train.« less

Cross-Domain Semi-Supervised Learning Using Feature Formulation.

PubMed

Xingquan Zhu

2011-12-01

Semi-Supervised Learning (SSL) traditionally makes use of unlabeled samples by including them into the training set through an automated labeling process. Such a primitive Semi-Supervised Learning (pSSL) approach suffers from a number of disadvantages including false labeling and incapable of utilizing out-of-domain samples. In this paper, we propose a formative Semi-Supervised Learning (fSSL) framework which explores hidden features between labeled and unlabeled samples to achieve semi-supervised learning. fSSL regards that both labeled and unlabeled samples are generated from some hidden concepts with labeling information partially observable for some samples. The key of the fSSL is to recover the hidden concepts, and take them as new features to link labeled and unlabeled samples for semi-supervised learning. Because unlabeled samples are only used to generate new features, but not to be explicitly included in the training set like pSSL does, fSSL overcomes the inherent disadvantages of the traditional pSSL methods, especially for samples not within the same domain as the labeled instances. Experimental results and comparisons demonstrate that fSSL significantly outperforms pSSL-based methods for both within-domain and cross-domain semi-supervised learning.

A survey of food safety training in small food manufacturers.

PubMed

Worsfold, Denise

2005-08-01

A survey of food safety training was conducted in small food manufacturing firms in South Wales. Structured interviews with managers were used to collect information on the extent and level of food hygiene and HACCP training and the manager's perceptions of and attitude towards training. All the businesses surveyed had undertaken some hygiene training. Hygiene induction programmes were often unstructured and generally unrecorded. Low-risk production workers were usually trained on the job whilst high-care production staff were trained in hygiene to Level 1. Part-time and temporary staff received less training than full-timers. Regular refresher training was undertaken by less than half of the sample. None of the businesses made use of National Vocational Qualification (NVQ) qualifications. Over half of the managers/senior staff had undertaken higher levels of hygiene training and half had attended a HACCP course. Managers trained the workforce to operate the HACCP system. Formal training-related activities were generally only found in the larger businesses. Few of the manufacturers had made use of training consultants. Managers held positive attitudes towards training but most regarded it as operating expense rather than an investment. Resource poverty, in terms of time and money was perceived to be a major inhibiting factor to continual, systematic training.

Complex segregation analysis of blood pressure and heart rate measured before and after a 20-week endurance exercise training program: the HERITAGE Family Study.

PubMed

An, P; Rice, T; Pérusse, L; Borecki, I B; Gagnon, J; Leon, A S; Skinner, J S; Wilmore, J H; Bouchard, C; Rao, D C

2000-05-01

Complex segregation analysis of baseline resting blood pressure (BP) and heart rate (HR) and their responses to training (post-training minus baseline) were performed in a sample of 482 individuals from 99 white families who participated in the HERITAGE Family Study. Resting BP and HR were measured at baseline and after a 20-week training program. Baseline resting BP and HR were age-adjusted and age-BMI-adjusted, and the responses to training were age-adjusted and age-baseline-adjusted, within four gender-by-generation groups. This study also analyzed the responses to training in two subsets of families: (1) the so-called "high" subsample, 45 families (216 individuals) with at least one member whose baseline resting BP is in the high end of the normal BP range (the upper 95th percentile: systolic BP [SBP] > or = 135 or diastolic BP [DBP] > or = 80 mm Hg); and (2) the so-called "nonhigh" subsample, the 54 remaining families (266 individuals). Baseline resting SBP was influenced by a multifactorial component (23%), which was independent of body mass index (BMI). Baseline resting DBP was influenced by a putative recessive locus, which accounted for 31% of the variance. In addition to the major gene effect, which may impact BMI as well, baseline resting DBP was also influenced by a multifactorial component (29%). Baseline resting HR was influenced by a putative dominant locus independent of BMI, which accounted for 31% of the variance. For the responses to training, no familiality was found in the whole sample or in the nonhigh subsample. However, in the high subsample, resting SBP response to training was influenced by a putative recessive locus, which accounted for 44% of the variance. No familiality was found for resting DBP response to training. Resting HR response to training was influenced by a major effect (accounting for 35% of the variance), with an ambiguous transmission from parents to offspring.

A genetic study of dehydroepiandrosterone sulfate measured before and after a 20-week endurance exercise training program: the HERITAGE Family Study.

PubMed

An, P; Rice, T; Gagnon, J; Hong, Y; Leon, A S; Skinner, J S; Wilmore, J H; Bouchard, C; Rao, D C

2000-03-01

Familial aggregation and possible major gene effects were evaluated for the baseline serum dehydroepiandrosterone sulfate (DHEAS) level and the change in DHEAS in response to a 20-week exercise training program in a sample of 481 individuals from 99 Caucasian families who were sedentary at baseline and who participated in the HERITAGE Family Study. Baseline DHEAS levels were not normally distributed, and were therefore logarithmically transformed and adjusted for the effects of age and sex prior to genetic analysis. The DHEAS response to training was computed as the simple difference, post-training minus baseline, and was adjusted for the baseline DHEAS level, age, and sex. Maximal (genetic and familial environmental) heritabilities (using a familial correlation model) reached 58% and 30% for the baseline and the response to training, respectively. Our estimate for the baseline is generally in agreement with previous reports, suggesting that the magnitude of the familial effect underlying this phenotype in these sedentary families is similar to that in the general population. However, segregation analysis showed no evidence for a multifactorial familial component in data for either the baseline or the response to training. Rather, a major additive gene controlling the baseline was found. For the response to training in the complete sample, transmission of the major effect from parents to offspring was ambiguous, but in a subset of 56 "responsive" families (with at least 1 family member whose response to training was greater than 1 standard deviation) this major effect was Mendelian in nature. The putative major genes accounted for 50% and 33% of the variance for the baseline and the response to training, respectively. The novel finding in this study is that the baseline DHEAS level and the change in DHEAS in response to training may be influenced by major gene effects.

Training attentional control in older adults.

PubMed

Mackay-Brandt, Anna

2011-07-01

Recent research has demonstrated benefits for older adults from training attentional control using a variable priority strategy, but the construct validity of the training task and the degree to which benefits of training transfer to other contexts are unclear. The goal of this study was to characterize baseline performance on the training task in a sample of 105 healthy older adults and to test for transfer of training in a subset (n = 21). Training gains after 5 days and extent of transfer was compared to another subset (n = 20) that served as a control group. Baseline performance on the training task was characterized by a two-factor model of working memory and processing speed. Processing speed correlated with the training task. Training gains in speed and accuracy were reliable and robust (ps <.001, η(2) = .57 to .90). Transfer to an analogous task was observed (ps <.05, η(2) = .10 to .17). The beneficial effect of training did not translate to improved performance on related measures of processing speed. This study highlights the robust effect of training and transfer to a similar context using a variable priority training task. Although processing speed is an important aspect of the training task, training benefit is either related to an untested aspect of the training task or transfer of training is limited to the training context.

A generic template for automated bioanalytical ligand-binding assays using modular robotic scripts in support of discovery biotherapeutic programs.

PubMed

Duo, Jia; Dong, Huijin; DeSilva, Binodh; Zhang, Yan J

2013-07-01

Sample dilution and reagent pipetting are time-consuming steps in ligand-binding assays (LBAs). Traditional automation-assisted LBAs use assay-specific scripts that require labor-intensive script writing and user training. Five major script modules were developed on Tecan Freedom EVO liquid handling software to facilitate the automated sample preparation and LBA procedure: sample dilution, sample minimum required dilution, standard/QC minimum required dilution, standard/QC/sample addition, and reagent addition. The modular design of automation scripts allowed the users to assemble an automated assay with minimal script modification. The application of the template was demonstrated in three LBAs to support discovery biotherapeutic programs. The results demonstrated that the modular scripts provided the flexibility in adapting to various LBA formats and the significant time saving in script writing and scientist training. Data generated by the automated process were comparable to those by manual process while the bioanalytical productivity was significantly improved using the modular robotic scripts.

A method for feature selection of APT samples based on entropy

NASA Astrophysics Data System (ADS)

Du, Zhenyu; Li, Yihong; Hu, Jinsong

2018-05-01

By studying the known APT attack events deeply, this paper propose a feature selection method of APT sample and a logic expression generation algorithm IOCG (Indicator of Compromise Generate). The algorithm can automatically generate machine readable IOCs (Indicator of Compromise), to solve the existing IOCs logical relationship is fixed, the number of logical items unchanged, large scale and cannot generate a sample of the limitations of the expression. At the same time, it can reduce the redundancy and useless APT sample processing time consumption, and improve the sharing rate of information analysis, and actively respond to complex and volatile APT attack situation. The samples were divided into experimental set and training set, and then the algorithm was used to generate the logical expression of the training set with the IOC_ Aware plug-in. The contrast expression itself was different from the detection result. The experimental results show that the algorithm is effective and can improve the detection effect.

Audiologists' communication behaviour during hearing device management appointments.

PubMed

Muñoz, Karen; Ong, Clarissa W; Borrie, Stephanie A; Nelson, Lauri H; Twohig, Michael P

2017-05-01

The aim of this exploratory study was to describe audiologist communication behaviours during appointments for hearing device monitoring and management before and after participation in counselling skills training. The study used a longitudinal design with three assessment points over 6 months. The sample included 10 audiologists and audiology graduate students interacting in a professional setting with their clients. Audiologists reported improvement in their counselling skills from pre-training to follow-up, which was consistent with objective findings that audiologist relative speaking time decreased from pre-training to post-training as well as from pre-training to follow-up. Observer-rated scores of participants' counselling skills; however, yielded no significant differences across time. Some improvement was noted in audiologists' counselling behaviour following a 1-day communication skills workshop and continued learning support. It is evident; however, that further training, such as increased training and performance feedback, is needed to maintain and enhance audiologist progress in the various aspects of counselling.

Use of Unlabeled Samples for Mitigating the Hughes Phenomenon

NASA Technical Reports Server (NTRS)

Landgrebe, David A.; Shahshahani, Behzad M.

1993-01-01

The use of unlabeled samples in improving the performance of classifiers is studied. When the number of training samples is fixed and small, additional feature measurements may reduce the performance of a statistical classifier. It is shown that by using unlabeled samples, estimates of the parameters can be improved and therefore this phenomenon may be mitigated. Various methods for using unlabeled samples are reviewed and experimental results are provided.

Measurement of glucose concentration by image processing of thin film slides

NASA Astrophysics Data System (ADS)

Piramanayagam, Sankaranaryanan; Saber, Eli; Heavner, David

2012-02-01

Measurement of glucose concentration is important for diagnosis and treatment of diabetes mellitus and other medical conditions. This paper describes a novel image-processing based approach for measuring glucose concentration. A fluid drop (patient sample) is placed on a thin film slide. Glucose, present in the sample, reacts with reagents on the slide to produce a color dye. The color intensity of the dye formed varies with glucose at different concentration levels. Current methods use spectrophotometry to determine the glucose level of the sample. Our proposed algorithm uses an image of the slide, captured at a specific wavelength, to automatically determine glucose concentration. The algorithm consists of two phases: training and testing. Training datasets consist of images at different concentration levels. The dye-occupied image region is first segmented using a Hough based technique and then an intensity based feature is calculated from the segmented region. Subsequently, a mathematical model that describes a relationship between the generated feature values and the given concentrations is obtained. During testing, the dye region of a test slide image is segmented followed by feature extraction. These two initial steps are similar to those done in training. However, in the final step, the algorithm uses the model (feature vs. concentration) obtained from the training and feature generated from test image to predict the unknown concentration. The performance of the image-based analysis was compared with that of a standard glucose analyzer.

Neural Spike Train Synchronisation Indices: Definitions, Interpretations and Applications.

PubMed

Halliday, D M; Rosenberg, J R

2017-04-24

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% { 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1 - 250 spikes/sec). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multi electrode array data is briefly discussed.

Selecting Strategies to Reduce High-Risk Unsafe Work Behaviors Using the Safety Behavior Sampling Technique and Bayesian Network Analysis.

PubMed

Ghasemi, Fakhradin; Kalatpour, Omid; Moghimbeigi, Abbas; Mohammadfam, Iraj

2017-03-04

High-risk unsafe behaviors (HRUBs) have been known as the main cause of occupational accidents. Considering the financial and societal costs of accidents and the limitations of available resources, there is an urgent need for managing unsafe behaviors at workplaces. The aim of the present study was to find strategies for decreasing the rate of HRUBs using an integrated approach of safety behavior sampling technique and Bayesian networks analysis. A cross-sectional study. The Bayesian network was constructed using a focus group approach. The required data was collected using the safety behavior sampling, and the parameters of the network were estimated using Expectation-Maximization algorithm. Using sensitivity analysis and belief updating, it was determined that which factors had the highest influences on unsafe behavior. Based on BN analyses, safety training was the most important factor influencing employees' behavior at the workplace. High quality safety training courses can reduce the rate of HRUBs about 10%. Moreover, the rate of HRUBs increased by decreasing the age of employees. The rate of HRUBs was higher in the afternoon and last days of a week. Among the investigated variables, training was the most important factor affecting safety behavior of employees. By holding high quality safety training courses, companies would be able to reduce the rate of HRUBs significantly.

Sense of Coherence (SOC) Among Psychotherapists in Austria, Differentiated According to Number of Individually Completed Training Therapy Sessions

PubMed Central

Binder, Heinz P.; Mesenholl-Strehler, Elke; Paß, Paul; Endler, P. Christian

2006-01-01

The sense of coherence (according Aaron Antonovsky, 1923—1994, when a persons sense that his/her own life and the world are sufficiently comprehensible, manageable, and meaningful) of Austrian psychotherapists was assessed and compared with a standard sample, as well as with the sense of coherence (SOC) of members of other professions. In addition, the question as to whether psychotherapists who had completed more extensive individual training therapy/self-awareness sessions had a higher SOC than do those with fewer, was addressed. Forty psychotherapists who worked in private practices and various psychosocial health care institutions in Styria, Austria took part in the study. The investigation was conducted in the form of a questionnaire assessment. The evaluation showed that the overall SOC value of the professional group in question was significantly higher than that of the standard sample (162.3 vs. 145.7), as well as other samples (physicians: SOC = 153.8; teachers: SOC = 156.1; physiotherapists SOC = 158.1). Concerning whether psychotherapists who had completed more individual training therapy/self-awareness sessions had higher SOC values than did those with fewer, we found no difference in regard to the overall SOC score or SOC scores for individual components. The SOC of psychotherapists did not seem to depend on the number of additional training therapy/self-awareness sessions. PMID:17370015

The Role of Legitimation in the Professional Socialization of Second-Year Undergraduate Athletic Training Students

PubMed Central

Klossner, Joanne

2008-01-01

Context: Professional socialization during formal educational preparation can help students learn professional roles and can lead to improved organizational socialization as students emerge as members of the occupation's culture. Professional socialization research in athletic training is limited. Objective: To present the role of legitimation and how it influences the professional socialization of second-year athletic training students. Design: Modified constructivist grounded theory and case study methods were used for this qualitative study. Setting: An accredited undergraduate athletic training education program. Patients or Other Participants: Twelve second-year students were selected purposively. The primary sample group (n  =  4) was selected according to theoretical sampling guidelines. The remaining students made up the cohort sample (n  =  8). Theoretically relevant data were gathered from 14 clinical instructors to clarify emergent student data. Data Collection and Analysis: Data collection included document examination, observations, and interviews during 1 academic semester. Data were collected and analyzed through constant comparative analysis. Data triangulation, member checking, and peer-review strategies were used to ensure trustworthiness. Results: Legitimation from various socializing agents initiated professional socialization. Students viewed trust and team membership as rewards for role fulfillment. Conclusions: My findings are consistent with the socialization literature that shows how learning a social or professional role, using rewards to facilitate role performance, and building trusting relationships with socializing agents are important aspects of legitimation and, ultimately, professional socialization. PMID:18668171

Development of a wheelchair maintenance training programme and questionnaire for clinicians and wheelchair users.

PubMed

Toro, Maria Luisa; Bird, Emily; Oyster, Michelle; Worobey, Lynn; Lain, Michael; Bucior, Samuel; Cooper, Rory A; Pearlman, Jonathan

2017-11-01

Purpose of state: The aims of this study were to develop a Wheelchair Maintenance Training Programme (WMTP) as a tool for clinicians to teach wheelchair users (and caregivers when applicable) in a group setting to perform basic maintenance at home in the USA and to develop a Wheelchair Maintenance Training Questionnaire (WMT-Q) to evaluate wheelchair maintenance knowledge in clinicians, manual and power wheelchair users. The WMTP and WMT-Q were developed through an iterative process. A convenience sample of clinicians (n = 17), manual wheelchair (n ∞ 5), power wheelchair users (n = 4) and caregivers (n = 4) provided feedback on the training programme. A convenience sample of clinicians (n = 38), manual wheelchair (n = 25), and power wheelchair users (n = 30) answered the WMT-Q throughout different phases of development. The subscores of the WMT-Q achieved a reliability that ranged between ICC(3,1) = 0.48 to ICC(3,1) = 0.89. The WMTP and WMT-Q were implemented with 15 clinicians who received in-person training in the USA using the materials developed and showed a significant increase in all except one of the WMT-Q subscores after the WMTP (p < 0.007). The WMTP will continue to be revised as it is further implemented. The WMT-Q is an acceptable instrument to measure pre- and post-training maintenance knowledge. Implications for Rehabilitation The Wheelchair Maintenance Training Program can be used to educate rehabilitation clinicians and technicians to improve wheelchair service and delivery to end users. This training complements the World Health Organization basic wheelchair service curriculum, which only includes training of the clinicians, but does not include detailed information to train wheelchair users and caregivers. This training program offers a time efficient method for providing education to end users in a group setting that may mitigate adverse consequences resulting from wheelchair breakdown. This training program has significant potential for impact among wheelchair users in areas where access to repair services is limited.

Working memory and executive functions: effects of training on academic achievement.

PubMed

Titz, Cora; Karbach, Julia

2014-11-01

The aim of this review is to illustrate the role of working memory and executive functions for scholastic achievement as an introduction to the question of whether and how working memory and executive control training may improve academic abilities. The review of current research showed limited but converging evidence for positive effects of process-based complex working-memory training on academic abilities, particularly in the domain of reading. These benefits occurred in children suffering from cognitive and academic deficits as well as in healthy students. Transfer of training to mathematical abilities seemed to be very limited and to depend on the training regime and the characteristics of the study sample. A core issue in training research is whether high- or low-achieving children benefit more from cognitive training. Individual differences in terms of training-related benefits suggested that process-based working memory and executive control training often induced compensation effects with larger benefits in low performing individuals. Finally, we discuss the effects of process-based training in relation to other types of interventions aimed at improving academic achievement.

Self-reported comfort treating severe mental illnesses among pre-doctoral graduate students in clinical psychology.

PubMed

Buck, Benjamin; Romeo, Katy Harper; Olbert, Charles M; Penn, David L

2014-12-01

One possible explanation for the dearth of psychologists working in severe mental illness (SMI) areas is a lack of training opportunities. Recent studies have shown that while training opportunities have increased, there remain fewer resources available for SMI training compared to other disorders. Examines whether students express discomfort working with this population and whether they are satisfied with their level of training in SMI. One-hundred sixty-nine students currently enrolled in doctoral programs in clinical psychology in the United States and Canada were surveyed for their comfort treating and satisfaction with training related to a number of disorders. RESULTS indicate that students are significantly less comfortable treating and finding a referral for a patient with schizophrenia as well as dissatisfied with their current training in SMI and desirous of more training. Regression analyses showed that dissatisfaction with training predicted a desire for more training; however, discomfort in treating people with SMI did not predict a desire for more training in this sample. This pattern generally held across disorders. Our results suggest general discomfort among students surveyed in treating SMI compared to other disorders.

Resilience training with soldiers during basic combat training: randomisation by platoon.

PubMed

Adler, Amy B; Williams, Jason; McGurk, Dennis; Moss, Andrew; Bliese, Paul D

2015-03-01

Resilience Training has the potential to mitigate mental health symptoms when provided during initial military training. The present study examined the impact of Resilience Training on US soldier well-being and attitudes during Basic Combat Training. Platoons were randomly assigned to Resilience Training or Military History provided during the first few days of Basic Combat Training. Surveys were conducted at baseline, post-intervention, and 3, 6, and 9 weeks. The sample resulted in a total of 1,939 soldiers who completed at least the baseline and one follow-up survey. There were no significant differences between conditions in terms of depression symptoms, anxiety symptoms, or sleep problems. However, while anxiety decreased in both conditions, the rate of decrease was faster in the Resilience Training condition. In contrast, Resilience Training had a slower rate of increase in group cohesion over time than the Military History condition. In addition, Resilience Training was associated with greater confidence in helping others and received more positive ratings than Military History. Findings demonstrate that the brief Resilience Training studied here may have some utility in supporting mental health and peer support but may not benefit unit climate. © 2014 The International Association of Applied Psychology.

Effectiveness of gait training using an electromechanical gait trainer, with and without functional electric stimulation, in subacute stroke: a randomized controlled trial.

PubMed

Tong, Raymond K; Ng, Maple F; Li, Leonard S

2006-10-01

To compare the therapeutic effects of conventional gait training (CGT), gait training using an electromechanical gait trainer (EGT), and gait training using an electromechanical gait trainer with functional electric stimulation (EGT-FES) in people with subacute stroke. Nonblinded randomized controlled trial. Rehabilitation hospital for adults. Fifty patients were recruited within 6 weeks after stroke onset; 46 of these completed the 4-week training period. Participants were randomly assigned to 1 of 3 gait intervention groups: CGT, EGT, or EGT-FES. The experimental intervention was a 20-minute session per day, 5 days a week (weekdays) for 4 weeks. In addition, all participants received their 40-minute sessions of regular physical therapy every weekday as part of their treatment by the hospital. Five-meter walking speed test, Elderly Mobility Scale (EMS), Berg Balance Scale, Functional Ambulatory Category (FAC), Motricity Index leg subscale, FIM instrument score, and Barthel Index. The EGT and EGT-FES groups had statistically significantly more improvement than the CGT group in the 5-m walking speed test (CGT vs EGT, P=.011; CGT vs EGT-FES, P=.001), Motricity Index (CGT vs EGT-FES, P=.011), EMS (CGT vs EGT, P=.006; CGT vs EGT-FES, P=.009), and FAC (CGT vs EGT, P=.005; CGT vs EGT-FES, P=.002) after the 4 weeks of training. No statistically significant differences were found between the EGT and EGT-FES groups in all outcome measures. In this sample with subacute stroke, participants who trained on the electromechanical gait trainer with body-weight support, with or without FES, had a faster gait, better mobility, and improvement in functional ambulation than participants who underwent conventional gait training. Future studies with assessor blinding and larger sample sizes are warranted.

Effects of developmental training of basketball cadets realised in the competitive period.

PubMed

Trninić, S; Marković, G; Heimer, S

2001-12-01

The analysis of effects of a two-month developmental training cycle realised within a basketball season revealed statistically significant positive changes at the multivariate level in components of motor-functional conditioning (fitness) status of the sample of talented basketball cadets (15-16 years). The greatest correlations with discriminant function were found in variables with statistically significant changes at the univariate level, more explicitly in variables of explosive and repetitive power of the upper body and trunk, anaerobic lactic endurance, as well as in jumping type explosive leg power. The presented developmental conditioning training programme, although implemented within the competitive period, induced multiple positive fitness effects between the two control time points in this sample of basketball players. The authors suggest that, to assess power of shoulders and upper back, the test overgrip pull-up should not be applied to basketball players of this age due to its poor sensitivity. Instead, they propose the undergrip pull-up test, which is a facilitated version of the same test. The results presented in this article reinforce experienced opinion of experts that, in the training process with youth teams, the developmental conditioning training programme is effectively applicable throughout the entire competitive season. The proposed training model is a system of various training procedures, operating synergistically, aimed at enhancing integral fitness (preparedness) of basketball players. Further investigations should be focused on assessing effects of both the proposed and other developmental training cycle programmes, by means of assessing and monitoring actual quality (overall performance) of players, on the one hand, and, on the other, by following-up hormonal and biochemical changes over multiple time points.

Crop identification and area estimation over large geographic areas using LANDSAT MSS data

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator)

1977-01-01

The author has identified the following significant results. LANDSAT MSS data was adequate to accurately identify wheat in Kansas; corn and soybean estimates in Indiana were less accurate. Computer-aided analysis techniques were effectively used to extract crop identification information from LANDSAT data. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels. Training statistics were successfully extended from one county to other counties having similar crops and soils if the training areas sampled the total variation of the area to be classified.

Understanding biological mechanisms underlying adverse birth outcomes in developing countries: protocol for a prospective cohort (AMANHI bio-banking) study.

PubMed

Baqui, Abdullah H; Khanam, Rasheda; Rahman, Mohammad Sayedur; Ahmed, Aziz; Rahman, Hasna Hena; Moin, Mamun Ibne; Ahmed, Salahuddin; Jehan, Fyezah; Nisar, Imran; Hussain, Atiya; Ilyas, Muhammad; Hotwani, Aneeta; Sajid, Muhammad; Qureshi, Shahida; Zaidi, Anita; Sazawal, Sunil; Ali, Said M; Deb, Saikat; Juma, Mohammed Hamad; Dhingra, Usha; Dutta, Arup; Ame, Shaali Makame; Hayward, Caroline; Rudan, Igor; Zangenberg, Mike; Russell, Donna; Yoshida, Sachiyo; Polašek, Ozren; Manu, Alexander; Bahl, Rajiv

2017-12-01

The AMANHI study aims to seek for biomarkers as predictors of important pregnancy-related outcomes, and establish a biobank in developing countries for future research as new methods and technologies become available. AMANHI is using harmonised protocols to enrol 3000 women in early pregnancies (8-19 weeks of gestation) for population-based follow-up in pregnancy up to 42 days postpartum in Bangladesh, Pakistan and Tanzania, with collection taking place between August 2014 and June 2016. Urine pregnancy tests will be used to confirm reported or suspected pregnancies for screening ultrasound by trained sonographers to accurately date the pregnancy. Trained study field workers will collect very detailed phenotypic and epidemiological data from the pregnant woman and her family at scheduled home visits during pregnancy (enrolment, 24-28 weeks, 32-36 weeks & 38+ weeks) and postpartum (days 0-6 or 42-60). Trained phlebotomists will collect maternal and umbilical blood samples, centrifuge and obtain aliquots of serum, plasma and the buffy coat for storage. They will also measure HbA1C and collect a dried spot sample of whole blood. Maternal urine samples will also be collected and stored, alongside placenta, umbilical cord tissue and membrane samples, which will both be frozen and prepared for histology examination. Maternal and newborn stool (for microbiota) as well as paternal and newborn saliva samples (for DNA extraction) will also be collected. All samples will be stored at -80°C in the biobank in each of the three sites. These samples will be linked to numerous epidemiological and phenotypic data with unique study identification numbers. AMANHI biobank proves that biobanking is feasible to implement in LMICs, but recognises that biobank creation is only the first step in addressing current global challenges.

Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

PubMed

Zhao, Xiaowei; Ning, Qiao; Chai, Haiting; Ma, Zhiqiang

2015-06-07

As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimental approaches, computational predictions of succinylation sites are much desirable due to their convenient and fast speed. Currently, numerous computational models have been developed to identify PTMs sites through various types of two-class machine learning algorithms. These methods require both positive and negative samples for training. However, designation of the negative samples of PTMs was difficult and if it is not properly done can affect the performance of computational models dramatically. So that in this work, we implemented the first application of positive samples only learning (PSoL) algorithm to succinylation sites prediction problem, which was a special class of semi-supervised machine learning that used positive samples and unlabeled samples to train the model. Meanwhile, we proposed a novel succinylation sites computational predictor called SucPred (succinylation site predictor) by using multiple feature encoding schemes. Promising results were obtained by the SucPred predictor with an accuracy of 88.65% using 5-fold cross validation on the training dataset and an accuracy of 84.40% on the independent testing dataset, which demonstrated that the positive samples only learning algorithm presented here was particularly useful for identification of protein succinylation sites. Besides, the positive samples only learning algorithm can be applied to build predictors for other types of PTMs sites with ease. A web server for predicting succinylation sites was developed and was freely accessible at http://59.73.198.144:8088/SucPred/. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factors influencing training transfer in nursing profession: a qualitative study.

PubMed

Ma, Fang; Bai, Yangjing; Bai, Yangjuan; Ma, Weiguang; Yang, Xiangyu; Li, Jiping

2018-03-20

There is a growing recognition that training is not translated into performance and the 'transfer problem' exists in organization training today. Although factors contributing to training transfer have been identified in business and industry, the factors influencing training transfer in nursing profession remain less clear. A qualitative descriptive study was undertaken in two tertiary referral hospitals in China from February 2013 to September 2013. Purposeful sampling of 24 nursing staffs were interviewed about the factors influencing training transfer. Seven themes evolved from the analysis, categorized in 4 main domains, which described the factors influencing training transfer in nursing profession in trainee characteristics, training design, work environment and profession domain. The trainee characteristics domain included attitude and ability. The training design domain included training content and instruction method. The work environment domain included supports as facilitators and opposition as hindrance. The theme pertaining to the profession domain was professional development. Health care managers need to understand the factors influencing training transfer for maximizing the benefits of training. The right beliefs and values about training, the rigorous employee selection for training, the relevance of training content, training instructions facilitating learning and transfer, supports from peer, supervisors and the organization, organizational culture such as change, sharing, learning and support, and professional development are key to successful training transfer. Furthermore, managers should be aware of the opposition from co-workers and find ways to prevent it.

Empirical Validation of a Procedure to Correct Position and Stimulus Biases in Matching-to-Sample

ERIC Educational Resources Information Center

Kangas, Brian D.; Branch, Marc N.

2008-01-01

The development of position and stimulus biases often occurs during initial training on matching-to-sample tasks. Furthermore, without intervention, these biases can be maintained via intermittent reinforcement provided by matching-to-sample contingencies. The present study evaluated the effectiveness of a correction procedure designed to…

Research on Abnormal Detection Based on Improved Combination of K - means and SVDD

NASA Astrophysics Data System (ADS)

Hao, Xiaohong; Zhang, Xiaofeng

2018-01-01

In order to improve the efficiency of network intrusion detection and reduce the false alarm rate, this paper proposes an anomaly detection algorithm based on improved K-means and SVDD. The algorithm first uses the improved K-means algorithm to cluster the training samples of each class, so that each class is independent and compact in class; Then, according to the training samples, the SVDD algorithm is used to construct the minimum superspheres. The subordinate relationship of the samples is determined by calculating the distance of the minimum superspheres constructed by SVDD. If the test sample is less than the center of the hypersphere, the test sample belongs to this class, otherwise it does not belong to this class, after several comparisons, the final test of the effective detection of the test sample.In this paper, we use KDD CUP99 data set to simulate the proposed anomaly detection algorithm. The results show that the algorithm has high detection rate and low false alarm rate, which is an effective network security protection method.

Semantic False Memories in the Form of Derived Relational Intrusions Following Training

ERIC Educational Resources Information Center

Guinther, Paul M.; Dougher, Michael J.

2010-01-01

Contemporary behavior analytic research is making headway in characterizing memory phenomena that typically have been characterized by cognitive models, and the current study extends this development by producing "false memories" in the form of functional equivalence responding. A match-to-sample training procedure was administered in order to…

Burnout and Competency Development in Pre-Service Teacher Training

ERIC Educational Resources Information Center

Rodríguez-Hidalgo, Antonio J.; Calmaestra, Juan; Dios, Irene

2014-01-01

Introduction: The burnout syndrome negatively affects the students' academic performance. The relation between academic burnout and the self-perception of skills in initial teacher training is subjected to analysis. Method: A sample of 274 students (average age = 20,61 years old) from the Bachelor Degree in Early Childhood Education and the…

A Study in Difference: Structures and Cultures in Registered Training Organisations. Support Document 3

ERIC Educational Resources Information Center

Clayton, Berwyn; Fisher, Thea; Harris, Roger; Bateman, Andrea; Brown, Mike

2008-01-01

This document supports the report "A Study in Difference: Structures and Cultures in Registered Training Organisations." The first section outlines the methodology used to undertake the research and covers the design of the research, sample details, the data collection process and the strategy for data analysis and reporting. The…

Exploring the Relations between In-Service Training, Prior Contacts and Teachers' Attitudes towards Persons with Intellectual Disability

ERIC Educational Resources Information Center

Sermier Dessemontet, Rachel; Morin, Diane; Crocker, Anne G.

2014-01-01

This study investigates the relations between teachers' attitudes towards persons with intellectual disability (ID), in-service training on ID, and prior contacts with persons with ID. A sample of Canadian elementary school teachers (N?=?118) completed the Attitudes Toward Intellectual Disability Questionnaire, which measures cognitive, affective…

A Quantitative Investigation of Stakeholder Variation in Training Program Evaluation.

ERIC Educational Resources Information Center

Michalski, Greg V.

A survey was conducted to investigate variation in stakeholder perceptions of training results and evaluation within the context of a high-technology product development firm (the case organization). A scannable questionnaire survey booklet was developed and scanned data were exported and analyzed. Based on an achieved sample of 280 (70% response…

Influence of Conflict Resolution Training on Conflict Handling Styles of College Students

ERIC Educational Resources Information Center

Waithaka, Abel Gitimu; Moore-Austin, Shante'; Gitimu, Priscilla N.

2015-01-01

The purpose of this study was to investigate the influence of conflict resolution skills training on conflict handling styles, and conflict orientation of college students. Conflict handling styles was measured by the Thomas-Kilmann MODE instrument, while Conflict orientation was measured by conflict orientation survey instrument. A sample of 135…

Experiences with Counselor Training in Central Europe: Voices from Student Trainees

ERIC Educational Resources Information Center

Jacob, Charles; Roth, Gregory; Flanders, Jessica; Jackson, Cheria; Park-Davidson, Caitlin; Grubrova, Tereza; Guynn, Jacqueline; Shoemaker, Rebecca; Goldberg, Rachael; Chehayl, Casy

2017-01-01

Globalization has led to an increase in United States-influenced counseling programs the world over; however, the extent to which these training models apply to other cultures is unclear. Using a sample of master's-level counseling students studying in the Czech Republic (n = 5), the authors conducted a phenomenological inquiry examining the…

Linking Vocational Education to Business/Industry Training Needs. Final Report.

ERIC Educational Resources Information Center

Gilbertson, Alan; And Others

A study investigated the processes Wisconsin's businesses and industries use to identify training and retraining needs and the mechanisms they use to communicate these needs to the state's vocational, technical, and adult education (VTAE) system. Data were collected by a survey questionnaire sent to a representative sample of 361 Wisconsin firms.…

Effectiveness of a Self-Instruction Program for Microcounseling Skills Training

ERIC Educational Resources Information Center

Schonrock-Adema, Johanna; Van der Molen, Henk T.; van der Zee, Karen I.

2009-01-01

This article describes the effects of self-instruction training (SIT) in microcounseling skills compared to those of a traditional trainer-guided program (TT) in a pretest-posttest comparison group design. A sample of 193 undergraduate psychology students participated in this study: 97 students followed SIT and 96 students followed TT. We used…

Training Objectives, Transfer, Validation and Evaluation: A Sri Lankan Study

ERIC Educational Resources Information Center

Wickramasinghe, Vathsala M.

2006-01-01

Using a stratified random sample, this paper examines the training practices of setting objectives, transfer, validation and evaluation in Sri Lanka. The paper further sets out to compare those practices across local, foreign and joint-venture companies based on the assumption that there may be significant differences across companies of different…

Evaluation of an In-Service Training Program for Child Welfare Practitioners

ERIC Educational Resources Information Center

Turcotte, Daniel; Lamonde, Genevieve; Beaudoin, Andre

2009-01-01

Objective: To test the effectiveness of an in-training program for practitioners in public child welfare organizations. Method: The sample consists of practitioners (N = 945) working in youth centers or in local community service centers. Data are collected through self-administered questionnaires prior to and after the program. Results: The data…

Effective Leadership in Vocational Education and Training. CRLRA Discussion Paper.

ERIC Educational Resources Information Center

Falk, Ian; Smith, Tony

The question of the extent to which effective leadership in vocational education and training (VET) depends on the specific context in which it occurs was examined. Data were collected from the following sources: an intensive literature analysis; studies of purposive sample of 12 diverse VET sites across Australia; and individual interviews with…

Barriers to Employer Sponsored Training in Ontario. Results of a Field Study.

ERIC Educational Resources Information Center

Harvey, Edward B.

Results of a field survey of Canadian companies, trade unions, employer associations, educational establishments, and government agencies regarding the extent and possibilities of employer-sponsored training for workers are compiled in this report. Concentrating on the forty-nine companies in the survey sample, with collateral data from the…

Evaluation of LEAA Funded Courts Training Programs. Volume I.

ERIC Educational Resources Information Center

McManis Associates, Inc., Washington, DC.

An impact evaluation of eight courts training project (CTP) institutes funded by the Law Enforcement Assistance Administration was conducted. After a literature search and visits to potential evaluation sites in all fifty states, twelve sites were selected from a random stratified sample of court systems. Data were obtained from 1047 respondents…

Therapist Personal Agency: A Model for Examining the Training Context

ERIC Educational Resources Information Center

Mutchler, Matthew; Anderson, Stephen

2010-01-01

This study reviews the creation and testing of a model of Therapist Personal Agency during MFT training. A model including self-efficacy, trainee developmental level, supervisor working alliance, family of origin relationships, and psychological states was supported by data collected from a national sample of MFT students. The model supported by…

Factors Influencing Practical Training Quality in Iranian Agricultural Higher Education

ERIC Educational Resources Information Center

Mojarradi, Gholamreza; Karamidehkordi, Esmail

2016-01-01

This paper presents an analysis of the factors influencing the practical training quality of agricultural higher education programmes from the senior students' perspective. The study was conducted in two public universities located in the north-west of Iran using a cross-sectional survey and structured interviews with a randomised sample of 254…

Tuberculosis Detection by Giant African Pouched Rats

ERIC Educational Resources Information Center

Poling, Alan; Weetjens, Bart; Cox, Christophe; Beyene, Negussie; Durgin, Amy; Mahoney, Amanda

2011-01-01

In recent years, operant discrimination training procedures have been used to teach giant African pouched rats to detect tuberculosis (TB) in human sputum samples. This article summarizes how the rats are trained and used operationally, as well as their performance in studies published to date. Available data suggest that pouched rats, which can…

Teachers' Attitudes towards Training in ICT: A Critical Approach

ERIC Educational Resources Information Center

Giavrimis, Panagiotis; Giossi, Stella; Papastamatis, Adamantios

2011-01-01

Purpose: The aim of the present study is to investigate why teachers participate in Information and Communication Technology (ICT) programmes, what their sociological approaches are, and where they focus their attention in order to achieve the objectives of their training in these new technologies. Design/methodology/approach: The sample group of…

Counseling Psychology Trainees' Perceptions of Training and Commitments to Social Justice

ERIC Educational Resources Information Center

Beer, Amanda M.; Spanierman, Lisa B.; Greene, Jennifer C.; Todd, Nathan R.

2012-01-01

This mixed methods study examined social justice commitments of counseling psychology graduate trainees. In the quantitative portion of the study, a national sample of trainees (n = 260) completed a web-based survey assessing their commitments to social justice and related personal and training variables. Results suggested that students desired…

A Study of Operator and Mechnaic Training Needs in the Transit Industry. Volume II, Appendices. Final Report.

ERIC Educational Resources Information Center

Henderson, Harold L.; And Others

Surveys of 188 transit properties and on-site visits were conducted to determine the training needs of operators and mechanics in the urban mass transportation industry. The appendices include listings of respondents and sample copies of the survey questionnaires and visit reports. (NTIS)

NHEXAS PHASE I MARYLAND STUDY--STANDARD OPERATING PROCEDURE FOR TRAINING OF FIELD COORDINATION CENTER STAFF (G11)

EPA Science Inventory

The purpose of this SOP is to outline (1) the responsibilities of the Field Coordination Center (FCC) staff before, during, and after sampling at residences, and (2) to outline the training program that teaches FCC staff what they need to know to handle these responsibilities. F...

Cigarette Smoking and Anti-Smoking Counseling Practices among Physicians in Wuhan, China

ERIC Educational Resources Information Center

Gong, Jie; Zhang, Zhifeng; Zhu, Zhaoyang; Wan, Jun; Yang, Niannian; Li, Fang; Sun, Huiling; Li, Weiping; Xia, Jiang; Zhou, Dunjin; Chen, Xinguang

2012-01-01

Purpose: The paper seeks to report data on cigarette smoking, anti-smoking practices, physicians' receipt of anti-smoking training, and the association between receipt of the training and anti-smoking practice among physicians in Wuhan, China. Design/methodology/approach: Participants were selected through the stratified random sampling method.…

Relating Training to Job Satisfaction: A Survey of Online Faculty Members

ERIC Educational Resources Information Center

Hoekstra, Brian

2014-01-01

The purpose of this study was to determine whether training affected the job satisfaction reported by online faculty members. A convenience sample of 492 Iowa Community College Online Consortium (ICCOC) faculty members were invited to participate in a quantitative survey, and 148 responded. Overall Job Satisfaction was operationalized through the…

Closing the Gap: Private and Public Job Training. EQW Issues Number 7.

ERIC Educational Resources Information Center

Zemsky, Robert; Oedel, Penney

In the United States, job training programs tend to be categorized as either privately sponsored career advancement for valued employees or publicly funded employment remediation for disadvantaged workers. Findings of two federally mandated surveys that regularly asked nearly identical samples whether they had received job or job-related training…

Racial/Ethnic Identity, Gender-Role Attitudes, and Multicultural Counseling Competence: The Role of Multicultural Counseling Training

ERIC Educational Resources Information Center

Chao, Ruth Chu-Lien

2012-01-01

Researchers and practitioners have been pursuing how to enhance counselors' multicultural counseling competencies (MCC). With a sample of 460 counselors, the author examined whether multicultural training changed the relationship between (a) racial/ethnic identity and MCC and (b) gender-role attitudes and MCC. The author found significant…

Factors Associated with Transfer of Training in Workplace E-Learning

ERIC Educational Resources Information Center

Park, Ji-Hye; Wentling, Tim

2007-01-01

Purpose--The purpose of this study is to investigate the effect of factors associated with e-learning, particularly computer attitudes and usability, on transfer of training in workplace e-learning courses. Design/methodology/approach--This study relied on quantitative data obtained from four online survey questionnaires. The sample of this study…

Assessment Practices and Training Needs of Early Childhood Professionals

ERIC Educational Resources Information Center

Banerjee, Rashida; Luckner, John L.

2013-01-01

Assessment plays a critical role in the planning and delivery of quality services for young children and their families. The purpose of this study was to identify the current assessment practices and training needs of early childhood professionals. A large sample of early childhood professionals responded to a comprehensive survey. The most…

Evaluation of Cross-Cultural Training Programs for International Students from East Europe

ERIC Educational Resources Information Center

Kovacova, Michaela; Eckert, Stefan

2010-01-01

This paper presents a comparative evaluation of didactic and experiential training in Germany carried out on a sample of international university students from Eastern Europe. The long-term evaluation was conducted by using a quasi-experimental design with a control group according to Kirkpatrick's model including three steps: reaction, learning…

Effects of Culturally Adapted Parent Management Training on Latino Youth Behavioral Health Outcomes

ERIC Educational Resources Information Center

Martinez, Charles R.; Eddy, J. Mark

2005-01-01

A randomized experimental test of the implementation feasibility and the efficacy of a culturally adapted Parent Management Training intervention was conducted with a sample of 73 Spanish-speaking Latino parents with middle-school-aged youth at risk for problem behaviors. Intervention feasibility was evaluated through weekly parent satisfaction…

Intensive Training in Youth Sport: An Example of Unequal Opportunity.

ERIC Educational Resources Information Center

Rowley, Stephen R. W.; Graham, Philip J.

1999-01-01

Examined the social composition of an unselected sample of 282 English 8- to 16-year olds involved in intensive training in football, swimming, tennis, and gymnastics. Found that working-class children and those from single-parent families were underrepresented in all sports. Concluded that financial considerations and difficulties in accessing…