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Sample records for supervised sequence labelling

  1. Supervised Sequence Labelling with Recurrent Neural Networks

    CERN Document Server

    Graves, Alex

    2012-01-01

    Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary.    The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional...

  2. Semi-Supervised Learning for Classification of Protein Sequence Data

    Directory of Open Access Journals (Sweden)

    Brian R. King

    2008-01-01

    Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.

  3. Label Information Guided Graph Construction for Semi-Supervised Learning.

    Science.gov (United States)

    Zhuang, Liansheng; Zhou, Zihan; Gao, Shenghua; Yin, Jingwen; Lin, Zhouchen; Ma, Yi

    2017-09-01

    In the literature, most existing graph-based semi-supervised learning methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph. In this paper, we argue that it is beneficial to consider the label information in the graph learning stage. Specifically, by enforcing the weight of edges between labeled samples of different classes to be zero, we explicitly incorporate the label information into the state-of-the-art graph learning methods, such as the low-rank representation (LRR), and propose a novel semi-supervised graph learning method called semi-supervised low-rank representation. This results in a convex optimization problem with linear constraints, which can be solved by the linearized alternating direction method. Though we take LRR as an example, our proposed method is in fact very general and can be applied to any self-representation graph learning methods. Experiment results on both synthetic and real data sets demonstrate that the proposed graph learning method can better capture the global geometric structure of the data, and therefore is more effective for semi-supervised learning tasks.

  4. A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification.

    Science.gov (United States)

    Peikari, Mohammad; Salama, Sherine; Nofech-Mozes, Sharon; Martel, Anne L

    2018-05-08

    Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a large number of unlabeled data points. In this paper, we investigated the possibility of using clustering analysis to identify the underlying structure of the data space for SSL. A cluster-then-label method was proposed to identify high-density regions in the data space which were then used to help a supervised SVM in finding the decision boundary. We have compared our method with other supervised and semi-supervised state-of-the-art techniques using two different classification tasks applied to breast pathology datasets. We found that compared with other state-of-the-art supervised and semi-supervised methods, our SSL method is able to improve classification performance when a limited number of labeled data instances are made available. We also showed that it is important to examine the underlying distribution of the data space before applying SSL techniques to ensure semi-supervised learning assumptions are not violated by the data.

  5. Binning sequences using very sparse labels within a metagenome

    Directory of Open Access Journals (Sweden)

    Halgamuge Saman K

    2008-04-01

    Full Text Available Abstract Background In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the current methods of binning, such as BLAST, k-mer and PhyloPythia, involve assigning sequence fragments by comparing sequence similarity or sequence composition with already-sequenced genomes that are still far from comprehensive. We propose a semi-supervised seeding method for binning that does not depend on knowledge of completed genomes. Instead, it extracts the flanking sequences of highly conserved 16S rRNA from the metagenome and uses them as seeds (labels to assign other reads based on their compositional similarity. Results The proposed seeding method is implemented on an unsupervised Growing Self-Organising Map (GSOM, and called Seeded GSOM (S-GSOM. We compared it with four well-known semi-supervised learning methods in a preliminary test, separating random-length prokaryotic sequence fragments sampled from the NCBI genome database. We identified the flanking sequences of the highly conserved 16S rRNA as suitable seeds that could be used to group the sequence fragments according to their species. S-GSOM showed superior performance compared to the semi-supervised methods tested. Additionally, S-GSOM may also be used to visually identify some species that do not have seeds. The proposed method was then applied to simulated metagenomic datasets using two different confidence threshold settings and compared with PhyloPythia, k-mer and BLAST. At the reference taxonomic level Order, S-GSOM outperformed all k-mer and BLAST results and showed comparable results with PhyloPythia for each of the corresponding confidence settings, where S-GSOM performed better than PhyloPythia in the ≥ 10 reads datasets and comparable in the ≥ 8 kb benchmark tests. Conclusion In the task of binning using semi-supervised learning methods, results indicate S-GSOM to be the best of

  6. Automated labelling of cancer textures in colorectal histopathology slides using quasi-supervised learning.

    Science.gov (United States)

    Onder, Devrim; Sarioglu, Sulen; Karacali, Bilge

    2013-04-01

    Quasi-supervised learning is a statistical learning algorithm that contrasts two datasets by computing estimate for the posterior probability of each sample in either dataset. This method has not been applied to histopathological images before. The purpose of this study is to evaluate the performance of the method to identify colorectal tissues with or without adenocarcinoma. Light microscopic digital images from histopathological sections were obtained from 30 colorectal radical surgery materials including adenocarcinoma and non-neoplastic regions. The texture features were extracted by using local histograms and co-occurrence matrices. The quasi-supervised learning algorithm operates on two datasets, one containing samples of normal tissues labelled only indirectly, and the other containing an unlabeled collection of samples of both normal and cancer tissues. As such, the algorithm eliminates the need for manually labelled samples of normal and cancer tissues for conventional supervised learning and significantly reduces the expert intervention. Several texture feature vector datasets corresponding to different extraction parameters were tested within the proposed framework. The Independent Component Analysis dimensionality reduction approach was also identified as the one improving the labelling performance evaluated in this series. In this series, the proposed method was applied to the dataset of 22,080 vectors with reduced dimensionality 119 from 132. Regions containing cancer tissue could be identified accurately having false and true positive rates up to 19% and 88% respectively without using manually labelled ground-truth datasets in a quasi-supervised strategy. The resulting labelling performances were compared to that of a conventional powerful supervised classifier using manually labelled ground-truth data. The supervised classifier results were calculated as 3.5% and 95% for the same case. The results in this series in comparison with the benchmark

  7. A semi-supervised approach using label propagation to support citation screening.

    Science.gov (United States)

    Kontonatsios, Georgios; Brockmeier, Austin J; Przybyła, Piotr; McNaught, John; Mu, Tingting; Goulermas, John Y; Ananiadou, Sophia

    2017-08-01

    Citation screening, an integral process within systematic reviews that identifies citations relevant to the underlying research question, is a time-consuming and resource-intensive task. During the screening task, analysts manually assign a label to each citation, to designate whether a citation is eligible for inclusion in the review. Recently, several studies have explored the use of active learning in text classification to reduce the human workload involved in the screening task. However, existing approaches require a significant amount of manually labelled citations for the text classification to achieve a robust performance. In this paper, we propose a semi-supervised method that identifies relevant citations as early as possible in the screening process by exploiting the pairwise similarities between labelled and unlabelled citations to improve the classification performance without additional manual labelling effort. Our approach is based on the hypothesis that similar citations share the same label (e.g., if one citation should be included, then other similar citations should be included also). To calculate the similarity between labelled and unlabelled citations we investigate two different feature spaces, namely a bag-of-words and a spectral embedding based on the bag-of-words. The semi-supervised method propagates the classification codes of manually labelled citations to neighbouring unlabelled citations in the feature space. The automatically labelled citations are combined with the manually labelled citations to form an augmented training set. For evaluation purposes, we apply our method to reviews from clinical and public health. The results show that our semi-supervised method with label propagation achieves statistically significant improvements over two state-of-the-art active learning approaches across both clinical and public health reviews. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  8. MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING

    Data.gov (United States)

    National Aeronautics and Space Administration — MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING MOHAMMAD SALIM AHMED, LATIFUR KHAN, NIKUNJ OZA, AND MANDAVA RAJESWARI Abstract....

  9. Multi-Label Classification by Semi-Supervised Singular Value Decomposition.

    Science.gov (United States)

    Jing, Liping; Shen, Chenyang; Yang, Liu; Yu, Jian; Ng, Michael K

    2017-10-01

    Multi-label problems arise in various domains, including automatic multimedia data categorization, and have generated significant interest in computer vision and machine learning community. However, existing methods do not adequately address two key challenges: exploiting correlations between labels and making up for the lack of labelled data or even missing labelled data. In this paper, we proposed to use a semi-supervised singular value decomposition (SVD) to handle these two challenges. The proposed model takes advantage of the nuclear norm regularization on the SVD to effectively capture the label correlations. Meanwhile, it introduces manifold regularization on mapping to capture the intrinsic structure among data, which provides a good way to reduce the required labelled data with improving the classification performance. Furthermore, we designed an efficient algorithm to solve the proposed model based on the alternating direction method of multipliers, and thus, it can efficiently deal with large-scale data sets. Experimental results for synthetic and real-world multimedia data sets demonstrate that the proposed method can exploit the label correlations and obtain promising and better label prediction results than the state-of-the-art methods.

  10. An empirical study of ensemble-based semi-supervised learning approaches for imbalanced splice site datasets.

    Science.gov (United States)

    Stanescu, Ana; Caragea, Doina

    2015-01-01

    Recent biochemical advances have led to inexpensive, time-efficient production of massive volumes of raw genomic data. Traditional machine learning approaches to genome annotation typically rely on large amounts of labeled data. The process of labeling data can be expensive, as it requires domain knowledge and expert involvement. Semi-supervised learning approaches that can make use of unlabeled data, in addition to small amounts of labeled data, can help reduce the costs associated with labeling. In this context, we focus on the problem of predicting splice sites in a genome using semi-supervised learning approaches. This is a challenging problem, due to the highly imbalanced distribution of the data, i.e., small number of splice sites as compared to the number of non-splice sites. To address this challenge, we propose to use ensembles of semi-supervised classifiers, specifically self-training and co-training classifiers. Our experiments on five highly imbalanced splice site datasets, with positive to negative ratios of 1-to-99, showed that the ensemble-based semi-supervised approaches represent a good choice, even when the amount of labeled data consists of less than 1% of all training data. In particular, we found that ensembles of co-training and self-training classifiers that dynamically balance the set of labeled instances during the semi-supervised iterations show improvements over the corresponding supervised ensemble baselines. In the presence of limited amounts of labeled data, ensemble-based semi-supervised approaches can successfully leverage the unlabeled data to enhance supervised ensembles learned from highly imbalanced data distributions. Given that such distributions are common for many biological sequence classification problems, our work can be seen as a stepping stone towards more sophisticated ensemble-based approaches to biological sequence annotation in a semi-supervised framework.

  11. Porosity estimation by semi-supervised learning with sparsely available labeled samples

    Science.gov (United States)

    Lima, Luiz Alberto; Görnitz, Nico; Varella, Luiz Eduardo; Vellasco, Marley; Müller, Klaus-Robert; Nakajima, Shinichi

    2017-09-01

    This paper addresses the porosity estimation problem from seismic impedance volumes and porosity samples located in a small group of exploratory wells. Regression methods, trained on the impedance as inputs and the porosity as output labels, generally suffer from extremely expensive (and hence sparsely available) porosity samples. To optimally make use of the valuable porosity data, a semi-supervised machine learning method was proposed, Transductive Conditional Random Field Regression (TCRFR), showing good performance (Görnitz et al., 2017). TCRFR, however, still requires more labeled data than those usually available, which creates a gap when applying the method to the porosity estimation problem in realistic situations. In this paper, we aim to fill this gap by introducing two graph-based preprocessing techniques, which adapt the original TCRFR for extremely weakly supervised scenarios. Our new method outperforms the previous automatic estimation methods on synthetic data and provides a comparable result to the manual labored, time-consuming geostatistics approach on real data, proving its potential as a practical industrial tool.

  12. Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning.

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    Hocking, Toby Dylan; Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi; Bourque, Guillaume

    2017-02-15

    Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/ , R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError. toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  13. The helpfulness of category labels in semi-supervised learning depends on category structure.

    Science.gov (United States)

    Vong, Wai Keen; Navarro, Daniel J; Perfors, Amy

    2016-02-01

    The study of semi-supervised category learning has generally focused on how additional unlabeled information with given labeled information might benefit category learning. The literature is also somewhat contradictory, sometimes appearing to show a benefit to unlabeled information and sometimes not. In this paper, we frame the problem differently, focusing on when labels might be helpful to a learner who has access to lots of unlabeled information. Using an unconstrained free-sorting categorization experiment, we show that labels are useful to participants only when the category structure is ambiguous and that people's responses are driven by the specific set of labels they see. We present an extension of Anderson's Rational Model of Categorization that captures this effect.

  14. Multiple tag labeling method for DNA sequencing

    Science.gov (United States)

    Mathies, R.A.; Huang, X.C.; Quesada, M.A.

    1995-07-25

    A DNA sequencing method is described which uses single lane or channel electrophoresis. Sequencing fragments are separated in the lane and detected using a laser-excited, confocal fluorescence scanner. Each set of DNA sequencing fragments is separated in the same lane and then distinguished using a binary coding scheme employing only two different fluorescent labels. Also described is a method of using radioisotope labels. 5 figs.

  15. Semi-supervised sparse coding

    KAUST Repository

    Wang, Jim Jing-Yan; Gao, Xin

    2014-01-01

    Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.

  16. Semi-supervised sparse coding

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-07-06

    Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.

  17. A SURVEY OF SEMI-SUPERVISED LEARNING

    OpenAIRE

    Amrita Sadarangani *, Dr. Anjali Jivani

    2016-01-01

    Semi Supervised Learning involves using both labeled and unlabeled data to train a classifier or for clustering. Semi supervised learning finds usage in many applications, since labeled data can be hard to find in many cases. Currently, a lot of research is being conducted in this area. This paper discusses the different algorithms of semi supervised learning and then their advantages and limitations are compared. The differences between supervised classification and semi-supervised classific...

  18. Optimistic semi-supervised least squares classification

    DEFF Research Database (Denmark)

    Krijthe, Jesse H.; Loog, Marco

    2017-01-01

    The goal of semi-supervised learning is to improve supervised classifiers by using additional unlabeled training examples. In this work we study a simple self-learning approach to semi-supervised learning applied to the least squares classifier. We show that a soft-label and a hard-label variant ...

  19. Managing complex processing of medical image sequences by program supervision techniques

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    Crubezy, Monica; Aubry, Florent; Moisan, Sabine; Chameroy, Virginie; Thonnat, Monique; Di Paola, Robert

    1997-05-01

    Our objective is to offer clinicians wider access to evolving medical image processing (MIP) techniques, crucial to improve assessment and quantification of physiological processes, but difficult to handle for non-specialists in MIP. Based on artificial intelligence techniques, our approach consists in the development of a knowledge-based program supervision system, automating the management of MIP libraries. It comprises a library of programs, a knowledge base capturing the expertise about programs and data and a supervision engine. It selects, organizes and executes the appropriate MIP programs given a goal to achieve and a data set, with dynamic feedback based on the results obtained. It also advises users in the development of new procedures chaining MIP programs.. We have experimented the approach for an application of factor analysis of medical image sequences as a means of predicting the response of osteosarcoma to chemotherapy, with both MRI and NM dynamic image sequences. As a result our program supervision system frees clinical end-users from performing tasks outside their competence, permitting them to concentrate on clinical issues. Therefore our approach enables a better exploitation of possibilities offered by MIP and higher quality results, both in terms of robustness and reliability.

  20. Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

    Directory of Open Access Journals (Sweden)

    Qingyu Chen

    Full Text Available First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases.We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.

  1. Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

    Science.gov (United States)

    Chen, Qingyu; Zobel, Justin; Zhang, Xiuzhen; Verspoor, Karin

    2016-01-01

    First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases. We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.

  2. Constraint Satisfaction Inference : Non-probabilistic Global Inference for Sequence Labelling

    NARCIS (Netherlands)

    Canisius, S.V.M.; van den Bosch, A.; Daelemans, W.; Basili, R.; Moschitti, A.

    2006-01-01

    We present a new method for performing sequence labelling based on the idea of using a machine-learning classifier to generate several possible output sequences, and then applying an inference procedure to select the best sequence among those. Most sequence labelling methods following a similar

  3. Human semi-supervised learning.

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    Gibson, Bryan R; Rogers, Timothy T; Zhu, Xiaojin

    2013-01-01

    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and machine learning research, we explain how these semi-supervised techniques can be applied to human learning. A series of experiments are described which show that semi-supervised learning models prove useful for explaining human behavior when exposed to both labeled and unlabeled data. We then discuss some machine learning models that do not have familiar human categorization counterparts. Finally, we discuss some challenges yet to be addressed in the use of semi-supervised models for modeling human categorization. Copyright © 2013 Cognitive Science Society, Inc.

  4. Cross-Domain Semi-Supervised Learning Using Feature Formulation.

    Science.gov (United States)

    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.

  5. Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.

    Science.gov (United States)

    Chen, Ke; Wang, Shihai

    2011-01-01

    Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into account during boosting learning. In this paper, we propose a novel cost functional consisting of the margin cost on labeled data and the regularization penalty on unlabeled data based on three fundamental semi-supervised assumptions. Thus, minimizing our proposed cost functional with a greedy yet stagewise functional optimization procedure leads to a generic boosting framework for semi-supervised learning. Extensive experiments demonstrate that our algorithm yields favorite results for benchmark and real-world classification tasks in comparison to state-of-the-art semi-supervised learning algorithms, including newly developed boosting algorithms. Finally, we discuss relevant issues and relate our algorithm to the previous work.

  6. Robust Semi-Supervised Manifold Learning Algorithm for Classification

    Directory of Open Access Journals (Sweden)

    Mingxia Chen

    2018-01-01

    Full Text Available In the recent years, manifold learning methods have been widely used in data classification to tackle the curse of dimensionality problem, since they can discover the potential intrinsic low-dimensional structures of the high-dimensional data. Given partially labeled data, the semi-supervised manifold learning algorithms are proposed to predict the labels of the unlabeled points, taking into account label information. However, these semi-supervised manifold learning algorithms are not robust against noisy points, especially when the labeled data contain noise. In this paper, we propose a framework for robust semi-supervised manifold learning (RSSML to address this problem. The noisy levels of the labeled points are firstly predicted, and then a regularization term is constructed to reduce the impact of labeled points containing noise. A new robust semi-supervised optimization model is proposed by adding the regularization term to the traditional semi-supervised optimization model. Numerical experiments are given to show the improvement and efficiency of RSSML on noisy data sets.

  7. Elephant: Sequence Labeling for Word and Sentence Segmentation

    NARCIS (Netherlands)

    Evang, Kilian; Basile, Valerio; Chrupala, Grzegorz; Bos, Johan

    2013-01-01

    Tokenization is widely regarded as a solved problem due to the high accuracy that rule-based tokenizers achieve. But rule-based tokenizers are hard to maintain and their rules language specific. We show that high-accuracy word and sentence segmentation can be achieved by using supervised sequence

  8. Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling

    NARCIS (Netherlands)

    Zhu, Zhemin; Hiemstra, Djoerd; Apers, Peter M.G.

    2014-01-01

    Sequence labeling has wide applications in natural language processing and speech processing. Popular sequence labeling models suffer from some known problems. Hidden Markov models (HMMs) are generative models and they cannot encode transition features; Conditional Markov models (CMMs) suffer from

  9. Enhanced manifold regularization for semi-supervised classification.

    Science.gov (United States)

    Gan, Haitao; Luo, Zhizeng; Fan, Yingle; Sang, Nong

    2016-06-01

    Manifold regularization (MR) has become one of the most widely used approaches in the semi-supervised learning field. It has shown superiority by exploiting the local manifold structure of both labeled and unlabeled data. The manifold structure is modeled by constructing a Laplacian graph and then incorporated in learning through a smoothness regularization term. Hence the labels of labeled and unlabeled data vary smoothly along the geodesics on the manifold. However, MR has ignored the discriminative ability of the labeled and unlabeled data. To address the problem, we propose an enhanced MR framework for semi-supervised classification in which the local discriminative information of the labeled and unlabeled data is explicitly exploited. To make full use of labeled data, we firstly employ a semi-supervised clustering method to discover the underlying data space structure of the whole dataset. Then we construct a local discrimination graph to model the discriminative information of labeled and unlabeled data according to the discovered intrinsic structure. Therefore, the data points that may be from different clusters, though similar on the manifold, are enforced far away from each other. Finally, the discrimination graph is incorporated into the MR framework. In particular, we utilize semi-supervised fuzzy c-means and Laplacian regularized Kernel minimum squared error for semi-supervised clustering and classification, respectively. Experimental results on several benchmark datasets and face recognition demonstrate the effectiveness of our proposed method.

  10. Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

    Science.gov (United States)

    Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C

    2010-09-13

    Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.

  11. Hidden Markov models for labeled sequences

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose

    1994-01-01

    A hidden Markov model for labeled observations, called a class HMM, is introduced and a maximum likelihood method is developed for estimating the parameters of the model. Instead of training it to model the statistics of the training sequences it is trained to optimize recognition. It resembles MMI...

  12. Maximum margin semi-supervised learning with irrelevant data.

    Science.gov (United States)

    Yang, Haiqin; Huang, Kaizhu; King, Irwin; Lyu, Michael R

    2015-10-01

    Semi-supervised learning (SSL) is a typical learning paradigms training a model from both labeled and unlabeled data. The traditional SSL models usually assume unlabeled data are relevant to the labeled data, i.e., following the same distributions of the targeted labeled data. In this paper, we address a different, yet formidable scenario in semi-supervised classification, where the unlabeled data may contain irrelevant data to the labeled data. To tackle this problem, we develop a maximum margin model, named tri-class support vector machine (3C-SVM), to utilize the available training data, while seeking a hyperplane for separating the targeted data well. Our 3C-SVM exhibits several characteristics and advantages. First, it does not need any prior knowledge and explicit assumption on the data relatedness. On the contrary, it can relieve the effect of irrelevant unlabeled data based on the logistic principle and maximum entropy principle. That is, 3C-SVM approaches an ideal classifier. This classifier relies heavily on labeled data and is confident on the relevant data lying far away from the decision hyperplane, while maximally ignoring the irrelevant data, which are hardly distinguished. Second, theoretical analysis is provided to prove that in what condition, the irrelevant data can help to seek the hyperplane. Third, 3C-SVM is a generalized model that unifies several popular maximum margin models, including standard SVMs, Semi-supervised SVMs (S(3)VMs), and SVMs learned from the universum (U-SVMs) as its special cases. More importantly, we deploy a concave-convex produce to solve the proposed 3C-SVM, transforming the original mixed integer programming, to a semi-definite programming relaxation, and finally to a sequence of quadratic programming subproblems, which yields the same worst case time complexity as that of S(3)VMs. Finally, we demonstrate the effectiveness and efficiency of our proposed 3C-SVM through systematical experimental comparisons. Copyright

  13. Machine Learned Replacement of N-Labels for Basecalled Sequences in DNA Barcoding.

    Science.gov (United States)

    Ma, Eddie Y T; Ratnasingham, Sujeevan; Kremer, Stefan C

    2018-01-01

    This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to replace with basecalls (A,C,G,T). An N-label correction is defined given an additional read of the same sequence, and a human finished sequence. Corrections are added to the dataset when an alignment determines the additional read and human agree on the identity of the N-label. KB must also rate the replacement with quality value of in the additional read. Corrections are only available during system training. Developing the system, nearly 850,000 N-labels are obtained from Barcode of Life Datasystems, the premier database of genetic markers called DNA Barcodes. Increasing the number of correct bases improves reference sequence reliability, increases sequence identification accuracy, and assures analysis correctness. Keeping with barcoding standards, our system maintains an error rate of percent. Our system only applies corrections when it estimates low rate of error. Tested on this data, our automation selects and recovers: 79 percent of N-labels from COI (animal barcode); 80 percent from matK and rbcL (plant barcodes); and 58 percent from non-protein-coding sequences (across eukaryotes).

  14. Structured prediction models for RNN based sequence labeling in clinical text.

    Science.gov (United States)

    Jagannatha, Abhyuday N; Yu, Hong

    2016-11-01

    Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

  15. SemiBoost: boosting for semi-supervised learning.

    Science.gov (United States)

    Mallapragada, Pavan Kumar; Jin, Rong; Jain, Anil K; Liu, Yi

    2009-11-01

    Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We call this as the Semi-supervised improvement problem, to distinguish the proposed approach from the existing approaches. We design a metasemi-supervised learning algorithm that wraps around the underlying supervised algorithm and improves its performance using unlabeled data. This problem is particularly important when we need to train a supervised learning algorithm with a limited number of labeled examples and a multitude of unlabeled examples. We present a boosting framework for semi-supervised learning, termed as SemiBoost. The key advantages of the proposed semi-supervised learning approach are: 1) performance improvement of any supervised learning algorithm with a multitude of unlabeled data, 2) efficient computation by the iterative boosting algorithm, and 3) exploiting both manifold and cluster assumption in training classification models. An empirical study on 16 different data sets and text categorization demonstrates that the proposed framework improves the performance of several commonly used supervised learning algorithms, given a large number of unlabeled examples. We also show that the performance of the proposed algorithm, SemiBoost, is comparable to the state-of-the-art semi-supervised learning algorithms.

  16. Supervised detection of exoplanets in high-contrast imaging sequences

    Science.gov (United States)

    Gomez Gonzalez, C. A.; Absil, O.; Van Droogenbroeck, M.

    2018-06-01

    Context. Post-processing algorithms play a key role in pushing the detection limits of high-contrast imaging (HCI) instruments. State-of-the-art image processing approaches for HCI enable the production of science-ready images relying on unsupervised learning techniques, such as low-rank approximations, for generating a model point spread function (PSF) and subtracting the residual starlight and speckle noise. Aims: In order to maximize the detection rate of HCI instruments and survey campaigns, advanced algorithms with higher sensitivities to faint companions are needed, especially for the speckle-dominated innermost region of the images. Methods: We propose a reformulation of the exoplanet detection task (for ADI sequences) that builds on well-established machine learning techniques to take HCI post-processing from an unsupervised to a supervised learning context. In this new framework, we present algorithmic solutions using two different discriminative models: SODIRF (random forests) and SODINN (neural networks). We test these algorithms on real ADI datasets from VLT/NACO and VLT/SPHERE HCI instruments. We then assess their performances by injecting fake companions and using receiver operating characteristic analysis. This is done in comparison with state-of-the-art ADI algorithms, such as ADI principal component analysis (ADI-PCA). Results: This study shows the improved sensitivity versus specificity trade-off of the proposed supervised detection approach. At the diffraction limit, SODINN improves the true positive rate by a factor ranging from 2 to 10 (depending on the dataset and angular separation) with respect to ADI-PCA when working at the same false-positive level. Conclusions: The proposed supervised detection framework outperforms state-of-the-art techniques in the task of discriminating planet signal from speckles. In addition, it offers the possibility of re-processing existing HCI databases to maximize their scientific return and potentially improve

  17. Guess Where? Actor-Supervision for Spatiotemporal Action Localization

    KAUST Repository

    Escorcia, Victor

    2018-04-05

    This paper addresses the problem of spatiotemporal localization of actions in videos. Compared to leading approaches, which all learn to localize based on carefully annotated boxes on training video frames, we adhere to a weakly-supervised solution that only requires a video class label. We introduce an actor-supervised architecture that exploits the inherent compositionality of actions in terms of actor transformations, to localize actions. We make two contributions. First, we propose actor proposals derived from a detector for human and non-human actors intended for images, which is linked over time by Siamese similarity matching to account for actor deformations. Second, we propose an actor-based attention mechanism that enables the localization of the actions from action class labels and actor proposals and is end-to-end trainable. Experiments on three human and non-human action datasets show actor supervision is state-of-the-art for weakly-supervised action localization and is even competitive to some fully-supervised alternatives.

  18. Guess Where? Actor-Supervision for Spatiotemporal Action Localization

    KAUST Repository

    Escorcia, Victor; Dao, Cuong D.; Jain, Mihir; Ghanem, Bernard; Snoek, Cees

    2018-01-01

    This paper addresses the problem of spatiotemporal localization of actions in videos. Compared to leading approaches, which all learn to localize based on carefully annotated boxes on training video frames, we adhere to a weakly-supervised solution that only requires a video class label. We introduce an actor-supervised architecture that exploits the inherent compositionality of actions in terms of actor transformations, to localize actions. We make two contributions. First, we propose actor proposals derived from a detector for human and non-human actors intended for images, which is linked over time by Siamese similarity matching to account for actor deformations. Second, we propose an actor-based attention mechanism that enables the localization of the actions from action class labels and actor proposals and is end-to-end trainable. Experiments on three human and non-human action datasets show actor supervision is state-of-the-art for weakly-supervised action localization and is even competitive to some fully-supervised alternatives.

  19. Semi-supervised Learning with Deep Generative Models

    NARCIS (Netherlands)

    Kingma, D.P.; Rezende, D.J.; Mohamed, S.; Welling, M.

    2014-01-01

    The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised learning one of the problems of significant practical importance in modern data analysis. We revisit the approach to semi-supervised learning with generative models and

  20. Discriminative semi-supervised feature selection via manifold regularization.

    Science.gov (United States)

    Xu, Zenglin; King, Irwin; Lyu, Michael Rung-Tsong; Jin, Rong

    2010-07-01

    Feature selection has attracted a huge amount of interest in both research and application communities of data mining. We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number of labeled samples are usually insufficient for identifying the relevant features, the critical problem arising from semi-supervised feature selection is how to take advantage of the information underneath the unlabeled data. To address this problem, we propose a novel discriminative semi-supervised feature selection method based on the idea of manifold regularization. The proposed approach selects features through maximizing the classification margin between different classes and simultaneously exploiting the geometry of the probability distribution that generates both labeled and unlabeled data. In comparison with previous semi-supervised feature selection algorithms, our proposed semi-supervised feature selection method is an embedded feature selection method and is able to find more discriminative features. We formulate the proposed feature selection method into a convex-concave optimization problem, where the saddle point corresponds to the optimal solution. To find the optimal solution, the level method, a fairly recent optimization method, is employed. We also present a theoretic proof of the convergence rate for the application of the level method to our problem. Empirical evaluation on several benchmark data sets demonstrates the effectiveness of the proposed semi-supervised feature selection method.

  1. Weakly supervised visual dictionary learning by harnessing image attributes.

    Science.gov (United States)

    Gao, Yue; Ji, Rongrong; Liu, Wei; Dai, Qionghai; Hua, Gang

    2014-12-01

    Bag-of-features (BoFs) representation has been extensively applied to deal with various computer vision applications. To extract discriminative and descriptive BoF, one important step is to learn a good dictionary to minimize the quantization loss between local features and codewords. While most existing visual dictionary learning approaches are engaged with unsupervised feature quantization, the latest trend has turned to supervised learning by harnessing the semantic labels of images or regions. However, such labels are typically too expensive to acquire, which restricts the scalability of supervised dictionary learning approaches. In this paper, we propose to leverage image attributes to weakly supervise the dictionary learning procedure without requiring any actual labels. As a key contribution, our approach establishes a generative hidden Markov random field (HMRF), which models the quantized codewords as the observed states and the image attributes as the hidden states, respectively. Dictionary learning is then performed by supervised grouping the observed states, where the supervised information is stemmed from the hidden states of the HMRF. In such a way, the proposed dictionary learning approach incorporates the image attributes to learn a semantic-preserving BoF representation without any genuine supervision. Experiments in large-scale image retrieval and classification tasks corroborate that our approach significantly outperforms the state-of-the-art unsupervised dictionary learning approaches.

  2. Weakly Supervised Dictionary Learning

    Science.gov (United States)

    You, Zeyu; Raich, Raviv; Fern, Xiaoli Z.; Kim, Jinsub

    2018-05-01

    We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and restoration as well as high-level classification tasks, which can be applied to audio and image analysis. Synthesis dictionary learning aims at jointly learning a dictionary and corresponding sparse coefficients to provide accurate data representation. This approach is useful for denoising and signal restoration, but may lead to sub-optimal classification performance. By contrast, analysis dictionary learning provides a transform that maps data to a sparse discriminative representation suitable for classification. We consider the problem of analysis dictionary learning for time-series data under a weak supervision setting in which signals are assigned with a global label instead of an instantaneous label signal. We propose a discriminative probabilistic model that incorporates both label information and sparsity constraints on the underlying latent instantaneous label signal using cardinality control. We present the expectation maximization (EM) procedure for maximum likelihood estimation (MLE) of the proposed model. To facilitate a computationally efficient E-step, we propose both a chain and a novel tree graph reformulation of the graphical model. The performance of the proposed model is demonstrated on both synthetic and real-world data.

  3. Supervised Transfer Sparse Coding

    KAUST Repository

    Al-Shedivat, Maruan

    2014-07-27

    A combination of the sparse coding and transfer learn- ing techniques was shown to be accurate and robust in classification tasks where training and testing objects have a shared feature space but are sampled from differ- ent underlying distributions, i.e., belong to different do- mains. The key assumption in such case is that in spite of the domain disparity, samples from different domains share some common hidden factors. Previous methods often assumed that all the objects in the target domain are unlabeled, and thus the training set solely comprised objects from the source domain. However, in real world applications, the target domain often has some labeled objects, or one can always manually label a small num- ber of them. In this paper, we explore such possibil- ity and show how a small number of labeled data in the target domain can significantly leverage classifica- tion accuracy of the state-of-the-art transfer sparse cod- ing methods. We further propose a unified framework named supervised transfer sparse coding (STSC) which simultaneously optimizes sparse representation, domain transfer and classification. Experimental results on three applications demonstrate that a little manual labeling and then learning the model in a supervised fashion can significantly improve classification accuracy.

  4. Active link selection for efficient semi-supervised community detection

    Science.gov (United States)

    Yang, Liang; Jin, Di; Wang, Xiao; Cao, Xiaochun

    2015-01-01

    Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods. However, most of them focus on how to integrate supervised information with topology information; few of them pay attention to which information is critical for performance improvement. This leads to large amounts of demand for supervised information, which is expensive or difficult to obtain in most fields. For this problem we propose an active link selection framework, that is we actively select the most uncertain and informative links for human labeling for the efficient utilization of the supervised information. We also disconnect the most likely inter-community edges to further improve the efficiency. Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly labeling links as the existing methods did. Experiments on both synthetic and real networks demonstrate that our new approach significantly outperforms the existing methods in terms of the efficiency of using supervised information. It needs ~13% of the supervised information to achieve a performance similar to that of the original semi-supervised approaches. PMID:25761385

  5. Flexible manifold embedding: a framework for semi-supervised and unsupervised dimension reduction.

    Science.gov (United States)

    Nie, Feiping; Xu, Dong; Tsang, Ivor Wai-Hung; Zhang, Changshui

    2010-07-01

    We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the new data points. For semi-supervised dimension reduction, we aim to find the optimal prediction labels F for all the training samples X, the linear regression function h(X) and the regression residue F(0) = F - h(X) simultaneously. Our new objective function integrates two terms related to label fitness and manifold smoothness as well as a flexible penalty term defined on the residue F(0). Our Semi-Supervised learning framework, referred to as flexible manifold embedding (FME), can effectively utilize label information from labeled data as well as a manifold structure from both labeled and unlabeled data. By modeling the mismatch between h(X) and F, we show that FME relaxes the hard linear constraint F = h(X) in manifold regularization (MR), making it better cope with the data sampled from a nonlinear manifold. In addition, we propose a simplified version (referred to as FME/U) for unsupervised dimension reduction. We also show that our proposed framework provides a unified view to explain and understand many semi-supervised, supervised and unsupervised dimension reduction techniques. Comprehensive experiments on several benchmark databases demonstrate the significant improvement over existing dimension reduction algorithms.

  6. Projected estimators for robust semi-supervised classification

    DEFF Research Database (Denmark)

    Krijthe, Jesse H.; Loog, Marco

    2017-01-01

    For semi-supervised techniques to be applied safely in practice we at least want methods to outperform their supervised counterparts. We study this question for classification using the well-known quadratic surrogate loss function. Unlike other approaches to semi-supervised learning, the procedure...... specifically, we prove that, measured on the labeled and unlabeled training data, this semi-supervised procedure never gives a lower quadratic loss than the supervised alternative. To our knowledge this is the first approach that offers such strong, albeit conservative, guarantees for improvement over...... the supervised solution. The characteristics of our approach are explicated using benchmark datasets to further understand the similarities and differences between the quadratic loss criterion used in the theoretical results and the classification accuracy typically considered in practice....

  7. Semi-supervised Learning for Phenotyping Tasks.

    Science.gov (United States)

    Dligach, Dmitriy; Miller, Timothy; Savova, Guergana K

    2015-01-01

    Supervised learning is the dominant approach to automatic electronic health records-based phenotyping, but it is expensive due to the cost of manual chart review. Semi-supervised learning takes advantage of both scarce labeled and plentiful unlabeled data. In this work, we study a family of semi-supervised learning algorithms based on Expectation Maximization (EM) in the context of several phenotyping tasks. We first experiment with the basic EM algorithm. When the modeling assumptions are violated, basic EM leads to inaccurate parameter estimation. Augmented EM attenuates this shortcoming by introducing a weighting factor that downweights the unlabeled data. Cross-validation does not always lead to the best setting of the weighting factor and other heuristic methods may be preferred. We show that accurate phenotyping models can be trained with only a few hundred labeled (and a large number of unlabeled) examples, potentially providing substantial savings in the amount of the required manual chart review.

  8. Implicity Defined Neural Networks for Sequence Labeling

    Science.gov (United States)

    2017-02-13

    assumption - that a hid- den variable changes its state based only on its current state and observables. In finding maximum likelihood state sequences...this setup, we have the following variables : data X labels Y parameters θ and functions: implicit hidden layer definition H = F (θ, ξ,H) loss function L...tagging task. In future work, we intend to consider implicit varia - tions of other archetectures, such as the LSTM, as well as additional, more challenging

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

    Science.gov (United States)

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

    2018-05-01

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

  10. PySeqLab: an open source Python package for sequence labeling and segmentation.

    Science.gov (United States)

    Allam, Ahmed; Krauthammer, Michael

    2017-11-01

    Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data. Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks. It implements CRFs models, that is discriminative models from (i) first-order to higher-order linear-chain CRFs, and from (ii) first-order to higher-order semi-Markov CRFs (semi-CRFs). Moreover, it provides multiple learning algorithms for estimating model parameters such as (i) stochastic gradient descent (SGD) and its multiple variations, (ii) structured perceptron with multiple averaging schemes supporting exact and inexact search using 'violation-fixing' framework, (iii) search-based probabilistic online learning algorithm (SAPO) and (iv) an interface for Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited-memory BFGS algorithms. Viterbi and Viterbi A* are used for inference and decoding of sequences. Using PySeqLab, we built models (classifiers) and evaluated their performance in three different domains: (i) biomedical Natural language processing (NLP), (ii) predictive DNA sequence analysis and (iii) Human activity recognition (HAR). State-of-the-art performance comparable to machine-learning based systems was achieved in the three domains without feature engineering or the use of knowledge sources. PySeqLab is available through https://bitbucket.org/A_2/pyseqlab with tutorials and documentation. ahmed.allam@yale.edu or michael.krauthammer@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  11. Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors.

    Science.gov (United States)

    Khoshgoftaar, Taghi M; Van Hulse, Jason; Napolitano, Amri

    2010-05-01

    Neural network algorithms such as multilayer perceptrons (MLPs) and radial basis function networks (RBFNets) have been used to construct learners which exhibit strong predictive performance. Two data related issues that can have a detrimental impact on supervised learning initiatives are class imbalance and labeling errors (or class noise). Imbalanced data can make it more difficult for the neural network learning algorithms to distinguish between examples of the various classes, and class noise can lead to the formulation of incorrect hypotheses. Both class imbalance and labeling errors are pervasive problems encountered in a wide variety of application domains. Many studies have been performed to investigate these problems in isolation, but few have focused on their combined effects. This study presents a comprehensive empirical investigation using neural network algorithms to learn from imbalanced data with labeling errors. In particular, the first component of our study investigates the impact of class noise and class imbalance on two common neural network learning algorithms, while the second component considers the ability of data sampling (which is commonly used to address the issue of class imbalance) to improve their performances. Our results, for which over two million models were trained and evaluated, show that conclusions drawn using the more commonly studied C4.5 classifier may not apply when using neural networks.

  12. Semi-supervised learning for ordinal Kernel Discriminant Analysis.

    Science.gov (United States)

    Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

    2016-12-01

    Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. 9 CFR 592.340 - Supervision of marking and packaging.

    Science.gov (United States)

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Supervision of marking and packaging... § 592.340 Supervision of marking and packaging. (a) Evidence of label approval. Inspection program... evidence that such official identification or packaging material bearing such official identification has...

  14. Coupled dimensionality reduction and classification for supervised and semi-supervised multilabel learning.

    Science.gov (United States)

    Gönen, Mehmet

    2014-03-01

    Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F 1 , and micro F 1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks.

  15. 9 CFR 590.418 - Supervision of marking and packaging.

    Science.gov (United States)

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Supervision of marking and packaging...) Identifying and Marking Product § 590.418 Supervision of marking and packaging. (a) Evidence of label approval... has on file evidence that such official identification or packaging material bearing such official...

  16. Multi-Modal Curriculum Learning for Semi-Supervised Image Classification.

    Science.gov (United States)

    Gong, Chen; Tao, Dacheng; Maybank, Stephen J; Liu, Wei; Kang, Guoliang; Yang, Jie

    2016-07-01

    Semi-supervised image classification aims to classify a large quantity of unlabeled images by typically harnessing scarce labeled images. Existing semi-supervised methods often suffer from inadequate classification accuracy when encountering difficult yet critical images, such as outliers, because they treat all unlabeled images equally and conduct classifications in an imperfectly ordered sequence. In this paper, we employ the curriculum learning methodology by investigating the difficulty of classifying every unlabeled image. The reliability and the discriminability of these unlabeled images are particularly investigated for evaluating their difficulty. As a result, an optimized image sequence is generated during the iterative propagations, and the unlabeled images are logically classified from simple to difficult. Furthermore, since images are usually characterized by multiple visual feature descriptors, we associate each kind of features with a teacher, and design a multi-modal curriculum learning (MMCL) strategy to integrate the information from different feature modalities. In each propagation, each teacher analyzes the difficulties of the currently unlabeled images from its own modality viewpoint. A consensus is subsequently reached among all the teachers, determining the currently simplest images (i.e., a curriculum), which are to be reliably classified by the multi-modal learner. This well-organized propagation process leveraging multiple teachers and one learner enables our MMCL to outperform five state-of-the-art methods on eight popular image data sets.

  17. Deep Web Search Interface Identification: A Semi-Supervised Ensemble Approach

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-12-01

    Full Text Available To surface the Deep Web, one crucial task is to predict whether a given web page has a search interface (searchable HyperText Markup Language (HTML form or not. Previous studies have focused on supervised classification with labeled examples. However, labeled data are scarce, hard to get and requires tediousmanual work, while unlabeled HTML forms are abundant and easy to obtain. In this research, we consider the plausibility of using both labeled and unlabeled data to train better models to identify search interfaces more effectively. We present a semi-supervised co-training ensemble learning approach using both neural networks and decision trees to deal with the search interface identification problem. We show that the proposed model outperforms previous methods using only labeled data. We also show that adding unlabeled data improves the effectiveness of the proposed model.

  18. Weakly supervised semantic segmentation using fore-background priors

    Science.gov (United States)

    Han, Zheng; Xiao, Zhitao; Yu, Mingjun

    2017-07-01

    Weakly-supervised semantic segmentation is a challenge in the field of computer vision. Most previous works utilize the labels of the whole training set and thereby need the construction of a relationship graph about image labels, thus result in expensive computation. In this study, we tackle this problem from a different perspective. We proposed a novel semantic segmentation algorithm based on background priors, which avoids the construction of a huge graph in whole training dataset. Specifically, a random forest classifier is obtained using weakly supervised training data .Then semantic texton forest (STF) feature is extracted from image superpixels. Finally, a CRF based optimization algorithm is proposed. The unary potential of CRF derived from the outputting probability of random forest classifier and the robust saliency map as background prior. Experiments on the MSRC21 dataset show that the new algorithm outperforms some previous influential weakly-supervised segmentation algorithms. Furthermore, the use of efficient decision forests classifier and parallel computing of saliency map significantly accelerates the implementation.

  19. Semi-Supervised Classification for Fault Diagnosis in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Ma, Jian Ping; Jiang, Jin

    2014-01-01

    Pattern classification methods have become important tools for fault diagnosis in industrial systems. However, it is normally difficult to obtain reliable labeled data to train a supervised pattern classification model for applications in a nuclear power plant (NPP). However, unlabeled data easily become available through increased deployment of supervisory, control, and data acquisition (SCADA) systems. In this paper, a fault diagnosis scheme based on semi-supervised classification (SSC) method is developed with specific applications for NPP. In this scheme, newly measured plant data are treated as unlabeled data. They are integrated with selected labeled data to train a SSC model which is then used to estimate labels of the new data. Compared to exclusive supervised approaches, the proposed scheme requires significantly less number of labeled data to train a classifier. Furthermore, it is shown that higher degree of uncertainties in the labeled data can be tolerated. The developed scheme has been validated using the data generated from a desktop NPP simulator and also from a physical NPP simulator using a graph-based SSC algorithm. Two case studies have been used in the validation process. In the first case study, three faults have been simulated on the desktop simulator. These faults have all been classified successfully with only four labeled data points per fault case. In the second case, six types of fault are simulated on the physical NPP simulator. All faults have been successfully diagnosed. The results have demonstrated that SSC is a promising tool for fault diagnosis

  20. Semi-Supervised Transductive Hot Spot Predictor Working on Multiple Assumptions

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-05-23

    Protein-protein interactions are critically dependent on just a few residues (“hot spots”) at the interfaces. Hot spots make a dominant contribution to the binding free energy and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there exists a need for accurate and reliable computational hot spot prediction methods. Compared to the supervised hot spot prediction algorithms, the semi-supervised prediction methods can take into consideration both the labeled and unlabeled residues in the dataset during the prediction procedure. The transductive support vector machine has been utilized for this task and demonstrated a better prediction performance. To the best of our knowledge, however, none of the transductive semi-supervised algorithms takes all the three semisupervised assumptions, i.e., smoothness, cluster and manifold assumptions, together into account during learning. In this paper, we propose a novel semi-supervised method for hot spot residue prediction, by considering all the three semisupervised assumptions using nonlinear models. Our algorithm, IterPropMCS, works in an iterative manner. In each iteration, the algorithm first propagates the labels of the labeled residues to the unlabeled ones, along the shortest path between them on a graph, assuming that they lie on a nonlinear manifold. Then it selects the most confident residues as the labeled ones for the next iteration, according to the cluster and smoothness criteria, which is implemented by a nonlinear density estimator. Experiments on a benchmark dataset, using protein structure-based features, demonstrate that our approach is effective in predicting hot spots and compares favorably to other available methods. The results also show that our method outperforms the state-of-the-art transductive learning methods.

  1. Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

    Science.gov (United States)

    Huang, Yan; Wang, Wei; Wang, Liang; Tan, Tieniu

    2017-09-01

    Relation learning is a fundamental problem in many vision tasks. Recently, high-order Boltzmann machine and its variants have shown their great potentials in learning various types of data relation in a range of tasks. But most of these models are learned in an unsupervised way, i.e., without using relation class labels, which are not very discriminative for some challenging tasks, e.g., face verification. In this paper, with the goal to perform supervised relation learning, we introduce relation class labels into conventional high-order multiplicative interactions with pairwise input samples, and propose a conditional high-order Boltzmann Machine (CHBM), which can learn to classify the data relation in a binary classification way. To be able to deal with more complex data relation, we develop two improved variants of CHBM: 1) latent CHBM, which jointly performs relation feature learning and classification, by using a set of latent variables to block the pathway from pairwise input samples to output relation labels and 2) gated CHBM, which untangles factors of variation in data relation, by exploiting a set of latent variables to multiplicatively gate the classification of CHBM. To reduce the large number of model parameters generated by the multiplicative interactions, we approximately factorize high-order parameter tensors into multiple matrices. Then, we develop efficient supervised learning algorithms, by first pretraining the models using joint likelihood to provide good parameter initialization, and then finetuning them using conditional likelihood to enhance the discriminant ability. We apply the proposed models to a series of tasks including invariant recognition, face verification, and action similarity labeling. Experimental results demonstrate that by exploiting supervised relation labels, our models can greatly improve the performance.

  2. Semi-Supervised Multi-View Ensemble Learning Based On Extracting Cross-View Correlation

    Directory of Open Access Journals (Sweden)

    ZALL, R.

    2016-05-01

    Full Text Available Correlated information between different views incorporate useful for learning in multi view data. Canonical correlation analysis (CCA plays important role to extract these information. However, CCA only extracts the correlated information between paired data and cannot preserve correlated information between within-class samples. In this paper, we propose a two-view semi-supervised learning method called semi-supervised random correlation ensemble base on spectral clustering (SS_RCE. SS_RCE uses a multi-view method based on spectral clustering which takes advantage of discriminative information in multiple views to estimate labeling information of unlabeled samples. In order to enhance discriminative power of CCA features, we incorporate the labeling information of both unlabeled and labeled samples into CCA. Then, we use random correlation between within-class samples from cross view to extract diverse correlated features for training component classifiers. Furthermore, we extend a general model namely SSMV_RCE to construct ensemble method to tackle semi-supervised learning in the presence of multiple views. Finally, we compare the proposed methods with existing multi-view feature extraction methods using multi-view semi-supervised ensembles. Experimental results on various multi-view data sets are presented to demonstrate the effectiveness of the proposed methods.

  3. Graph-Based Semi-Supervised Hyperspectral Image Classification Using Spatial Information

    Science.gov (United States)

    Jamshidpour, N.; Homayouni, S.; Safari, A.

    2017-09-01

    Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

  4. GRAPH-BASED SEMI-SUPERVISED HYPERSPECTRAL IMAGE CLASSIFICATION USING SPATIAL INFORMATION

    Directory of Open Access Journals (Sweden)

    N. Jamshidpour

    2017-09-01

    Full Text Available Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

  5. Graph-based semi-supervised learning

    CERN Document Server

    Subramanya, Amarnag

    2014-01-01

    While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL algorithms, which bring together these two lines of work, have been shown to outperform the state-of-the-art in many applications in speech processing, computer visi

  6. Well-spread sequences and edge-labellings with constant Hamilton-weight

    Directory of Open Access Journals (Sweden)

    P. Mark Kayll

    2004-12-01

    Full Text Available A sequence (a i of integers is well-spread if the sums a i +a j, for isequence 0≤ a 1 <…label Λ(n in a `most-efficient' metric, injective edge-labelling of K n with the property that every Hamilton cycle has the same length; we prove that 2n 2-O(n 3/2<Λ(n<2n 2 +O(n 61/40.

  7. Optimizing area under the ROC curve using semi-supervised learning.

    Science.gov (United States)

    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.

  8. Polyfluorophore Labels on DNA: Dramatic Sequence Dependence of Quenching

    Science.gov (United States)

    Teo, Yin Nah; Wilson, James N.

    2010-01-01

    We describe studies carried out in the DNA context to test how a common fluorescence quencher, dabcyl, interacts with oligodeoxynu-cleoside fluorophores (ODFs)—a system of stacked, electronically interacting fluorophores built on a DNA scaffold. We tested twenty different tetrameric ODF sequences containing varied combinations and orderings of pyrene (Y), benzopyrene (B), perylene (E), dimethylaminostilbene (D), and spacer (S) monomers conjugated to the 3′ end of a DNA oligomer. Hybridization of this probe sequence to a dabcyl-labeled complementary strand resulted in strong quenching of fluorescence in 85% of the twenty ODF sequences. The high efficiency of quenching was also established by their large Stern–Volmer constants (KSV) of between 2.1 × 104 and 4.3 × 105M−1, measured with a free dabcyl quencher. Interestingly, quenching of ODFs displayed strong sequence dependence. This was particularly evident in anagrams of ODF sequences; for example, the sequence BYDS had a KSV that was approximately two orders of magnitude greater than that of BSDY, which has the same dye composition. Other anagrams, for example EDSY and ESYD, also displayed different responses upon quenching by dabcyl. Analysis of spectra showed that apparent excimer and exciplex emission bands were quenched with much greater efficiency compared to monomer emission bands by at least an order of magnitude. This suggests an important role played by delocalized excited states of the π stack of fluorophores in the amplified quenching of fluorescence. PMID:19780115

  9. Robust semi-supervised learning : projections, limits & constraints

    NARCIS (Netherlands)

    Krijthe, J.H.

    2018-01-01

    In many domains of science and society, the amount of data being gathered is increasing rapidly. To estimate input-output relationships that are often of interest, supervised learning techniques rely on a specific type of data: labeled examples for which we know both the input and an outcome. The

  10. A Novel Semi-Supervised Electronic Nose Learning Technique: M-Training

    Directory of Open Access Journals (Sweden)

    Pengfei Jia

    2016-03-01

    Full Text Available When an electronic nose (E-nose is used to distinguish different kinds of gases, the label information of the target gas could be lost due to some fault of the operators or some other reason, although this is not expected. Another fact is that the cost of getting the labeled samples is usually higher than for unlabeled ones. In most cases, the classification accuracy of an E-nose trained using labeled samples is higher than that of the E-nose trained by unlabeled ones, so gases without label information should not be used to train an E-nose, however, this wastes resources and can even delay the progress of research. In this work a novel multi-class semi-supervised learning technique called M-training is proposed to train E-noses with both labeled and unlabeled samples. We employ M-training to train the E-nose which is used to distinguish three indoor pollutant gases (benzene, toluene and formaldehyde. Data processing results prove that the classification accuracy of E-nose trained by semi-supervised techniques (tri-training and M-training is higher than that of an E-nose trained only with labeled samples, and the performance of M-training is better than that of tri-training because more base classifiers can be employed by M-training.

  11. AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

    Science.gov (United States)

    Wang, Sheng; Sun, Siqi; Xu, Jinbo

    2016-09-01

    Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

  12. Semi-supervised Eigenvectors for Locally-biased Learning

    DEFF Research Database (Denmark)

    Hansen, Toke Jansen; Mahoney, Michael W.

    2012-01-01

    In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks "nearby" that pre-specified target region. Locally-biased problems of t...

  13. Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Zhi He

    2017-10-01

    Full Text Available Classification of hyperspectral image (HSI is an important research topic in the remote sensing community. Significant efforts (e.g., deep learning have been concentrated on this task. However, it is still an open issue to classify the high-dimensional HSI with a limited number of training samples. In this paper, we propose a semi-supervised HSI classification method inspired by the generative adversarial networks (GANs. Unlike the supervised methods, the proposed HSI classification method is semi-supervised, which can make full use of the limited labeled samples as well as the sufficient unlabeled samples. Core ideas of the proposed method are twofold. First, the three-dimensional bilateral filter (3DBF is adopted to extract the spectral-spatial features by naturally treating the HSI as a volumetric dataset. The spatial information is integrated into the extracted features by 3DBF, which is propitious to the subsequent classification step. Second, GANs are trained on the spectral-spatial features for semi-supervised learning. A GAN contains two neural networks (i.e., generator and discriminator trained in opposition to one another. The semi-supervised learning is achieved by adding samples from the generator to the features and increasing the dimension of the classifier output. Experimental results obtained on three benchmark HSI datasets have confirmed the effectiveness of the proposed method , especially with a limited number of labeled samples.

  14. Deep Web Search Interface Identification: A Semi-Supervised Ensemble Approach

    OpenAIRE

    Hong Wang; Qingsong Xu; Lifeng Zhou

    2014-01-01

    To surface the Deep Web, one crucial task is to predict whether a given web page has a search interface (searchable HyperText Markup Language (HTML) form) or not. Previous studies have focused on supervised classification with labeled examples. However, labeled data are scarce, hard to get and requires tediousmanual work, while unlabeled HTML forms are abundant and easy to obtain. In this research, we consider the plausibility of using both labeled and unlabeled data to train better models to...

  15. Efficient use of unlabeled data for protein sequence classification: a comparative study.

    Science.gov (United States)

    Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

    2009-04-29

    Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags-the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably.

  16. Semi-supervised detection of intracranial pressure alarms using waveform dynamics

    International Nuclear Information System (INIS)

    Scalzo, Fabien; Hu, Xiao

    2013-01-01

    Patient monitoring systems in intensive care units (ICU) are usually set to trigger alarms when abnormal values are detected. Alarms are generated by threshold-crossing rules that lead to high false alarm rates. This is a recognized issue that causes alarm fatigue, waste of human resources, and increased patient risks. Recently developed smart alarm models require alarms to be validated by experts during the training phase. The manual annotation process involved is time-consuming and virtually impossible to achieve for the thousands of alarms recorded in the ICU every week. To tackle this problem, we investigate in this study if the use of semi-supervised learning methods, that can naturally integrate unlabeled data samples in the model, can be used to improve the accuracy of the alarm detection. As a proof of concept, the detection system is evaluated on intracranial pressure (ICP) signal alarms. Specific morphological and trending features are extracted from the ICP signal waveform to capture the dynamic of the signal prior to alarms. This study is based on a comprehensive dataset of 4791 manually labeled alarms recorded from 108 neurosurgical patients. A comparative analysis is provided between kernel spectral regression (SR-KDA) and support vector machine (SVM) both modified for the semi-supervised setting. Results obtained during the experimental evaluations indicate that the two models can significantly reduce false alarms using unlabeled samples; especially in the presence of a restrained number of labeled examples. At a true alarm recognition rate of 99%, the false alarm reduction rates improved from 9% (supervised) to 27% (semi-supervised) for SR-KDA, and from 3% (supervised) to 16% (semi-supervised) for SVM. (paper)

  17. Abusive Supervision Scale Development in Indonesia

    Directory of Open Access Journals (Sweden)

    Fenika Wulani

    2014-02-01

    Full Text Available The purpose of this study was to develop a scale of abusive supervision in Indonesia. The study was conducted with a different context and scale development method from Tepper’s (2000 abusive supervision scale. The abusive supervision scale from Tepper (2000 was developed in the U.S., which has a cultural orientation of low power distance. The current study was conducted in Indonesia, which has a high power distance. This study used interview procedures to obtain information about supervisor’s abusive behavior, and it was also assessed by experts. The results of this study indicated that abusive supervision was a 3-dimensional construct. There were anger-active abuse (6 items, humiliation-active abuse (4 items, and passive abuse (15 items. These scales have internal reliabilities of 0.947, 0.922, and 0.845, in sequence.

  18. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Science.gov (United States)

    Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

    2014-01-01

    The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  19. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Directory of Open Access Journals (Sweden)

    Chihyun Park

    Full Text Available BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. RESULTS: In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. CONCLUSIONS: The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  20. Improving Semi-Supervised Learning with Auxiliary Deep Generative Models

    DEFF Research Database (Denmark)

    Maaløe, Lars; Sønderby, Casper Kaae; Sønderby, Søren Kaae

    Deep generative models based upon continuous variational distributions parameterized by deep networks give state-of-the-art performance. In this paper we propose a framework for extending the latent representation with extra auxiliary variables in order to make the variational distribution more...... expressive for semi-supervised learning. By utilizing the stochasticity of the auxiliary variable we demonstrate how to train discriminative classifiers resulting in state-of-the-art performance within semi-supervised learning exemplified by an 0.96% error on MNIST using 100 labeled data points. Furthermore...

  1. Supervised and Unsupervised Classification for Pattern Recognition Purposes

    Directory of Open Access Journals (Sweden)

    Catalina COCIANU

    2006-01-01

    Full Text Available A cluster analysis task has to identify the grouping trends of data, to decide on the sound clusters as well as to validate somehow the resulted structure. The identification of the grouping tendency existing in a data collection assumes the selection of a framework stated in terms of a mathematical model allowing to express the similarity degree between couples of particular objects, quasi-metrics expressing the similarity between an object an a cluster and between clusters, respectively. In supervised classification, we are provided with a collection of preclassified patterns, and the problem is to label a newly encountered pattern. Typically, the given training patterns are used to learn the descriptions of classes which in turn are used to label a new pattern. The final section of the paper presents a new methodology for supervised learning based on PCA. The classes are represented in the measurement/feature space by a continuous repartitions

  2. Improving head and body pose estimation through semi-supervised manifold alignment

    KAUST Repository

    Heili, Alexandre

    2014-10-27

    In this paper, we explore the use of a semi-supervised manifold alignment method for domain adaptation in the context of human body and head pose estimation in videos. We build upon an existing state-of-the-art system that leverages on external labelled datasets for the body and head features, and on the unlabelled test data with weak velocity labels to do a coupled estimation of the body and head pose. While this previous approach showed promising results, the learning of the underlying manifold structure of the features in the train and target data and the need to align them were not explored despite the fact that the pose features between two datasets may vary according to the scene, e.g. due to different camera point of view or perspective. In this paper, we propose to use a semi-supervised manifold alignment method to bring the train and target samples closer within the resulting embedded space. To this end, we consider an adaptation set from the target data and rely on (weak) labels, given for example by the velocity direction whenever they are reliable. These labels, along with the training labels are used to bias the manifold distance within each manifold and to establish correspondences for alignment.

  3. In vivo MR detection of fluorine-labeled human MSC using the bSSFP sequence.

    Science.gov (United States)

    Ribot, Emeline J; Gaudet, Jeffrey M; Chen, Yuhua; Gilbert, Kyle M; Foster, Paula J

    2014-01-01

    Mesenchymal stem cells (MSC) are used to restore deteriorated cell environments. There is a need to specifically track these cells following transplantation in order to evaluate different methods of implantation, to follow their migration within the body, and to quantify their accumulation at the target. Cellular magnetic resonance imaging (MRI) using fluorine-based nanoemulsions is a great means to detect these transplanted cells in vivo because of the high specificity for fluorine detection and the capability for precise quantification. This technique, however, has low sensitivity, necessitating improvement in MR sequences. To counteract this issue, the balanced steady-state free precession (bSSFP) imaging sequence can be of great interest due to the high signal-to-noise ratio (SNR). Furthermore, it can be applied to obtain 3D images within short acquisition times. In this paper, bSSFP provided accurate quantification of samples of the perfluorocarbon Cell Sense-labeled cells in vitro. Cell Sense was internalized by human MSC (hMSC) without adverse alterations in cell viability or differentiation into adipocytes/osteocytes. The bSSFP sequence was applied in vivo to track and quantify the signals from both Cell Sense-labeled and iron-labeled hMSC after intramuscular implantation. The fluorine signal was observed to decrease faster and more significantly than the volume of iron-associated voids, which points to the advantage of quantifying the fluorine signal and the complexity of quantifying signal loss due to iron.

  4. Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery.

    Science.gov (United States)

    Sigdel, Madhav; Dinç, İmren; Dinç, Semih; Sigdel, Madhu S; Pusey, Marc L; Aygün, Ramazan S

    2014-03-01

    In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training. Secondly, we analyze the performance of Yet Another Two Stage Idea (YATSI) semi-supervised learning using NB, SMO, multilayer perceptron (MLP), J48 and random forest (RF) classifiers. These results are compared with the basic supervised learning using the same training sets. We perform our experiments on a dataset consisting of 2250 protein crystallization images for different proportions of training and test data. Our results indicate that NB and SMO using both self-training and YATSI semi-supervised approaches improve accuracies with respect to supervised learning. On the other hand, MLP, J48 and RF perform better using basic supervised learning. Overall, random forest classifier yields the best accuracy with supervised learning for our dataset.

  5. Supervised versus unsupervised categorization: two sides of the same coin?

    Science.gov (United States)

    Pothos, Emmanuel M; Edwards, Darren J; Perlman, Amotz

    2011-09-01

    Supervised and unsupervised categorization have been studied in separate research traditions. A handful of studies have attempted to explore a possible convergence between the two. The present research builds on these studies, by comparing the unsupervised categorization results of Pothos et al. ( 2011 ; Pothos et al., 2008 ) with the results from two procedures of supervised categorization. In two experiments, we tested 375 participants with nine different stimulus sets and examined the relation between ease of learning of a classification, memory for a classification, and spontaneous preference for a classification. After taking into account the role of the number of category labels (clusters) in supervised learning, we found the three variables to be closely associated with each other. Our results provide encouragement for researchers seeking unified theoretical explanations for supervised and unsupervised categorization, but raise a range of challenging theoretical questions.

  6. Semi-supervised clustering methods.

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as "semi-supervised clustering" methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided.

  7. Instance annotation for multi-instance multi-label learning

    Science.gov (United States)

    F. Briggs; X.Z. Fern; R. Raich; Q. Lou

    2013-01-01

    Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels. For example, an image can be represented as a bag of segments and associated with a list of objects it contains. Prior work on MIML has focused on predicting label sets for previously unseen...

  8. Safe semi-supervised learning based on weighted likelihood.

    Science.gov (United States)

    Kawakita, Masanori; Takeuchi, Jun'ichi

    2014-05-01

    We are interested in developing a safe semi-supervised learning that works in any situation. Semi-supervised learning postulates that n(') unlabeled data are available in addition to n labeled data. However, almost all of the previous semi-supervised methods require additional assumptions (not only unlabeled data) to make improvements on supervised learning. If such assumptions are not met, then the methods possibly perform worse than supervised learning. Sokolovska, Cappé, and Yvon (2008) proposed a semi-supervised method based on a weighted likelihood approach. They proved that this method asymptotically never performs worse than supervised learning (i.e., it is safe) without any assumption. Their method is attractive because it is easy to implement and is potentially general. Moreover, it is deeply related to a certain statistical paradox. However, the method of Sokolovska et al. (2008) assumes a very limited situation, i.e., classification, discrete covariates, n(')→∞ and a maximum likelihood estimator. In this paper, we extend their method by modifying the weight. We prove that our proposal is safe in a significantly wide range of situations as long as n≤n('). Further, we give a geometrical interpretation of the proof of safety through the relationship with the above-mentioned statistical paradox. Finally, we show that the above proposal is asymptotically safe even when n(')

  9. Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules.

    Science.gov (United States)

    Feng, Xinyang; Yang, Jie; Laine, Andrew F; Angelini, Elsa D

    2017-09-01

    Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis. Existing supervised approaches for automated nodule segmentation on CT scans require voxel-based annotations for training, which are labor- and time-consuming to obtain. In this work, we propose a weakly-supervised method that generates accurate voxel-level nodule segmentation trained with image-level labels only. By adapting a convolutional neural network (CNN) trained for image classification, our proposed method learns discriminative regions from the activation maps of convolution units at different scales, and identifies the true nodule location with a novel candidate-screening framework. Experimental results on the public LIDC-IDRI dataset demonstrate that, our weakly-supervised nodule segmentation framework achieves competitive performance compared to a fully-supervised CNN-based segmentation method.

  10. 3' end labelling of RNA with /sup 32/P suitable for rapid gel sequencing

    Energy Technology Data Exchange (ETDEWEB)

    Winter, G; Brownlee, G G [Medical Research Council, Cambridge (UK)

    1978-09-01

    A new general method of labelling the 2', 3'-diol end of RNA with /sup 32/P has been devised suitable for gel sequencing. Poly(A) polymerase (E.coli) is incubated with the RNA and limiting amounts of ..cap alpha..-/sup 32/P-ATP. The mono-addition product is then cleaved with periodate and ..beta..-eliminated with aniline, leaving the RNA terminally labelled with 3'/sup 32/P-phosphate. When applied to a model compound, tRNAsup(Phe) from E. coli, over 28 residues could be read from the 3' end.

  11. Semantic Role Labeling

    CERN Document Server

    Palmer, Martha; Xue, Nianwen

    2011-01-01

    This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applyin

  12. The use of DNase I, buffer gradient gel, and 35S label for DNA sequencing

    International Nuclear Information System (INIS)

    Hong, G.F.

    1987-01-01

    The use of microcentrifuge tubes and mixing of sequencing reactions and brief centrifugation in racks rather than the original capillary tube method has made sequencing reactions relatively simple. Buffer gradient gels and 15 S label are simple means of increasing the rate of sequence analysis; they add little time to that required for determining the sequences of a given number of clones, need no elaborate equipment, and increase the amount of useful data per gel. The standard approach of running 2- and 4-hr gels generates about 300 bases of sequence. The above improvements allow the same number of bases to be read with more confidence from a single 50-cm gel for each clone sequenced due to the changed spacing between sharpened bands

  13. Active semi-supervised learning method with hybrid deep belief networks.

    Science.gov (United States)

    Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

    2014-01-01

    In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

  14. Semi-supervised learning and domain adaptation in natural language processing

    CERN Document Server

    Søgaard, Anders

    2013-01-01

    This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data. One reason for that is data sparsity, i.e., the limited amounts of data we have available in NLP. However, in most real-world NLP applications our labeled data is also heavily biased. This book introduces extensions of supervised learning algorithms to cope with data sparsity and different kinds of sampling bias.This book is intended to be both

  15. Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

    KAUST Repository

    Wang, Jingbin; Zhou, Yihua; Duan, Kanghong; Wang, Jim Jing-Yan; Bensmail, Halima

    2015-01-01

    . In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor

  16. Semi-supervised clustering methods

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

  17. Catalytic center of lecithin:cholesterol acyltransferase: isolation and sequence of diisopropyl fluorophosphate-labeled peptides

    Energy Technology Data Exchange (ETDEWEB)

    Park, Y.B.; Yueksel, U.G.; Gracy, R.W.; Lacko, A.G.

    1987-02-27

    Lecithin:cholesterol acyltransferase (LCAT) was purified from hog plasma and subsequently reacted with (/sup 3/H)-Diisopropyl fluorophosphate (DFP). The labeled enzyme was digested with pepsin and the peptides separated by high performance liquid chromatography (HPLC). Two radioactive peptides were isolated, subjected to automated amino acid sequencing and yielded the following data: A) Ile-Ser-Leu-Gly-Ala-Pro-Trp-Gly-Gly-Ser, and B) Tyr-Ile-Phe-Asp-x-Gly-Phe-Pro-Tyr-x-Asp-Pro-Val. Both of these sequences represent very highly conserved regions of the enzyme when compared to the sequence of human LCAT. Peptide (A) is considered to represent the catalytic center of LCAT based on comparisons with data reported in the literature.

  18. In vivo MR detection of fluorine-labeled human MSC using the bSSFP sequence

    Directory of Open Access Journals (Sweden)

    Ribot EJ

    2014-04-01

    Full Text Available Emeline J Ribot,1 Jeffrey M Gaudet,1,2 Yuhua Chen,1 Kyle M Gilbert,1 Paula J Foster1,2 1Imaging Research Laboratories, Robarts Research Institute, London, ON, Canada; 2Department of Medical Biophysics, University of Western Ontario, London, ON, Canada Abstract: Mesenchymal stem cells (MSC are used to restore deteriorated cell environments. There is a need to specifically track these cells following transplantation in order to evaluate different methods of implantation, to follow their migration within the body, and to quantify their accumulation at the target. Cellular magnetic resonance imaging (MRI using fluorine-based nanoemulsions is a great means to detect these transplanted cells in vivo because of the high specificity for fluorine detection and the capability for precise quantification. This technique, however, has low sensitivity, necessitating improvement in MR sequences. To counteract this issue, the balanced steady-state free precession (bSSFP imaging sequence can be of great interest due to the high signal-to-noise ratio (SNR. Furthermore, it can be applied to obtain 3D images within short acquisition times. In this paper, bSSFP provided accurate quantification of samples of the perfluorocarbon Cell Sense-labeled cells in vitro. Cell Sense was internalized by human MSC (hMSC without adverse alterations in cell viability or differentiation into adipocytes/osteocytes. The bSSFP sequence was applied in vivo to track and quantify the signals from both Cell Sense-labeled and iron-labeled hMSC after intramuscular implantation. The fluorine signal was observed to decrease faster and more significantly than the volume of iron-associated voids, which points to the advantage of quantifying the fluorine signal and the complexity of quantifying signal loss due to iron. Keywords: bSSFP, fluorine MRI, mesenchymal stem cell, mouse, cell tracking

  19. Sequence- and structure-dependent DNA base dynamics: Synthesis, structure, and dynamics of site and sequence specifically spin-labeled DNA

    International Nuclear Information System (INIS)

    Spaltenstein, A.; Robinson, B.H.; Hopkins, P.B.

    1989-01-01

    A nitroxide spin-labeled analogue of thymidine (1a), in which the methyl group is replaced by an acetylene-tethered nitroxide, was evaluated as a probe for structural and dynamics studies of sequence specifically spin-labeled DNA. Residue 1a was incorporated into synthetic deoxyoligonucleotides by using automated phosphite triester methods. 1 H NMR, CD, and thermal denaturation studies indicate that 1a (T) does not significantly alter the structure of 5'-d(CGCGAATT*CGCG) from that of the native dodecamer. EPR studies on monomer, single-stranded, and duplexed DNA show that 1a readily distinguishes environments of different rigidity. Comparison of the general line-shape features of the observed EPR spectra of several small duplexes (12-mer, 24-mer) with simulated EPR spectra assuming isotropic motion suggests that probe 1a monitors global tumbling of small duplexes. Increasing the length of the DNA oligomers results in significant deviation from isotropic motion, with line-shape features similar to those of calculated spectra of objects with isotropic rotational correlation times of 20-100 ns. EPR spectra of a spin-labeled GT mismatch and a T bulge in long DNAs are distinct from those of spin-labeled Watson-Crick paired DNAs, further demonstrating the value of EPR as a tool in the evaluation of local dynamic and structural features in macromolecules

  20. Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition

    KAUST Repository

    Alghamdi, Masheal M.

    2014-05-01

    Face recognition is a challenging problem in computer vision. Difficulties such as slight differences between similar faces of different people, changes in facial expressions, light and illumination condition, and pose variations add extra complications to the face recognition research. Many algorithms are devoted to solving the face recognition problem, among which the family of nonnegative matrix factorization (NMF) algorithms has been widely used as a compact data representation method. Different versions of NMF have been proposed. Wang et al. proposed the graph-based semi-supervised nonnegative learning (S2N2L) algorithm that uses labeled data in constructing intrinsic and penalty graph to enforce separability of labeled data, which leads to a greater discriminating power. Moreover the geometrical structure of labeled and unlabeled data is preserved through using the smoothness assumption by creating a similarity graph that conserves the neighboring information for all labeled and unlabeled data. However, S2N2L is sensitive to light changes, illumination, and partial occlusion. In this thesis, we propose a Semi-Supervised Half-Quadratic NMF (SSHQNMF) algorithm that combines the benefits of S2N2L and the robust NMF by the half- quadratic minimization (HQNMF) algorithm.Our algorithm improves upon the S2N2L algorithm by replacing the Frobenius norm with a robust M-Estimator loss function. A multiplicative update solution for our SSHQNMF algorithmis driven using the half- 4 quadratic (HQ) theory. Extensive experiments on ORL, Yale-A and a subset of the PIE data sets for nine M-estimator loss functions for both SSHQNMF and HQNMF algorithms are investigated, and compared with several state-of-the-art supervised and unsupervised algorithms, along with the original S2N2L algorithm in the context of classification, clustering, and robustness against partial occlusion. The proposed algorithm outperformed the other algorithms. Furthermore, SSHQNMF with Maximum Correntropy

  1. Sequences of 12 monoclonal anti-dinitrophenyl spin-label antibodies for NMR studies

    International Nuclear Information System (INIS)

    Leahy, D.J.; Rule, G.S.; Whittaker, M.M.; McConnell, H.M.

    1988-01-01

    Eleven monoclonal antibodies specific for a spin-labeled dinitrophenyl hapten (DNP-SL) have been produces for use in NMR studies. They have been named AN01 and ANO3-AN12. The stability constants for the association of these antibodies with DNP-SL and related haptens were measured by fluorescence quenching. cDNA clones coding for the heavy and light chains of each antibody and of an additional anti-DNP-SL monoclonal antibody, ANO2, have been isolated. The nucleic acid sequence of the 5' end of each clone has been determined, and the amino acid sequence of the variable regions of each antibody has been deduced from the cDNA sequence. The sequences are relatively heterogeneous, but both the heavy and the light chains of ANO1 and ANO3 are derived from the same variable-region gene families as those of the ANO2 antibody. ANO7 has a heavy chain that is related to that of ANO2, and ANO9 has a related light chain. ANO5 and ANO6 are unrelated to ANO2 but share virtually identical heavy and light chains. Preliminary NMR difference spectra comparing related antibodies show that sequence-specific assignment of resonances is possible. Such spectra also provide a measure of structural relatedness

  2. Study on multiple-hops performance of MOOC sequences-based optical labels for OPS networks

    Science.gov (United States)

    Zhang, Chongfu; Qiu, Kun; Ma, Chunli

    2009-11-01

    In this paper, we utilize a new study method that is under independent case of multiple optical orthogonal codes to derive the probability function of MOOCS-OPS networks, discuss the performance characteristics for a variety of parameters, and compare some characteristics of the system employed by single optical orthogonal code or multiple optical orthogonal codes sequences-based optical labels. The performance of the system is also calculated, and our results verify that the method is effective. Additionally it is found that performance of MOOCS-OPS networks would, negatively, be worsened, compared with single optical orthogonal code-based optical label for optical packet switching (SOOC-OPS); however, MOOCS-OPS networks can greatly enlarge the scalability of optical packet switching networks.

  3. Self-supervised Chinese ontology learning from online encyclopedias.

    Science.gov (United States)

    Hu, Fanghuai; Shao, Zhiqing; Ruan, Tong

    2014-01-01

    Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO.

  4. Distant Supervision for Relation Extraction with Ranking-Based Methods

    Directory of Open Access Journals (Sweden)

    Yang Xiang

    2016-05-01

    Full Text Available Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion. However, distant supervision is still greatly limited by the quality of training data, due to its natural motivation for greatly reducing the heavy cost of data annotation. In this paper, we construct an architecture called MIML-sort (Multi-instance Multi-label Learning with Sorting Strategies, which is built on the famous MIML framework. Based on MIML-sort, we propose three ranking-based methods for sample selection with which we identify relation extractors from a subset of the training data. Experiments are set up on the KBP (Knowledge Base Propagation corpus, one of the benchmark datasets for distant supervision, which is large and noisy. Compared with previous work, the proposed methods produce considerably better results. Furthermore, the three methods together achieve the best F1 on the official testing set, with an optimal enhancement of F1 from 27.3% to 29.98%.

  5. Information-theoretic semi-supervised metric learning via entropy regularization.

    Science.gov (United States)

    Niu, Gang; Dai, Bo; Yamada, Makoto; Sugiyama, Masashi

    2014-08-01

    We propose a general information-theoretic approach to semi-supervised metric learning called SERAPH (SEmi-supervised metRic leArning Paradigm with Hypersparsity) that does not rely on the manifold assumption. Given the probability parameterized by a Mahalanobis distance, we maximize its entropy on labeled data and minimize its entropy on unlabeled data following entropy regularization. For metric learning, entropy regularization improves manifold regularization by considering the dissimilarity information of unlabeled data in the unsupervised part, and hence it allows the supervised and unsupervised parts to be integrated in a natural and meaningful way. Moreover, we regularize SERAPH by trace-norm regularization to encourage low-dimensional projections associated with the distance metric. The nonconvex optimization problem of SERAPH could be solved efficiently and stably by either a gradient projection algorithm or an EM-like iterative algorithm whose M-step is convex. Experiments demonstrate that SERAPH compares favorably with many well-known metric learning methods, and the learned Mahalanobis distance possesses high discriminability even under noisy environments.

  6. SSC-EKE: Semi-Supervised Classification with Extensive Knowledge Exploitation.

    Science.gov (United States)

    Qian, Pengjiang; Xi, Chen; Xu, Min; Jiang, Yizhang; Su, Kuan-Hao; Wang, Shitong; Muzic, Raymond F

    2018-01-01

    We introduce a new, semi-supervised classification method that extensively exploits knowledge. The method has three steps. First, the manifold regularization mechanism, adapted from the Laplacian support vector machine (LapSVM), is adopted to mine the manifold structure embedded in all training data, especially in numerous label-unknown data. Meanwhile, by converting the labels into pairwise constraints, the pairwise constraint regularization formula (PCRF) is designed to compensate for the few but valuable labelled data. Second, by further combining the PCRF with the manifold regularization, the precise manifold and pairwise constraint jointly regularized formula (MPCJRF) is achieved. Third, by incorporating the MPCJRF into the framework of the conventional SVM, our approach, referred to as semi-supervised classification with extensive knowledge exploitation (SSC-EKE), is developed. The significance of our research is fourfold: 1) The MPCJRF is an underlying adjustment, with respect to the pairwise constraints, to the graph Laplacian enlisted for approximating the potential data manifold. This type of adjustment plays the correction role, as an unbiased estimation of the data manifold is difficult to obtain, whereas the pairwise constraints, converted from the given labels, have an overall high confidence level. 2) By transforming the values of the two terms in the MPCJRF such that they have the same range, with a trade-off factor varying within the invariant interval [0, 1), the appropriate impact of the pairwise constraints to the graph Laplacian can be self-adaptively determined. 3) The implication regarding extensive knowledge exploitation is embodied in SSC-EKE. That is, the labelled examples are used not only to control the empirical risk but also to constitute the MPCJRF. Moreover, all data, both labelled and unlabelled, are recruited for the model smoothness and manifold regularization. 4) The complete framework of SSC-EKE organically incorporates multiple

  7. Computerized breast cancer analysis system using three stage semi-supervised learning method.

    Science.gov (United States)

    Sun, Wenqing; Tseng, Tzu-Liang Bill; Zhang, Jianying; Qian, Wei

    2016-10-01

    A large number of labeled medical image data is usually a requirement to train a well-performed computer-aided detection (CAD) system. But the process of data labeling is time consuming, and potential ethical and logistical problems may also present complications. As a result, incorporating unlabeled data into CAD system can be a feasible way to combat these obstacles. In this study we developed a three stage semi-supervised learning (SSL) scheme that combines a small amount of labeled data and larger amount of unlabeled data. The scheme was modified on our existing CAD system using the following three stages: data weighing, feature selection, and newly proposed dividing co-training data labeling algorithm. Global density asymmetry features were incorporated to the feature pool to reduce the false positive rate. Area under the curve (AUC) and accuracy were computed using 10 fold cross validation method to evaluate the performance of our CAD system. The image dataset includes mammograms from 400 women who underwent routine screening examinations, and each pair contains either two cranio-caudal (CC) or two mediolateral-oblique (MLO) view mammograms from the right and the left breasts. From these mammograms 512 regions were extracted and used in this study, and among them 90 regions were treated as labeled while the rest were treated as unlabeled. Using our proposed scheme, the highest AUC observed in our research was 0.841, which included the 90 labeled data and all the unlabeled data. It was 7.4% higher than using labeled data only. With the increasing amount of labeled data, AUC difference between using mixed data and using labeled data only reached its peak when the amount of labeled data was around 60. This study demonstrated that our proposed three stage semi-supervised learning can improve the CAD performance by incorporating unlabeled data. Using unlabeled data is promising in computerized cancer research and may have a significant impact for future CAD system

  8. Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD.

    Science.gov (United States)

    Cao, Peng; Liu, Xiaoli; Bao, Hang; Yang, Jinzhu; Zhao, Dazhe

    2015-01-01

    The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these challenges, we propose oversampling and semi-supervised learning methods based on the restricted Boltzmann machines (RBMs) to solve the classification of imbalanced data with a few labeled samples. To evaluate the proposed method, we conducted a comprehensive performance study and compared its results with the commonly used techniques. Experiments on benchmark dataset of DDSM demonstrate the effectiveness of the RBMs based oversampling and semi-supervised learning method in terms of geometric mean (G-mean) for false positive reduction in Breast CAD.

  9. Co-Labeling for Multi-View Weakly Labeled Learning.

    Science.gov (United States)

    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

  10. Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Ghodsi, Ali; Clemmensen, Line H.

    2017-01-01

    Principal component analysis (PCA) is one of the main unsupervised pre-processing methods for dimension reduction. When the training labels are available, it is worth using a supervised PCA strategy. In cases that both dimension reduction and variable selection are required, sparse PCA (SPCA...

  11. Supervised Machine Learning for Population Genetics: A New Paradigm

    Science.gov (United States)

    Schrider, Daniel R.; Kern, Andrew D.

    2018-01-01

    As population genomic datasets grow in size, researchers are faced with the daunting task of making sense of a flood of information. To keep pace with this explosion of data, computational methodologies for population genetic inference are rapidly being developed to best utilize genomic sequence data. In this review we discuss a new paradigm that has emerged in computational population genomics: that of supervised machine learning (ML). We review the fundamentals of ML, discuss recent applications of supervised ML to population genetics that outperform competing methods, and describe promising future directions in this area. Ultimately, we argue that supervised ML is an important and underutilized tool that has considerable potential for the world of evolutionary genomics. PMID:29331490

  12. Predicting human activities in sequences of actions in RGB-D videos

    Science.gov (United States)

    Jardim, David; Nunes, Luís.; Dias, Miguel

    2017-03-01

    In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

  13. Toward Determination of Venous Thrombosis Ages by Using Fuzzy Logic and Supervised Bayes Classification

    National Research Council Canada - National Science Library

    Lim, P

    2001-01-01

    .... Thus, the proposed learning base is constructed in a 3-tuple: observation, label, membership value in term of fuzzy logic for each class and not a 2-tuple as in the usual supervised Bayes classification application...

  14. The validation of the Supervision of Thesis Questionnaire (STQ).

    Science.gov (United States)

    Henricson, Maria; Fridlund, Bengt; Mårtensson, Jan; Hedberg, Berith

    2018-06-01

    The supervision process is characterized by differences between the supervisors' and the students' expectations before the start of writing a bachelor thesis as well as after its completion. A review of the literature did not reveal any scientifically tested questionnaire for evaluating nursing students' expectations of the supervision process when writing a bachelor thesis. The aim of the study was to determine the construct validity and internal consistency reliability of a questionnaire for measuring nursing students' expectations of the bachelor thesis supervision process. The study had a developmental and methodological design carried out in four steps including construct validity and internal consistency reliability statistical procedures: construction of the items, assessment of face validity, data collection and data analysis. This study was conducted at a university in southern Sweden, where students on the "Nursing student thesis, 15 ECTS" course were consecutively selected for participation. Of the 512 questionnaires distributed, 327 were returned, a response rate of 64%. Five factors with a total variance of 74% and good communalities, ≥0.64, were extracted from the 10-item STQ. The internal consistency of the 10 items was 0.68. The five factors were labelled: The nature of the supervision process, The supervisor's role as a coach, The students' progression to self-support, The interaction between students and supervisor and supervisor competence. A didactic, useful and secure questionnaire measuring nursing students' expectations of the bachelor thesis supervision process based on three main forms of supervision was created. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Transfer learning improves supervised image segmentation across imaging protocols

    DEFF Research Database (Denmark)

    van Opbroek, Annegreet; Ikram, M. Arfan; Vernooij, Meike W.

    2015-01-01

    with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two MRI brain-segmentation tasks with multi-site data: white matter, gray matter, and CSF segmentation; and white-matter- /MS-lesion segmentation......The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform...... well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore...

  16. Java graphical user interface for the supervision of Tore Supra

    International Nuclear Information System (INIS)

    Utzel, Nadine; Guillerminet, Bernard; Leluyer, Mireille; Moulin, Daniele

    2002-01-01

    The graphical user interface (GUI) for the supervision of Tore Supra is intended to supervise the start-up and the shut-down of the installation, to control general state (state of all diagnostics, state of the system and network) and to follow the pulse sequence. Implementation of a new multi-platform, modular GUI for Tore Supra is in progress. This provides not only a simpler, more structured view for the non-specialist user, but also is open-ended and adaptable to a wide variety of uses. The actual implementation of a GUI is a question of user-ergonomics. Hence, a user-directed study in 2000 produced a specification for the interface. The information is treated with a hierarchical order. At the top level, only the global state of the supervised elements appears, i.e. the general state of every diagnostics, the pulse sequence, the safety systems. If a problem occurs, the operator has access to the lower level detailed state of the concerned element, simply with a double-click. An event log also helps the operator to analyse the chronology of the alarms arising during the pulse. Although the GUI is mainly used in the control room on X terminals under Unix, it should also be accessible via a portable PC for the purpose of maintenance, or directly from any office to see how the physics program is progressing. The choice of Java, multi-platform object programming language was thus adopted with access via any web browser. The modularity of the GUI is made possible by a distributed architecture (remote method invocation) between the graphic client and different servers: one for the diagnostics and the sequence, one for the system and the network and one for the configuration database. All the components interact with each other in a very simple and standard way. This distributed architecture allows the progressive set up of the new interface. The first step, being produced for mid-2001 is the GUI for the supervision of diagnostics. This prototype will help us to

  17. Java graphical user interface for the supervision of Tore Supra

    Energy Technology Data Exchange (ETDEWEB)

    Utzel, Nadine E-mail: nutzel@cea.fr; Guillerminet, Bernard; Leluyer, Mireille; Moulin, Daniele

    2002-06-01

    The graphical user interface (GUI) for the supervision of Tore Supra is intended to supervise the start-up and the shut-down of the installation, to control general state (state of all diagnostics, state of the system and network) and to follow the pulse sequence. Implementation of a new multi-platform, modular GUI for Tore Supra is in progress. This provides not only a simpler, more structured view for the non-specialist user, but also is open-ended and adaptable to a wide variety of uses. The actual implementation of a GUI is a question of user-ergonomics. Hence, a user-directed study in 2000 produced a specification for the interface. The information is treated with a hierarchical order. At the top level, only the global state of the supervised elements appears, i.e. the general state of every diagnostics, the pulse sequence, the safety systems. If a problem occurs, the operator has access to the lower level detailed state of the concerned element, simply with a double-click. An event log also helps the operator to analyse the chronology of the alarms arising during the pulse. Although the GUI is mainly used in the control room on X terminals under Unix, it should also be accessible via a portable PC for the purpose of maintenance, or directly from any office to see how the physics program is progressing. The choice of Java, multi-platform object programming language was thus adopted with access via any web browser. The modularity of the GUI is made possible by a distributed architecture (remote method invocation) between the graphic client and different servers: one for the diagnostics and the sequence, one for the system and the network and one for the configuration database. All the components interact with each other in a very simple and standard way. This distributed architecture allows the progressive set up of the new interface. The first step, being produced for mid-2001 is the GUI for the supervision of diagnostics. This prototype will help us to

  18. A Supervised Machine Learning Study of Online Discussion Forums about Type-2 Diabetes

    DEFF Research Database (Denmark)

    Reichert, Jonathan-Raphael; Kristensen, Klaus Langholz; Mukkamala, Raghava Rao

    2017-01-01

    supervised machine learning techniques to analyze the online conversations. In order to analyse these online textual conversations, we have chosen four domain specific models (Emotions, Sentiment, Personality Traits and Patient Journey). As part of text classification, we employed the ensemble learning...... method by using 5 different supervised machine learning algorithms to build a set of text classifiers by using the voting method to predict most probable label for a given textual conversation from the online discussion forums. Our findings show that there is a high amount of trust expressed by a subset...

  19. Transfer learning improves supervised image segmentation across imaging protocols.

    Science.gov (United States)

    van Opbroek, Annegreet; Ikram, M Arfan; Vernooij, Meike W; de Bruijne, Marleen

    2015-05-01

    The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

  20. A hierarchical scheme for geodesic anatomical labeling of airway trees

    DEFF Research Database (Denmark)

    Feragen, Aasa; Petersen, Jens; Owen, Megan

    2012-01-01

    We present a fast and robust supervised algorithm for label- ing anatomical airway trees, based on geodesic distances in a geometric tree-space. Possible branch label configurations for a given unlabeled air- way tree are evaluated based on the distances to a training set of labeled airway trees....... In tree-space, the airway tree topology and geometry change continuously, giving a natural way to automatically handle anatomical differences and noise. The algorithm is made efficient using a hierarchical approach, in which labels are assigned from the top down. We only use features of the airway...

  1. Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

    Science.gov (United States)

    Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

    2017-12-01

    Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

  2. Nonparametric Mixture Models for Supervised Image Parcellation.

    Science.gov (United States)

    Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina

    2009-09-01

    We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

  3. Integrating the Supervised Information into Unsupervised Learning

    Directory of Open Access Journals (Sweden)

    Ping Ling

    2013-01-01

    Full Text Available This paper presents an assembling unsupervised learning framework that adopts the information coming from the supervised learning process and gives the corresponding implementation algorithm. The algorithm consists of two phases: extracting and clustering data representatives (DRs firstly to obtain labeled training data and then classifying non-DRs based on labeled DRs. The implementation algorithm is called SDSN since it employs the tuning-scaled Support vector domain description to collect DRs, uses spectrum-based method to cluster DRs, and adopts the nearest neighbor classifier to label non-DRs. The validation of the clustering procedure of the first-phase is analyzed theoretically. A new metric is defined data dependently in the second phase to allow the nearest neighbor classifier to work with the informed information. A fast training approach for DRs’ extraction is provided to bring more efficiency. Experimental results on synthetic and real datasets verify that the proposed idea is of correctness and performance and SDSN exhibits higher popularity in practice over the traditional pure clustering procedure.

  4. Pervasive Sound Sensing: A Weakly Supervised Training Approach.

    Science.gov (United States)

    Kelly, Daniel; Caulfield, Brian

    2016-01-01

    Modern smartphones present an ideal device for pervasive sensing of human behavior. Microphones have the potential to reveal key information about a person's behavior. However, they have been utilized to a significantly lesser extent than other smartphone sensors in the context of human behavior sensing. We postulate that, in order for microphones to be useful in behavior sensing applications, the analysis techniques must be flexible and allow easy modification of the types of sounds to be sensed. A simplification of the training data collection process could allow a more flexible sound classification framework. We hypothesize that detailed training, a prerequisite for the majority of sound sensing techniques, is not necessary and that a significantly less detailed and time consuming data collection process can be carried out, allowing even a nonexpert to conduct the collection, labeling, and training process. To test this hypothesis, we implement a diverse density-based multiple instance learning framework, to identify a target sound, and a bag trimming algorithm, which, using the target sound, automatically segments weakly labeled sound clips to construct an accurate training set. Experiments reveal that our hypothesis is a valid one and results show that classifiers, trained using the automatically segmented training sets, were able to accurately classify unseen sound samples with accuracies comparable to supervised classifiers, achieving an average F -measure of 0.969 and 0.87 for two weakly supervised datasets.

  5. 9 CFR 317.1 - Labels required; supervision by Program employee.

    Science.gov (United States)

    2010-01-01

    ..., DEPARTMENT OF AGRICULTURE AGENCY ORGANIZATION AND TERMINOLOGY; MANDATORY MEAT AND POULTRY PRODUCTS INSPECTION... to bear such a label. (1) Wrappings of dressed carcasses and primal parts in an unprocessed state...

  6. Semi-Supervised Generation with Cluster-aware Generative Models

    DEFF Research Database (Denmark)

    Maaløe, Lars; Fraccaro, Marco; Winther, Ole

    2017-01-01

    Deep generative models trained with large amounts of unlabelled data have proven to be powerful within the domain of unsupervised learning. Many real life data sets contain a small amount of labelled data points, that are typically disregarded when training generative models. We propose the Clust...... a log-likelihood of −79.38 nats on permutation invariant MNIST, while also achieving competitive semi-supervised classification accuracies. The model can also be trained fully unsupervised, and still improve the log-likelihood performance with respect to related methods.......Deep generative models trained with large amounts of unlabelled data have proven to be powerful within the domain of unsupervised learning. Many real life data sets contain a small amount of labelled data points, that are typically disregarded when training generative models. We propose the Cluster...

  7. Semi-supervised eigenvectors for large-scale locally-biased learning

    DEFF Research Database (Denmark)

    Hansen, Toke Jansen; Mahoney, Michael W.

    2014-01-01

    improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph......In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks nearby that prespecified target region. For example, one might......-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing...

  8. Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments

    Science.gov (United States)

    Han, Wenjing; Coutinho, Eduardo; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

    2016-01-01

    Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances. PMID:27627768

  9. Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

    Science.gov (United States)

    Han, Wenjing; Coutinho, Eduardo; Ruan, Huabin; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

    2016-01-01

    Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances.

  10. An immune-inspired semi-supervised algorithm for breast cancer diagnosis.

    Science.gov (United States)

    Peng, Lingxi; Chen, Wenbin; Zhou, Wubai; Li, Fufang; Yang, Jin; Zhang, Jiandong

    2016-10-01

    Breast cancer is the most frequently and world widely diagnosed life-threatening cancer, which is the leading cause of cancer death among women. Early accurate diagnosis can be a big plus in treating breast cancer. Researchers have approached this problem using various data mining and machine learning techniques such as support vector machine, artificial neural network, etc. The computer immunology is also an intelligent method inspired by biological immune system, which has been successfully applied in pattern recognition, combination optimization, machine learning, etc. However, most of these diagnosis methods belong to a supervised diagnosis method. It is very expensive to obtain labeled data in biology and medicine. In this paper, we seamlessly integrate the state-of-the-art research on life science with artificial intelligence, and propose a semi-supervised learning algorithm to reduce the need for labeled data. We use two well-known benchmark breast cancer datasets in our study, which are acquired from the UCI machine learning repository. Extensive experiments are conducted and evaluated on those two datasets. Our experimental results demonstrate the effectiveness and efficiency of our proposed algorithm, which proves that our algorithm is a promising automatic diagnosis method for breast cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

    Science.gov (United States)

    Yamazaki, Keisuke

    2015-09-01

    Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation process, respectively. Unsupervised learning tasks, such as cluster analysis, are regarded as estimations of latent variables based on the observable ones. The estimation of latent variables in semi-supervised learning, where some labels are observed, will be more precise than that in unsupervised, and one of the concerns is to clarify the effect of the labeled data. However, there has not been sufficient theoretical analysis of the accuracy of the estimation of latent variables. In a previous study, a distribution-based error function was formulated, and its asymptotic form was calculated for unsupervised learning with generative models. It has been shown that, for the estimation of latent variables, the Bayes method is more accurate than the maximum-likelihood method. The present paper reveals the asymptotic forms of the error function in Bayesian semi-supervised learning for both discriminative and generative models. The results show that the generative model, which uses all of the given data, performs better when the model is well specified. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Magnetic bead purification of labeled DNA fragments forhigh-throughput capillary electrophoresis sequencing

    Energy Technology Data Exchange (ETDEWEB)

    Elkin, Christopher; Kapur, Hitesh; Smith, Troy; Humphries, David; Pollard, Martin; Hammon, Nancy; Hawkins, Trevor

    2001-09-15

    We have developed an automated purification method for terminator sequencing products based on a magnetic bead technology. This 384-well protocol generates labeled DNA fragments that are essentially free of contaminates for less than $0.005 per reaction. In comparison to laborious ethanol precipitation protocols, this method increases the phred20 read length by forty bases with various DNA templates such as PCR fragments, Plasmids, Cosmids and RCA products. Our method eliminates centrifugation and is compatible with both the MegaBACE 1000 and ABIPrism 3700 capillary instruments. As of September 2001, this method has produced over 1.6 million samples with 93 percent averaging 620 phred20 bases as part of Joint Genome Institutes Production Process.

  13. Effectiveness of Group Supervision versus Combined Group and Individual Supervision.

    Science.gov (United States)

    Ray, Dee; Altekruse, Michael

    2000-01-01

    Investigates the effectiveness of different types of supervision (large group, small group, combined group, individual supervision) with counseling students (N=64). Analyses revealed that all supervision formats resulted in similar progress in counselor effectiveness and counselor development. Participants voiced a preference for individual…

  14. Kollegial supervision

    DEFF Research Database (Denmark)

    Andersen, Ole Dibbern; Petersson, Erling

    Publikationen belyser, hvordan kollegial supervision i en kan organiseres i en uddannelsesinstitution......Publikationen belyser, hvordan kollegial supervision i en kan organiseres i en uddannelsesinstitution...

  15. Learning Supervised Topic Models for Classification and Regression from Crowds.

    Science.gov (United States)

    Rodrigues, Filipe; Lourenco, Mariana; Ribeiro, Bernardete; Pereira, Francisco C

    2017-12-01

    The growing need to analyze large collections of documents has led to great developments in topic modeling. Since documents are frequently associated with other related variables, such as labels or ratings, much interest has been placed on supervised topic models. However, the nature of most annotation tasks, prone to ambiguity and noise, often with high volumes of documents, deem learning under a single-annotator assumption unrealistic or unpractical for most real-world applications. In this article, we propose two supervised topic models, one for classification and another for regression problems, which account for the heterogeneity and biases among different annotators that are encountered in practice when learning from crowds. We develop an efficient stochastic variational inference algorithm that is able to scale to very large datasets, and we empirically demonstrate the advantages of the proposed model over state-of-the-art approaches.

  16. Observation versus classification in supervised category learning.

    Science.gov (United States)

    Levering, Kimery R; Kurtz, Kenneth J

    2015-02-01

    The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

  17. Out-of-Sample Generalizations for Supervised Manifold Learning for Classification.

    Science.gov (United States)

    Vural, Elif; Guillemot, Christine

    2016-03-01

    Supervised manifold learning methods for data classification map high-dimensional data samples to a lower dimensional domain in a structure-preserving way while increasing the separation between different classes. Most manifold learning methods compute the embedding only of the initially available data; however, the generalization of the embedding to novel points, i.e., the out-of-sample extension problem, becomes especially important in classification applications. In this paper, we propose a semi-supervised method for building an interpolation function that provides an out-of-sample extension for general supervised manifold learning algorithms studied in the context of classification. The proposed algorithm computes a radial basis function interpolator that minimizes an objective function consisting of the total embedding error of unlabeled test samples, defined as their distance to the embeddings of the manifolds of their own class, as well as a regularization term that controls the smoothness of the interpolation function in a direction-dependent way. The class labels of test data and the interpolation function parameters are estimated jointly with an iterative process. Experimental results on face and object images demonstrate the potential of the proposed out-of-sample extension algorithm for the classification of manifold-modeled data sets.

  18. Legislation and supervision

    International Nuclear Information System (INIS)

    1998-01-01

    In this part next aspects are described: (1) Legislative and supervision-related framework (reviews of structure of supervisory bodies; legislation; state supervision in the nuclear safety area, and state supervision in the area of health protection against radiation are given); (2) Operator's responsibility

  19. Supervised Learning for Dynamical System Learning.

    Science.gov (United States)

    Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

    2015-01-01

    Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

  20. Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

    KAUST Repository

    Wang, Jingbin

    2015-10-09

    In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of data, i.e., An image and a text. Cross-modal factor analysis (CFA) has been proposed to project the two different modals of data to a shared data space, so that the classification of a image or a text can be performed directly in this space. A disadvantage of CFA is that it has ignored the supervision information. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor in the shared space to use the class label information. The factor analysis parameter and the predictor parameter are learned jointly by solving one single objective function. With this objective function, we minimize the distance between the projections of image and text of the same document, and the classification error of the projection measured by hinge loss function. The objective function is optimized by an alternate optimization strategy in an iterative algorithm. Experiments in two different multiple modal document data sets show the advantage of the proposed algorithm over other CFA methods.

  1. Collective academic supervision

    DEFF Research Database (Denmark)

    Nordentoft, Helle Merete; Thomsen, Rie; Wichmann-Hansen, Gitte

    2013-01-01

    Supervision of students is a core activity in higher education. Previous research on student supervision in higher education focus on individual and relational aspects in the supervisory relationship rather than collective, pedagogical and methodical aspects of the planning of the supervision...... process. This article fills these gaps by discussing potentials and challenges in “Collective Academic Supervision”, a model for supervision at the Master of Education in Guidance at Aarhus University in Denmark. The pedagogical rationale behind the model is that students’ participation and learning...

  2. Social constructionism and supervision: experiences of AAMFT supervisors and supervised therapists.

    Science.gov (United States)

    Hair, Heather J; Fine, Marshall

    2012-10-01

    A phenomenological research process was used to investigate the supervision experience for supervisors and therapists when supervisors use a social constructionist perspective. Participants of the one-to-one interviews were six AAMFT Approved Supervisors and six therapists providing counseling to individuals, couples and families. The findings suggest supervisors were committed to their self-identified supervision philosophy and intentionally sought out congruence between epistemology and practice. The shared experience of therapists indicates they associated desirable supervision experiences with their supervisors' social constructionist perspective. Our findings also indicated that supervisors' and therapists' understanding of social constructionism included the more controversial concepts of agency and extra-discursiveness. This research has taken an empirical step in the direction of understanding what the social constructionist supervision experience is like for supervisors and therapists. Our findings suggest a linkage between epistemology and supervision practice and a satisfaction with the supervision process. © 2012 American Association for Marriage and Family Therapy.

  3. Security system signal supervision

    International Nuclear Information System (INIS)

    Chritton, M.R.; Matter, J.C.

    1991-09-01

    This purpose of this NUREG is to present technical information that should be useful to NRC licensees for understanding and applying line supervision techniques to security communication links. A review of security communication links is followed by detailed discussions of link physical protection and DC/AC static supervision and dynamic supervision techniques. Material is also presented on security for atmospheric transmission and video line supervision. A glossary of security communication line supervision terms is appended. 16 figs

  4. Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

    Science.gov (United States)

    Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

    2018-01-01

    The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

  5. Man-machine supervision; Supervision homme-machine

    Energy Technology Data Exchange (ETDEWEB)

    Montmain, J. [CEA Valrho, Dir. de l' Energie Nucleaire (DEN), 30 - Marcoule (France)

    2005-05-01

    Today's complexity of systems where man is involved has led to the development of more and more sophisticated information processing systems where decision making has become more and more difficult. The operator task has moved from operation to supervision and the production tool has become indissociable from its numerical instrumentation and control system. The integration of more and more numerous and sophisticated control indicators in the control room does not necessary fulfill the expectations of the operation team. It is preferable to develop cooperative information systems which are real situation understanding aids. The stake is not the automation of operators' cognitive tasks but the supply of a reasoning help. One of the challenges of interactive information systems is the selection, organisation and dynamical display of information. The efficiency of the whole man-machine system depends on the communication interface efficiency. This article presents the principles and specificities of man-machine supervision systems: 1 - principle: operator's role in control room, operator and automation, monitoring and diagnosis, characteristics of useful models for supervision; 2 - qualitative reasoning: origin, trends, evolutions; 3 - causal reasoning: causality, causal graph representation, causal and diagnostic graph; 4 - multi-points of view reasoning: multi flow modeling method, Sagace method; 5 - approximate reasoning: the symbolic numerical interface, the multi-criteria decision; 6 - example of application: supervision in a spent-fuel reprocessing facility. (J.S.)

  6. Electrochemical direct immobilization of DNA sequences for label-free herpes virus detection

    Science.gov (United States)

    Tam, Phuong Dinh; Trung, Tran; Tuan, Mai Anh; Chien, Nguyen Duc

    2009-09-01

    DNA sequences/bio-macromolecules of herpes virus (5'-AT CAC CGA CCC GGA GAG GGA C-3') were directly immobilized into polypyrrole matrix by using the cyclic voltammetry method, and grafted onto arrays of interdigitated platinum microelectrodes. The morphology surface of the obtained PPy/DNA of herpes virus composite films was investigated by a FESEM Hitachi-S 4800. Fourier transform infrared spectroscopy (FTIR) was used to characterize the PPy/DNA film and to study the specific interactions that may exist between DNA biomacromolecules and PPy chains. Attempts are made to use these PPy/DNA composite films for label-free herpes virus detection revealed a response time of 60 s in solutions containing as low as 2 nM DNA concentration, and self life of six months when immerged in double distilled water and kept refrigerated.

  7. Electrochemical direct immobilization of DNA sequences for label-free herpes virus detection

    International Nuclear Information System (INIS)

    Phuong Dinh Tam; Mai Anh Tuan; Tran Trung; Nguyen Duc Chien

    2009-01-01

    DNA sequences/bio-macromolecules of herpes virus (5'-AT CAC CGA CCC GGA GAG GGA C-3') were directly immobilized into polypyrrole matrix by using the cyclic voltammetry method, and grafted onto arrays of interdigitated platinum microelectrodes. The morphology surface of the obtained PPy/DNA of herpes virus composite films was investigated by a FESEM Hitachi-S 4800. Fourier transform infrared spectroscopy (FTIR) was used to characterize the PPy/DNA film and to study the specific interactions that may exist between DNA biomacromolecules and PPy chains. Attempts are made to use these PPy/DNA composite films for label-free herpes virus detection revealed a response time of 60 s in solutions containing as low as 2 nM DNA concentration, and self life of six months when emerged in double distilled water and kept refrigerated.

  8. RenderGAN: Generating Realistic Labeled Data

    Directory of Open Access Journals (Sweden)

    Leon Sixt

    2018-06-01

    Full Text Available Deep Convolutional Neuronal Networks (DCNNs are showing remarkable performance on many computer vision tasks. Due to their large parameter space, they require many labeled samples when trained in a supervised setting. The costs of annotating data manually can render the use of DCNNs infeasible. We present a novel framework called RenderGAN that can generate large amounts of realistic, labeled images by combining a 3D model and the Generative Adversarial Network framework. In our approach, image augmentations (e.g., lighting, background, and detail are learned from unlabeled data such that the generated images are strikingly realistic while preserving the labels known from the 3D model. We apply the RenderGAN framework to generate images of barcode-like markers that are attached to honeybees. Training a DCNN on data generated by the RenderGAN yields considerably better performance than training it on various baselines.

  9. Good supervision and PBL

    DEFF Research Database (Denmark)

    Otrel-Cass, Kathrin

    This field study was conducted at the Faculty of Social Sciences at Aalborg University with the intention to investigate how students reflect on their experiences with supervision in a PBL environment. The overall aim of this study was to inform about the continued work in strengthening supervision...... at this faculty. This particular study invited Master level students to discuss: • How a typical supervision process proceeds • How they experienced and what they expected of PBL in the supervision process • What makes a good supervision process...

  10. A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine.

    Directory of Open Access Journals (Sweden)

    Fei Gao

    Full Text Available For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic data selection mechanism. In this paper, inspired by human learning process, a novel classification algorithm based on incremental semi-supervised support vector machine (SVM is proposed. Through the analysis of prediction confidence of samples and data distribution in a changing environment, a "soft-start" approach, a data selection mechanism and a data cleaning mechanism are designed, which complete the construction of our incremental semi-supervised learning system. Noticeably, with the ingenious design procedure of our proposed algorithm, the computation complexity is reduced effectively. In addition, for the possible appearance of some new labeled samples in the learning process, a detailed analysis is also carried out. The results show that our algorithm does not rely on the model of sample distribution, has an extremely low rate of introducing wrong semi-labeled samples and can effectively make use of the unlabeled samples to enrich the knowledge system of classifier and improve the accuracy rate. Moreover, our method also has outstanding generalization performance and the ability to overcome the concept drift in a changing environment.

  11. A semi-supervised learning approach for RNA secondary structure prediction.

    Science.gov (United States)

    Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

    2015-08-01

    RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Whither Supervision?

    Directory of Open Access Journals (Sweden)

    Duncan Waite

    2006-11-01

    Full Text Available This paper inquires if the school supervision is in decadence. Dr. Waite responds that the answer will depend on which perspective you look at it. Dr. Waite suggests taking in consideration three elements that are related: the field itself, the expert in the field (the professor, the theorist, the student and the administrator, and the context. When these three elements are revised, it emphasizes that there is not a consensus about the field of supervision, but there are coincidences related to its importance and that it is related to the improvement of the practice of the students in the school for their benefit. Dr. Waite suggests that the practice on this field is not always in harmony with what the theorists affirm. When referring to the supervisor or the skilled person, the author indicates that his or her perspective depends on his or her epistemological believes or in the way he or she conceives the learning; that is why supervision can be understood in different ways. About the context, Waite suggests that there have to be taken in consideration the social or external forces that influent the people and the society, because through them the education is affected. Dr. Waite concludes that the way to understand the supervision depends on the performer’s perspective. He responds to the initial question saying that the supervision authorities, the knowledge on this field, the performers, and its practice, are maybe spread but not extinct because the supervision will always be part of the great enterprise that we called education.

  13. Reflecting reflection in supervision

    DEFF Research Database (Denmark)

    Lystbæk, Christian Tang

    associated with reflection and an exploration of alternative conceptions that view reflection within the context of settings which have a more group- and team-based orientation. Drawing on an action research project on health care supervision, the paper questions whether we should reject earlier views...... of reflection, rehabilitate them in order to capture broader connotations or move to new ways of regarding reflection that are more in keeping with not only reflective but also emotive, normative and formative views on supervision. The paper presents a critical perspective on supervision that challenge...... the current reflective paradigm I supervision and relate this to emotive, normative and formative views supervision. The paper is relevant for Nordic educational research into the supervision and guidance...

  14. Learning from Weak and Noisy Labels for Semantic Segmentation

    KAUST Repository

    Lu, Zhiwu

    2016-04-08

    A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these ‘free’ tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.

  15. Learning from Weak and Noisy Labels for Semantic Segmentation

    KAUST Repository

    Lu, Zhiwu; Fu, Zhenyong; Xiang, Tao; Han, Peng; Wang, Liwei; Gao, Xin

    2016-01-01

    A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these ‘free’ tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.

  16. A supervised learning rule for classification of spatiotemporal spike patterns.

    Science.gov (United States)

    Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

    2016-08-01

    This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

  17. Protocols for 16S rDNA Array Analyses of Microbial Communities by Sequence-Specific Labeling of DNA Probes

    Directory of Open Access Journals (Sweden)

    Knut Rudi

    2003-01-01

    Full Text Available Analyses of complex microbial communities are becoming increasingly important. Bottlenecks in these analyses, however, are the tools to actually describe the biodiversity. Novel protocols for DNA array-based analyses of microbial communities are presented. In these protocols, the specificity obtained by sequence-specific labeling of DNA probes is combined with the possibility of detecting several different probes simultaneously by DNA array hybridization. The gene encoding 16S ribosomal RNA was chosen as the target in these analyses. This gene contains both universally conserved regions and regions with relatively high variability. The universally conserved regions are used for PCR amplification primers, while the variable regions are used for the specific probes. Protocols are presented for DNA purification, probe construction, probe labeling, and DNA array hybridizations.

  18. Resistance to group clinical supervision

    DEFF Research Database (Denmark)

    Buus, Niels; Delgado, Cynthia; Traynor, Michael

    2018-01-01

    This present study is a report of an interview study exploring personal views on participating in group clinical supervision among mental health nursing staff members who do not participate in supervision. There is a paucity of empirical research on resistance to supervision, which has traditiona......This present study is a report of an interview study exploring personal views on participating in group clinical supervision among mental health nursing staff members who do not participate in supervision. There is a paucity of empirical research on resistance to supervision, which has...... traditionally been theorized as a supervisee's maladaptive coping with anxiety in the supervision process. The aim of the present study was to examine resistance to group clinical supervision by interviewing nurses who did not participate in supervision. In 2015, we conducted semistructured interviews with 24...... Danish mental health nursing staff members who had been observed not to participate in supervision in two periods of 3 months. Interviews were audio-recorded and subjected to discourse analysis. We constructed two discursive positions taken by the informants: (i) 'forced non-participation', where...

  19. Optimal preventive bank supervision

    OpenAIRE

    Belhaj, Mohamed; Klimenko, Nataliya

    2012-01-01

    Early regulator interventions into problem banks is one of the key suggestions of Basel Committee on Banking Supervision. However, no guidance is given on their design. To fill this gap, we outline an incentive-based preventive supervision strategy that eliminates bad asset management in banks. Two supervision techniques are combined: temporary regulatory administration and random audits. Our design ensures good management without excessive supervision costs, through a gradual adjustment of...

  20. Morpholino spin-labeling for base-pair sequencing of a 3'-terminal RNA stem by proton homonuclear Overhauser enhancements: yeast ribosomal 5S RNA

    International Nuclear Information System (INIS)

    Lee, K.M.; Marshall, A.G.

    1987-01-01

    Base-pair sequences for 5S and 5.8S RNAs are not readily extracted from proton homonuclear nuclear Overhauser enhancement (NOE) connectivity experiments alone, due to extensive peak overlap in the downfield (11-15 ppm) proton NMR spectrum. In this paper, we introduce a new method for base-pair proton peak assignment for ribosomal RNAs, based upon the distance-dependent broadening of the resonances of base-pair protons spatially proximal to a paramagnetic group. Introduction of a nitroxide spin-label covalently attached to the 3'-terminal ribose provides an unequivocal starting point for base-pair hydrogen-bond proton NMR assignment. Subsequent NOE connectivities then establish the base-pair sequence for the terminal stem of a 5S RNA. Periodate oxidation of yeast 5S RNA, followed by reaction with 4-amino-2,2,6,6-tetramethylpiperidinyl-1-oxy (TEMPO-NH2) and sodium borohydride reduction, produces yeast 5S RNA specifically labeled with a paramagnetic nitroxide group at the 3'-terminal ribose. Comparison of the 500-MHz 1H NMR spectra of native and 3'-terminal spin-labeled yeast 5S RNA serves to identify the terminal base pair (G1 . C120) and its adjacent base pair (G2 . U119) on the basis of their proximity to the 3'-terminal spin-label. From that starting point, we have then identified (G . C, A . U, or G . U) and sequenced eight of the nine base pairs in the terminal helix via primary and secondary NOE's

  1. Electrochemical direct immobilization of DNA sequences for label-free herpes virus detection

    Energy Technology Data Exchange (ETDEWEB)

    Phuong Dinh Tam; Mai Anh Tuan [International Training Institute for Materials Science (Viet Nam); Tran Trung [Department of Electrochemistry, Hung-Yen University of Technology and Education (Viet Nam); Nguyen Duc Chien [Institute of Engineering Physics, Hanoi University of Technology, 1 Dai Co Viet Road, Hanoi (Viet Nam)], E-mail: tr_trunghut@yahoo.com

    2009-09-01

    DNA sequences/bio-macromolecules of herpes virus (5'-AT CAC CGA CCC GGA GAG GGA C-3') were directly immobilized into polypyrrole matrix by using the cyclic voltammetry method, and grafted onto arrays of interdigitated platinum microelectrodes. The morphology surface of the obtained PPy/DNA of herpes virus composite films was investigated by a FESEM Hitachi-S 4800. Fourier transform infrared spectroscopy (FTIR) was used to characterize the PPy/DNA film and to study the specific interactions that may exist between DNA biomacromolecules and PPy chains. Attempts are made to use these PPy/DNA composite films for label-free herpes virus detection revealed a response time of 60 s in solutions containing as low as 2 nM DNA concentration, and self life of six months when emerged in double distilled water and kept refrigerated.

  2. Visual texture perception via graph-based semi-supervised learning

    Science.gov (United States)

    Zhang, Qin; Dong, Junyu; Zhong, Guoqiang

    2018-04-01

    Perceptual features, for example direction, contrast and repetitiveness, are important visual factors for human to perceive a texture. However, it needs to perform psychophysical experiment to quantify these perceptual features' scale, which requires a large amount of human labor and time. This paper focuses on the task of obtaining perceptual features' scale of textures by small number of textures with perceptual scales through a rating psychophysical experiment (what we call labeled textures) and a mass of unlabeled textures. This is the scenario that the semi-supervised learning is naturally suitable for. This is meaningful for texture perception research, and really helpful for the perceptual texture database expansion. A graph-based semi-supervised learning method called random multi-graphs, RMG for short, is proposed to deal with this task. We evaluate different kinds of features including LBP, Gabor, and a kind of unsupervised deep features extracted by a PCA-based deep network. The experimental results show that our method can achieve satisfactory effects no matter what kind of texture features are used.

  3. Supervised Learning

    Science.gov (United States)

    Rokach, Lior; Maimon, Oded

    This chapter summarizes the fundamental aspects of supervised methods. The chapter provides an overview of concepts from various interrelated fields used in subsequent chapters. It presents basic definitions and arguments from the supervised machine learning literature and considers various issues, such as performance evaluation techniques and challenges for data mining tasks.

  4. Psykoterapi og supervision

    DEFF Research Database (Denmark)

    Jacobsen, Claus Haugaard

    2014-01-01

    Kapitlet beskriver supervisionen funktioner i forhold til psykoterapi. Supervision af psykoterapi henviser i almindelighed til, at en psykoterapeut konsulterer en ofte mere erfaren kollega (supervisor) med henblik på drøftelse af et konkret igangværende psykoterapeutisk behandlingsforløb. Formålet...... er at fremme denne fagpersons (psykoterapeutens) faglige udvikling samt sikre kvaliteten af behandlingen.kan defineres som i. Der redegøres for, hvorfor supervision er vigtig del af psykoterapeutens profession samt vises, hvorledes supervision foruden den faglige udvikling også er vigtigt redskab i...... psykoterapiens kvalitetssikring. Efter at have drøftet nogle etiske forhold ved supervision, fremlægges endelig nogle få forskningsresultater vedr. psykoterapisupervision af danske psykologer....

  5. Sequencing of Isotope-Labeled Small RNA Using Femtosecond Laser Ablation Time-of-Flight Mass Spectrometry

    Science.gov (United States)

    Kurata-Nishimura, Mizuki; Ando, Yoshinari; Kobayashi, Tohru; Matsuo, Yukari; Suzuki, Harukazu; Hayashizaki, Yoshihide; Kawai, Jun

    2010-04-01

    A novel method for the analysis of sequences of small RNAs using nucleotide triphosphates labeled with stable isotopes has been developed using time-of-flight mass spectroscopy combined with femtosecond laser ablation (fsLA-TOF-MS). Small RNAs synthesized with nucleotides enriched in 13C and 15N were efficiently atomized and ionized by single-shot fsLA and the isotope ratios 13C/12C and 15N/14N were evaluated using the TOF-MS method. By comparing the isotope ratios among four different configurations, the number of nucleotide contents of the control RNA sample were successfully reproduced.

  6. Rethinking Educational Supervision

    OpenAIRE

    Burhanettin DÖNMEZ; Kadir BEYCİOĞLU

    2009-01-01

    The history of educational (school) supervision has been influenced by the history of the interaction of intellectual movements in politics, society, philosophy and industrial movements. The purpose of this conceptual and theoretical study is to have a brief look at the concept of educational supervision with related historical developments in the field. The paper also intends to see the terms and issues critically, and to conceptualize some issues associated with educational supervision in...

  7. Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis.

    Science.gov (United States)

    Li, Chaoshun; Zhou, Jianzhong

    2014-09-01

    Supervised learning method, like support vector machine (SVM), has been widely applied in diagnosing known faults, however this kind of method fails to work correctly when new or unknown fault occurs. Traditional unsupervised kernel clustering can be used for unknown fault diagnosis, but it could not make use of the historical classification information to improve diagnosis accuracy. In this paper, a semi-supervised kernel clustering model is designed to diagnose known and unknown faults. At first, a novel semi-supervised weighted kernel clustering algorithm based on gravitational search (SWKC-GS) is proposed for clustering of dataset composed of labeled and unlabeled fault samples. The clustering model of SWKC-GS is defined based on wrong classification rate of labeled samples and fuzzy clustering index on the whole dataset. Gravitational search algorithm (GSA) is used to solve the clustering model, while centers of clusters, feature weights and parameter of kernel function are selected as optimization variables. And then, new fault samples are identified and diagnosed by calculating the weighted kernel distance between them and the fault cluster centers. If the fault samples are unknown, they will be added in historical dataset and the SWKC-GS is used to partition the mixed dataset and update the clustering results for diagnosing new fault. In experiments, the proposed method has been applied in fault diagnosis for rotatory bearing, while SWKC-GS has been compared not only with traditional clustering methods, but also with SVM and neural network, for known fault diagnosis. In addition, the proposed method has also been applied in unknown fault diagnosis. The results have shown effectiveness of the proposed method in achieving expected diagnosis accuracy for both known and unknown faults of rotatory bearing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Manifold Adaptive Label Propagation for Face Clustering.

    Science.gov (United States)

    Pei, Xiaobing; Lyu, Zehua; Chen, Changqing; Chen, Chuanbo

    2015-08-01

    In this paper, a novel label propagation (LP) method is presented, called the manifold adaptive label propagation (MALP) method, which is to extend original LP by integrating sparse representation constraint into regularization framework of LP method. Similar to most LP, first of all, MALP also finds graph edges from given data and gives weights to the graph edges. Our goal is to find graph weights matrix adaptively. The key advantage of our approach is that MALP simultaneously finds graph weights matrix and predicts the label of unlabeled data. This paper also derives efficient algorithm to solve the proposed problem. Extensions of our MALP in kernel space and robust version are presented. The proposed method has been applied to the problem of semi-supervised face clustering using the well-known ORL, Yale, extended YaleB, and PIE datasets. Our experimental evaluations show the effectiveness of our method.

  9. MULTIPERIOD BANKING SUPERVISION

    OpenAIRE

    KARL-THEODOR EISELE; PHILIPPE ARTZNER

    2013-01-01

    This paper is based on a general method for multiperiod prudential supervision of companies submitted to hedgeable and non-hedgeable risks. Having treated the case of insurance in an earlier paper, we now consider a quantitative approach to supervision of commercial banks. The various elements under supervision are the bank’s current amount of tradeable assets, the deposit amount, and four flow processes: future trading risk exposures, deposit flows, flows of loan repayments and of deposit re...

  10. Discussion on posting and labeling for radioprotection

    International Nuclear Information System (INIS)

    Suzuki, Fabio F.

    2009-01-01

    The radioprotection aims the protection of people against exposure to ionizing radiation or radioactive substances as well as the safety of radiation sources. As ionizing radiation is not perceived by human senses, the warning signs and labels on radiation sources and the safety posters in controlled and supervised areas have an important role to keep the doses and risks as low as reasonably achievable, to prevent radiological accidents and to mitigate their consequences. In Brazil, several technical regulations require such safety labels and posters, however, despite their importance, there is quite few guidance about their format or contents. In this paper the posting and labeling requirements for radiological control existing in Brazilian technical regulations are discussed, confronting them with national, foreign and international technical standards and by drawing up a parallel with requirements of technical regulations from other countries. Changes are suggested in some parts of the national regulations, to prevent some differences in the current guidance, allowing the optimization of posting and labeling programs of radiological facilities. (author)

  11. Effect of denoising on supervised lung parenchymal clusters

    Science.gov (United States)

    Jayamani, Padmapriya; Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Bartholmai, Brian J.; Robb, Richard A.

    2012-03-01

    Denoising is a critical preconditioning step for quantitative analysis of medical images. Despite promises for more consistent diagnosis, denoising techniques are seldom explored in clinical settings. While this may be attributed to the esoteric nature of the parameter sensitve algorithms, lack of quantitative measures on their ecacy to enhance the clinical decision making is a primary cause of physician apathy. This paper addresses this issue by exploring the eect of denoising on the integrity of supervised lung parenchymal clusters. Multiple Volumes of Interests (VOIs) were selected across multiple high resolution CT scans to represent samples of dierent patterns (normal, emphysema, ground glass, honey combing and reticular). The VOIs were labeled through consensus of four radiologists. The original datasets were ltered by multiple denoising techniques (median ltering, anisotropic diusion, bilateral ltering and non-local means) and the corresponding ltered VOIs were extracted. Plurality of cluster indices based on multiple histogram-based pair-wise similarity measures were used to assess the quality of supervised clusters in the original and ltered space. The resultant rank orders were analyzed using the Borda criteria to nd the denoising-similarity measure combination that has the best cluster quality. Our exhaustive analyis reveals (a) for a number of similarity measures, the cluster quality is inferior in the ltered space; and (b) for measures that benet from denoising, a simple median ltering outperforms non-local means and bilateral ltering. Our study suggests the need to judiciously choose, if required, a denoising technique that does not deteriorate the integrity of supervised clusters.

  12. Tracking mobile users in wireless networks via semi-supervised colocalization.

    Science.gov (United States)

    Pan, Jeffrey Junfeng; Pan, Sinno Jialin; Yin, Jie; Ni, Lionel M; Yang, Qiang

    2012-03-01

    Recent years have witnessed the growing popularity of sensor and sensor-network technologies, supporting important practical applications. One of the fundamental issues is how to accurately locate a user with few labeled data in a wireless sensor network, where a major difficulty arises from the need to label large quantities of user location data, which in turn requires knowledge about the locations of signal transmitters or access points. To solve this problem, we have developed a novel machine learning-based approach that combines collaborative filtering with graph-based semi-supervised learning to learn both mobile users' locations and the locations of access points. Our framework exploits both labeled and unlabeled data from mobile devices and access points. In our two-phase solution, we first build a manifold-based model from a batch of labeled and unlabeled data in an offline training phase and then use a weighted k-nearest-neighbor method to localize a mobile client in an online localization phase. We extend the two-phase colocalization to an online and incremental model that can deal with labeled and unlabeled data that come sequentially and adapt to environmental changes. Finally, we embed an action model to the framework such that additional kinds of sensor signals can be utilized to further boost the performance of mobile tracking. Compared to other state-of-the-art systems, our framework has been shown to be more accurate while requiring less calibration effort in our experiments performed on three different testbeds.

  13. Quantifying emphysema extent from weakly labeled CT scans of the lungs using label proportions learning

    DEFF Research Database (Denmark)

    Ørting, Silas Nyboe; Petersen, Jens; Wille, Mathilde

    2016-01-01

    Quantification of emphysema extent is important in diagnosing and monitoring patients with chronic obstructive pulmonary disease (COPD). Several studies have shown that emphysema quantification by supervised texture classification is more robust and accurate than traditional densitometry. Current...... techniques require highly time consuming manual annotations of patches or use only weak labels indicating overall disease status (e.g, COPD or healthy). We show how visual scoring of regional emphysema extent can be exploited in a learning with label proportions (LLP) framework to both predict presence...... of emphysema in smaller patches and estimate regional extent. We evaluate performance on 195 visually scored CT scans and achieve an intraclass correlation of 0.72 (0.65–0.78) between predicted region extent and expert raters. To our knowledge this is the first time that LLP methods have been applied...

  14. A Supervision of Solidarity

    Science.gov (United States)

    Reynolds, Vikki

    2010-01-01

    This article illustrates an approach to therapeutic supervision informed by a philosophy of solidarity and social justice activism. Called a "Supervision of Solidarity", this approach addresses the particular challenges in the supervision of therapists who work alongside clients who are subjected to social injustice and extreme marginalization. It…

  15. Large-scale weakly supervised object localization via latent category learning.

    Science.gov (United States)

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

  16. A Label Correcting Algorithm for Partial Disassembly Sequences in the Production Planning for End-of-Life Products

    Directory of Open Access Journals (Sweden)

    Pei-Fang (Jennifer Tsai

    2012-01-01

    Full Text Available Remanufacturing of used products has become a strategic issue for cost-sensitive businesses. Due to the nature of uncertain supply of end-of-life (EoL products, the reverse logistic can only be sustainable with a dynamic production planning for disassembly process. This research investigates the sequencing of disassembly operations as a single-period partial disassembly optimization (SPPDO problem to minimize total disassembly cost. AND/OR graph representation is used to include all disassembly sequences of a returned product. A label correcting algorithm is proposed to find an optimal partial disassembly plan if a specific reusable subpart is retrieved from the original return. Then, a heuristic procedure that utilizes this polynomial-time algorithm is presented to solve the SPPDO problem. Numerical examples are used to demonstrate the effectiveness of this solution procedure.

  17. Regular graph construction for semi-supervised learning

    International Nuclear Information System (INIS)

    Vega-Oliveros, Didier A; Berton, Lilian; Eberle, Andre Mantini; Lopes, Alneu de Andrade; Zhao, Liang

    2014-01-01

    Semi-supervised learning (SSL) stands out for using a small amount of labeled points for data clustering and classification. In this scenario graph-based methods allow the analysis of local and global characteristics of the available data by identifying classes or groups regardless data distribution and representing submanifold in Euclidean space. Most of methods used in literature for SSL classification do not worry about graph construction. However, regular graphs can obtain better classification accuracy compared to traditional methods such as k-nearest neighbor (kNN), since kNN benefits the generation of hubs and it is not appropriate for high-dimensionality data. Nevertheless, methods commonly used for generating regular graphs have high computational cost. We tackle this problem introducing an alternative method for generation of regular graphs with better runtime performance compared to methods usually find in the area. Our technique is based on the preferential selection of vertices according some topological measures, like closeness, generating at the end of the process a regular graph. Experiments using the global and local consistency method for label propagation show that our method provides better or equal classification rate in comparison with kNN

  18. A National Survey of School Counselor Supervision Practices: Administrative, Clinical, Peer, and Technology Mediated Supervision

    Science.gov (United States)

    Perera-Diltz, Dilani M.; Mason, Kimberly L.

    2012-01-01

    Supervision is vital for personal and professional development of counselors. Practicing school counselors (n = 1557) across the nation were surveyed to explore current supervision practices. Results indicated that 41.1% of school counselors provide supervision. Although 89% receive some type of supervision, only 10.3% of school counselors receive…

  19. Ensemble learning with trees and rules: supervised, semi-supervised, unsupervised

    Science.gov (United States)

    In this article, we propose several new approaches for post processing a large ensemble of conjunctive rules for supervised and semi-supervised learning problems. We show with various examples that for high dimensional regression problems the models constructed by the post processing the rules with ...

  20. Statistical-mechanics analysis of Gaussian labeled-unlabeled classification problems

    International Nuclear Information System (INIS)

    Tanaka, Toshiyuki

    2013-01-01

    The labeled-unlabeled classification problem in semi-supervised learning is studied via statistical-mechanics approach. We analytically investigate performance of a learner with an equal-weight mixture of two symmetrically-located Gaussians, performing posterior mean estimation of the parameter vector on the basis of a dataset consisting of labeled and unlabeled data generated from the same probability model as that assumed by the learner. Under the assumption of replica symmetry, we have analytically obtained a set of saddle-point equations, which allows us to numerically evaluate performance of the learner. On the basis of the analytical result we have observed interesting phenomena, in particular the coexistence of good and bad solutions, which may happen when the number of unlabeled data is relatively large compared with that of labeled data

  1. The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing

    DEFF Research Database (Denmark)

    Binladen, Jonas; Gilbert, M Thomas P; Bollback, Jonathan P

    2007-01-01

    BACKGROUND: The invention of the Genome Sequence 20 DNA Sequencing System (454 parallel sequencing platform) has enabled the rapid and high-volume production of sequence data. Until now, however, individual emulsion PCR (emPCR) reactions and subsequent sequencing runs have been unable to combine...... primers that is dependent on the 5' nucleotide of the tag. In particular, primers 5' labelled with a cytosine are heavily overrepresented among the final sequences, while those 5' labelled with a thymine are strongly underrepresented. A weaker bias also exists with regards to the distribution...

  2. An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

    Science.gov (United States)

    Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

    2014-01-01

    The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

  3. Adequate supervision for children and adolescents.

    Science.gov (United States)

    Anderst, James; Moffatt, Mary

    2014-11-01

    Primary care providers (PCPs) have the opportunity to improve child health and well-being by addressing supervision issues before an injury or exposure has occurred and/or after an injury or exposure has occurred. Appropriate anticipatory guidance on supervision at well-child visits can improve supervision of children, and may prevent future harm. Adequate supervision varies based on the child's development and maturity, and the risks in the child's environment. Consideration should be given to issues as wide ranging as swimming pools, falls, dating violence, and social media. By considering the likelihood of harm and the severity of the potential harm, caregivers may provide adequate supervision by minimizing risks to the child while still allowing the child to take "small" risks as needed for healthy development. Caregivers should initially focus on direct (visual, auditory, and proximity) supervision of the young child. Gradually, supervision needs to be adjusted as the child develops, emphasizing a safe environment and safe social interactions, with graduated independence. PCPs may foster adequate supervision by providing concrete guidance to caregivers. In addition to preventing injury, supervision includes fostering a safe, stable, and nurturing relationship with every child. PCPs should be familiar with age/developmentally based supervision risks, adequate supervision based on those risks, characteristics of neglectful supervision based on age/development, and ways to encourage appropriate supervision throughout childhood. Copyright 2014, SLACK Incorporated.

  4. Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

    Science.gov (United States)

    Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

    2018-09-01

    Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

  5. Group supervision for general practitioners

    DEFF Research Database (Denmark)

    Galina Nielsen, Helena; Sofie Davidsen, Annette; Dalsted, Rikke

    2013-01-01

    AIM: Group supervision is a sparsely researched method for professional development in general practice. The aim of this study was to explore general practitioners' (GPs') experiences of the benefits of group supervision for improving the treatment of mental disorders. METHODS: One long-establish......AIM: Group supervision is a sparsely researched method for professional development in general practice. The aim of this study was to explore general practitioners' (GPs') experiences of the benefits of group supervision for improving the treatment of mental disorders. METHODS: One long...... considered important prerequisites for disclosing and discussing professional problems. CONCLUSION: The results of this study indicate that participation in a supervision group can be beneficial for maintaining and developing GPs' skills in dealing with patients with mental health problems. Group supervision...... influenced other areas of GPs' professional lives as well. However, more studies are needed to assess the impact of supervision groups....

  6. Evaluering af kollegial supervision

    DEFF Research Database (Denmark)

    Petersen, Anne Line Bjerre Folsgaard; Bager, Lene Tortzen; Jørgensen, Mette Eg

    2015-01-01

    Videoen er en evaluering af arbejdet med en metodisk tilgang til kollegial supervision på VIA Ergoterapeutuddannelsen gennem et par år. Evalueringen sætter fokus på selve metoden, der er anvendt til kollegial supervision. Derudover er der fokus på erfaringer og udbytte af at arbejde systematisk med...... kollegial supervision blandt undervisere på VIA Ergoterapeutuddannelsen....

  7. Rethinking Educational Supervision

    Directory of Open Access Journals (Sweden)

    Burhanettin DÖNMEZ

    2009-08-01

    Full Text Available The history of educational (school supervision has been influenced by the history of the interaction of intellectual movements in politics, society, philosophy and industrial movements. The purpose of this conceptual and theoretical study is to have a brief look at the concept of educational supervision with related historical developments in the field. The paper also intends to see the terms and issues critically, and to conceptualize some issues associated with educational supervision in practice. In the paper, the issues are discussed and a number of suggestions are addressed for debate.

  8. A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

    Science.gov (United States)

    Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

    2017-10-12

    Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT model.

  9. Rooting out institutional corruption to manage inappropriate off-label drug use.

    Science.gov (United States)

    Rodwin, Marc A

    2013-01-01

    Prescribing drugs for uses that the FDA has not approved - off-label drug use - can sometimes be justified but is typically not supported by substantial evidence of effectiveness. At the root of inappropriate off-label drug use lie perverse incentives for pharmaceutical firms and flawed oversight of prescribing physicians. Typical reform proposals such as increased sanctions for manufacturers might reduce the incidence of unjustified off-label use, but they do not remove the source of the problem. Public policy should address the cause and control the practice. To manage inappropriate off-label drug use, off-label prescriptions must be tracked in order to monitor the risks and benefits and the manufacturers' conduct. Even more important, reimbursement rules should be changed so that manufacturers cannot profit from off-label sales. When off-label sales pass a critical threshold, manufacturers should also be required to pay for independent testing of the safety and effectiveness of off-label drug uses and for the FDA to review the evidence. Manufacturers should also finance, under FDA supervision, programs designed to warn physicians and the public about the risks of off-label drug use. © 2013 American Society of Law, Medicine & Ethics, Inc.

  10. Social construction : discursive perspective towards supervision

    OpenAIRE

    Naujanienė, Rasa

    2010-01-01

    The aim of publication is to discuss the development of supervision theory in relation with social and social work theory and practice. Main focus in the analysis is done to social constructionist ideas and its’ relevance to supervision practice. The development of supervision is related with supervision practice. Starting in 19th century supervision from giving practical advices supervision came to 21st century as dialog based on critical and philosophical reflection. Different theory and pr...

  11. Facial Action Unit Recognition under Incomplete Data Based on Multi-label Learning with Missing Labels

    KAUST Repository

    Li, Yongqiang

    2016-07-07

    Facial action unit (AU) recognition has been applied in a wild range of fields, and has attracted great attention in the past two decades. Most existing works on AU recognition assumed that the complete label assignment for each training image is available, which is often not the case in practice. Labeling AU is expensive and time consuming process. Moreover, due to the AU ambiguity and subjective difference, some AUs are difficult to label reliably and confidently. Many AU recognition works try to train the classifier for each AU independently, which is of high computation cost and ignores the dependency among different AUs. In this work, we formulate AU recognition under incomplete data as a multi-label learning with missing labels (MLML) problem. Most existing MLML methods usually employ the same features for all classes. However, we find this setting is unreasonable in AU recognition, as the occurrence of different AUs produce changes of skin surface displacement or face appearance in different face regions. If using the shared features for all AUs, much noise will be involved due to the occurrence of other AUs. Consequently, the changes of the specific AUs cannot be clearly highlighted, leading to the performance degradation. Instead, we propose to extract the most discriminative features for each AU individually, which are learned by the supervised learning method. The learned features are further embedded into the instance-level label smoothness term of our model, which also includes the label consistency and the class-level label smoothness. Both a global solution using st-cut and an approximated solution using conjugate gradient (CG) descent are provided. Experiments on both posed and spontaneous facial expression databases demonstrate the superiority of the proposed method in comparison with several state-of-the-art works.

  12. Facial Action Unit Recognition under Incomplete Data Based on Multi-label Learning with Missing Labels

    KAUST Repository

    Li, Yongqiang; Wu, Baoyuan; Ghanem, Bernard; Zhao, Yongping; Yao, Hongxun; Ji, Qiang

    2016-01-01

    Facial action unit (AU) recognition has been applied in a wild range of fields, and has attracted great attention in the past two decades. Most existing works on AU recognition assumed that the complete label assignment for each training image is available, which is often not the case in practice. Labeling AU is expensive and time consuming process. Moreover, due to the AU ambiguity and subjective difference, some AUs are difficult to label reliably and confidently. Many AU recognition works try to train the classifier for each AU independently, which is of high computation cost and ignores the dependency among different AUs. In this work, we formulate AU recognition under incomplete data as a multi-label learning with missing labels (MLML) problem. Most existing MLML methods usually employ the same features for all classes. However, we find this setting is unreasonable in AU recognition, as the occurrence of different AUs produce changes of skin surface displacement or face appearance in different face regions. If using the shared features for all AUs, much noise will be involved due to the occurrence of other AUs. Consequently, the changes of the specific AUs cannot be clearly highlighted, leading to the performance degradation. Instead, we propose to extract the most discriminative features for each AU individually, which are learned by the supervised learning method. The learned features are further embedded into the instance-level label smoothness term of our model, which also includes the label consistency and the class-level label smoothness. Both a global solution using st-cut and an approximated solution using conjugate gradient (CG) descent are provided. Experiments on both posed and spontaneous facial expression databases demonstrate the superiority of the proposed method in comparison with several state-of-the-art works.

  13. Public Supervision over Private Relationships : Towards European Supervision Private Law?

    NARCIS (Netherlands)

    Cherednychenko, O.O.

    2014-01-01

    The rise of public supervision over private relationships in many areas of private law has led to the development of what, in the author’s view, could be called ‘European supervision private law’. This emerging body of law forms part of European regulatory private law and is made up of

  14. Forskellighed i supervision

    DEFF Research Database (Denmark)

    Petersen, Birgitte; Beck, Emma

    2009-01-01

    Indtryk og tendenser fra den anden danske konference om supervision, som blev holdt på Københavns Universitet i oktober 2008......Indtryk og tendenser fra den anden danske konference om supervision, som blev holdt på Københavns Universitet i oktober 2008...

  15. Supervision af psykoterapi

    DEFF Research Database (Denmark)

    SUPERVISION AF PSYKOTERAPI indtager en central position i uddannelsen og udviklingen af psykoterapeuter. Trods flere lighedspunkter med psykoterapi, undervisning og konsultation er psykoterapisupervision et selvstændigt virksomhedsområde. Supervisor må foruden at være en trænet psykoterapeut kende...... supervisionens rammer og indplacering i forhold til organisation og samfund. En række kapitler drejer sig om supervisors opgaver, roller og kontrolfunktion, supervision set fra supervisandens perspektiv samt betragtninger over relationer og processer i supervision. Der drøftes fordele og ulemper ved de...... forskellige måder, hvorpå en sag kan fremlægges. Bogens første del afsluttes med refleksioner over de etiske aspekter ved psykoterapisupervision. Bogens anden del handler om de særlige forhold, der gør sig gældende ved supervision af en række specialiserede behandlingsformer eller af psykoterapi med bestemte...

  16. An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species

    Directory of Open Access Journals (Sweden)

    Deborah Galpert

    2015-01-01

    Full Text Available Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles are combined in a supervised pairwise ortholog detection approach to improve effectiveness considering low ortholog ratios in relation to the possible pairwise comparison between two genomes. In this scenario, big data supervised classifiers managing imbalance between ortholog and nonortholog pair classes allow for an effective scaling solution built from two genomes and extended to other genome pairs. The supervised approach was compared with RBH, RSD, and OMA algorithms by using the following yeast genome pairs: Saccharomyces cerevisiae-Kluyveromyces lactis, Saccharomyces cerevisiae-Candida glabrata, and Saccharomyces cerevisiae-Schizosaccharomyces pombe as benchmark datasets. Because of the large amount of imbalanced data, the building and testing of the supervised model were only possible by using big data supervised classifiers managing imbalance. Evaluation metrics taking low ortholog ratios into account were applied. From the effectiveness perspective, MapReduce Random Oversampling combined with Spark SVM outperformed RBH, RSD, and OMA, probably because of the consideration of gene pair features beyond alignment similarities combined with the advances in big data supervised classification.

  17. Researching online supervision

    DEFF Research Database (Denmark)

    Bengtsen, Søren S. E.; Mathiasen, Helle

    2014-01-01

    Online supervision and the use of digital media in supervisory dialogues is a fast increasing practice in higher education today. However, the concepts in our pedagogical repertoire often reflect the digital tools used for supervision purposes as either a prolongation of the face-to-face contact...

  18. Implementation of Instructional Supervision in Secondary School ...

    African Journals Online (AJOL)

    Science, Technology and Arts Research Journal ... Supervision is critical in the development of any educational program in both developed and ... Clinical Supervision, Collegial Supervision, Self-directive supervision, Informal Supervision etc.

  19. Does the Drug Facts Label for nonprescription drugs meet its design objectives? A new procedure for assessing label effectiveness

    Directory of Open Access Journals (Sweden)

    Michael P Ryan

    2017-07-01

    Full Text Available We demonstrate an expanded procedure for assessing drug-label comprehension. Innovations include a pretest of drug preconceptions, verbal ability and label attentiveness measures, a label-scanning task, a free-recall test, category-clustering measures, and preconception-change scores. In total, 55 female and 39 male undergraduates read a facsimile Drug Facts Label for aspirin, a Cohesive-Prose Label, or a Scrambled-Prose Label. The Drug Facts Label outperformed the Scrambled-Prose Label, but not the Cohesive-Prose Label, in scanning effectiveness. The Drug Facts Label was no better than the Cohesive-Prose Label or the Scrambled-Prose Label in promoting attentiveness, recall and organization of drug facts, or misconception refutation. Discussion focuses on the need for refutational labels based on a sequence-of-events text schema.

  20. 20 CFR 656.21 - Supervised recruitment.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Supervised recruitment. 656.21 Section 656.21... Supervised recruitment. (a) Supervised recruitment. Where the Certifying Officer determines it appropriate, post-filing supervised recruitment may be required of the employer for the pending application or...

  1. Supervision Duty of School Principals

    Directory of Open Access Journals (Sweden)

    Kürşat YILMAZ

    2009-04-01

    Full Text Available Supervision by school administrators is becoming more and more important. The change in the roles ofschool administrators has a great effect on that increase. At present, school administrators are consideredmore than as technical directors, but as instructional leaders. This increased the importance of schooladministrators’ expected supervision acts. In this respect, the aim of this study is to make a conceptualanalysis about school administrators’ supervision duties. For this reason, a literature review related withsupervision and contemporary supervision approaches was done, and the official documents concerningsupervision were examined. As a result, it can be said that school administrators’ supervision duties havebecome very important. And these duties must certainly be carried out by school administrators.

  2. Moment constrained semi-supervised LDA

    DEFF Research Database (Denmark)

    Loog, Marco

    2012-01-01

    This BNAIC compressed contribution provides a summary of the work originally presented at the First IAPR Workshop on Partially Supervised Learning and published in [5]. It outlines the idea behind supervised and semi-supervised learning and highlights the major shortcoming of many current methods...

  3. Enhanced throughput for infrared automated DNA sequencing

    Science.gov (United States)

    Middendorf, Lyle R.; Gartside, Bill O.; Humphrey, Pat G.; Roemer, Stephen C.; Sorensen, David R.; Steffens, David L.; Sutter, Scott L.

    1995-04-01

    Several enhancements have been developed and applied to infrared automated DNA sequencing resulting in significantly higher throughput. A 41 cm sequencing gel (31 cm well- to-read distance) combines high resolution of DNA sequencing fragments with optimized run times yielding two runs per day of 500 bases per sample. A 66 cm sequencing gel (56 cm well-to-read distance) produces sequence read lengths of up to 1000 bases for ds and ss templates using either T7 polymerase or cycle-sequencing protocols. Using a multichannel syringe to load 64 lanes allows 16 samples (compatible with 96-well format) to be visualized for each run. The 41 cm gel configuration allows 16,000 bases per day (16 samples X 500 bases/sample X 2 ten hour runs/day) to be sequenced with the advantages of infrared technology. Enhancements to internal labeling techniques using an infrared-labeled dATP molecule (Boehringer Mannheim GmbH, Penzberg, Germany; Sequenase (U.S. Biochemical) have also been made. The inclusion of glycerol in the sequencing reactions yields greatly improved results for some primer and template combinations. The inclusion of (alpha) -Thio-dNTP's in the labeling reaction increases signal intensity two- to three-fold.

  4. Asco 2044 nuclear power plant: supervision; Central nuclear Asco 2044: supervision

    Energy Technology Data Exchange (ETDEWEB)

    Sabartes, J.

    2010-07-01

    Good supervision constitutes an efficient barrier to avoid the errors caused by inadequate work practices. In this sense, it is necessary to strengthen supervision to make sure that the work is carried out with adequate human performance, tending to avoid error ande provinding safety quality and efficiency at work. (Author).

  5. Whither Supervision?

    OpenAIRE

    Duncan Waite

    2006-01-01

    This paper inquires if the school supervision is in decadence. Dr. Waite responds that the answer will depend on which perspective you look at it. Dr. Waite suggests taking in consideration three elements that are related: the field itself, the expert in the field (the professor, the theorist, the student and the administrator), and the context. When these three elements are revised, it emphasizes that there is not a consensus about the field of supervision, but there are coincidences related...

  6. Effects of coaching supervision, mentoring supervision and abusive supervision on talent development among trainee doctors in public hospitals: moderating role of clinical learning environment.

    Science.gov (United States)

    Subramaniam, Anusuiya; Silong, Abu Daud; Uli, Jegak; Ismail, Ismi Arif

    2015-08-13

    Effective talent development requires robust supervision. However, the effects of supervisory styles (coaching, mentoring and abusive supervision) on talent development and the moderating effects of clinical learning environment in the relationship between supervisory styles and talent development among public hospital trainee doctors have not been thoroughly researched. In this study, we aim to achieve the following, (1) identify the extent to which supervisory styles (coaching, mentoring and abusive supervision) can facilitate talent development among trainee doctors in public hospital and (2) examine whether coaching, mentoring and abusive supervision are moderated by clinical learning environment in predicting talent development among trainee doctors in public hospital. A questionnaire-based critical survey was conducted among trainee doctors undergoing housemanship at six public hospitals in the Klang Valley, Malaysia. Prior permission was obtained from the Ministry of Health Malaysia to conduct the research in the identified public hospitals. The survey yielded 355 responses. The results were analysed using SPSS 20.0 and SEM with AMOS 20.0. The findings of this research indicate that coaching and mentoring supervision are positively associated with talent development, and that there is no significant relationship between abusive supervision and talent development. The findings also support the moderating role of clinical learning environment on the relationships between coaching supervision-talent development, mentoring supervision-talent development and abusive supervision-talent development among public hospital trainee doctors. Overall, the proposed model indicates a 26 % variance in talent development. This study provides an improved understanding on the role of the supervisory styles (coaching and mentoring supervision) on facilitating talent development among public hospital trainee doctors. Furthermore, this study extends the literature to better

  7. Advanced Music Therapy Supervision Training

    DEFF Research Database (Denmark)

    Pedersen, Inge Nygaard

    2009-01-01

    supervision training excerpts live in the workshop will be offered. The workshop will include demonstrating a variety of supervision methods and techniques used in A) post graduate music therapy training programs b) a variety of work contexts such as psychiatry and somatic music psychotherapy. The workshop......The presentation will illustrate training models in supervision for experienced music therapists where transference/counter transference issues are in focus. Musical, verbal and body related tools will be illustrated from supervision practice by the presenters. A possibility to experience small...

  8. Using a Mixed Model to Explore Evaluation Criteria for Bank Supervision: A Banking Supervision Law Perspective.

    Directory of Open Access Journals (Sweden)

    Sang-Bing Tsai

    Full Text Available Financial supervision means that monetary authorities have the power to supervise and manage financial institutions according to laws. Monetary authorities have this power because of the requirements of improving financial services, protecting the rights of depositors, adapting to industrial development, ensuring financial fair trade, and maintaining stable financial order. To establish evaluation criteria for bank supervision in China, this study integrated fuzzy theory and the decision making trial and evaluation laboratory (DEMATEL and proposes a fuzzy-DEMATEL model. First, fuzzy theory was applied to examine bank supervision criteria and analyze fuzzy semantics. Second, the fuzzy-DEMATEL model was used to calculate the degree to which financial supervision criteria mutually influenced one another and their causal relationship. Finally, an evaluation criteria model for evaluating bank and financial supervision was established.

  9. Using a Mixed Model to Explore Evaluation Criteria for Bank Supervision: A Banking Supervision Law Perspective

    Science.gov (United States)

    Tsai, Sang-Bing; Chen, Kuan-Yu; Zhao, Hongrui; Wei, Yu-Min; Wang, Cheng-Kuang; Zheng, Yuxiang; Chang, Li-Chung; Wang, Jiangtao

    2016-01-01

    Financial supervision means that monetary authorities have the power to supervise and manage financial institutions according to laws. Monetary authorities have this power because of the requirements of improving financial services, protecting the rights of depositors, adapting to industrial development, ensuring financial fair trade, and maintaining stable financial order. To establish evaluation criteria for bank supervision in China, this study integrated fuzzy theory and the decision making trial and evaluation laboratory (DEMATEL) and proposes a fuzzy-DEMATEL model. First, fuzzy theory was applied to examine bank supervision criteria and analyze fuzzy semantics. Second, the fuzzy-DEMATEL model was used to calculate the degree to which financial supervision criteria mutually influenced one another and their causal relationship. Finally, an evaluation criteria model for evaluating bank and financial supervision was established. PMID:27992449

  10. Supervision in banking industry

    OpenAIRE

    Šmída, David

    2012-01-01

    The aim of submitted thesis Supervision in banking is to define the nature and the importance of banking supervision, to justify its existence and to analyze the applicable mechanisms while the system of banking regulation and supervision in this thesis is primarily examined in the European context, with a focus on the Czech Republic. The thesis is divided into five main chapters. The first chapter is devoted to the financial system and the importance of banks in this system, it defines the c...

  11. 17 CFR 166.3 - Supervision.

    Science.gov (United States)

    2010-04-01

    ... 17 Commodity and Securities Exchanges 1 2010-04-01 2010-04-01 false Supervision. 166.3 Section 166.3 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION CUSTOMER PROTECTION RULES § 166.3 Supervision. Each Commission registrant, except an associated person who has no supervisory duties, must diligently supervise the handling b...

  12. 28 CFR 810.1 - Supervision contact requirements.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Supervision contact requirements. 810.1 Section 810.1 Judicial Administration COURT SERVICES AND OFFENDER SUPERVISION AGENCY FOR THE DISTRICT OF COLUMBIA COMMUNITY SUPERVISION: ADMINISTRATIVE SANCTIONS § 810.1 Supervision contact requirements. If you are an offender under supervision by th...

  13. Online tutoring procedure for research project supervision: management, organization and key elements

    Directory of Open Access Journals (Sweden)

    Antònia Darder Mesquida

    2015-07-01

    Full Text Available Research project tutoring appears as a crucial element for teaching; it is a planned action based on the relationship between a tutor and a student. This paper presents the findings of a design and development research which has as its main aim to create an organization system for the tutoring of online research projects. That system seeks to facilitate the tutoring and supervision task with trainee researchers, providing guidance for its management and instruments for its implementation. The main conclusions arising from this research derive from considering the need to offer a solution to the problem of distance research project supervision and has materialized in organization and sequencing through a model about the variables that influence the research project tutoring problem.

  14. Mentoring, coaching and supervision

    OpenAIRE

    McMahon, Samantha; Dyer, Mary; Barker, Catherine

    2016-01-01

    This chapter considers the purpose of coaching, mentoring and supervision in early childhood eduaction and care. It examines a number of different approaches and considers the key skills required for effective coaching, mentoring and supervision.

  15. Empirical study of supervised gene screening

    Directory of Open Access Journals (Sweden)

    Ma Shuangge

    2006-12-01

    Full Text Available Abstract Background Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray measurements usually consists of three steps: (1 unsupervised gene screening; (2 supervised gene screening; and (3 statistical model building. Supervised gene screening based on marginal gene ranking is commonly used to reduce the number of genes in the model building. Various simple statistics, such as t-statistic or signal to noise ratio, have been used to rank genes in the supervised screening. Despite of its extensive usage, statistical study of supervised gene screening remains scarce. Our study is partly motivated by the differences in gene discovery results caused by using different supervised gene screening methods. Results We investigate concordance and reproducibility of supervised gene screening based on eight commonly used marginal statistics. Concordance is assessed by the relative fractions of overlaps between top ranked genes screened using different marginal statistics. We propose a Bootstrap Reproducibility Index, which measures reproducibility of individual genes under the supervised screening. Empirical studies are based on four public microarray data. We consider the cases where the top 20%, 40% and 60% genes are screened. Conclusion From a gene discovery point of view, the effect of supervised gene screening based on different marginal statistics cannot be ignored. Empirical studies show that (1 genes passed different supervised screenings may be considerably different; (2 concordance may vary, depending on the underlying data structure and percentage of selected genes; (3 evaluated with the Bootstrap Reproducibility Index, genes passed supervised screenings are only moderately reproducible; and (4 concordance cannot be improved by supervised screening based on reproducibility.

  16. 32 CFR 727.11 - Supervision.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 5 2010-07-01 2010-07-01 false Supervision. 727.11 Section 727.11 National Defense Department of Defense (Continued) DEPARTMENT OF THE NAVY PERSONNEL LEGAL ASSISTANCE § 727.11 Supervision. The Judge Advocate General will exercise supervision over all legal assistance activities in the Department of the Navy. Subject to the...

  17. The vision in supervision: transference-countertransference dynamics and disclosure in the supervision relationship.

    Science.gov (United States)

    Coburn, W J

    1997-01-01

    The centrality of the supervision experience in the development of the supervisee's personal and professional capacities is addressed. The supervision relationship and process are explored in light of the potential effects of transference-countertransference configurations of supervisor and supervisee. Parallels between supervision and treatment are highlighted. The importance of developing and utilizing the capacity for reflectivity is reviewed, as is the impact of supervisee nondisclosure to supervisor. The direct use of countertransference experiences in the context of supervision is explored, and the centrality of self-disclosure is highlighted. It is recommended that supervisor and supervisee remain receptive to exploring these experiences in the service of developing a shared subjective sense of the patient, of increasing the supervisee's capacity to treat his or her patient, and of providing the supervisee with a novel, growth-enhancing relationship.

  18. WLAN Fingerprint Indoor Positioning Strategy Based on Implicit Crowdsourcing and Semi-Supervised Learning

    Directory of Open Access Journals (Sweden)

    Chunjing Song

    2017-11-01

    Full Text Available Wireless local area network (WLAN fingerprint positioning is an indoor localization technique with high accuracy and low hardware requirements. However, collecting received signal strength (RSS samples for the fingerprint database is time-consuming and labor-intensive, hindering the use of this technique. The popular crowdsourcing sampling technique has been introduced to reduce the workload of sample collection, but has two challenges: one is the heterogeneity of devices, which can significantly affect the positioning accuracy; the other is the requirement of users’ intervention in traditional crowdsourcing, which reduces the practicality of the system. In response to these challenges, we have proposed a new WLAN indoor positioning strategy, which incorporates a new preprocessing method for RSS samples, the implicit crowdsourcing sampling technique, and a semi-supervised learning algorithm. First, implicit crowdsourcing does not require users’ intervention. The acquisition program silently collects unlabeled samples, the RSS samples, without information about the position. Secondly, to cope with the heterogeneity of devices, the preprocessing method maps all the RSS values of samples to a uniform range and discretizes them. Finally, by using a large number of unlabeled samples with some labeled samples, Co-Forest, the introduced semi-supervised learning algorithm, creates and repeatedly refines a random forest ensemble classifier that performs well for location estimation. The results of experiments conducted in a real indoor environment show that the proposed strategy reduces the demand for large quantities of labeled samples and achieves good positioning accuracy.

  19. Classification of gene expression data: A hubness-aware semi-supervised approach.

    Science.gov (United States)

    Buza, Krisztian

    2016-04-01

    Classification of gene expression data is the common denominator of various biomedical recognition tasks. However, obtaining class labels for large training samples may be difficult or even impossible in many cases. Therefore, semi-supervised classification techniques are required as semi-supervised classifiers take advantage of unlabeled data. Gene expression data is high-dimensional which gives rise to the phenomena known under the umbrella of the curse of dimensionality, one of its recently explored aspects being the presence of hubs or hubness for short. Therefore, hubness-aware classifiers have been developed recently, such as Naive Hubness-Bayesian k-Nearest Neighbor (NHBNN). In this paper, we propose a semi-supervised extension of NHBNN which follows the self-training schema. As one of the core components of self-training is the certainty score, we propose a new hubness-aware certainty score. We performed experiments on publicly available gene expression data. These experiments show that the proposed classifier outperforms its competitors. We investigated the impact of each of the components (classification algorithm, semi-supervised technique, hubness-aware certainty score) separately and showed that each of these components are relevant to the performance of the proposed approach. Our results imply that our approach may increase classification accuracy and reduce computational costs (i.e., runtime). Based on the promising results presented in the paper, we envision that hubness-aware techniques will be used in various other biomedical machine learning tasks. In order to accelerate this process, we made an implementation of hubness-aware machine learning techniques publicly available in the PyHubs software package (http://www.biointelligence.hu/pyhubs) implemented in Python, one of the most popular programming languages of data science. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  20. GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting

    Directory of Open Access Journals (Sweden)

    Lintao Yang

    2018-01-01

    Full Text Available With the development of smart power grids, communication network technology and sensor technology, there has been an exponential growth in complex electricity load data. Irregular electricity load fluctuations caused by the weather and holiday factors disrupt the daily operation of the power companies. To deal with these challenges, this paper investigates a day-ahead electricity peak load interval forecasting problem. It transforms the conventional continuous forecasting problem into a novel interval forecasting problem, and then further converts the interval forecasting problem into the classification forecasting problem. In addition, an indicator system influencing the electricity load is established from three dimensions, namely the load series, calendar data, and weather data. A semi-supervised feature selection algorithm is proposed to address an electricity load classification forecasting issue based on the group method of data handling (GMDH technology. The proposed algorithm consists of three main stages: (1 training the basic classifier; (2 selectively marking the most suitable samples from the unclassified label data, and adding them to an initial training set; and (3 training the classification models on the final training set and classifying the test samples. An empirical analysis of electricity load dataset from four Chinese cities is conducted. Results show that the proposed model can address the electricity load classification forecasting problem more efficiently and effectively than the FW-Semi FS (forward semi-supervised feature selection and GMDH-U (GMDH-based semi-supervised feature selection for customer classification models.

  1. Supervision som undervisningsform i voksenspecialundervisningen

    DEFF Research Database (Denmark)

    Kristensen, René

    2000-01-01

    Supervision som undervisningsform i voksenspecialundervisningen. Procesarbejde i undervisning af voksne.......Supervision som undervisningsform i voksenspecialundervisningen. Procesarbejde i undervisning af voksne....

  2. Multi combined Adlerian supervision in Counseling

    OpenAIRE

    Gungor, Abdi

    2017-01-01

    For counselor professional and counselor education, supervision is an important process, in which more experienced professional helps and guides less experienced professional. To provide an effective and beneficial supervision, various therapy, development, or process based approaches and models have been developed. In addition, different eclectic models integrating more than one model have been developed. In this paper, as a supervision model, multi combined Adlerian supervision model is pro...

  3. Nursing supervision for care comprehensiveness

    Directory of Open Access Journals (Sweden)

    Lucieli Dias Pedreschi Chaves

    Full Text Available ABSTRACT Objective: To reflect on nursing supervision as a management tool for care comprehensiveness by nurses, considering its potential and limits in the current scenario. Method: A reflective study based on discourse about nursing supervision, presenting theoretical and practical concepts and approaches. Results: Limits on the exercise of supervision are related to the organization of healthcare services based on the functional and clinical model of care, in addition to possible gaps in the nurse training process and work overload. Regarding the potential, researchers emphasize that supervision is a tool for coordinating care and management actions, which may favor care comprehensiveness, and stimulate positive attitudes toward cooperation and contribution within teams, co-responsibility, and educational development at work. Final considerations: Nursing supervision may help enhance care comprehensiveness by implying continuous reflection on including the dynamics of the healthcare work process and user needs in care networks.

  4. Learning Dynamics in Doctoral Supervision

    DEFF Research Database (Denmark)

    Kobayashi, Sofie

    investigates learning opportunities in supervision with multiple supervisors. This was investigated through observations and recording of supervision, and subsequent analysis of transcripts. The analyses used different perspectives on learning; learning as participation, positioning theory and variation theory....... The research illuminates how learning opportunities are created in the interaction through the scientific discussions. It also shows how multiple supervisors can contribute to supervision by providing new perspectives and opinions that have a potential for creating new understandings. The combination...... of different theoretical frameworks from the perspectives of learning as individual acquisition and a sociocultural perspective on learning contributed to a nuanced illustration of the otherwise implicit practices of supervision....

  5. Supervision and group dynamics

    DEFF Research Database (Denmark)

    Hansen, Søren; Jensen, Lars Peter

    2004-01-01

     An important aspect of the problem based and project organized study at Aalborg University is the supervision of the project groups. At the basic education (first year) it is stated in the curriculum that part of the supervisors' job is to deal with group dynamics. This is due to the experience...... that many students are having difficulties with practical issues such as collaboration, communication, and project management. Most supervisors either ignore this demand, because they do not find it important or they find it frustrating, because they do not know, how to supervise group dynamics...... as well as at Aalborg University. The first visible result has been participating supervisors telling us that the course has inspired them to try supervising group dynamics in the future. This paper will explore some aspects of supervising group dynamics as well as, how to develop the Aalborg model...

  6. Clinical Supervision in Denmark

    DEFF Research Database (Denmark)

    Jacobsen, Claus Haugaard

    2011-01-01

    Core Questionnaire (DPCCQ) has only few questions on supervision. To rectify this limitation, a recent Danish version of the DPCCQ included two new sections on supervision, one focusing on supervisees and another on supervisors and their supervisory training. This paper presents our initial findings...

  7. Networks of Professional Supervision

    Science.gov (United States)

    Annan, Jean; Ryba, Ken

    2013-01-01

    An ecological analysis of the supervisory activity of 31 New Zealand school psychologists examined simultaneously the theories of school psychology, supervision practices, and the contextual qualities that mediated participants' supervisory actions. The findings indicated that the school psychologists worked to achieve the supervision goals of…

  8. Supervised Convolutional Sparse Coding

    KAUST Repository

    Affara, Lama Ahmed

    2018-04-08

    Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. In this work, we extend the applicability of this model by proposing a supervised approach to convolutional sparse coding, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements to be discriminative. Experimental results show that using supervised convolutional learning results in two key advantages. First, we learn more semantically relevant filters in the dictionary and second, we achieve improved image reconstruction on unseen data.

  9. (Off-label drug use for children at community pharmacies in Yogyakarta, Indonesia

    Directory of Open Access Journals (Sweden)

    Ndaru Setyaningrum

    2017-12-01

    Full Text Available Population of children is at risk of getting off-label medication because of its particular condition. This study was conducted to find out how the prevalence of off-label drug use for children at community pharmacies in Yogyakarta. This was a retrospective, medical record-based study using the 2014-2015. The study subjects consisted of children under 12 years old. About 828 prescriptions were reviewed, 268 were included accord with completeness diagnose data in patients medical records. The accumulative of drug use among 268 prescriptions were 816 drugs use with 76 item drugs. We have identified 268 prescriptions, of those 268 prescriptions, we found off label drugs in 57 prescriptions (21%. identified, off-label use accounted for 57 prescriptions (21%. The prevalence of off-label use classified as off-label age accounted for 91 use (11.1%; off-label indications accounted for 7 use (0.8%; and did not find off-label category dosage, route of administration and contraindication. The three highest use off-label drugs respectively pseudoephedrine accounted for 47 (5.7%, tripolidine 20 (2.4%, and dextromethorphan 14 (1.7% of all drug use. Based on the results of this study, we found that the use of off-label drugs in children is quite high (21% so that supervision-related risks of drug use need to be done.

  10. Educational Supervision Appropriate for Psychiatry Trainee's Needs

    Science.gov (United States)

    Rele, Kiran; Tarrant, C. Jane

    2010-01-01

    Objective: The authors studied the regularity and content of supervision sessions in one of the U.K. postgraduate psychiatric training schemes (Mid-Trent). Methods: A questionnaire sent to psychiatry trainees assessed the timing and duration of supervision, content and protection of supervision time, and overall quality of supervision. The authors…

  11. Tværfaglig supervision

    DEFF Research Database (Denmark)

    Tværfaglig supervision dækker over supervision af forskellige faggrupper. Det er en kompleks disciplin der stiller store krav tl supervisor. Bogens første del præsenterer fire faglige supervisionsmodeller: En almen, en psykodynamisk, en kognitiv adfærdsterapeutisk og en narrativ. Anden del...

  12. Methods of Feminist Family Therapy Supervision.

    Science.gov (United States)

    Prouty, Anne M.; Thomas, Volker; Johnson, Scott; Long, Janie K.

    2001-01-01

    Presents three supervision methods which emerged from a qualitative study of the experiences of feminist family therapy supervisors and the therapists they supervised: the supervision contract, collaborative methods, and hierarchical methods. Provides a description of the participants' experiences of these methods and discusses their fit with…

  13. Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

    Science.gov (United States)

    Lu, Shen; Xia, Yong; Cai, Tom Weidong; Feng, David Dagan

    2015-01-01

    Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine learning based dementia classification methods using medical imaging have been proposed and most of them achieve accurate results. However, most of these methods make use of supervised learning requiring fully labeled image dataset, which usually is not practical in real clinical environment. Using large amount of unlabeled images can improve the dementia classification performance. In this study we propose a new semi-supervised dementia classification method based on random manifold learning with affinity regularization. Three groups of spatial features are extracted from positron emission tomography (PET) images to construct an unsupervised random forest which is then used to regularize the manifold learning objective function. The proposed method, stat-of-the-art Laplacian support vector machine (LapSVM) and supervised SVM are applied to classify AD and normal controls (NC). The experiment results show that learning with unlabeled images indeed improves the classification performance. And our method outperforms LapSVM on the same dataset.

  14. 28 CFR 2.91 - Supervision responsibility.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Supervision responsibility. 2.91 Section 2.91 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS District of Columbia Code: Prisoners and Parolees § 2.91 Supervision responsibility. (a) Pursuan...

  15. 20 CFR 655.30 - Supervised recruitment.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Supervised recruitment. 655.30 Section 655.30... Workers) § 655.30 Supervised recruitment. (a) Supervised recruitment. Where an employer is found to have... failed to adequately conduct recruitment activities or failed in any obligation of this part, the CO may...

  16. New syntheses of No-carrier-added 123I-labeled agents via organoborane chemistry

    International Nuclear Information System (INIS)

    Kabalka, G.W.

    1985-01-01

    No-carrier-added 123 I-labeled agents are readily prepared via the reaction of organoboranes with sodium iodide- 123 I in the presence of mild oxidizing agents. The reactions are rapid and regiospecific, and they produce excellent yields of the labeled products. The organoboranes are readily prepared from alkenes and alkynes via the hydroboration reaction. A wide variety of functional groups are tolerated by the hydroboration-iodination sequence. The sequence has been utilized to prepare 123 I-labeled steroids and fatty acids, as well as a number of labeled esters, and aromatic derivatives

  17. Man-machine supervision

    International Nuclear Information System (INIS)

    Montmain, J.

    2005-01-01

    Today's complexity of systems where man is involved has led to the development of more and more sophisticated information processing systems where decision making has become more and more difficult. The operator task has moved from operation to supervision and the production tool has become indissociable from its numerical instrumentation and control system. The integration of more and more numerous and sophisticated control indicators in the control room does not necessary fulfill the expectations of the operation team. It is preferable to develop cooperative information systems which are real situation understanding aids. The stake is not the automation of operators' cognitive tasks but the supply of a reasoning help. One of the challenges of interactive information systems is the selection, organisation and dynamical display of information. The efficiency of the whole man-machine system depends on the communication interface efficiency. This article presents the principles and specificities of man-machine supervision systems: 1 - principle: operator's role in control room, operator and automation, monitoring and diagnosis, characteristics of useful models for supervision; 2 - qualitative reasoning: origin, trends, evolutions; 3 - causal reasoning: causality, causal graph representation, causal and diagnostic graph; 4 - multi-points of view reasoning: multi flow modeling method, Sagace method; 5 - approximate reasoning: the symbolic numerical interface, the multi-criteria decision; 6 - example of application: supervision in a spent-fuel reprocessing facility. (J.S.)

  18. Evolution in banking supervision

    OpenAIRE

    Edward J. Stevens

    2000-01-01

    Banking supervision must keep pace with technical innovations in the banking industry. The international Basel Committee on Banking Supervision currently is reviewing public comments on its proposed new method for judging whether a bank maintains enough capital to absorb unexpected losses. This Economic Commentary explains how existing standards became obsolete and describes the new plan.

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

    Science.gov (United States)

    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.

  20. High-Throughput Block Optical DNA Sequence Identification.

    Science.gov (United States)

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

    2018-01-01

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

  1. Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

    Science.gov (United States)

    Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

    2017-09-01

    Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

  2. Current Risk Management Practices in Psychotherapy Supervision.

    Science.gov (United States)

    Mehrtens, Ilayna K; Crapanzano, Kathleen; Tynes, L Lee

    2017-12-01

    Psychotherapy competence is a core skill for psychiatry residents, and psychotherapy supervision is a time-honored approach to teaching this skill. To explore the current supervision practices of psychiatry training programs, a 24-item questionnaire was sent to all program directors of Accreditation Council for Graduate Medical Education (ACGME)-approved adult psychiatry programs. The questionnaire included items regarding adherence to recently proposed therapy supervision practices aimed at reducing potential liability risk. The results suggested that current therapy supervision practices do not include sufficient management of the potential liability involved in therapy supervision. Better protections for patients, residents, supervisors and the institutions would be possible with improved credentialing practices and better documentation of informed consent and supervision policies and procedures. © 2017 American Academy of Psychiatry and the Law.

  3. Supervised Kernel Optimized Locality Preserving Projection with Its Application to Face Recognition and Palm Biometrics

    Directory of Open Access Journals (Sweden)

    Chuang Lin

    2015-01-01

    Full Text Available Kernel Locality Preserving Projection (KLPP algorithm can effectively preserve the neighborhood structure of the database using the kernel trick. We have known that supervised KLPP (SKLPP can preserve within-class geometric structures by using label information. However, the conventional SKLPP algorithm endures the kernel selection which has significant impact on the performances of SKLPP. In order to overcome this limitation, a method named supervised kernel optimized LPP (SKOLPP is proposed in this paper, which can maximize the class separability in kernel learning. The proposed method maps the data from the original space to a higher dimensional kernel space using a data-dependent kernel. The adaptive parameters of the data-dependent kernel are automatically calculated through optimizing an objective function. Consequently, the nonlinear features extracted by SKOLPP have larger discriminative ability compared with SKLPP and are more adaptive to the input data. Experimental results on ORL, Yale, AR, and Palmprint databases showed the effectiveness of the proposed method.

  4. A Study of Supervision of China's Commercial Banks from the Perspective of the Trinity-Characteristics of Bank Supervision System

    Institute of Scientific and Technical Information of China (English)

    LV Jianglin; HUANG Guang

    2015-01-01

    Based on the theoretical analysis,this paper applies the entropy method to establish a comprehensive index system for the evaluation of the overall level of risk control and comprehensive efficiency of the supervision of China's commercial banks.Considering the trinity-characteristics of bank supervision system consisting of the People's Bank of China(PBC),the CBRC and the financial offices of local governments,the following conclusions have been drawn:the amount of penalties on banking illegal transactions is not correlated with the supervision efficiency of China's commercial banks;the capital adequacy ratio,the loan to deposit ratio,the percentage point of the non-performing loan rate of urban commercial banks higher than that of the national joint-stock banks are negatively correlated with the supervision efficiency of China 's commercial banks;the total asset variation of the PBC and the different loan balance in local and foreign currency of the banks are positively correlated with the supervision efficiency of China's commercial banks,but the effect is minor.Therefore,China should give the capital adequacy ratio a full play in the bank supervision,accelerate the construction of supervision information system and improve the supervision function of the local governments.

  5. Classification without labels: learning from mixed samples in high energy physics

    Science.gov (United States)

    Metodiev, Eric M.; Nachman, Benjamin; Thaler, Jesse

    2017-10-01

    Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the simulation. In this paper, we introduce the paradigm of classification without labels (CWoLa) in which a classifier is trained to distinguish statistical mixtures of classes, which are common in collider physics. Crucially, neither individual labels nor class proportions are required, yet we prove that the optimal classifier in the CWoLa paradigm is also the optimal classifier in the traditional fully-supervised case where all label information is available. After demonstrating the power of this method in an analytical toy example, we consider a realistic benchmark for collider physics: distinguishing quark- versus gluon-initiated jets using mixed quark/gluon training samples. More generally, CWoLa can be applied to any classification problem where labels or class proportions are unknown or simulations are unreliable, but statistical mixtures of the classes are available.

  6. Minimal hardware Bluetooth tracking for long-term at-home elder supervision.

    Science.gov (United States)

    Kelly, Damian; McLoone, Sean; Farrell, Ronan

    2010-01-01

    The ability to automatically detect the location of an elder within their own home is a significant enabler of remote elder supervision and interaction applications. This location information is typically generated via a myriad of sensors throughout the home environment. Even with high sensor redundancy, there are still situations where traditional elder monitoring systems are unable to resolve the location of the elder. This work develops a minimal infrastructure radio-frequency localisation system for long-term elder location tracking. An RFID room-labelling technique is employed and with it, the localisation system developed in this work is shown to exhibit superior performance to more traditional localisation systems in realistic long-term deployments.

  7. Supervision Experiences of Professional Counselors Providing Crisis Counseling

    Science.gov (United States)

    Dupre, Madeleine; Echterling, Lennis G.; Meixner, Cara; Anderson, Robin; Kielty, Michele

    2014-01-01

    In this phenomenological study, the authors explored supervision experiences of 13 licensed professional counselors in situations requiring crisis counseling. Five themes concerning crisis and supervision were identified from individual interviews. Findings support intensive, immediate crisis supervision and postlicensure clinical supervision.

  8. GIF Video Sentiment Detection Using Semantic Sequence

    Directory of Open Access Journals (Sweden)

    Dazhen Lin

    2017-01-01

    Full Text Available With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs.

  9. Intelligent multivariate process supervision

    International Nuclear Information System (INIS)

    Visuri, Pertti.

    1986-01-01

    This thesis addresses the difficulties encountered in managing large amounts of data in supervisory control of complex systems. Some previous alarm and disturbance analysis concepts are reviewed and a method for improving the supervision of complex systems is presented. The method, called multivariate supervision, is based on adding low level intelligence to the process control system. By using several measured variables linked together by means of deductive logic, the system can take into account the overall state of the supervised system. Thus, it can present to the operators fewer messages with higher information content than the conventional control systems which are based on independent processing of each variable. In addition, the multivariate method contains a special information presentation concept for improving the man-machine interface. (author)

  10. On psychoanalytic supervision as signature pedagogy.

    Science.gov (United States)

    Watkins, C Edward

    2014-04-01

    What is signature pedagogy in psychoanalytic education? This paper examines that question, considering why psychoanalytic supervision best deserves that designation. In focusing on supervision as signature pedagogy, I accentuate its role in building psychoanalytic habits of mind, habits of hand, and habits of heart, and transforming theory and self-knowledge into practical product. Other facets of supervision as signature pedagogy addressed in this paper include its features of engagement, uncertainty, formation, and pervasiveness, as well as levels of surface, deep, and implicit structure. Epistemological, ontological, and axiological in nature, psychoanalytic supervision engages trainees in learning to do, think, and value what psychoanalytic practitioners in the field do, think, and value: It is, most fundamentally, professional preparation for competent, "good work." In this paper, effort is made to shine a light on and celebrate the pivotal role of supervision in "making" or developing budding psychoanalysts and psychoanalytic psychotherapists. Now over a century old, psychoanalytic supervision remains unparalleled in (1) connecting and integrating conceptualization and practice, (2) transforming psychoanalytic theory and self-knowledge into an informed analyzing instrument, and (3) teaching, transmitting, and perpetuating the traditions, practice, and culture of psychoanalytic treatment.

  11. Abusive Supervision and Subordinate Performance : Instrumentality Considerations in the Emergence and Consequences of Abusive Supervision

    NARCIS (Netherlands)

    Walter, Frank; Lam, Catherine K.; van der Vegt, Geert; Huang, X.; Miao, Q.

    Drawing from moral exclusion theory, this article examines outcome dependence and interpersonal liking as key boundary conditions for the linkage between perceived subordinate performance and abusive supervision. Moreover, it investigates the role of abusive supervision for subordinates' subsequent,

  12. Supervision of radiation environment management of nuclear facilities

    International Nuclear Information System (INIS)

    Luo Mingyan

    2013-01-01

    Through literature and documents, the basis, content and implementation of the supervision of radiation environment management of nuclear facilities were defined. Such supervision was extensive and complicated with various tasks and overlapping duties, and had large social impact. Therefore, it was recommend to make further research on this supervision should be done, clarify and specify responsibilities of the executor of the supervision so as to achieve institutionalization, standardization and routinization of the supervision. (author)

  13. Skærpet bevidsthed om supervision

    DEFF Research Database (Denmark)

    Pedersen, Inge Nygaard

    2002-01-01

    This article presents a historical survey of the initiatives which have taken place in european music therapy towards developing a deeper consciousness about supervision. Supervision as a disciplin in music therapy training, as a maintenance of music therapy profession and as a postgraduate...... training for examined music therapists. Definitions are presented and methods developed by working groups in european music therapy supervision are presented....

  14. Human Supervision of Multiple Autonomous Vehicles

    Science.gov (United States)

    2013-03-22

    AFRL-RH-WP-TR-2013-0143 HUMAN SUPERVISION OF MULTIPLE AUTONOMOUS VEHICLES Heath A. Ruff Ball...REPORT TYPE Interim 3. DATES COVERED (From – To) 09-16-08 – 03-22-13 4. TITLE AND SUBTITLE HUMAN SUPERVISION OF MULTIPLE AUTONOMOUS VEHICLES 5a...Supervision of Multiple Autonomous Vehicles To support the vision of a system that enables a single operator to control multiple next-generation

  15. Providing effective supervision in clinical neuropsychology.

    Science.gov (United States)

    Stucky, Kirk J; Bush, Shane; Donders, Jacobus

    2010-01-01

    A specialty like clinical neuropsychology is shaped by its selection of trainees, educational standards, expected competencies, and the structure of its training programs. The development of individual competency in this specialty is dependent to a considerable degree on the provision of competent supervision to its trainees. In clinical neuropsychology, as in other areas of professional health-service psychology, supervision is the most frequently used method for teaching a variety of skills, including assessment, report writing, differential diagnosis, and treatment. Although much has been written about the provision of quality supervision in clinical and counseling psychology, very little published guidance is available regarding the teaching and provision of supervision in clinical neuropsychology. The primary focus of this article is to provide a framework and guidance for the development of suggested competency standards for training of neuropsychological supervisors, particularly at the residency level. In this paper we outline important components of supervision for neuropsychology trainees and suggest ways in which clinicians can prepare for supervisory roles. Similar to Falender and Shafranske (2004), we propose a competency-based approach to supervision that advocates for a science-informed, formalized, and objective process that clearly delineates the competencies required for good supervisory practice. As much as possible, supervisory competencies are related to foundational and functional competencies in professional psychology, as well as recent legislative initiatives mandating training in supervision. It is our hope that this article will foster further discussion regarding this complex topic, and eventually enhance training in clinical neuropsychology.

  16. BRONCHIAL ASTHMA SUPERVISION AMONG TEENAGERS

    Directory of Open Access Journals (Sweden)

    N.M. Nenasheva

    2008-01-01

    Full Text Available The article highlights the results of the act test based bronchial asthma supervision evaluation among teenagers and defines the interrelation of the objective and subjective asthma supervision parameters. The researchers examined 214 male teenagers aged from 16 to 18, suffering from the bronchial asthma, who were sent to the allergy department to verify the diagnosis. Bronchial asthma supervision evaluation was assisted by the act test. The research has showed that over a half (56% of teenagers, suffering from mild bronchial asthma, mention its un control course, do not receive any adequate pharmacotherapy and are consequently a risk group in terms of the bronchial asthma exacerbation. Act test results correlate with the functional indices (fev1, as well as with the degree of the bronchial hyperresponsiveness, which is one of the markers of an allergic inflammation in the lower respiratory passages.Key words: bronchial asthma supervision, act test, teenagers.

  17. Multicultural Supervision: What Difference Does Difference Make?

    Science.gov (United States)

    Eklund, Katie; Aros-O'Malley, Megan; Murrieta, Imelda

    2014-01-01

    Multicultural sensitivity and competency represent critical components to contemporary practice and supervision in school psychology. Internship and supervision experiences are a capstone experience for many new school psychologists; however, few receive formal training and supervision in multicultural competencies. As an increased number of…

  18. Projected estimators for robust semi-supervised classification

    NARCIS (Netherlands)

    Krijthe, J.H.; Loog, M.

    2017-01-01

    For semi-supervised techniques to be applied safely in practice we at least want methods to outperform their supervised counterparts. We study this question for classification using the well-known quadratic surrogate loss function. Unlike other approaches to semi-supervised learning, the

  19. 28 CFR 2.207 - Supervision reports to Commission.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Supervision reports to Commission. 2.207 Section 2.207 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS District of Columbia Supervised Releasees § 2.207 Supervision reports to Commission. A...

  20. Postgraduate research supervision in a socially distributed ...

    African Journals Online (AJOL)

    Postgraduate supervision is a higher education practice with a long history. Through the conventional "apprenticeship" model postgraduate supervision has served as an important vehicle of intellectual inheritance between generations. However, this model of supervision has come under scrutiny as a consequence of the ...

  1. Supervision Experiences of New Professional School Counselors

    Science.gov (United States)

    Bultsma, Shawn A.

    2012-01-01

    This qualitative study examined the supervision experiences of 11 new professional school counselors. They reported that their supervision experiences were most often administrative in nature; reports of clinical and developmental supervision were limited to participants whose supervisors were licensed as professional counselors. In addition,…

  2. Online supervision at the university

    DEFF Research Database (Denmark)

    Bengtsen, Søren Smedegaard; Jensen, Gry Sandholm

    2015-01-01

    supervision proves unhelpful when trying to understand how online supervision and feedback is a pedagogical phenomenon in its own right, and irreducible to the face-to-face context. Secondly we show that not enough attention has been given to the way different digital tools and platforms influence...... pedagogy we forge a new concept of “format supervision” that enables supervisors to understand and reflect their supervision practice, not as caught in the physical-virtual divide, but as a choice between face-to-face and online formats that each conditions the supervisory dialogue in their own particular...

  3. Enzymatic labelling of. gamma. -globulin and insulin with iodine-125

    Energy Technology Data Exchange (ETDEWEB)

    Lucka, B; Russin, K [Institute of Nuclear Physics, Krakow (Poland)

    1979-01-01

    The parameters of enzymatic labelling of proteins with iodine 125 were examined. The manner and sequence of reagent addition, the effects of reagent concentration, reaction time and total Na/sup 125/I activity on the labelling yield were determined.

  4. Multicultural supervision: lessons learned about an ongoing struggle.

    Science.gov (United States)

    Christiansen, Abigail Tolhurst; Thomas, Volker; Kafescioglu, Nilufer; Karakurt, Gunnur; Lowe, Walter; Smith, William; Wittenborn, Andrea

    2011-01-01

    This article examines the experiences of seven diverse therapists in a supervision course as they wrestled with the real-world application of multicultural supervision. Existing literature on multicultural supervision does not address the difficulties that arise in addressing multicultural issues in the context of the supervision relationship. The experiences of six supervisory candidates and one mentoring supervisor in addressing multicultural issues in supervision are explored. Guidelines for conversations regarding multicultural issues are provided. © 2011 American Association for Marriage and Family Therapy.

  5. Optimum supervision intervals and order of supervision in nuclear reactor protective systems

    International Nuclear Information System (INIS)

    Kontoleon, J.M.

    1978-01-01

    The optimum inspection strategy of an m-out-of-n:G nuclear reactor protective system with nonidentical units is analyzed. A 2-out-of-4:G system is used to formulate a multi-variable optimization problem to determine (a) the optimum order of supervision of the units and (b) the optimum supervision intervals between units. The case of systems with identical units is a special case of the above. Numerical results are derived using a computer algorithm

  6. Safety supervision on high-pressure gas regulations

    International Nuclear Information System (INIS)

    Lee, Won Il

    1991-01-01

    The first part lists the regulation on safety supervision of high-pressure gas, enforcement ordinance on high-pressure gas safety supervision and enforcement regulations about high-pressure gas safety supervision. The second part indicates safety regulations on liquefied petroleum gas and business, enforcement ordinance of safety on liquefied petroleum gas and business, enforcement regulation of safety supervision over liquefied petroleum gas and business. The third part lists regulation on gas business, enforcement ordinance and enforcement regulations on gas business. Each part has theory and explanation for questions.

  7. Nuclear safety culture and nuclear safety supervision

    International Nuclear Information System (INIS)

    Chai Jianshe

    2013-01-01

    In this paper, the author reviews systematically and summarizes up the development process and stage characteristics of nuclear safety culture, analysis the connotation and characteristics of nuclear safety culture, sums up the achievements of our country's nuclear safety supervision, dissects the challenges and problems of nuclear safety supervision. This thesis focused on the relationship between nuclear safety culture and nuclear safety supervision, they are essential differences, but there is a close relationship. Nuclear safety supervision needs to introduce some concepts of nuclear safety culture, lays emphasis on humanistic care and improves its level and efficiency. Nuclear safety supervision authorities must strengthen nuclear safety culture training, conduct the development of nuclear safety culture, make sure that nuclear safety culture can play significant roles. (author)

  8. Exploring paraprofessional and classroom factors affecting teacher supervision.

    Science.gov (United States)

    Irvin, Dwight W; Ingram, Paul; Huffman, Jonathan; Mason, Rose; Wills, Howard

    2018-02-01

    Paraprofessionals serve a primary role in supporting students with disabilities in the classroom, which necessitates teachers' supervision as a means to improve their practice. Yet, little is known regarding what factors affect teacher supervision. We sought to identify how paraprofessional competence and classroom type affected the levels of teacher direction. We administered an adapted version of the Paraprofessional Needs, Knowledge & Tasks Survey and the Survey for Teachers Supervising Paraprofessionals to teachers supervising paraprofessionals in elementary schools. Structural Equation Modeling was used to examine the link between paraprofessional competence and classroom factors affecting the level of teacher supervision. Our results indicated that when teachers perceived paraprofessionals as being more skilled, they provided more supervision, and when more supervision was provided the less they thought paraprofessionals should be doing their assigned tasks. Additionally, paraprofessionals working in classrooms with more students with mild disabilities received less supervision than paraprofessionals working in classrooms with more students with moderate-to-severe disabilities. Those paraprofessionals in classrooms serving mostly children with mild disabilities were also perceived as having lower levels of skill competence than those serving in classrooms with students with more moderate-to-severe disabilities. By understanding the factors that affect teacher supervision, policy and professional development opportunities can be refined/developed to better support both supervising teachers and paraprofessionals and, in turn, improve the outcomes of children with disabilities. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Abusive Supervision Scale Development in Indonesia

    OpenAIRE

    Wulani, Fenika; Purwanto, Bernadinus M; Handoko, Hani

    2014-01-01

    The purpose of this study was to develop a scale of abusive supervision in Indonesia. The study was conducted with a different context and scale development method from Tepper’s (2000) abusive supervision scale. The abusive supervision scale from Tepper (2000) was developed in the U.S., which has a cultural orientation of low power distance. The current study was conducted in Indonesia, which has a high power distance. This study used interview procedures to obtain information about superviso...

  10. Intuitive expertise in ICT graduate supervision

    Directory of Open Access Journals (Sweden)

    Jill Jameson

    2002-12-01

    Full Text Available Intuitive expertise in the application of advanced interdisciplinary facilitation is the subject of this personal reflection on the graduate supervisory style of Professor David Squires in computers in education. This single-case reflective study examines the characteristics of effective supervision observed during masters and doctoral supervision at King's College in the years 1990-9. Interdisciplinarity in ICT graduate studies particularly requires a fluency of supervisory expertise in enabling supervisees to combine multiple complex perspectives from a number of fields of knowledge. Intuitive combinatory aspects of supervision are highlighted in this reflection on the role carried out by an academic expert in facilitating student success. This is examined from a perspective incorporating affective as well as intellectual elements, informed by characteristics identified in professional sports and performing arts coaching/mentoring. Key characteristics comprising a model of intuitive expertise in ICT graduate supervision were outlined. The resultant portrait aims to complement existing literature on graduate supervision, with reference to the field of ICTI computers in education relating to student hypermedia composition.

  11. 46 CFR 131.420 - Manning and supervision.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Manning and supervision. 131.420 Section 131.420 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) OFFSHORE SUPPLY VESSELS OPERATIONS Sufficiency and Supervision of Crew of Survival Craft § 131.420 Manning and supervision. (a) There must be enough trained persons aboard each survival craf...

  12. 32 CFR 631.3 - Supervision.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Supervision. 631.3 Section 631.3 National Defense Department of Defense (Continued) DEPARTMENT OF THE ARMY (CONTINUED) LAW ENFORCEMENT AND CRIMINAL INVESTIGATIONS ARMED FORCES DISCIPLINARY CONTROL BOARDS AND OFF-INSTALLATION LIAISON AND OPERATIONS General § 631.3 Supervision. The following will...

  13. Online supervision at the university - A comparative study of supervision on student assignments face-to-face and online

    Directory of Open Access Journals (Sweden)

    Søren Smedegaard Bengtsen

    2015-09-01

    Full Text Available Through an empirical study of supervision on student assignments at the university across face-to-face and online settings, we show firstly the limiting implications of traditional dichotomies between face-to-face and online supervision. Secondly we show that more attention must be given to the way different digital tools influence the supervisory dialogue. These findings illustrate a form of ‘torn pedagogy’; that online tools and platforms destabilize and tear traditional understandings of supervision pedagogy apart. Also we forge a new concept of “format supervision” that enables supervisors to understand and reflect their supervision practice as a deliberate choice between face-to-face and online formats.

  14. Online supervision at the university - A comparative study of supervision on student assignments face-to-face and online

    Directory of Open Access Journals (Sweden)

    Søren Smedegaard Bengtsen

    2015-02-01

    Full Text Available Through an empirical study of supervision on student assignments at the university across face-to-face and online settings, we show firstly the limiting implications of traditional dichotomies between face-to-face and online supervision. Secondly we show that more attention must be given to the way different digital tools influence the supervisory dialogue. These findings illustrate a form of ‘torn pedagogy’; that online tools and platforms destabilize and tear traditional understandings of supervision pedagogy apart. Also we forge a new concept of “format supervision” that enables supervisors to understand and reflect their supervision practice as a deliberate choice between face-to-face and online formats.

  15. Combination of supervised and semi-supervised regression models for improved unbiased estimation

    DEFF Research Database (Denmark)

    Arenas-Garía, Jeronimo; Moriana-Varo, Carlos; Larsen, Jan

    2010-01-01

    In this paper we investigate the steady-state performance of semisupervised regression models adjusted using a modified RLS-like algorithm, identifying the situations where the new algorithm is expected to outperform standard RLS. By using an adaptive combination of the supervised and semisupervi......In this paper we investigate the steady-state performance of semisupervised regression models adjusted using a modified RLS-like algorithm, identifying the situations where the new algorithm is expected to outperform standard RLS. By using an adaptive combination of the supervised...

  16. Supervision in social work NGOs in Bihor County

    Directory of Open Access Journals (Sweden)

    Cristiana Marcela MARC

    2012-01-01

    Full Text Available This paper presents a qualitative research which aims at analyzing supervision in the social services provided by NGOs in Bihor County. We used the method of sociological investigation by means of interview and data collection was accomplished through the technique of individual semi-structured interview. The obtained responses demonstrate that individual supervision was mostly used and in most cases the professional supervisor was from outside the organization. The respondents considered that supervision reduces professional stress. The main problems encountered in the implementation of supervision are the lack of financial resources and the association of supervision with bureaucratic control.

  17. Medical supervision of radiation workers

    International Nuclear Information System (INIS)

    Santani, S.B.; Nandakumar, A.N.; Subramanian, G.

    1982-01-01

    The basic elements of an occupational medical supervision programme for radiation workers are very much the same as those relevant to other professions with some additional special features. This paper cites examples from literature and recommends measures such as spot checks and continuance of medical supervision even after a radiation worker leaves this profession. (author)

  18. Application of semi-supervised deep learning to lung sound analysis.

    Science.gov (United States)

    Chamberlain, Daniel; Kodgule, Rahul; Ganelin, Daniela; Miglani, Vivek; Fletcher, Richard Ribon

    2016-08-01

    The analysis of lung sounds, collected through auscultation, is a fundamental component of pulmonary disease diagnostics for primary care and general patient monitoring for telemedicine. Despite advances in computation and algorithms, the goal of automated lung sound identification and classification has remained elusive. Over the past 40 years, published work in this field has demonstrated only limited success in identifying lung sounds, with most published studies using only a small numbers of patients (typically Ndeep learning algorithm for automatically classify lung sounds from a relatively large number of patients (N=284). Focusing on the two most common lung sounds, wheeze and crackle, we present results from 11,627 sound files recorded from 11 different auscultation locations on these 284 patients with pulmonary disease. 890 of these sound files were labeled to evaluate the model, which is significantly larger than previously published studies. Data was collected with a custom mobile phone application and a low-cost (US$30) electronic stethoscope. On this data set, our algorithm achieves ROC curves with AUCs of 0.86 for wheeze and 0.74 for crackle. Most importantly, this study demonstrates how semi-supervised deep learning can be used with larger data sets without requiring extensive labeling of data.

  19. spa: Semi-Supervised Semi-Parametric Graph-Based Estimation in R

    Directory of Open Access Journals (Sweden)

    Mark Culp

    2011-04-01

    Full Text Available In this paper, we present an R package that combines feature-based (X data and graph-based (G data for prediction of the response Y . In this particular case, Y is observed for a subset of the observations (labeled and missing for the remainder (unlabeled. We examine an approach for fitting Y = Xβ + f(G where β is a coefficient vector and f is a function over the vertices of the graph. The procedure is semi-supervised in nature (trained on the labeled and unlabeled sets, requiring iterative algorithms for fitting this estimate. The package provides several key functions for fitting and evaluating an estimator of this type. The package is illustrated on a text analysis data set, where the observations are text documents (papers, the response is the category of paper (either applied or theoretical statistics, the X information is the name of the journal in which the paper resides, and the graph is a co-citation network, with each vertex an observation and each edge the number of times that the two papers cite a common paper. An application involving classification of protein location using a protein interaction graph and an application involving classification on a manifold with part of the feature data converted to a graph are also presented.

  20. Cultural Humility in Psychotherapy Supervision.

    Science.gov (United States)

    Hook, Joshua N; Watkins, C Edward; Davis, Don E; Owen, Jesse; Van Tongeren, Daryl R; Ramos, Marciana J

    2016-01-01

    As a core component of multicultural orientation, cultural humility can be considered an important attitude for clinical supervisees to adopt and practically implement. How can cultural humility be most meaningfully incorporated in supervision? In what ways can supervisors stimulate the development of a culturally humble attitude in our supervisees? We consider those questions in this paper and present a model for addressing cultural humility in clinical supervision. The primary focus is given to two areas: (a) modeling and teaching of cultural humility through interpersonal interactions in supervision, and (b) teaching cultural humility through outside activities and experiences. Two case studies illustrating the model are presented, and a research agenda for work in this area is outlined.

  1. Assessment of Counselors' Supervision Processes

    Science.gov (United States)

    Ünal, Ali; Sürücü, Abdullah; Yavuz, Mustafa

    2013-01-01

    The aim of this study is to investigate elementary and high school counselors' supervision processes and efficiency of their supervision. The interview method was used as it was thought to be better for realizing the aim of the study. The study group was composed of ten counselors who were chosen through purposeful sampling method. Data were…

  2. Predicting protein amidation sites by orchestrating amino acid sequence features

    Science.gov (United States)

    Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

    2017-08-01

    Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.

  3. Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

    Science.gov (United States)

    Jiang, Yizhang; Wu, Dongrui; Deng, Zhaohong; Qian, Pengjiang; Wang, Jun; Wang, Guanjin; Chung, Fu-Lai; Choi, Kup-Sze; Wang, Shitong

    2017-12-01

    Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and the amount of training data may not be enough. In addition, most machine learning approaches generate black-box models that are difficult to interpret. In this paper, we integrate transductive transfer learning, semi-supervised learning and TSK fuzzy system to tackle these three problems. More specifically, we use transfer learning to reduce the discrepancy in data distribution between the training and testing data, employ semi-supervised learning to use the unlabeled testing data to remedy the shortage of training data, and adopt TSK fuzzy system to increase model interpretability. Two learning algorithms are proposed to train the system. Our experimental results show that the proposed approaches can achieve better performance than many state-of-the-art seizure classification algorithms.

  4. Indirect MRI of 17 o-labeled water using steady-state sequences: Signal simulation and preclinical experiment.

    Science.gov (United States)

    Kudo, Kohsuke; Harada, Taisuke; Kameda, Hiroyuki; Uwano, Ikuko; Yamashita, Fumio; Higuchi, Satomi; Yoshioka, Kunihiro; Sasaki, Makoto

    2018-05-01

    Few studies have been reported for T 2 -weighted indirect 17 O imaging. To evaluate the feasibility of steady-state sequences for indirect 17 O brain imaging. Signal simulation, phantom measurements, and prospective animal experiments were performed in accordance with the institutional guidelines for animal experiments. Signal simulations of balanced steady-state free precession (bSSFP) were performed for concentrations of 17 O ranging from 0.037-1.600%. Phantom measurements with concentrations of 17 O water ranging from 0.037-1.566% were also conducted. Six healthy beagle dogs were scanned with intravenous administration of 20% 17 O-labeled water (1 mL/kg). Dynamic 3D-bSSFP scans were performed at 3T MRI. 17 O-labeled water was injected 60 seconds after the scan start, and the total scan duration was 5 minutes. Based on the result of signal simulation and phantom measurement, signal changes in the beagle dogs were measured and converted into 17 O concentrations. The 17 O concentrations were averaged for every 15 seconds, and compared to the baseline (30-45 sec) with Dunnett's multiple comparison tests. Signal simulation revealed that the relationships between 17 O concentration and the natural logarithm of relative signals were linear. The intraclass correlation coefficient between relative signals in phantom measurement and signal simulations was 0.974. In the animal experiments, significant increases in 17 O concentration (P O. At the end of scanning, mean respective 17 O concentrations of 0.084 ± 0.026%, 0.117 ± 0.038, 0.082 ± 0.037%, and 0.049 ± 0.004% were noted for the cerebral cortex, cerebellar cortex, cerebral white matter, and ventricle. Dynamic steady-state sequences were feasible for indirect 17 O imaging, and absolute quantification was possible. This method can be applied for the measurement of permeability and blood flow in the brain, and for kinetic analysis of cerebrospinal fluid. 2 Technical Efficacy: Stage 1 J. Magn. Reson

  5. Direct fluorescence anisotropy assay for cocaine using tetramethylrhodamine-labeled aptamer.

    Science.gov (United States)

    Liu, Yingxiong; Zhao, Qiang

    2017-06-01

    Development of simple, sensitive, and rapid method for cocaine detection is important in medicine and drug abuse monitoring. Taking advantage of fluorescence anisotropy and aptamer, this study reports a direct fluorescence anisotropy (FA) assay for cocaine by employing an aptamer probe with tetramethylrhodamine (TMR) labeled on a specific position. The binding of cocaine and the aptamer causes a structure change of the TMR-labeled aptamer, leading to changes of the interaction between labeled TMR and adjacent G bases in aptamer sequence, so FA of TMR varies with increasing of cocaine. After screening different labeling positions of the aptamer, including thymine (T) bases and terminals of the aptamer, we obtained a favorable aptamer probe with TMR labeled on the 25th base T in the sequence, which exhibited sensitive and significant FA-decreasing responses upon cocaine. Under optimized assay conditions, this TMR-labeled aptamer allowed for direct FA detection of cocaine as low as 5 μM. The maximum FA change reached about 0.086. This FA method also enabled the detection of cocaine spiked in diluted serum and urine samples, showing potential for applications. Graphical Abstract The binding of cocaine to the TMR-labeled aptamer causes conformation change and alteration of the intramolecular interaction between TMR and bases of aptamer, leading to variance of fluorescence anisotropy (FA) of TMR, so direct FA analyis of cocaine is achieved.

  6. Opportunities to Learn Scientific Thinking in Joint Doctoral Supervision

    Science.gov (United States)

    Kobayashi, Sofie; Grout, Brian W.; Rump, Camilla Østerberg

    2015-01-01

    Research into doctoral supervision has increased rapidly over the last decades, yet our understanding of how doctoral students learn scientific thinking from supervision is limited. Most studies are based on interviews with little work being reported that is based on observation of actual supervision. While joint supervision has become widely…

  7. Framing doctoral supervision as formative assessment

    DEFF Research Database (Denmark)

    Kobayashi, Sofie

    Doctoral supervision has been described through a number of models useful for understanding different aspects of supervision. None of these are all-encompassing, but each emphasizes a particular perspective, like the relationship, personal vs. structural support, process vs. product orientation. ...

  8. Re-thinking reflection in supervision

    DEFF Research Database (Denmark)

    Lystbæk, Christian Tang

    The paper presents a socio-cultural perspective on supervision in professional education, which challenges the current reflective paradigm and move the debate on reflection in supervision in professional education and learning towards a recognition of context, power dynamics and ideological...... of reflective practice has been formalized by regulatory bodies as a way to develop the professionalism of both individual professional practitioners as students through continuing professional developmental processes. Consequently, reflection is often used as a `tool´ for personal and professional development...... al., 2010). This conceptual paper presents a critical, socio-cultural perspective on the current paradigm or dogma of reflective practice within supervision in professional education and learning. The purpose I to challenge the dogma and critically to analyze and move the debate on reflection...

  9. The efficiency of government supervision

    International Nuclear Information System (INIS)

    Paetzold, H.

    1992-01-01

    In 1970, fires as events initiating plant failure were included in the accident analyses of nuclear power plant design concepts. In the meantime, they have been expressed in more precise terms and incorporated into the bodies of nuclear technical rules and regulations. Following a suggestion by the Baden-Wuerttemberg State Ministry for the Environment, the efficiency of government supervision has been examined for the example of fire protection measures or the site of Phillipsburg with one BWR and one PWR plant in operation. The result of the examination indicated that pragmatic approaches and the establishment of key areas of supervision could further enhance the efficiency of government supervision under Section 19 of the German Atomic Energy Act and achieve improvements in plant safety. (orig.) [de

  10. Technetium-99m somatostatin analogues: effect of labelling methods and peptide sequence

    International Nuclear Information System (INIS)

    Decristoforo, C.; Mather, S.J.

    1999-01-01

    In this paper the preclinical evaluation of the somatostatin analogue RC160 labelled with technetium-99m using bifunctional chelators (BFCs) based on the hydrazinonicotinamide (HYNIC) and N 3 S system is described and a comparison made with [Tyr 3 ]-octreotide (TOC). Conjugates of both peptides with HYNIC, and of RC160 with benzoyl-MAG 3 and an N 3 S-adipate derivative were prepared and radiolabelling performed at high specific activities using tricine, tricine/nicotinic acid and ethylenediamine-N,N'-diacetic adic (EDDA) as co-ligands for HYNIC conjugates. All conjugates and 99m Tc-labelled peptides showed preserved binding affinity for the somatostatin receptor (IC50, Kd 99m Tc-RC160 derivatives compared with 99m Tc-EDDA/HYNIC-[Tyr 3 ]-octreotide (0.2%-3.5%ID/g vs 9.7%ID/g) and correlated well with the reduced internalisation rate for RC160 derivatives. Our results show that the selection of the labelling approach as well as the right choice of the peptide structure are crucial for labelling peptides with 99m Tc to achieve complexes with favourable biodistribution. Despite the relatively low tumour uptake compared with 99m Tc-EDDA/HYNIC-[Tyr 3 ]-octreotide, 99m Tc-RC160 could play a role in imaging tumours that do not bind octreotide derivatives. (orig.)

  11. Organization and competences of nuclear supervision in Poland

    International Nuclear Information System (INIS)

    Sowinski, M.

    1989-01-01

    Organization and tasks of nuclear supervision are presented. All supervised nuclear installations are listed. The rights of the president of the National Atomic Energy Agency and the chief inspector of nuclear supervision are given. Licensing and cooperation with the IAEA are described. (A.S.)

  12. Doctoral Dissertation Supervision: Identification and Evaluation of Models

    Directory of Open Access Journals (Sweden)

    Ngozi Agu

    2014-01-01

    Full Text Available Doctoral research supervision is one of the major avenues for sustaining students’ satisfaction with the programme, preparing students to be independent researchers and effectively initiating students into the academic community. This work reports doctoral students’ evaluation of their various supervision models, their satisfaction with these supervision models, and development of research-related skills. The study used a descriptive research design and was guided by three research questions and two hypotheses. A sample of 310 Ph.D. candidates drawn from a federal university in Eastern part of Nigeria was used for this study. The data generated through the questionnaire was analyzed using descriptive statistics and t-tests. Results show that face-to-face interactive model was not only the most frequently used, but also the most widely adopted in doctoral thesis supervision while ICT-based models were rarely used. Students supervised under face-to-face interactive model reported being more satisfied with dissertation supervision than those operating under face-to-face noninteractive model. However, students supervised under these two models did not differ significantly in their perceived development in research-related skills.

  13. Effective use of technology in clinical supervision

    Directory of Open Access Journals (Sweden)

    Priya Martin

    2017-06-01

    Full Text Available Clinical supervision is integral to continuing professional development of health professionals. With advances in technology, clinical supervision too can be undertaken using mediums such as videoconference, email and teleconference. This mode of clinical supervision is termed as telesupervision. While telesupervision could be useful in any context, its value is amplified for health professionals working in rural and remote areas where access to supervisors within the local work environment is often diminished. While telesupervision offers innovative means to undertake clinical supervision, there remain gaps in the literature in terms of its parameters of use in clinical practice. This article outlines ten evidence-informed, practical tips stemming from a review of the literature that will enable health care stakeholders to use technology effectively and efficiently while undertaking clinical supervision. By highlighting the “how to” aspect, telesupervision can be delivered in the right way, to the right health professional, at the right time.

  14. Application of Contingency Theories to the Supervision of Student Teachers.

    Science.gov (United States)

    Phelps, Julia D.

    1985-01-01

    This article examines selected approaches to student teacher supervision within the context of contingency theory. These include authentic supervision, developmental supervision, and supervision based on the student's level of maturity. (MT)

  15. The Cryogenic Supervision System in NSRRC

    CERN Document Server

    Li, Hsing-Chieh; Chiou, Wen-Song; Hsiao, Feng-Zone; Tsai, Zong-Da

    2005-01-01

    The helium cryogenic system in NSRRC is a fully automatic PLC system using the Siemens SIMATIC 300 controller. Modularization in both hardware and software makes it easy in the program reading, the system modification and the problem debug. Based on the Laview program we had developed a supervision system taking advantage of the Internet technology to get system's real-time information in any place. The functions of this supervision system include the real-time data accessing with more than 300 digital/analog signals, the data restore, the history trend display, and the human machine interface. The data is accessed via a Profibus line connecting the PLC system and the supervision system with a maximum baud rate 1.5 Mbit/s. Due to this supervision system, it is easy to master the status of the cryogenic system within a short time and diagnose the problem.

  16. Supervision and inspection plans of plants activities; Plan de inspeccion y supervision de actividades en planta

    Energy Technology Data Exchange (ETDEWEB)

    Feijoo, J. P.

    2009-07-01

    Any idea of hierarchization between supervisor and supervised in inspection and supervision activities should necessarily be dismissed, and the independence of the supervisor when executing has tasks should be guaranteed. The inspection and supervision program enable the detection and resolution of materials and human problems alike. In addition, they are a solution to anticipate potential problems in the future, which results in a very significant reduction of industrial accidents and human errors, as well as better use and upkeep of equipment. With these programs we improve our management and our work, and without a doubt they help to strengthen the safety culture in Cofrentes Nuclear Power Plant. (Author)

  17. Educational Technology and Distance Supervision in Counselor Education

    Science.gov (United States)

    Carlisle, Robert Milton; Hays, Danica G.; Pribesh, Shana L.; Wood, Chris T.

    2017-01-01

    The authors used a nonexperimental descriptive design to examine the prevalence of distance supervision in counselor education programs, educational technology used in supervision, training on technology in supervision, and participants' (N = 673) perceptions of legal and ethical compliance. Program policies are recommended to guide the training…

  18. Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

    Science.gov (United States)

    Wu, Lin; Wang, Yang; Pan, Shirui

    2017-12-01

    It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

  19. State Radiation Protection Supervision and Control

    International Nuclear Information System (INIS)

    2003-01-01

    Radiation Protection Centre is carrying state supervision and control of radiation protection. The main objective of state supervision and control of radiation protection is assessing how licensees comply with requirements of the appropriate legislation and enforcement. Summary of inspections conducted in 2002 is presented

  20. State Radiation Protection Supervision and Control

    CERN Document Server

    2002-01-01

    Radiation Protection Centre is carrying state supervision and control of radiation protection. The main objective of state supervision and control of radiation protection is assessing how licensees comply with requirements of the appropriate legislation and enforcement. Summary of inspections conducted in 2002 is presented.

  1. [Possibilities of supervision in medical practice].

    Science.gov (United States)

    Lönnqvist, Jouko

    2014-01-01

    In supervision, a doctor examines in interaction with the supervisor her/his work, work role and collaborative relationships with the aim to develop herself/himself and the associated work community. In clinical supervision, a doctor's way of acting in interactive relationships with the patients is examined through patient cases, based on the doctor's own experience. Supervision can be used to strengthen the physician identity, clarify the work role, assimilate and delve into clinical work, support professional development and working career, manage one's own work and coping at work, develop collaboration and team work, and support the work of medical directors.

  2. An extended sequence specificity for UV-induced DNA damage.

    Science.gov (United States)

    Chung, Long H; Murray, Vincent

    2018-01-01

    The sequence specificity of UV-induced DNA damage was determined with a higher precision and accuracy than previously reported. UV light induces two major damage adducts: cyclobutane pyrimidine dimers (CPDs) and pyrimidine(6-4)pyrimidone photoproducts (6-4PPs). Employing capillary electrophoresis with laser-induced fluorescence and taking advantages of the distinct properties of the CPDs and 6-4PPs, we studied the sequence specificity of UV-induced DNA damage in a purified DNA sequence using two approaches: end-labelling and a polymerase stop/linear amplification assay. A mitochondrial DNA sequence that contained a random nucleotide composition was employed as the target DNA sequence. With previous methodology, the UV sequence specificity was determined at a dinucleotide or trinucleotide level; however, in this paper, we have extended the UV sequence specificity to a hexanucleotide level. With the end-labelling technique (for 6-4PPs), the consensus sequence was found to be 5'-GCTC*AC (where C* is the breakage site); while with the linear amplification procedure, it was 5'-TCTT*AC. With end-labelling, the dinucleotide frequency of occurrence was highest for 5'-TC*, 5'-TT* and 5'-CC*; whereas it was 5'-TT* for linear amplification. The influence of neighbouring nucleotides on the degree of UV-induced DNA damage was also examined. The core sequences consisted of pyrimidine nucleotides 5'-CTC* and 5'-CTT* while an A at position "1" and C at position "2" enhanced UV-induced DNA damage. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  3. Semi-supervised and unsupervised extreme learning machines.

    Science.gov (United States)

    Huang, Gao; Song, Shiji; Gupta, Jatinder N D; Wu, Cheng

    2014-12-01

    Extreme learning machines (ELMs) have proven to be efficient and effective learning mechanisms for pattern classification and regression. However, ELMs are primarily applied to supervised learning problems. Only a few existing research papers have used ELMs to explore unlabeled data. In this paper, we extend ELMs for both semi-supervised and unsupervised tasks based on the manifold regularization, thus greatly expanding the applicability of ELMs. The key advantages of the proposed algorithms are as follows: 1) both the semi-supervised ELM (SS-ELM) and the unsupervised ELM (US-ELM) exhibit learning capability and computational efficiency of ELMs; 2) both algorithms naturally handle multiclass classification or multicluster clustering; and 3) both algorithms are inductive and can handle unseen data at test time directly. Moreover, it is shown in this paper that all the supervised, semi-supervised, and unsupervised ELMs can actually be put into a unified framework. This provides new perspectives for understanding the mechanism of random feature mapping, which is the key concept in ELM theory. Empirical study on a wide range of data sets demonstrates that the proposed algorithms are competitive with the state-of-the-art semi-supervised or unsupervised learning algorithms in terms of accuracy and efficiency.

  4. Is it possible to strengthen psychiatric nursing staff's clinical supervision?

    DEFF Research Database (Denmark)

    Gonge, Henrik; Buus, Niels

    2015-01-01

    AIM: To test the effects of a meta-supervision intervention in terms of participation, effectiveness and benefits of clinical supervision of psychiatric nursing staff. BACKGROUND: Clinical supervision is regarded as a central component in developing mental health nursing practices, but the evidence...... an intervention group (n = 40) receiving the meta-supervision in addition to attending usual supervision or to a control group (n = 43) attending usual supervision. METHODS: Self-reported questionnaire measures of clinical supervision effectiveness and benefits were collected at base line in January 2012...... and at follow-up completed in February 2013. In addition, a prospective registration of clinical supervision participation was carried out over 3 months subsequent to the intervention. RESULTS: The main result was that it was possible to motivate staff in the intervention group to participate significantly more...

  5. REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era

    Science.gov (United States)

    Leonard, Guy; Stevens, Jamie R.; Richards, Thomas A.

    2009-01-01

    The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment file, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree files (with a user-defined combination of species name and/or database accession number). Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file) and generation of species and accession number lists for use in supplementary materials or figure legends. PMID:19812722

  6. Multiplicity in supervision relationships: A factor in improving ...

    African Journals Online (AJOL)

    Supervision has been identified as an important factor in the success of postgraduate students, even as the most significant variable and a large number of studies have been conducted to identify factors that contribute to supervision success. However the dependent variable in these studies – supervision success – has ...

  7. 28 CFR 2.94 - Supervision reports to Commission.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Supervision reports to Commission. 2.94 Section 2.94 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS District of Columbia Code: Prisoners and Parolees § 2.94 Supervision reports to Commissio...

  8. 48 CFR 836.572 - Government supervision.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Government supervision. 836.572 Section 836.572 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS SPECIAL CATEGORIES OF CONTRACTING CONSTRUCTION AND ARCHITECT-ENGINEER CONTRACTS Contract Clauses 836.572 Government supervision. The contracting officer shal...

  9. New developments in technology-assisted supervision and training: a practical overview.

    Science.gov (United States)

    Rousmaniere, Tony; Abbass, Allan; Frederickson, Jon

    2014-11-01

    Clinical supervision and training are now widely available online. In this article, three of the most accessible and widely adopted new developments in clinical supervision and training technology are described: Videoconference supervision, cloud-based file sharing software, and clinical outcome tracking software. Partial transcripts from two online supervision sessions are provided as examples of videoconference-based supervision. The benefits and limitations of technology in supervision and training are discussed, with an emphasis on supervision process, ethics, privacy, and security. Recommendations for supervision practice are made, including methods to enhance experiential learning, the supervisory working alliance, and online security. © 2014 Wiley Periodicals, Inc.

  10. Teacher Supervision Practices and Principals' Characteristics

    Science.gov (United States)

    April, Daniel; Bouchamma, Yamina

    2015-01-01

    A questionnaire was used to determine the individual and collective teacher supervision practices of school principals and vice-principals in Québec (n = 39) who participated in a research-action study on pedagogical supervision. These practices were then analyzed in terms of the principals' sociodemographic and socioprofessional characteristics…

  11. 32 CFR 552.65 - Command supervision.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 3 2010-07-01 2010-07-01 true Command supervision. 552.65 Section 552.65 National Defense Department of Defense (Continued) DEPARTMENT OF THE ARMY MILITARY RESERVATIONS AND NATIONAL CEMETERIES REGULATIONS AFFECTING MILITARY RESERVATIONS Solicitation on Military Reservations § 552.65 Command supervision. (a) All insurance...

  12. Ethics in education supervision

    Directory of Open Access Journals (Sweden)

    Fatma ÖZMEN

    2008-06-01

    Full Text Available Supervision in education plays a crucial role in attaining educational goals. In addition to determining the present situation, it has a theoretical and practical function regarding the actions to be taken in general and the achievement of teacher development in particular to meet the educational goals in the most effective way. For the education supervisors to act ethically in their tasks while achieving this vital mission shall facilitate them to build up trust, to enhance the level of collaboration and sharing, thus it shall contribute to organizational effectiveness. Ethics is an essential component of educational supervision. Yet, it demonstrates rather vague quality due to the conditions, persons, and situations. Therefore, it is a difficult process to develop the ethical standards in institutions. This study aims to clarify the concept of ethics, to bring up its importance, and to make recommendations for more effective supervisions from the aspect of ethics, based on the literature review, some research results, and sample cases reported by teachers and supervisors.

  13. Clinical Supervision of International Supervisees: Suggestions for Multicultural Supervision

    Science.gov (United States)

    Lee, Ahram

    2018-01-01

    An increase of international students in various settings has been noted in a range of disciplines including counseling and other mental health professions. The author examined the literature on international counseling students related to their experiences in counseling training, particularly in supervision. From the counseling literature, five…

  14. Who attends clinical supervision? The uptake of clinical supervision by hospital nurses.

    Science.gov (United States)

    Koivu, Aija; Hyrkäs, Kristiina; Saarinen, Pirjo Irmeli

    2011-01-01

    The aim of the present study was to identify which nurses decide to participate in clinical supervision (CS) when it is provided for all nursing staff. Clinical supervision is available today for health care providers in many organisations. However, regardless of evidence showing the benefits of CS, some providers decide not to participate in the sessions. A baseline survey on work and health issues was conducted in 2003 with a 3-year follow-up of the uptake of CS by the respondents. Background characteristics and perceptions of work and health were compared between medical and surgical nurses who had undertaken CS (n=124) and their peers who decided not to undertake it (n=204). Differences in the perceptions of work and dimensions of burnout were found between the two groups. Nurses attracted to CS form a distinctive group in the unit, standing out as self-confident, committed and competent professionals supported by empowering and fair leadership. Facilitating clinical supervision for committed and innovative nurses may be seen as part of the empowering leadership of the nurse manager. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

  15. Active relearning for robust supervised classification of pulmonary emphysema

    Science.gov (United States)

    Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Bartholmai, Brian J.; Robb, Richard A.

    2012-03-01

    Radiologists are adept at recognizing the appearance of lung parenchymal abnormalities in CT scans. However, the inconsistent differential diagnosis, due to subjective aggregation, mandates supervised classification. Towards optimizing Emphysema classification, we introduce a physician-in-the-loop feedback approach in order to minimize uncertainty in the selected training samples. Using multi-view inductive learning with the training samples, an ensemble of Support Vector Machine (SVM) models, each based on a specific pair-wise dissimilarity metric, was constructed in less than six seconds. In the active relearning phase, the ensemble-expert label conflicts were resolved by an expert. This just-in-time feedback with unoptimized SVMs yielded 15% increase in classification accuracy and 25% reduction in the number of support vectors. The generality of relearning was assessed in the optimized parameter space of six different classifiers across seven dissimilarity metrics. The resultant average accuracy improved to 21%. The co-operative feedback method proposed here could enhance both diagnostic and staging throughput efficiency in chest radiology practice.

  16. Defeating abusive supervision: Training supervisors to support subordinates.

    Science.gov (United States)

    Gonzalez-Morales, M Gloria; Kernan, Mary C; Becker, Thomas E; Eisenberger, Robert

    2018-04-01

    Although much is known about the antecedents and consequences of abusive supervision, scant attention has been paid to investigating procedures to reduce its frequency. We conducted a quasiexperiment to examine the effects of supervisor support training on subordinate perceptions of abusive supervision and supervisor support. Supervisors (n = 23) in 4 restaurants were trained in 4 supportive supervision strategies (benevolence, sincerity, fairness, and experiential processing) during 4 2-hr sessions over a period of 2 months. We compared perceived supervisor support and abusive supervision before and 9 months after training for 208 employees whose supervisors received support training and 241 employees in 4 similar control restaurants. Compared to employees in the control restaurants, employees whose supervisors received the support training reported higher levels of perceived supervisor support and less abusive supervision. These findings suggest that a relatively brief training program can help managers become more supportive and less abusive. Theoretical and practical implications for effectively managing abusive supervision are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  17. Improving supervision: a team approach.

    Science.gov (United States)

    1993-01-01

    This issue of "The Family Planning Manager" outlines an interactive team supervision strategy as a means of improving family planning service quality and enabling staff to perform to their maximum potential. Such an approach to supervision requires a shift from a monitoring to a facilitative role. Because supervisory visits to the field are infrequent, the regional supervisor, clinic manager, and staff should form a team to share ongoing supervisory responsibilities. The team approach removes individual blame and builds consensus. An effective team is characterized by shared leadership roles, concrete work problems, mutual accountability, an emphasis on achieving team objectives, and problem resolution within the group. The team supervision process includes the following steps: prepare a visit plan and schedule; meet with the clinic manager and staff to explain how the visit will be conducted; supervise key activity areas (clinical, management, and personnel); conduct a problem-solving team meeting; conduct a debriefing meeting with the clinic manager; and prepare a report on the visit, including recommendations and follow-up plans. In Guatemala's Family Planning Unit, teams identify problem areas on the basis of agreement that a problem exists, belief that the problem can be solved with available resources, and individual willingness to accept responsibility for the specific actions identified to correct the problem.

  18. Asco 2044 nuclear power plant: supervision

    International Nuclear Information System (INIS)

    Sabartes, J.

    2010-01-01

    Good supervision constitutes an efficient barrier to avoid the errors caused by inadequate work practices. In this sense, it is necessary to strengthen supervision to make sure that the work is carried out with adequate human performance, tending to avoid error and providing safety quality and efficiency at work. (Author).

  19. 28 CFR 551.32 - Staff supervision.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Staff supervision. 551.32 Section 551.32 Judicial Administration BUREAU OF PRISONS, DEPARTMENT OF JUSTICE INSTITUTIONAL MANAGEMENT MISCELLANEOUS Inmate Organizations § 551.32 Staff supervision. (a) The Warden shall appoint a staff member as the institution's Inmate Organization Manager (IO...

  20. Development of the Artistic Supervision Model Scale (ASMS)

    Science.gov (United States)

    Kapusuzoglu, Saduman; Dilekci, Umit

    2017-01-01

    The purpose of the study is to develop the Artistic Supervision Model Scale in accordance with the perception of inspectors and the elementary and secondary school teachers on artistic supervision. The lack of a measuring instrument related to the model of artistic supervision in the field of literature reveals the necessity of such study. 290…

  1. Tub-Tag Labeling; Chemoenzymatic Incorporation of Unnatural Amino Acids.

    Science.gov (United States)

    Helma, Jonas; Leonhardt, Heinrich; Hackenberger, Christian P R; Schumacher, Dominik

    2018-01-01

    Tub-tag labeling is a chemoenzymatic method that enables the site-specific labeling of proteins. Here, the natural enzyme tubulin tyrosine ligase incorporates noncanonical tyrosine derivatives to the terminal carboxylic acid of proteins containing a 14-amino acid recognition sequence called Tub-tag. The tyrosine derivative carries a unique chemical reporter allowing for a subsequent bioorthogonal modification of proteins with a great variety of probes. Here, we describe the Tub-tag protein modification protocol in detail and explain its utilization to generate labeled proteins for advanced applications in cell biology, imaging, and diagnostics.

  2. Partial sequence determination of metabolically labeled radioactive proteins and peptides

    International Nuclear Information System (INIS)

    Anderson, C.W.

    1982-01-01

    The author has used the sequence analysis of radioactive proteins and peptides to approach several problems during the past few years. They, in collaboration with others, have mapped precisely several adenovirus proteins with respect to the nucleotide sequence of the adenovirus genome; identified hitherto missed proteins encoded by bacteriophage MS2 and by simian virus 40; analyzed the aminoterminal maturation of several virus proteins; determined the cleavage sites for processing of the poliovirus polyprotein; and analyzed the mechanism of frameshifting by excess normal tRNAs during cell-free protein synthesis. This chapter is designed to aid those without prior experience at protein sequence determinations. It is based primarily on the experience gained in the studies cited above, which made use of the Beckman 890 series automated protein sequencers

  3. [Temporary recommendation for use on off-label baclofen: viewpoint of Prescribers of the CAMTEA system].

    Science.gov (United States)

    Rolland, Benjamin; Deheul, Sylvie; Danel, Thierry; Bence, Camille; Blanquart, Marie-Christine; Bonord, Alexandre; Semal, Robin; Briand, Thierry; Sochala, Michel; Dubocage, Christelle; Dupriez, François; Duquesne, Damien; Gibour, Bernard; Loosfeld, Xavier; Henebelle, Dorothée; Henon, Michael; Vernalde, Elodie; Matton, Christian; Bacquet, Jean-Eudes; Molmy, Lucie; Sarasy, François; Simioni, Nicolas; Richez, Cécile; Gentil-Spinosi, Laure; Vosgien, Véronique; Yguel, Jacques; Ledent, Thierry; Auffret, Marine; Wilquin, Maroussia; Ziolkowski, Danièle; Sochala, Michel; Gautier, Sophie; Bordet, Régis; Cottencin, Olivier

    2015-01-01

    The use of high dose baclofen for alcohol-dependence emerged in France from 2008 based on empirical findings, and is still off-label. However, due to the rapid increase in this prescribing practice, the French health authorities have decided to frame it using an extraordinary regulatory measure named "temporary recommendation for use" (TRU). Baclofen prescribers from CAMTEA, a regional team-based off-label system for supervising baclofen prescribing, which was developed much prior to the TRU, discuss herein the pros and cons of this measure and the applicability of its different aspects in the daily clinical practice. © 2014 Société Française de Pharmacologie et de Thérapeutique.

  4. THE COMPARISON OF BANKING SUPERVISION MODEL IN INDONESIA, UNITED KINGDOM, SOUTH KOREA AS EFORTS TO IMPROVE INDONESIAN SUPERVISION SYSTEM

    OpenAIRE

    Sulistyandari; Arief Suryono

    2015-01-01

    This study aims to revise banking supervision by conducting comparative studies research model of banking supervision in Indonesia, the UK, South Korea and the aspirations of the respondents (Bank, OJK, theorist) in Central Java on efforts to improve banking supervision is now done in Indonesia. The results show Indonesian comparison with the UK and South Korea gives the idea that the OJK in charge of education and consumer protection to enhance its role as practiced by the FCA in...

  5. Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning.

    Science.gov (United States)

    Khajehnejad, Moein; Saatlou, Forough Habibollahi; Mohammadzade, Hoda

    2017-08-20

    Alzheimer's disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer's disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests; therefore, an efficient approach for accurate prediction of the condition of the brain through the classification of magnetic resonance imaging (MRI) images is greatly beneficial and yet very challenging. In this paper, a novel approach is proposed for the diagnosis of very early stages of AD through an efficient classification of brain MRI images, which uses label propagation in a manifold-based semi-supervised learning framework. We first apply voxel morphometry analysis to extract some of the most critical AD-related features of brain images from the original MRI volumes and also gray matter (GM) segmentation volumes. The features must capture the most discriminative properties that vary between a healthy and Alzheimer-affected brain. Next, we perform a principal component analysis (PCA)-based dimension reduction on the extracted features for faster yet sufficiently accurate analysis. To make the best use of the captured features, we present a hybrid manifold learning framework which embeds the feature vectors in a subspace. Next, using a small set of labeled training data, we apply a label propagation method in the created manifold space to predict the labels of the remaining images and classify them in the two groups of mild Alzheimer's and normal condition (MCI/NC). The accuracy of the classification using the proposed method is 93

  6. 19 CFR 111.28 - Responsible supervision.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 1 2010-04-01 2010-04-01 false Responsible supervision. 111.28 Section 111.28 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CUSTOMS BROKERS Duties and Responsibilities of Customs Brokers § 111.28 Responsible supervision. (a) General. Every individual broker...

  7. Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning.

    Science.gov (United States)

    Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

    2016-06-29

    The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images' spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines.

  8. Weakly supervised classification in high energy physics

    Energy Technology Data Exchange (ETDEWEB)

    Dery, Lucio Mwinmaarong [Physics Department, Stanford University,Stanford, CA, 94305 (United States); Nachman, Benjamin [Physics Division, Lawrence Berkeley National Laboratory,1 Cyclotron Rd, Berkeley, CA, 94720 (United States); Rubbo, Francesco; Schwartzman, Ariel [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA, 94025 (United States)

    2017-05-29

    As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using one of the most challenging binary classification tasks in high energy physics — quark versus gluon tagging — we show that weakly supervised classification can match the performance of fully supervised algorithms. Furthermore, by design, the new algorithm is insensitive to any mis-modeling of discriminating features in the data by the simulation. Weakly supervised classification is a general procedure that can be applied to a wide variety of learning problems to boost performance and robustness when detailed simulations are not reliable or not available.

  9. Weakly supervised classification in high energy physics

    International Nuclear Information System (INIS)

    Dery, Lucio Mwinmaarong; Nachman, Benjamin; Rubbo, Francesco; Schwartzman, Ariel

    2017-01-01

    As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using one of the most challenging binary classification tasks in high energy physics — quark versus gluon tagging — we show that weakly supervised classification can match the performance of fully supervised algorithms. Furthermore, by design, the new algorithm is insensitive to any mis-modeling of discriminating features in the data by the simulation. Weakly supervised classification is a general procedure that can be applied to a wide variety of learning problems to boost performance and robustness when detailed simulations are not reliable or not available.

  10. REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era

    Directory of Open Access Journals (Sweden)

    Guy Leonard

    2009-01-01

    Full Text Available The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment fi le, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree fi les (with a user-defined combination of species name and/or database accession number. Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file and generation of species and accession number lists for use in supplementary materials or figure legends.

  11. Unified Deep Learning Architecture for Modeling Biology Sequence.

    Science.gov (United States)

    Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

    2017-10-09

    Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

  12. Doctoral Supervision in Virtual Spaces: A Review of Research of Web-Based Tools to Develop Collaborative Supervision

    Science.gov (United States)

    Maor, Dorit; Ensor, Jason D.; Fraser, Barry J.

    2016-01-01

    Supervision of doctoral students needs to be improved to increase completion rates, reduce attrition rates (estimated to be at 25% or more) and improve quality of research. The current literature review aimed to explore the contribution that technology can make to higher degree research supervision. The articles selected included empirical studies…

  13. The LabelHash algorithm for substructure matching

    Directory of Open Access Journals (Sweden)

    Bryant Drew H

    2010-11-01

    Full Text Available Abstract Background There is an increasing number of proteins with known structure but unknown function. Determining their function would have a significant impact on understanding diseases and designing new therapeutics. However, experimental protein function determination is expensive and very time-consuming. Computational methods can facilitate function determination by identifying proteins that have high structural and chemical similarity. Results We present LabelHash, a novel algorithm for matching substructural motifs to large collections of protein structures. The algorithm consists of two phases. In the first phase the proteins are preprocessed in a fashion that allows for instant lookup of partial matches to any motif. In the second phase, partial matches for a given motif are expanded to complete matches. The general applicability of the algorithm is demonstrated with three different case studies. First, we show that we can accurately identify members of the enolase superfamily with a single motif. Next, we demonstrate how LabelHash can complement SOIPPA, an algorithm for motif identification and pairwise substructure alignment. Finally, a large collection of Catalytic Site Atlas motifs is used to benchmark the performance of the algorithm. LabelHash runs very efficiently in parallel; matching a motif against all proteins in the 95% sequence identity filtered non-redundant Protein Data Bank typically takes no more than a few minutes. The LabelHash algorithm is available through a web server and as a suite of standalone programs at http://labelhash.kavrakilab.org. The output of the LabelHash algorithm can be further analyzed with Chimera through a plugin that we developed for this purpose. Conclusions LabelHash is an efficient, versatile algorithm for large-scale substructure matching. When LabelHash is running in parallel, motifs can typically be matched against the entire PDB on the order of minutes. The algorithm is able to identify

  14. The Comparison of Banking Supervision Model in Indonesia, United Kingdom, South Korea as Eforts to Improve Indonesian Supervision System

    OpenAIRE

    Sulistyandari, Sulistyandari

    2015-01-01

    This study aims to improve banking supervision by conductingcomparative studies research model of banking supervision in Indonesia, the UK, South Korea and the aspirations of the respondents (Bank, OJK, theorist) in Central Java on efforts to improve banking supervision is now done in Indonesia. The results show Indonesian comparison with the UK and South Korea gives the idea that the OJK in charge of education and consumer protection to enhance its role as practiced by the FCA in the UK, and...

  15. 19 CFR 146.3 - Customs supervision.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 2 2010-04-01 2010-04-01 false Customs supervision. 146.3 Section 146.3 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) FOREIGN TRADE ZONES General Provisions § 146.3 Customs supervision. (a) Assignment of Customs officers. Customs officers will be...

  16. 36 CFR 25.3 - Supervision; suspensions.

    Science.gov (United States)

    2010-07-01

    ... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Supervision; suspensions. 25.3 Section 25.3 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE INTERIOR NATIONAL MILITARY PARKS; LICENSED GUIDE SERVICE REGULATIONS § 25.3 Supervision; suspensions. (a) The guide service will operate under the direction...

  17. Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification

    OpenAIRE

    Hwang, Kyuyeon; Sung, Wonyong

    2015-01-01

    Connectionist temporal classification (CTC) based supervised sequence training of recurrent neural networks (RNNs) has shown great success in many machine learning areas including end-to-end speech and handwritten character recognition. For the CTC training, however, it is required to unroll (or unfold) the RNN by the length of an input sequence. This unrolling requires a lot of memory and hinders a small footprint implementation of online learning or adaptation. Furthermore, the length of tr...

  18. The effectiveness of banking supervision

    OpenAIRE

    Davis, EP; Obasi, U

    2009-01-01

    Banking supervision is an essential aspect of modern financial systems, seeking crucially to monitor risk-taking by banks so as to protect depositors, the government safety net and the economy as a whole against systemic bank failure and its consequences. In this context, this paper seeks to explore the relationship between risk indicators for individual banks and the different approaches to banking supervision adopted around the world. This is the first work to make use of the currently avai...

  19. Single-Labeled Oligonucleotides Showing Fluorescence Changes upon Hybridization with Target Nucleic Acids

    Directory of Open Access Journals (Sweden)

    Gil Tae Hwang

    2018-01-01

    Full Text Available Sequence-specific detection of nucleic acids has been intensively studied in the field of molecular diagnostics. In particular, the detection and analysis of single-nucleotide polymorphisms (SNPs is crucial for the identification of disease-causing genes and diagnosis of diseases. Sequence-specific hybridization probes, such as molecular beacons bearing the fluorophore and quencher at both ends of the stem, have been developed to enable DNA mutation detection. Interestingly, DNA mutations can be detected using fluorescently labeled oligonucleotide probes with only one fluorophore. This review summarizes recent research on single-labeled oligonucleotide probes that exhibit fluorescence changes after encountering target nucleic acids, such as guanine-quenching probes, cyanine-containing probes, probes containing a fluorophore-labeled base, and microenvironment-sensitive probes.

  20. Counseling Supervision within a Feminist Framework: Guidelines for Intervention

    Science.gov (United States)

    Degges-White, Suzanne E.; Colon, Bonnie R.; Borzumato-Gainey, Christine

    2013-01-01

    Feminist supervision is based on the principles of feminist theory. Goals include sharing responsibility for the supervision process, empowering the supervisee, attending to the contextual assumptions about clients, and analyzing gender roles. This article explores feminist supervision and guidelines for providing counseling supervision…

  1. Nurses’ perceptions on nursing supervision in Primary Health Care

    Directory of Open Access Journals (Sweden)

    Beatriz Francisco Farah

    2016-01-01

    Full Text Available Objective: to understand the perceptions of nurses on nursing supervision in the work process. Methods: this is a qualitative research, with a semi-structured interview, performed with 16 nurses. Data analysis was performed through content analysis. Results: two meanings topics emerged from the speeches of the participants: Nurses´ activities in Primary Health Care Units and Nurses´ perceptions about nursing supervision. In the first category, the actions listed were filling out forms and reports under the supervision of the nursing service. In the second category, supervision was perceived as a function of management and follow-up of the activities planned by the team, in opposition to the classical supervision concept, which is inspecting. Conclusion: nursing supervision has been configured for primary care nurses as an administrative function that involves planning, organization, coordination, evaluation, follow-up and support for the health team.

  2. 21 CFR 640.62 - Medical supervision.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 7 2010-04-01 2010-04-01 false Medical supervision. 640.62 Section 640.62 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) BIOLOGICS ADDITIONAL STANDARDS FOR HUMAN BLOOD AND BLOOD PRODUCTS Source Plasma § 640.62 Medical supervision. A qualified licensed physician shall be on the...

  3. 19 CFR 19.34 - Customs supervision.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 1 2010-04-01 2010-04-01 false Customs supervision. 19.34 Section 19.34 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CUSTOMS WAREHOUSES, CONTAINER STATIONS AND CONTROL OF MERCHANDISE THEREIN Space Bonded for the Storage of Wheat § 19.34 Customs supervision. Port...

  4. 40 CFR 35.935-8 - Supervision.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Supervision. 35.935-8 Section 35.935-8 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY GRANTS AND OTHER FEDERAL ASSISTANCE STATE AND LOCAL ASSISTANCE Grants for Construction of Treatment Works-Clean Water Act § 35.935-8 Supervision. In the case of any project involving Step 3,...

  5. Risk-oriented banking supervision: understanding change of course

    Directory of Open Access Journals (Sweden)

    Vlasov K. A.

    2017-11-01

    Full Text Available in this article the existing model of national bank supervision, its substantial party are considered. By means of the legal analysis and comparative jurisprudence foreign models of bank supervision, the international standards of the «soft» right are investigated, the analysis of an opportunity and positive sides of change of approach of the operating bank supervision to substantial (risk-focused is made.

  6. Group Supervision in Psychotherapy. Main Findings from a Swedish Research Project on Psychotherapy Supervision in a Group Format

    Science.gov (United States)

    Ogren, Marie-Louise; Sundin, Eva C.

    2009-01-01

    Psychotherapy supervision is considered crucial for psychotherapists in training. During the last decades, group supervision has been a frequently used format in many countries. Until recently, very few studies had evaluated the small-group format for training of beginner psychotherapists and psychotherapy supervisors. This article aims to…

  7. An Approach to Supervision for Doctoral and Entry-Level Group Counseling Students

    Science.gov (United States)

    Walsh, Robyn; Bambacus, Elizabeth; Gibson, Donna

    2017-01-01

    The purpose of this article is to provide a supervision approach to experiential groups that replaces professors with doctoral students in the chain of supervision, enlists a faculty member to provide supervision of supervision to the doctoral students, and translates supervision theory to meet the unique needs of group counseling supervision.…

  8. THE COMPARISON OF BANKING SUPERVISION MODEL IN INDONESIA, UNITED KINGDOM, SOUTH KOREA AS EFORTS TO IMPROVE INDONESIAN SUPERVISION SYSTEM

    Directory of Open Access Journals (Sweden)

    Sulistyandari

    2015-05-01

    Full Text Available This study aims to revise banking supervision by conducting comparative studies research model of banking supervision in Indonesia, the UK, South Korea and the aspirations of the respondents (Bank, OJK, theorist in Central Java on efforts to improve banking supervision is now done in Indonesia. The results show Indonesian comparison with the UK and South Korea gives the idea that the OJK in charge of education and consumer protection to enhance its role as practiced by the FCA in the UK, and the LPS assignments need to be expanded in order to ensure that all consumers of financial institutions as was done by the FSCS in the UK and KDIC in South Korea. Aspirations of the people of the regulation and supervision of banking include aspects of regulatory, law enforcement, infrastructure, community (the Bank and culture.

  9. Computer-assisted high-pressure liquid chromatography of radio-labelled phenylthiohydantoin amino acids

    International Nuclear Information System (INIS)

    Bhown, A.S.; Mole, J.E.; Hollaway, W.L.; Bennet, J.C.

    1978-01-01

    A computer-controlled high-pressure liquid chromatographic (HPLC) system is described to identify in vitro phenyl [ 35 S]isothiocyanate-labelled phenylthiohydantoin (PTH) amino acids from a solid-phase sequencer. Each radio-labelled amino acid from the sequencer is added to a PTH amino acid standard and the mixture separated by HPLC using a computer, programmed to detect a slope change in the absorbance. Individual fractions corresponding to the PTH amino acids are collected and counted. The sensitivity of the system is demonstrated on 700 pmoles of lysozyme. (Auth.)

  10. A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation (tDCS) in Multiple Sclerosis (MS).

    Science.gov (United States)

    Kasschau, Margaret; Sherman, Kathleen; Haider, Lamia; Frontario, Ariana; Shaw, Michael; Datta, Abhishek; Bikson, Marom; Charvet, Leigh

    2015-12-26

    Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that uses low amplitude direct currents to alter cortical excitability. With well-established safety and tolerability, tDCS has been found to have the potential to ameliorate symptoms such as depression and pain in a range of conditions as well as to enhance outcomes of cognitive and physical training. However, effects are cumulative, requiring treatments that can span weeks or months and frequent, repeated visits to the clinic. The cost in terms of time and travel is often prohibitive for many participants, and ultimately limits real-world access. Following guidelines for remote tDCS application, we propose a protocol that would allow remote (in-home) participation that uses specially-designed devices for supervised use with materials modified for patient use, and real-time monitoring through a telemedicine video conferencing platform. We have developed structured training procedures and clear, detailed instructional materials to allow for self- or proxy-administration while supervised remotely in real-time. The protocol is designed to have a series of checkpoints, addressing attendance and tolerability of the session, to be met in order to continue to the next step. The feasibility of this protocol was then piloted for clinical use in an open label study of remotely-supervised tDCS in multiple sclerosis (MS). This protocol can be widely used for clinical study of tDCS.

  11. Machinery running state identification based on discriminant semi-supervised local tangent space alignment for feature fusion and extraction

    International Nuclear Information System (INIS)

    Su, Zuqiang; Xiao, Hong; Zhang, Yi; Tang, Baoping; Jiang, Yonghua

    2017-01-01

    Extraction of sensitive features is a challenging but key task in data-driven machinery running state identification. Aimed at solving this problem, a method for machinery running state identification that applies discriminant semi-supervised local tangent space alignment (DSS-LTSA) for feature fusion and extraction is proposed. Firstly, in order to extract more distinct features, the vibration signals are decomposed by wavelet packet decomposition WPD, and a mixed-domain feature set consisted of statistical features, autoregressive (AR) model coefficients, instantaneous amplitude Shannon entropy and WPD energy spectrum is extracted to comprehensively characterize the properties of machinery running state(s). Then, the mixed-dimension feature set is inputted into DSS-LTSA for feature fusion and extraction to eliminate redundant information and interference noise. The proposed DSS-LTSA can extract intrinsic structure information of both labeled and unlabeled state samples, and as a result the over-fitting problem of supervised manifold learning and blindness problem of unsupervised manifold learning are overcome. Simultaneously, class discrimination information is integrated within the dimension reduction process in a semi-supervised manner to improve sensitivity of the extracted fusion features. Lastly, the extracted fusion features are inputted into a pattern recognition algorithm to achieve the running state identification. The effectiveness of the proposed method is verified by a running state identification case in a gearbox, and the results confirm the improved accuracy of the running state identification. (paper)

  12. Emotional Literacy Support Assistants' Views on Supervision Provided by Educational Psychologists: What EPs Can Learn from Group Supervision

    Science.gov (United States)

    Osborne, Cara; Burton, Sheila

    2014-01-01

    The Educational Psychology Service in this study has responsibility for providing group supervision to Emotional Literacy Support Assistants (ELSAs) working in schools. To date, little research has examined this type of inter-professional supervision arrangement. The current study used a questionnaire to examine ELSAs' views on the supervision…

  13. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees.

    Science.gov (United States)

    Williams, Philip H; Eyles, Rod; Weiller, Georg

    2012-01-01

    MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA(∗) duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

  14. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees

    Directory of Open Access Journals (Sweden)

    Philip H. Williams

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require “read count” to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA∗ duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

  15. Is supervision necessary? Examining the effects of internet-based CBT training with and without supervision.

    Science.gov (United States)

    Rakovshik, Sarah G; McManus, Freda; Vazquez-Montes, Maria; Muse, Kate; Ougrin, Dennis

    2016-03-01

    To investigate the effect of Internet-based training (IBT), with and without supervision, on therapists' (N = 61) cognitive-behavioral therapy (CBT) skills in routine clinical practice. Participants were randomized into 3 conditions: (1) Internet-based training with use of a consultation worksheet (IBT-CW); (2) Internet-based training with CBT supervision via Skype (IBT-S); and (3) "delayed-training" controls (DTs), who did not receive the training until all data collection was completed. The IBT participants received access to training over a period of 3 months. CBT skills were evaluated at pre-, mid- and posttraining/wait using assessor competence ratings of recorded therapy sessions. Hierarchical linear analysis revealed that the IBT-S participants had significantly greater CBT competence at posttraining than did IBT-CW and DT participants at both the mid- and posttraining/wait assessment points. There were no significant differences between IBT-CW and the delayed (no)-training DTs. IBT programs that include supervision may be a scalable and effective method of disseminating CBT into routine clinical practice, particularly for populations without ready access to more-traditional "live" methods of training. There was no evidence for a significant effect of IBT without supervision over a nontraining control, suggesting that merely providing access to IBT programs may not be an effective method of disseminating CBT to routine clinical practice. (c) 2016 APA, all rights reserved).

  16. Ethical Issues in the Conduct of Supervision.

    Science.gov (United States)

    Sherry, Patrick

    1991-01-01

    Uses American Psychological Association code of ethics to understand ethical issues present in the conduct of supervision. Discusses ethical issues of responsibility, client and supervisee welfare, confidentiality, competency, moral and legal standards, public statements, and professional relationships in relation to supervision. (Author/NB)

  17. Challenges for Better thesis supervision.

    Science.gov (United States)

    Ghadirian, Laleh; Sayarifard, Azadeh; Majdzadeh, Reza; Rajabi, Fatemeh; Yunesian, Masoud

    2014-01-01

    Conduction of thesis by the students is one of their major academic activities. Thesis quality and acquired experiences are highly dependent on the supervision. Our study is aimed at identifing the challenges in thesis supervision from both students and faculty members point of view. This study was conducted using individual in-depth interviews and Focus Group Discussions (FGD). The participants were 43 students and faculty members selected by purposive sampling. It was carried out in Tehran University of Medical Sciences in 2012. Data analysis was done concurrently with data gathering using content analysis method. Our data analysis resulted in 162 codes, 17 subcategories and 4 major categories, "supervisory knowledge and skills", "atmosphere", "bylaws and regulations relating to supervision" and "monitoring and evaluation". This study showed that more attention and planning in needed for modifying related rules and regulations, qualitative and quantitative improvement in mentorship training, research atmosphere improvement and effective monitoring and evaluation in supervisory area.

  18. Opportunities to learn scientific thinking in joint doctoral supervision

    DEFF Research Database (Denmark)

    Kobayashi, Sofie; Grout, Brian William Wilson; Rump, Camilla Østerberg

    2015-01-01

    Research into doctoral supervision has increased rapidly over the last decades, yet our understanding of how doctoral students learn scientific thinking from supervision is limited. Most studies are based on interviews with little work being reported that is based on observation of actual...... supervision. While joint supervision has become widely used, its learning dynamics remains under-researched and this paper aims to address these gaps in research by exploring learning opportunities in doctoral supervision with two supervisors. The study explores how the tensions in scientific discussion...... between supervisors can become learning opportunities. We combine two different theoretical perspectives, using participation and positioning theory as a sociocultural perspective and variation theory as an individual constructivist perspective on learning. Based on our analysis of a complex episode we...

  19. Supervision as transformative leadership in the context of university ...

    African Journals Online (AJOL)

    This article discusses different models of supervision and promotion of Masters', Doctoral and PhD students. It argues that leadership is inherent in and underpins any model of supervision or promotion of students. The article advances a view that supervision and promotion of the said students should be transformative ...

  20. 18 CFR 367.80 - Supervision and engineering.

    Science.gov (United States)

    2010-04-01

    ... engineering. 367.80 Section 367.80 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT Operating Expense Instructions § 367.80 Supervision and engineering. (a) The supervision and engineering includible in the operating expense accounts must consist of the pay and expenses of...

  1. Wellness Model of Supervision: A Comparative Analysis

    Science.gov (United States)

    Lenz, A. Stephen; Sangganjanavanich, Varunee Faii; Balkin, Richard S.; Oliver, Marvarene; Smith, Robert L.

    2012-01-01

    This quasi-experimental study compared the effectiveness of the Wellness Model of Supervision (WELMS; Lenz & Smith, 2010) with alternative supervision models for developing wellness constructs, total personal wellness, and helping skills among counselors-in-training. Participants were 32 master's-level counseling students completing their…

  2. State Supervision and Control of Radiation Protection

    CERN Document Server

    2001-01-01

    Radiation Protection Centre is carrying state supervision and control of radiation protection. The main objective of state supervision and control of radiation protection is assessing how licensees comply with requirements of the appropriate legislation and enforcement. Summary of inspections conducted in 1999-2001 is presented.

  3. ECB Banking Supervision and beyond

    OpenAIRE

    Lannoo, Karel

    2014-01-01

    With publication of the results of its Comprehensive Assessment at the end of October 2014, the European Central Bank has set the standard for its new mandate as supervisor. But this was only the beginning. The heavy work started in early November, with the day-to-day supervision of the 120 most significant banks in the eurozone under the Single Supervisory Mechanism. The centralisation of the supervision in the eurozone will pose a number of challenges for the ECB in the coming months and ye...

  4. Radiation supervision - NPPs A-1, V-1, V-2

    International Nuclear Information System (INIS)

    2000-01-01

    In this leaflet the radiation supervision of the nuclear power plants A-1, V-1, V-2 is presented. Off-site radiation supervision laboratory is a part of monitoring scheme of the NPPs. More than 1150 samples are taken from the environment annually. The tele-dosimetric system was constructed to improve the quality of the Bohunice NPPs operation impacts supervision. It has been running in a continuous operation from 1992 and providing supervision of the nuclear power plant off-site area within 25 kilometres. The tele-dosimetric system is described

  5. Implicitly Defined Neural Networks for Sequence Labeling

    Science.gov (United States)

    2017-07-31

    ularity has soared for the Long Short - Term Memory (LSTM) (Hochreiter and Schmidhuber, 1997) and vari- ants such as Gated Recurrent Unit (GRU) (Cho et...610. Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short - term memory . Neural computation 9(8):1735– 1780. Zhiheng Huang, Wei Xu, and Kai Yu. 2015...network are coupled together, in order to improve perfor- mance on complex, long -range dependencies in either direction of a sequence. We contrast our

  6. General method of preparation of uniformly 13C, 15N-labeled DNA fragments for NMR analysis of DNA structures

    International Nuclear Information System (INIS)

    Rene, Brigitte; Masliah, Gregoire; Zargarian, Loussine; Mauffret, Olivier; Fermandjian, Serge

    2006-01-01

    Summary 13 C, 15 N labeling of biomolecules allows easier assignments of NMR resonances and provides a larger number of NMR parameters, which greatly improves the quality of DNA structures. However, there is no general DNA-labeling procedure, like those employed for proteins and RNAs. Here, we describe a general and widely applicable approach designed for preparation of isotopically labeled DNA fragments that can be used for NMR studies. The procedure is based on the PCR amplification of oligonucleotides in the presence of labeled deoxynucleotides triphosphates. It allows great flexibility thanks to insertion of a short DNA sequence (linker) between two repeats of DNA sequence to study. Size and sequence of the linker are designed as to create restriction sites at the junctions with DNA of interest. DNA duplex with desired sequence and size is released upon enzymatic digestion of the PCR product. The suitability of the procedure is validated through the preparation of two biological relevant DNA fragments

  7. The LHC string2 supervision system

    CERN Document Server

    Mayya, Y S; Sicard, Claude Henri

    2002-01-01

    This paper describes the implementation of the supervision system for the LHC Prototype Full-Cell also known as String 2. The supervision application is based on a commercial package targeted to industrial controls, but because of the complexity and the specifics of such a system, integration with custom components is necessary in order to merge the industrial requirements with the specificity of the accelerator controls.

  8. 18 CFR 367.9110 - Account 911, Supervision.

    Science.gov (United States)

    2010-04-01

    ... account must include the cost of labor and expenses incurred in the general direction and supervision of sales activities, except merchandising. Direct supervision of a specific activity, such as demonstrating, selling, or advertising, must be charged to the account wherein the costs of such activity are included...

  9. Progressive multi-atlas label fusion by dictionary evolution.

    Science.gov (United States)

    Song, Yantao; Wu, Guorong; Bahrami, Khosro; Sun, Quansen; Shen, Dinggang

    2017-02-01

    Accurate segmentation of anatomical structures in medical images is important in recent imaging based studies. In the past years, multi-atlas patch-based label fusion methods have achieved a great success in medical image segmentation. In these methods, the appearance of each input image patch is first represented by an atlas patch dictionary (in the image domain), and then the latent label of the input image patch is predicted by applying the estimated representation coefficients to the corresponding anatomical labels of the atlas patches in the atlas label dictionary (in the label domain). However, due to the generally large gap between the patch appearance in the image domain and the patch structure in the label domain, the estimated (patch) representation coefficients from the image domain may not be optimal for the final label fusion, thus reducing the labeling accuracy. To address this issue, we propose a novel label fusion framework to seek for the suitable label fusion weights by progressively constructing a dynamic dictionary in a layer-by-layer manner, where the intermediate dictionaries act as a sequence of guidance to steer the transition of (patch) representation coefficients from the image domain to the label domain. Our proposed multi-layer label fusion framework is flexible enough to be applied to the existing labeling methods for improving their label fusion performance, i.e., by extending their single-layer static dictionary to the multi-layer dynamic dictionary. The experimental results show that our proposed progressive label fusion method achieves more accurate hippocampal segmentation results for the ADNI dataset, compared to the counterpart methods using only the single-layer static dictionary. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Theory of Multiple Intelligences at Teacher Supervision

    Directory of Open Access Journals (Sweden)

    İzzet Döş

    2012-07-01

    Full Text Available This study aims to determine views of teachers and supervisors related to the multiple intelligences in students’ learning that they took into consideration in the evaluation of teachers during lesson supervision. The study was conducted with 5 supervisors who work at Kahramanmaraş provincial directorate of national education and 10 teachers who work at primary schools in the centre of Kahramanmaraş in 2011-2012 year. Data was gathered with the help of interview form consisting of five open-ended questions. In the analysis of the data content analysis which is one of the qualitative research methods. According to the results of the analysis, it has been found that usage of multiple intelligences theory in the evaluation students’ learning during supervision enabled them to evaluate students’ learning in a more detailed way. It also made it possible for the supervisors to examine supervision evaluations at different levels. It was also mentioned that supervisions made according to multiple intelligence theory has some limitations.

  11. Kontraktetablering i supervision

    DEFF Research Database (Denmark)

    Mortensen, Karen Vibeke; Jacobsen, Claus Haugaard

    2007-01-01

    Kapitlet behandler kontraktetablering i supervision, et element, der ofte er blevet negligeret eller endog helt forbigået ved indledningen af supervisionsforløb. Sikre aftaler om emner som tid, sted, procedurer for fremlæggelse, fortrolighed, ansvarsfordeling og evaluering skaber imidlertid trygh...

  12. Supervised hub-detection for brain connectivity

    DEFF Research Database (Denmark)

    Kasenburg, Niklas; Liptrot, Matthew George; Reislev, Nina Linde

    2016-01-01

    , but can smooth discriminative signals in the population, degrading predictive performance. We present a novel hub-detection optimized for supervised learning that both clusters network nodes based on population level variation in connectivity and also takes the learning problem into account. The found......A structural brain network consists of physical connections between brain regions. Brain network analysis aims to find features associated with a parameter of interest through supervised prediction models such as regression. Unsupervised preprocessing steps like clustering are often applied...... hubs are a low-dimensional representation of the network and are chosen based on predictive performance as features for a linear regression. We apply our method to the problem of finding age-related changes in structural connectivity. We compare our supervised hub-detection (SHD) to an unsupervised hub...

  13. Problems of Rural Food Safety and Strategies of Constructing Supervision System

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    This paper expounds the practical necessity of constructing diversified rural food safety supervision system as follows: it is the necessary requirements of guaranteeing people’s health and life safety; it is an important component of governmental function of social management and the logical extension of administrative responsibilities; it is the basis of maintaining order of rural society and constructing harmonious society. The main problems existing in the supervision of rural food safety are analyzed as follows: first, the legislative work of rural food safety lags behind to some extent; second, the supervision of governmental departments on rural food safety is insufficient; third, the industrial supervision mechanism of rural food security is not perfect; fourth, the role of rural social organizations in supervising food safety is limited; fifth, the farmers’ awareness of food safety supervision is not strong. Based on these problems, the targeted strategies of constructing diversified rural food safety supervision system are put forward as follows: accelerate the legislation of rural food safety, and ensure that there are laws to go by; give play to the dominant role of government, and strengthen administrative supervision on rural food safety; perfect industrial convention of rural food safety, and improve industrial supervision mechanism; actively support the fostering of social organizations, and give play to the role of supervision of organizations; cultivate correct concept of rights and obligations of farmers, and form awareness of food safety supervision.

  14. Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer

    Science.gov (United States)

    Chappelow, Jonathan; Viswanath, Satish; Monaco, James; Rosen, Mark; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant

    2008-03-01

    Computer-aided diagnosis (CAD) systems for the detection of cancer in medical images require precise labeling of training data. For magnetic resonance (MR) imaging (MRI) of the prostate, training labels define the spatial extent of prostate cancer (CaP); the most common source for these labels is expert segmentations. When ancillary data such as whole mount histology (WMH) sections, which provide the gold standard for cancer ground truth, are available, the manual labeling of CaP can be improved by referencing WMH. However, manual segmentation is error prone, time consuming and not reproducible. Therefore, we present the use of multimodal image registration to automatically and accurately transcribe CaP from histology onto MRI following alignment of the two modalities, in order to improve the quality of training data and hence classifier performance. We quantitatively demonstrate the superiority of this registration-based methodology by comparing its results to the manual CaP annotation of expert radiologists. Five supervised CAD classifiers were trained using the labels for CaP extent on MRI obtained by the expert and 4 different registration techniques. Two of the registration methods were affi;ne schemes; one based on maximization of mutual information (MI) and the other method that we previously developed, Combined Feature Ensemble Mutual Information (COFEMI), which incorporates high-order statistical features for robust multimodal registration. Two non-rigid schemes were obtained by succeeding the two affine registration methods with an elastic deformation step using thin-plate splines (TPS). In the absence of definitive ground truth for CaP extent on MRI, classifier accuracy was evaluated against 7 ground truth surrogates obtained by different combinations of the expert and registration segmentations. For 26 multimodal MRI-WMH image pairs, all four registration methods produced a higher area under the receiver operating characteristic curve compared to that

  15. Principals Performance of Supervision of Instructions in Public ...

    African Journals Online (AJOL)

    Data were collected from a sample of 604 out of 1640 teachers using stratified ... supervision of instructions in the school since effective supervision improves ... and reduces incidence of students' involvement in examination malpractices.

  16. Fast and robust segmentation of white blood cell images by self-supervised learning.

    Science.gov (United States)

    Zheng, Xin; Wang, Yong; Wang, Guoyou; Liu, Jianguo

    2018-04-01

    A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module as automatic labels to actively train a support vector machine (SVM) classifier. Then, the trained SVM classifier is further used to classify each pixel of the image and achieve a more accurate segmentation result. To improve its segmentation accuracy, median color features representing the topological structure and a new weak edge enhancement operator (WEEO) handling fuzzy boundary are introduced. To further reduce its time cost, an efficient cluster sampling strategy is also proposed. We tested the proposed approach with two blood cell image datasets obtained under various imaging and staining conditions. The experiment results show that our approach has a superior performance of accuracy and time cost on both datasets. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Supervision and inspection plans of plants activities

    International Nuclear Information System (INIS)

    Feijoo, J. P.

    2009-01-01

    Any idea of hierarchization between supervisor and supervised in inspection and supervision activities should necessarily be dismissed, and the independence of the supervisor when executing has tasks should be guaranteed. The inspection and supervision program enable the detection and resolution of materials and human problems alike. In addition, they are a solution to anticipate potential problems in the future, which results in a very significant reduction of industrial accidents and human errors, as well as better use and upkeep of equipment. With these programs we improve our management and our work, and without a doubt they help to strengthen the safety culture in Cofrentes Nuclear Power Plant. (Author)

  18. Weighting training images by maximizing distribution similarity for supervised segmentation across scanners

    DEFF Research Database (Denmark)

    van Opbroek, Annegreet; Vernooij, Meike W; Ikram, M.Arfan

    2015-01-01

    Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images to segment. However, due to differences between...... scanners, scanning parameters, and patients such a training set may be difficult to obtain. We present a transfer-learning approach to segmentation by multi-feature voxelwise classification. The presented method can be trained using a heterogeneous set of training images that may be obtained with different...... scanners than the target image. In our approach each training image is given a weight based on the distribution of its voxels in the feature space. These image weights are chosen as to minimize the difference between the weighted probability density function (PDF) of the voxels of the training images...

  19. Development of well construction and workover supervising in Russian Federation

    International Nuclear Information System (INIS)

    Sizov, A; Boyarko, G; Shenderova, I

    2014-01-01

    Despite long history of drilling supervising it still has a number of uncertainties. The period of rapid rise in supervising development at the beginning of the 90's changed in the 2000's. The necessity in the development of this sphere is obvious. The author describes the history of supervising, period of its market condition adaptation. The research also gives principles methods of supervising development and first steps for its position improvement

  20. Supervised Remote Robot with Guided Autonomy and Teleoperation (SURROGATE): A Framework for Whole-Body Manipulation

    Science.gov (United States)

    Hebert, Paul; Ma, Jeremy; Borders, James; Aydemir, Alper; Bajracharya, Max; Hudson, Nicolas; Shankar, Krishna; Karumanchi, Sisir; Douillard, Bertrand; Burdick, Joel

    2015-01-01

    The use of the cognitive capabilties of humans to help guide the autonomy of robotics platforms in what is typically called "supervised-autonomy" is becoming more commonplace in robotics research. The work discussed in this paper presents an approach to a human-in-the-loop mode of robot operation that integrates high level human cognition and commanding with the intelligence and processing power of autonomous systems. Our framework for a "Supervised Remote Robot with Guided Autonomy and Teleoperation" (SURROGATE) is demonstrated on a robotic platform consisting of a pan-tilt perception head, two 7-DOF arms connected by a single 7-DOF torso, mounted on a tracked-wheel base. We present an architecture that allows high-level supervisory commands and intents to be specified by a user that are then interpreted by the robotic system to perform whole body manipulation tasks autonomously. We use a concept of "behaviors" to chain together sequences of "actions" for the robot to perform which is then executed real time.

  1. Applying Services Marketing Principles to Postgraduate Supervision

    Science.gov (United States)

    Dann, Stephen

    2008-01-01

    Purpose: The paper aims to describe the application of two key service quality frameworks for improving the delivery of postgraduate research supervision. The services quality frameworks are used to identify key areas of overlap between services marketing practice and postgraduate supervision that can be used by the supervisor to improve research…

  2. School Counselor Perceptions of Administrative Supervision Practices

    Science.gov (United States)

    Eddings, Geoffrey Creighton

    2012-01-01

    This study examined the perceptions of school counselors regarding administrative supervision practices in K-12 public schools in South Carolina. Specifically, the goal was to gain insight into how school counselors view current building-level supervision practices in relation to Pajak's Twelve Dimensions of Supervisory Practice, as well as how…

  3. 48 CFR 852.236-78 - Government supervision.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Government supervision. 852.236-78 Section 852.236-78 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS CLAUSES AND FORMS SOLICITATION PROVISIONS AND CONTRACT CLAUSES Texts of Provisions and Clauses 852.236-78 Government supervision. As prescribed in...

  4. 28 CFR 810.3 - Consequences of violating the conditions of supervision.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Consequences of violating the conditions of supervision. 810.3 Section 810.3 Judicial Administration COURT SERVICES AND OFFENDER SUPERVISION AGENCY FOR THE DISTRICT OF COLUMBIA COMMUNITY SUPERVISION: ADMINISTRATIVE SANCTIONS § 810.3 Consequences of violating the conditions of supervision. ...

  5. Clinical supervision reflected in a Danish DPCCQ sample

    DEFF Research Database (Denmark)

    Nielsen, Jan; Jacobsen, Claus Haugaard

    Core Questionnaire (DPCCQ) has only few questions on supervision. To rectify this limitation, a recent Danish version of the DPCCQ included two new sections on supervision, one focusing on supervisees and another on supervisors and their supervisory training. This paper presents our initial findings...... on giving and receiving clinical supervision as reported by therapists in Denmark. Method: Currently, the Danish sample consists of 350 clinical psychologist doing psychotherapy who completed DPCCQ. Data are currently being prepared for statistical analysis. Results: This paper will focus primarily...... on describing the amount and type of supervision received and given by the sample. Findings from these descriptive statistics will be compared within the sample across demographic parameters such as age and sex, and professional characteristics such as career level, theoretical preferences, type of clients...

  6. Caregivers' satisfaction and supervision of primary health care ...

    African Journals Online (AJOL)

    Caregivers' satisfaction and supervision of primary health care services in Nnewi, ... made in the reduction of childhood health indicators in the previous decade, ... supervision of PHCs should also improve the quality of child health services.

  7. Exploring Organizational Barriers to Strengthening Clinical Supervision of Psychiatric Nursing Staff

    DEFF Research Database (Denmark)

    Gonge, Henrik; Buus, Niels

    2016-01-01

    This article reports findings from a longitudinal controlled intervention study of 115 psychiatric nursing staff. The twofold objective of the study was: (a) To test whether the intervention could increase clinical supervision participation and effectiveness of existing supervision practices, and...... in the experienced effectiveness of supervision. It is concluded that organizational support is an imperative for implementation of clinical supervision......., and (b) To explore organizational constraints to implementation of these strengthened practices. Questionnaire responses and registration of participation in clinical supervision were registered prior and subsequent to the intervention consisting of an action learning oriented reflection on staff......'s existing clinical supervision practices. Major organizational changes in the intervention group during the study period obstructed the implementation of strengthened clinical supervision practices, but offered an opportunity for studying the influences of organizational constraints. The main findings were...

  8. Pulse sequences for contrast-enhanced magnetic resonance imaging

    International Nuclear Information System (INIS)

    Graves, Martin J.

    2007-01-01

    The theory and application of magnetic resonance imaging (MRI) pulse sequences following the administration of an exogenous contrast agent are discussed. Pulse sequences are categorised according to the contrast agent mechanism: changes in proton density, relaxivity, magnetic susceptibility and resonant frequency shift. Applications in morphological imaging, magnetic resonance angiography, dynamic imaging and cell labelling are described. The importance of optimising the pulse sequence for each application is emphasised

  9. Supervised Convolutional Sparse Coding

    KAUST Repository

    Affara, Lama Ahmed; Ghanem, Bernard; Wonka, Peter

    2018-01-01

    coding, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements

  10. Institutional Arrangement of Financial Markets Supervision: The Case of the Czech Republic

    OpenAIRE

    Musílek, Petr

    2008-01-01

    The paper deals with institutional arrangement of financial supervision in the Czech Republic. Financial markets are composed of partial financial segments specialized in individual types of financial instruments and individual customer groups. Financial institutions gradually transform into financial supermarkets. There are several models of institutional arrangement of financial supervision (integrated financial supervision model, sectional financial supervision model, financial supervision...

  11. The technical supervision interface

    CERN Document Server

    Sollander, P

    1998-01-01

    The Technical Control Room (TCR) is currently using 30 different applications for the remote supervision of the technical infrastructure at CERN. These applications have all been developed with the CERN made Uniform Man Machine Interface (UMMI) tools built in 1990. However, the visualization technology has evolved phenomenally since 1990, the Technical Data Server (TDS) has radically changed our control system architecture, and the standardization and the maintenance of the UMMI applications have become important issues as their number increases. The Technical Supervision Interface is intended to replace the UMMI and solve the above problems. Using a standard WWW-browser for the display, it will be inherently multi-platform and hence available for control room operators, equipment specialists and on-call personnel.

  12. 19 CFR 19.38 - Supervision of exportation.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 1 2010-04-01 2010-04-01 false Supervision of exportation. 19.38 Section 19.38 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CUSTOMS WAREHOUSES, CONTAINER STATIONS AND CONTROL OF MERCHANDISE THEREIN Duty-Free Stores § 19.38 Supervision of exportation. (a) Sales...

  13. Evaluation Of Loan Disbursement And Repayment Of Supervised ...

    African Journals Online (AJOL)

    Evaluation Of Loan Disbursement And Repayment Of Supervised Credit ... bank as regard to loan supervision was scored low as a result of low rate of loan recovery, ... strategy to recover outstanding debts and reduce interest charge on loans.

  14. Constrained Deep Weak Supervision for Histopathology Image Segmentation.

    Science.gov (United States)

    Jia, Zhipeng; Huang, Xingyi; Chang, Eric I-Chao; Xu, Yan

    2017-11-01

    In this paper, we develop a new weakly supervised learning algorithm to learn to segment cancerous regions in histopathology images. This paper is under a multiple instance learning (MIL) framework with a new formulation, deep weak supervision (DWS); we also propose an effective way to introduce constraints to our neural networks to assist the learning process. The contributions of our algorithm are threefold: 1) we build an end-to-end learning system that segments cancerous regions with fully convolutional networks (FCNs) in which image-to-image weakly-supervised learning is performed; 2) we develop a DWS formulation to exploit multi-scale learning under weak supervision within FCNs; and 3) constraints about positive instances are introduced in our approach to effectively explore additional weakly supervised information that is easy to obtain and enjoy a significant boost to the learning process. The proposed algorithm, abbreviated as DWS-MIL, is easy to implement and can be trained efficiently. Our system demonstrates the state-of-the-art results on large-scale histopathology image data sets and can be applied to various applications in medical imaging beyond histopathology images, such as MRI, CT, and ultrasound images.

  15. Supervising undergraduate research: a collective approach utilising groupwork and peer support.

    Science.gov (United States)

    Baker, Mary-Jane; Cluett, Elizabeth; Ireland, Lorraine; Reading, Sheila; Rourke, Susan

    2014-04-01

    Nursing education now requires graduate entry for professional registration. The challenge is to ensure that students develop independence and team working in a resource effective manner. The dissertation is one opportunity for this. To evaluate changing from individual dissertation supervision to group peer supervision. Group supervision was implemented for one cohort. Dissertation outcomes were compared with two previous cohorts. Student evaluative data was assessed. Group supervision did not adversely affect dissertation outcomes (p=0.85). 88% of students reported peer supervision to be helpful, with themes being 'support and sharing', and 'progress and moving forward'. Peer group support provided consistent supervision harnessing the energy and resources of the students and Faculty, without adversely affecting outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. [3H]Azidodantrolene photoaffinity labeling, synthetic domain peptides and monoclonal antibody reactivity identify the dantrolene binding sequence on RyR1

    Energy Technology Data Exchange (ETDEWEB)

    Paul-Pletzer, Kalanethee; Yamamoto, Takeshi; Bhat, Manju B.; Ma, Jianjie; Ikemoto, Noriaki; Jimenez, Leslie S.; Morimoto, Hiromi; Williams, Philip G.; Parness, Jerome

    2002-06-14

    Dantrolene is a drug that suppresses intracellular Ca2+ release from sarcoplasmic reticulum in normal skeletal muscle and is used as a therapeutic agent in individuals susceptible to malignant hyperthermia. Though its precise mechanism of action has not been elucidated, we have identified the N-terminal region (amino acids 1-1400) of the skeletal muscle isoform of the ryanodine receptor (RyR1), the primary Ca2+ release channel in sarcoplasmic reticulum, as a molecular target for dantrolene using the photoaffinity analog [3H]azidodantrolene(1). Here, we demonstrate that heterologously expressed RyR1 retains its capacity to be specifically labeled with [3H]azidodantrolene,indicating that muscle specific factors are not required for this ligand-receptor interaction. Synthetic domain peptides of RyR1, previously shown to affect RyR1 function in vitro and in vivo, were exploited as potential drug binding site mimics and used in photoaffinity labeling experiments. Only DP1 and DP1-2, peptide s containing the amino acid sequence corresponding to RyR1 residues 590-609, were specifically labeled by [3H]azidodantrolene. A monoclonal anti-RyR1 antibody which recognizes RyR1 and its 1400 amino acid N-terminal fragment, recognizes DP1 and DP1-2 in both Western blots and immunoprecipitation assays, and specifically inhibits [3H]azidodantrolene photolabeling of RyR1 and its N-terminal fragment in sarcoplasmic reticulum. Our results indicate that synthetic domain peptides can mimic a native, ligand binding conformation in vitro, and that the dantrolene binding site and the epitope for the monoclonal antibody on RyR1 are equivalent and composed of amino-acids 590-609.

  17. A Delphi Study and Initial Validation of Counselor Supervision Competencies

    Science.gov (United States)

    Neuer Colburn, Anita A.; Grothaus, Tim; Hays, Danica G.; Milliken, Tammi

    2016-01-01

    The authors addressed the lack of supervision training standards for doctoral counseling graduates by developing and validating an initial list of supervision competencies. They used content analysis, Delphi polling, and content validity methods to generate a list, vetted by 2 different panels of supervision experts, of 33 competencies grouped…

  18. 7 CFR 550.32 - Project supervision and responsibilities.

    Science.gov (United States)

    2010-01-01

    ... Management of Agreements Program Management § 550.32 Project supervision and responsibilities. (a) The... with a project plan for use for external peer review. ... 7 Agriculture 6 2010-01-01 2010-01-01 false Project supervision and responsibilities. 550.32...

  19. The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing.

    Directory of Open Access Journals (Sweden)

    Jonas Binladen

    2007-02-01

    Full Text Available The invention of the Genome Sequence 20 DNA Sequencing System (454 parallel sequencing platform has enabled the rapid and high-volume production of sequence data. Until now, however, individual emulsion PCR (emPCR reactions and subsequent sequencing runs have been unable to combine template DNA from multiple individuals, as homologous sequences cannot be subsequently assigned to their original sources.We use conventional PCR with 5'-nucleotide tagged primers to generate homologous DNA amplification products from multiple specimens, followed by sequencing through the high-throughput Genome Sequence 20 DNA Sequencing System (GS20, Roche/454 Life Sciences. Each DNA sequence is subsequently traced back to its individual source through 5'tag-analysis.We demonstrate that this new approach enables the assignment of virtually all the generated DNA sequences to the correct source once sequencing anomalies are accounted for (miss-assignment rate<0.4%. Therefore, the method enables accurate sequencing and assignment of homologous DNA sequences from multiple sources in single high-throughput GS20 run. We observe a bias in the distribution of the differently tagged primers that is dependent on the 5' nucleotide of the tag. In particular, primers 5' labelled with a cytosine are heavily overrepresented among the final sequences, while those 5' labelled with a thymine are strongly underrepresented. A weaker bias also exists with regards to the distribution of the sequences as sorted by the second nucleotide of the dinucleotide tags. As the results are based on a single GS20 run, the general applicability of the approach requires confirmation. However, our experiments demonstrate that 5'primer tagging is a useful method in which the sequencing power of the GS20 can be applied to PCR-based assays of multiple homologous PCR products. The new approach will be of value to a broad range of research areas, such as those of comparative genomics, complete mitochondrial

  20. The Relationships between Doctoral Students’ Perceptions of Supervision and Burnout

    Directory of Open Access Journals (Sweden)

    Solveig Cornér

    2017-06-01

    Full Text Available Aim/Purpose: Both the quality and the quantity of doctoral supervision have been identified as central determinants of the doctoral journey. However, there is a gap in our understanding of how supervision activities are associated with lack of wellbeing, such as burnout, and also to completion of the studies among doctoral students. Background:\tThe study explored doctoral students’ perceptions of different aspects of supervision including the primary sources, frequency, expressed satisfaction and their interrelation with experienced stress, exhaustion and cynicism. Methodology: Altogether 248 doctoral students from three Finnish universities representing social sciences, arts and humanities, and natural and life sciences responded to an adapted version of a Doctoral Experience Survey. A combination of several measures was used to investigate the students’ experiences of supervision and burnout. Contribution:\tThe results showed that students benefit from having several and different kinds of supervision activities. Various sources contribute not only to experiences of the doctoral journey and burnout, but also to the completion of the studies. Findings: Experienced lack of satisfaction with supervision and equality within the researcher community and a low frequency of supervision were related to experiences of burnout. Experiences of burnout were connected to students’ attrition intentions. Attrition intentions were related to source of supervision, the form of thesis, and inadequate supervision frequency. Frequency was related to both experience of burnout and likelihood of attrition. Recommendations for Practitioners: A recommendation developed from this research is to assist doctoral students with sufficient support, especially equality within the scholarly community and frequency of supervision. Further, greater emphasis could be put on group supervision and other collective forms of supervision. It is important that doctoral

  1. Optimization of safety production supervision mode of coalmining enterprises

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, M.; Xiao, Z. [China University of Mining and Technology, Xuzhou (China). School of Management

    2005-12-01

    In view of the fact that safety production supervision of coal mines in China features low efficacy, this paper applies principles of cybernetics to simulate the dynamic process of safety supervision, and proposes that institutional variables be controlled to support intermediate goals, which in turn contribute to the ultimate safety production objective. Rather than focussing all attention on safety issues of working faces, supervising departments of coalmines are advised to pay much more attention to institutional factors that may impact people's attitude and behavior, which are responsible for most coalmine accidents. It is believed that such a shift of attention can effectively reduce coalmining production accidents and greatly enhance supervision efficacy. 8 refs., 5 figs.

  2. Preparing supervisors to provide safeguarding supervision for healthcare staff.

    Science.gov (United States)

    Smikle, Marcia

    2017-11-28

    This paper outlines why experienced supervisors at a London healthcare provider received skills training so they could offer safeguarding supervision to front-line colleagues with case management responsibilities for vulnerable children and young people. It examines how supervisors use the main functions of supervision and a cycle of reflection in clinical practice with supervisees. As well as the professional issues encountered by supervisors in relation to the benefits, the challenges of providing supervision and the action required to make safeguarding supervision a part of the organisational culture are also explored. ©2017 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.

  3. 28 CFR 2.206 - Travel approval and transfers of supervision.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Travel approval and transfers of supervision. 2.206 Section 2.206 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS District of Columbia Supervised Releasees § 2.206 Travel approval and...

  4. Performance Monitoring Applied to System Supervision

    Directory of Open Access Journals (Sweden)

    Bertille Somon

    2017-07-01

    Full Text Available Nowadays, automation is present in every aspect of our daily life and has some benefits. Nonetheless, empirical data suggest that traditional automation has many negative performance and safety consequences as it changed task performers into task supervisors. In this context, we propose to use recent insights into the anatomical and neurophysiological substrates of action monitoring in humans, to help further characterize performance monitoring during system supervision. Error monitoring is critical for humans to learn from the consequences of their actions. A wide variety of studies have shown that the error monitoring system is involved not only in our own errors, but also in the errors of others. We hypothesize that the neurobiological correlates of the self-performance monitoring activity can be applied to system supervision. At a larger scale, a better understanding of system supervision may allow its negative effects to be anticipated or even countered. This review is divided into three main parts. First, we assess the neurophysiological correlates of self-performance monitoring and their characteristics during error execution. Then, we extend these results to include performance monitoring and error observation of others or of systems. Finally, we provide further directions in the study of system supervision and assess the limits preventing us from studying a well-known phenomenon: the Out-Of-the-Loop (OOL performance problem.

  5. Alternative approaches to postgraduate supervision: A planning tool ...

    African Journals Online (AJOL)

    Increased demands on academics due to the changing work and higher educational environments challenge traditional approaches to postgraduate supervision. Supervisors often tend to follow the apprenticeship approach uncritically. Supervisors therefore need to be aware of alternative approaches to supervision and of ...

  6. Supervision is also about Addressing the Group Dynamics

    DEFF Research Database (Denmark)

    Jensen, Lars Peter; Hansen, S.

    2003-01-01

    that many students are having difficulties with practical issues such as collaboration, communication, and project management. Most supervisors either ignore this demand, because they do not find it important or they find it frustrating, because they do not know, how to supervise group dynamics......An important aspect of the problem based and project organized study at Aalborg University is the supervision of the project groups. At the basic education (first year) it is stated in the curriculum that part of the supervisors' job is to deal with group dynamics. This is due to the experience...... as well as at Aalborg University. The first visible result has been participating supervisors telling us that the course has inspired them to try supervising group dynamics in the future. This paper will explore some aspects of supervising group dynamics as well as, how to develop the Aalborg model...

  7. A new supervised learning algorithm for spiking neurons.

    Science.gov (United States)

    Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

    2013-06-01

    The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

  8. Nursing supervision for care comprehensiveness.

    Science.gov (United States)

    Chaves, Lucieli Dias Pedreschi; Mininel, Vivian Aline; Silva, Jaqueline Alcântara Marcelino da; Alves, Larissa Roberta; Silva, Maria Ferreira da; Camelo, Silvia Helena Henriques

    2017-01-01

    To reflect on nursing supervision as a management tool for care comprehensiveness by nurses, considering its potential and limits in the current scenario. A reflective study based on discourse about nursing supervision, presenting theoretical and practical concepts and approaches. Limits on the exercise of supervision are related to the organization of healthcare services based on the functional and clinical model of care, in addition to possible gaps in the nurse training process and work overload. Regarding the potential, researchers emphasize that supervision is a tool for coordinating care and management actions, which may favor care comprehensiveness, and stimulate positive attitudes toward cooperation and contribution within teams, co-responsibility, and educational development at work. Nursing supervision may help enhance care comprehensiveness by implying continuous reflection on including the dynamics of the healthcare work process and user needs in care networks. refletir a supervisão de enfermagem como instrumento gerencial do enfermeiro para integralidade do cuidado, considerando suas potencialidades e limitações no cenário atual. estudo reflexivo baseado na formulação discursiva sobre a supervisão de enfermagem, apresentando conceitos e enfoques teóricos e/ou práticos. limitações no exercício da supervisão estão relacionadas à organização dos serviços de saúde embasada no modelo funcional e clínico de atenção, assim como possíveis lacunas no processo de formação do enfermeiro e sobrecarga de trabalho. Quanto às potencialidades, destaca-se a supervisão como instrumento de articulação de ações assistenciais e gerenciais, que pode favorecer integralidade da atenção, estimular atitudes de cooperação e colaboração em equipe, além da corresponsabilização e promoção da educação no trabalho. supervisão de enfermagem pode contribuir para fortalecimento da integralidade do cuidado, pressupondo reflexão cont

  9. To Be or Not to Be: Community Supervision Deja Vu

    Science.gov (United States)

    Taxman, Faye S.

    2008-01-01

    Supervision is an undervalued part of the correctional services. Over the last three decades, innovations have focused on increasing the number of contacts between the offender and the supervision employee, to little avail. A new generation of innovations is occurring in the supervision field that is directed at changing the interaction between…

  10. Literature mining of protein-residue associations with graph rules learned through distant supervision

    Directory of Open Access Journals (Sweden)

    Ravikumar KE

    2012-10-01

    Full Text Available Abstract Background We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempts to correctly associate each mention with a protein also named in the text. The methods presented in this work will enable improved protein functional site extraction from articles, ultimately supporting protein function prediction. Our method made use of linguistic patterns for identifying the amino acid residue mentions in text. Further, we applied an automated graph-based method to learn syntactic patterns corresponding to protein-residue pairs mentioned in the text. We finally present an approach to automated construction of relevant training and test data using the distant supervision model. Results The performance of the method was assessed by extracting protein-residue relations from a new automatically generated test set of sentences containing high confidence examples found using distant supervision. It achieved a F-measure of 0.84 on automatically created silver corpus and 0.79 on a manually annotated gold data set for this task, outperforming previous methods. Conclusions The primary contributions of this work are to (1 demonstrate the effectiveness of distant supervision for automatic creation of training data for protein-residue relation extraction, substantially reducing the effort and time involved in manual annotation of a data set and (2 show that the graph-based relation extraction approach we used generalizes well to the problem of protein-residue association extraction. This work paves the way towards effective extraction of protein functional residues from the literature.

  11. Literature mining of protein-residue associations with graph rules learned through distant supervision.

    Science.gov (United States)

    Ravikumar, Ke; Liu, Haibin; Cohn, Judith D; Wall, Michael E; Verspoor, Karin

    2012-10-05

    We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempts to correctly associate each mention with a protein also named in the text. The methods presented in this work will enable improved protein functional site extraction from articles, ultimately supporting protein function prediction. Our method made use of linguistic patterns for identifying the amino acid residue mentions in text. Further, we applied an automated graph-based method to learn syntactic patterns corresponding to protein-residue pairs mentioned in the text. We finally present an approach to automated construction of relevant training and test data using the distant supervision model. The performance of the method was assessed by extracting protein-residue relations from a new automatically generated test set of sentences containing high confidence examples found using distant supervision. It achieved a F-measure of 0.84 on automatically created silver corpus and 0.79 on a manually annotated gold data set for this task, outperforming previous methods. The primary contributions of this work are to (1) demonstrate the effectiveness of distant supervision for automatic creation of training data for protein-residue relation extraction, substantially reducing the effort and time involved in manual annotation of a data set and (2) show that the graph-based relation extraction approach we used generalizes well to the problem of protein-residue association extraction. This work paves the way towards effective extraction of protein functional residues from the literature.

  12. The reflective meta-dialogue in psycho-dynamic supervision

    DEFF Research Database (Denmark)

    Frølund, Lone; Nielsen, Jan

    2009-01-01

    the therapeutic practice in the supervision. The mutual relations and processes between therapeutic practice and supervision will be illustrated by the so-called mirror axes, which play an important part in the transformation from learning to integrated experience. We will focus on the relationship...

  13. EEM{sup TM} wireless supervision

    Energy Technology Data Exchange (ETDEWEB)

    Bilic, H. [Ericsson-Nikola Tesla d.d. Zagreb (Croatia)

    2000-07-01

    By adding the GSM network to the communication level of Energy Management systems, energy operating centres (EOC) can offer wireless access to the supervised equipment. Furthermore EOC can profit from rapid service development in the GSM networks. With implementation of GPRS to the GSM network EOC can instantly offer wireless access to external IP based networks such as Internet and corporate Intranets. The author describes architecture and key characteristic of Ericsson EnergyMaster{sup TM} (EEM{sup TM}) system for Energy Management, how and where to implement wireless supervision, wireless access to IP addresses and also how to implement new services provided by the GSM network. (orig.)

  14. Shame, the scourge of supervision

    Directory of Open Access Journals (Sweden)

    Valérie Perret

    2017-07-01

    • How can the supervisor deal with it? My motivation in writing this article is born from my personal experience with shame. It inhibited my thinking, my spontaneity, my creativity, and therefore limited my personal and professional development. Freeing myself allowed me to recover liberty, energy and legitimacy. I gained in professional competence and assertiveness within my practice as supervisor. My purpose in writing this article is that we, as supervisors, reflect together on how we look at the process of shame in our supervision sessions.  Citation - APA format: Perret, V. (2017. Shame, the scourge of supervision. International Journal of Transactional Analysis Research & Practice, 8(2, 41-48.

  15. Contribution of technetium 99m-labelled pyrophosphate bone scintigraphy in infectious spondylodiscitis

    International Nuclear Information System (INIS)

    Capdepont, M.-T.

    1976-01-01

    This work examines the contribution of technetium 99m(sup(99m)Tc)-labelled pyrophosphate bone scintigraphy in infectious spondylodiscitis and attempts to define its importance in the diagnosis of lesions and their subsequent supervision in patients under treatment. 5 to 15 millicuries of sup(99m)Tc-labelled pyrophosphates are injected intraveinously. Bone uptake is strong and durable; 1.3% of the injected activity is found in the blood by the fifth hour. The skeleton may be explored: - either one segment at a tome with a scintillation camera, - or all at once and more quickly with a whole-body device taking front and black exposures. Bone scintigraphy appears as a basic technique in the study of infectious spondylodiscitis. Moreover the use of increasingly efficient equipment, the quantification of results and perhaps the development of new tracers augur well for a technique which is already acknowledged to be of fundamental interest [fr

  16. 3H-labeling of prokinetic motilide ABT-229 for biodistribution and metabolism studies

    International Nuclear Information System (INIS)

    Faghih, Ramin; Burnell-Curty, Cynthia; Surber, Bruce; Shoghi, Simin; Borre, Anthony; Ye Yao; Lartey, P.A.; Nellans, H.N.

    1996-01-01

    The prokinetic drug candidate, ABT-229, has been successfully [ 3 H]-labeled in the macrolactone ring. This was accomplished with [ 3 H]-NaBH 4 reduction of the 11-ketone analog in a four step synthetic sequence beginning with the drug candidate. The 3 H-labeled drug was obtained with specific activity of 9.0 Ci/mmol and radiochemical purity > 99%. This constitutes the first methodology for 3 H-labeling of the macrolactone in an erythromycin derivative. (author)

  17. In vivo MRI discrimination between live and lysed iron-labelled cells using balanced steady state free precession

    International Nuclear Information System (INIS)

    Ribot, E.J.; Foster, P.J.

    2012-01-01

    The goal of this study was to evaluate the ability of balanced steady state free precession (b-SSFP) magnetic resonance imaging sequence to distinguish between live and lysed iron-labelled cells. Human breast cancer cells were labelled with iron oxide nanoparticles. Cells were lysed using sonication. Imaging was performed at 3 T. The timing parameters for b-SSFP and the number of iron-labelled cells in samples were varied to optimise the b-SSFP signal difference between live and lysed iron-labelled cell samples. For in vivo experiments, cells were mixed with Matrigel and implanted into nude mice. Three mice implanted with live labelled cancer cells were irradiated to validate this method. Lysed iron-labelled cells have a significantly higher signal compared with live, intact iron-labelled cells in bSSFP images. The contrast between live and dead cells can be maximised by careful optimisation of timing parameters. A change in the b-SSFP signal was measured 6 days after irradiation, reflecting cell death in vivo. Histology confirmed the presence of dead cells in the implant. Our results show that the b-SSFP sequence can be optimised to allow for the discrimination of live iron-labelled cells and lysed iron-labelled cells in vitro and in vivo. (orig.)

  18. In vivo MRI discrimination between live and lysed iron-labelled cells using balanced steady state free precession

    Energy Technology Data Exchange (ETDEWEB)

    Ribot, E.J. [University of Western Ontario, Imaging Research Laboratories, Robarts Research Institute, London, ON (Canada); Foster, P.J. [University of Western Ontario, Imaging Research Laboratories, Robarts Research Institute, London, ON (Canada); University of Western Ontario, Department of Medical Biophysics, London, ON (Canada)

    2012-09-15

    The goal of this study was to evaluate the ability of balanced steady state free precession (b-SSFP) magnetic resonance imaging sequence to distinguish between live and lysed iron-labelled cells. Human breast cancer cells were labelled with iron oxide nanoparticles. Cells were lysed using sonication. Imaging was performed at 3 T. The timing parameters for b-SSFP and the number of iron-labelled cells in samples were varied to optimise the b-SSFP signal difference between live and lysed iron-labelled cell samples. For in vivo experiments, cells were mixed with Matrigel and implanted into nude mice. Three mice implanted with live labelled cancer cells were irradiated to validate this method. Lysed iron-labelled cells have a significantly higher signal compared with live, intact iron-labelled cells in bSSFP images. The contrast between live and dead cells can be maximised by careful optimisation of timing parameters. A change in the b-SSFP signal was measured 6 days after irradiation, reflecting cell death in vivo. Histology confirmed the presence of dead cells in the implant. Our results show that the b-SSFP sequence can be optimised to allow for the discrimination of live iron-labelled cells and lysed iron-labelled cells in vitro and in vivo. (orig.)

  19. Predict subcellular locations of singleplex and multiplex proteins by semi-supervised learning and dimension-reducing general mode of Chou's PseAAC.

    Science.gov (United States)

    Pacharawongsakda, Eakasit; Theeramunkong, Thanaruk

    2013-12-01

    Predicting protein subcellular location is one of major challenges in Bioinformatics area since such knowledge helps us understand protein functions and enables us to select the targeted proteins during drug discovery process. While many computational techniques have been proposed to improve predictive performance for protein subcellular location, they have several shortcomings. In this work, we propose a method to solve three main issues in such techniques; i) manipulation of multiplex proteins which may exist or move between multiple cellular compartments, ii) handling of high dimensionality in input and output spaces and iii) requirement of sufficient labeled data for model training. Towards these issues, this work presents a new computational method for predicting proteins which have either single or multiple locations. The proposed technique, namely iFLAST-CORE, incorporates the dimensionality reduction in the feature and label spaces with co-training paradigm for semi-supervised multi-label classification. For this purpose, the Singular Value Decomposition (SVD) is applied to transform the high-dimensional feature space and label space into the lower-dimensional spaces. After that, due to limitation of labeled data, the co-training regression makes use of unlabeled data by predicting the target values in the lower-dimensional spaces of unlabeled data. In the last step, the component of SVD is used to project labels in the lower-dimensional space back to those in the original space and an adaptive threshold is used to map a numeric value to a binary value for label determination. A set of experiments on viral proteins and gram-negative bacterial proteins evidence that our proposed method improve the classification performance in terms of various evaluation metrics such as Aiming (or Precision), Coverage (or Recall) and macro F-measure, compared to the traditional method that uses only labeled data.

  20. The supervisions in the field develop nuclear professionals

    International Nuclear Information System (INIS)

    Fernandez de la Casa, M.; Buedo, J. L.; Gonzalez, F.

    2015-01-01

    In 2011 Cofrentes Nuclear Power Plants began a training program for improving the supervision of managers in the field: the effort done not only has improved the quality of supervisions but also has defined a way to reinforce behavior expectations of Cofrentes Nuclear Power Plant. (Author)

  1. 77 FR 32881 - Supervised Securities Holding Company Registration

    Science.gov (United States)

    2012-06-04

    ...), The Report of Foreign Banking Organizations (FR Y-7), The Consolidated Financial Statements for Bank... Y-9ES), The Supplement to the Consolidated Financial Statements for Bank Holding Companies (FR Y-9CS... comprehensive consolidated supervision by a foreign regulator, a nonbank financial company supervised by the...

  2. DNA Sequencing by Capillary Electrophoresis

    Science.gov (United States)

    Karger, Barry L.; Guttman, Andras

    2009-01-01

    Sequencing of human and other genomes has been at the center of interest in the biomedical field over the past several decades and is now leading toward an era of personalized medicine. During this time, DNA sequencing methods have evolved from the labor intensive slab gel electrophoresis, through automated multicapillary electrophoresis systems using fluorophore labeling with multispectral imaging, to the “next generation” technologies of cyclic array, hybridization based, nanopore and single molecule sequencing. Deciphering the genetic blueprint and follow-up confirmatory sequencing of Homo sapiens and other genomes was only possible by the advent of modern sequencing technologies that was a result of step by step advances with a contribution of academics, medical personnel and instrument companies. While next generation sequencing is moving ahead at break-neck speed, the multicapillary electrophoretic systems played an essential role in the sequencing of the Human Genome, the foundation of the field of genomics. In this prospective, we wish to overview the role of capillary electrophoresis in DNA sequencing based in part of several of our articles in this journal. PMID:19517496

  3. Supervision og de tre k´er

    DEFF Research Database (Denmark)

    Schilling, Benedicte; Jacobsen, Claus Haugaard; Nielsen, Jan

    2010-01-01

    Kontrol, kontrakt og kontekst er supervisionens tre k'er. Men hvad er supervision i det hele taget for en størrelse, der spillerså central en rolle for den psykologfaglige profession?......Kontrol, kontrakt og kontekst er supervisionens tre k'er. Men hvad er supervision i det hele taget for en størrelse, der spillerså central en rolle for den psykologfaglige profession?...

  4. Supervising away from home: clinical, cultural and professional challenges.

    Science.gov (United States)

    Abramovitch, Henry; Wiener, Jan

    2017-02-01

    This paper explores some challenges of supervising clinical work of trainees, known as 'routers', who live in countries with diverse cultural, social and political traditions, and the analysts who travel to supervise them. It is written as an evolving dialogue between the authors, who explore together the effects of their own culture of origin, and in particular the legacy and values of their own training institutes on the styles and models of analytic supervision. Their dialogue is framed around the meaning of home and experiences of homesickness for analysts working away from home in an interactive field of strangeness in countries where analytical psychology is a relatively new discipline. The authors outline the findings from their own qualitative survey, where other supervisors working abroad, and those they have supervised, describe their experiences and their encounters with difference. The dialogue ends with both authors discussing what they have learned about teaching and supervising abroad, the implications for more flexible use of Jungian concepts, and how such visits have changed their clinical practice in their home countries. © 2017, The Society of Analytical Psychology.

  5. Label-free probing of genes by time-domain terahertz sensing

    International Nuclear Information System (INIS)

    Bolivar, P Haring; Brucherseifer, M; Nagel, M; Kurz, H; Bosserhoff, A; Buettner, R

    2002-01-01

    A label-free sensing approach for the label-free characterization of genetic material with terahertz (THz) electromagnetic waves is presented. Time-resolved THz analysis of polynucleotides demonstrates a strong dependence of the complex refractive index of DNA molecules in the THz frequency range on their hybridization state. By monitoring THz signals one can thus infer the binding state (hybridized or denatured) of oligo- and polynucleotides, enabling the label-free determination the genetic composition of unknown DNA sequences. A broadband experimental proof-of-principle in a free-space analytic configuration, as well as a higher-sensitivity approach using integrated THz sensors reaching femtomol detection levels and demonstrating the capability to detect single-base mutations, are presented. The potential application for next generation high-throughput label-free genetic analytic systems is discussed

  6. Label-free probing of genes by time-domain terahertz sensing

    Energy Technology Data Exchange (ETDEWEB)

    Bolivar, P Haring [Institut fuer Halbleitertechnik, RWTH Aachen, Sommerfeldstr. 24, D-52056 Aachen (Germany); Brucherseifer, M [Institut fuer Halbleitertechnik, RWTH Aachen, Sommerfeldstr. 24, D-52056 Aachen (Germany); Nagel, M [Institut fuer Halbleitertechnik, RWTH Aachen, Sommerfeldstr. 24, D-52056 Aachen (Germany); Kurz, H [Institut fuer Halbleitertechnik, RWTH Aachen, Sommerfeldstr. 24, D-52056 Aachen (Germany); Bosserhoff, A [Institut fuer Pathologie, Universitaet Regensburg, Franz-Josef-Strauss-Allee 11, D-93053 Regensburg (Germany); Buettner, R [Institut fuer Pathologie, Universitaetsklinikum Bonn, Sigmund-Freud-Str. 25, D-53127 Bonn (Germany)

    2002-11-07

    A label-free sensing approach for the label-free characterization of genetic material with terahertz (THz) electromagnetic waves is presented. Time-resolved THz analysis of polynucleotides demonstrates a strong dependence of the complex refractive index of DNA molecules in the THz frequency range on their hybridization state. By monitoring THz signals one can thus infer the binding state (hybridized or denatured) of oligo- and polynucleotides, enabling the label-free determination the genetic composition of unknown DNA sequences. A broadband experimental proof-of-principle in a free-space analytic configuration, as well as a higher-sensitivity approach using integrated THz sensors reaching femtomol detection levels and demonstrating the capability to detect single-base mutations, are presented. The potential application for next generation high-throughput label-free genetic analytic systems is discussed.

  7. A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

    Science.gov (United States)

    Zhang, Xiaotian; Yin, Jian; Zhang, Xu

    2018-03-02

    Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

  8. The Kokeshi Doll: A Tool for Family Supervision.

    Science.gov (United States)

    Sampson, Dick T.

    1996-01-01

    Claims that the use of Kokeshi dolls--a small limbless cylindrical wooden doll from Japan--allows counseling supervisees to focus on conceptualizations, personalization, and process skills. Uses a case study to illustrate how these dolls can enhance supervision, allowing trainees to become actively involved in the supervision process. (RJM)

  9. The Views of Educational Supervisors on Clinical Supervision

    Science.gov (United States)

    Kayikçi, Kemal; Yilmaz, Ozan; Sahin, Ahmet

    2017-01-01

    Contemporary educational supervision expresses democratic and leadership focused supervisory approach which consists of collaboration, trust, sharing and improving. The aims of the study are to investigate the answer of how current teacher supervision in Turkey is conducted according to the views of educational supervisors, and to unearth what the…

  10. Cliché, Gossip, and Anecdote as Supervision Training

    Science.gov (United States)

    Grealy, Liam

    2016-01-01

    This article expands on a co-authored project with Timothy Laurie on the practices and ethics of higher degree research (HDR) supervision (or advising): "What does good HDR supervision look like?" in contemporary universities. It connects that project with scholarship on the relevance of "common sense" to questions of…

  11. Online Lab Books for Supervision of Project Students

    Science.gov (United States)

    Badge, J. L.; Badge, R. M.

    2009-01-01

    In this article, the authors report a case study where Blackboard's wiki function was used to create electronic lab books for the supervision of undergraduate students completing laboratory based research projects. This successful experiment in supervision using electronic notebooks provided a searchable record of student work and a permanent…

  12. Professional Disclosure Statements and Formal Plans for Supervision: Two Strategies for Minimizing the Risk of Ethical Conflicts in Post-Master's Supervision.

    Science.gov (United States)

    Cobia, Debra C.; Boes, Susan R.

    2000-01-01

    Discusses ethical conflicts related to issues of informed consent, due process, competence, confidentiality, and dual relationships in supervision. Proposes two strategies as ways to minimize the potential for ethical conflict in post-master's supervision: the use of professional disclosure statements by supervisors and the development of formal…

  13. Study and development of equipment supervision technique system and its management software for nuclear electricity production

    International Nuclear Information System (INIS)

    Zhang Liying; Zou Pingguo; Zhu Chenghu; Lu Haoliang; Wu Jie

    2008-01-01

    The equipment supervision technique system, which standardized the behavior of supervision organizations in planning and implementing of equipment supervision, is built up based on equipment supervision technique documents, such as Quality Supervision Classifications, Special Supervision Plans and Supervision Guides. Furthermore, based on the research, the equipment supervision management information system is developed by Object Oriented Programming, which consists of supervision information, supervision technique, supervision implementation, quality statistics and analysis module. (authors)

  14. Psychiatric nursing menbers' reflections on participating in group-based clinical supervision

    DEFF Research Database (Denmark)

    Buus, Niels; Angel, Sanne; Traynor, Michael

    2011-01-01

    This paper is a report of an interview study exploring psychiatric hospital nursing staff members' reflections on participating in supervision. Clinical supervision is a pedagogical process designed to direct, develop, and support clinical nurses. Participation rates in clinical supervision...... they influence participation rates. Twenty-two psychiatric hospital nursing staff members were interviewed with a semistructured interview guide. Interview transcripts were interpreted by means of Ricoeur's hermeneutic method. The respondents understood clinical supervision to be beneficial, but with very...

  15. 28 CFR 2.95 - Early termination from supervision.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Early termination from supervision. 2.95 Section 2.95 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS District of Columbia Code: Prisoners and Parolees § 2.95 Early termination from...

  16. Gender Effects on Managing and Supervising Salespersons: A ...

    African Journals Online (AJOL)

    This study investigates student perceptions of the gender effect on managing and supervising efforts. Based on 385 surveys, the results for the entire sample of students, as well as for male and female samples, showed the existence of a significant gender effect for some aspects of managing and supervising. Also ...

  17. Supervision af psykologkandidater i privat praksis

    DEFF Research Database (Denmark)

    Petersen, Birgitte

    et litteratur review over relevante temaer i supervisionslitteraturen samt overvejelser om læring i supervision. Afhandlingens empiriske resultater vil blive belyst og diskuteret med udgangspunkt i tilsvarende fænomener i supervisionslitteraturen. Resultaterne af undersøgelsen viser, at der er en...... række vigtige elementer ved supervision, der skal være opfyldt, hvis den skal opleves som udviklende og lærerig af praksiskandidaterne. Det er elementer som kontraktetablering, rådgivning og teoretisk refleksion, en tydelig teoretisk referenceramme samt støtte og anerkendelse fra supervisor. Det...

  18. Declarative modeling for process supervision

    International Nuclear Information System (INIS)

    Leyval, L.

    1989-01-01

    Our work is a contribution to computer aided supervision of continuous processes. It is inspired by an area of Artificial Intelligence: qualitative physics. Here, supervision is based on a model which continuously provides operators with a synthetic view of the process; but this model is founded on general principles of control theory rather than on physics. It involves concepts such as high gain or small time response. It helps in linking temporally the evolution of various variables. Moreover, the model provides predictions of the future behaviour of the process, which allows action advice and alarm filtering. This should greatly reduce the famous cognitive overload associated to any complex and dangerous evolution of the process

  19. Supervision of tunnelling constructions and software used for their evaluation

    Science.gov (United States)

    Caravanas, Aristotelis; Hilar, Matous

    2017-09-01

    Supervision is a common instrument for controlling constructions of tunnels. In order to suit relevant project’s purposes a supervision procedure is modified by local conditions, habits, codes and ways of allocating of a particular tunnelling project. The duties of tunnel supervision are specified in an agreement with the client and they can include a wide range of activities. On large scale tunnelling projects the supervision tasks are performed by a high number of people of different professions. Teamwork, smooth communication and coordination are required in order to successfully fulfil supervision tasks. The efficiency and quality of tunnel supervision work are enhanced when specialized software applications are used. Such applications should allow on-line data management and the prompt evaluation, reporting and sharing of relevant construction information and other aspects. The client is provided with an as-built database that contains all the relevant information related to a construction process, which is a valuable tool for the claim management as well as for the evaluation of structure defects that can occur in the future. As a result, the level of risks related to tunnel constructions is decreased.

  20. Developing a manual for strengthening mental health nurses' clinical supervision

    DEFF Research Database (Denmark)

    Buus, Niels; Cassedy, Paul; Gonge, Henrik

    2013-01-01

    In this article, we report findings from a study aimed at developing the content and implementation of a manual for a research-based intervention on clinical supervision of mental health nursing staff. The intervention was designed to strengthen already existing supervision practices through...... educational preparation for supervision and systematic reflection on supervision. The intervention consists of three sessions and was implemented on two groups of mental health hospital staff. We present an outline of the manual and explain how the trial sessions made us adjust the preliminary manual....... The effects of implementing the manual will subsequently be analysed in an independent randomised controlled trial....

  1. Model for investigating the benefits of clinical supervision in psychiatric nursing

    DEFF Research Database (Denmark)

    Gonge, Henrik; Buus, Niels

    2011-01-01

    with the effectiveness of clinical supervision, as measured by the Manchester Clinical Supervision Scale (MCSS). Furthermore, MCSS scores were associated with benefits, such as increased job satisfaction, vitality, rational coping and less stress, emotional exhaustion, and depersonalization. Multivariate analyses......The objective of this study was to test a model for analysing the possible benefits of clinical supervision. The model suggested a pathway from participation to effectiveness to benefits of clinical supervision, and included possible influences of individual and workplace factors. The study sample...

  2. The ViewPoint radioprotection supervision workstation; Poste de supervision radioprotection viewpoint

    Energy Technology Data Exchange (ETDEWEB)

    Gaultier, E. [APVL Ingenierie- 6, bd Nobel - Equatop La Rabelais - 37540 Saint Cyr sur Loire (France)

    2009-07-01

    The author briefly presents the ViewPoint supervision global solution which incorporates audio and video advanced technologies to manage radioprotection operational measurements. Data can be transmitted by-wire or wireless. It can integrate a large number of radioprotection measurement instruments, such as a belt for the monitoring of physiological parameters (body temperature, breathing rhythm, body posture)

  3. Accelerated stem cell labeling with ferucarbotran and protamine

    Energy Technology Data Exchange (ETDEWEB)

    Golovko, Daniel M.; Henning, Tobias; Bauer, Jan S. [Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA (United States); Settles, Marcus; Rummeny, Ernst J. [Technical University Munich, Department of Radiology, Munich (Germany); Frenzel, Thomas [Bayer Schering Pharma AG, Berlin (Germany); Mayerhofer, Artur [Ludwig-Maximilians-Universitaet, Institute of Cell Biology, Munich (Germany); Daldrup-Link, Heike E. [Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA (United States); UCSF Medical Center, Contrast Agent Research Group, Department of Radiology, San Francisco, CA (United States)

    2010-03-15

    To develop and characterize a clinically applicable, fast and efficient method for stem cell labeling with ferucarbotran and protamine for depiction with clinical MRI. The hydrodynamic diameter, zeta potential and relaxivities of ferucarbotran and varying concentrations of protamine were measured. Once the optimized ratio was found, human mesenchymal stem cells (MSCs) were labeled at varying incubation times (1-24 h). Viability was assessed via Trypan blue exclusion testing. 150,000 labeled cells in Ficoll solution were imaged with T1-, T2- and T2*-weighted sequences at 3 T, and relaxation rates were calculated. Varying the concentrations of protamine allows for easy modification of the physicochemical properties. Simple incubation with ferucarbotran alone resulted in efficient labeling after 24 h of incubation while assisted labeling with protamine resulted in similar results after only 1 h. Cell viability remained unaffected. R2 and R2* relaxation rates were drastically increased. Electron microscopy confirmed intracellular iron oxide uptake in lysosomes. Relaxation times correlated with results from ICP-AES. Our results show internalization of ferucarbotran can be accelerated in MSCs with protamine, an approved heparin antagonist and potentially clinically applicable uptake-enhancing agent. (orig.)

  4. 19 CFR 191.44 - Destruction under Customs supervision.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 2 2010-04-01 2010-04-01 false Destruction under Customs supervision. 191.44 Section 191.44 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK Rejected Merchandise § 191.44 Destruction under Customs supervision. A claimant may destroy merchandise an...

  5. 19 CFR 191.37 - Destruction under Customs supervision.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 2 2010-04-01 2010-04-01 false Destruction under Customs supervision. 191.37 Section 191.37 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK Unused Merchandise Drawback § 191.37 Destruction under Customs supervision. A claimant may destroy...

  6. A Good Supervisor--Ten Facts of Caring Supervision

    Science.gov (United States)

    Määttä, Kaarina

    2015-01-01

    This article describes the elements of caring supervision of doctoral theses. The purpose was to describe the best practices as well as challenges of supervision especially from the supervisor's perspective. The analysis is based on the author's extensive experience as a supervisor and related data obtained for research and developmental purposes.…

  7. 19 CFR 191.25 - Destruction under Customs supervision.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 2 2010-04-01 2010-04-01 false Destruction under Customs supervision. 191.25 Section 191.25 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) DRAWBACK Manufacturing Drawback § 191.25 Destruction under Customs supervision. A claimant may destroy merchandise...

  8. 33 CFR 326.4 - Supervision of authorized activities.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Supervision of authorized activities. 326.4 Section 326.4 Navigation and Navigable Waters CORPS OF ENGINEERS, DEPARTMENT OF THE ARMY, DEPARTMENT OF DEFENSE ENFORCEMENT § 326.4 Supervision of authorized activities. (a) Inspections. District engineers will, at their discretion, take...

  9. Novel DNA sequence detection method based on fluorescence energy transfer

    International Nuclear Information System (INIS)

    Kobayashi, S.; Tamiya, E.; Karube, I.

    1987-01-01

    Recently the detection of specific DNA sequence, DNA analysis, has been becoming more important for diagnosis of viral genomes causing infections disease and human sequences related to inherited disorders. These methods typically involve electrophoresis, the immobilization of DNA on a solid support, hybridization to a complementary probe, the detection using labeled with /sup 32/P or nonisotopically with a biotin-avidin-enzyme system, and so on. These techniques are highly effective, but they are very time-consuming and expensive. A principle of fluorescene energy transfer is that the light energy from an excited donor (fluorophore) is transferred to an acceptor (fluorophore), if the acceptor exists in the vicinity of the donor and the excitation spectrum of donor overlaps the emission spectrum of acceptor. In this study, the fluorescence energy transfer was applied to the detection of specific DNA sequence using the hybridization method. The analyte, single-stranded DNA labeled with the donor fluorophore is hybridized to a probe DNA labeled with the acceptor. Because of the complementary DNA duplex formation, two fluorophores became to be closed to each other, and the fluorescence energy transfer was occurred

  10. Data integration modeling applied to drill hole planning through semi-supervised learning: A case study from the Dalli Cu-Au porphyry deposit in the central Iran

    Science.gov (United States)

    Fatehi, Moslem; Asadi, Hooshang H.

    2017-04-01

    In this study, the application of a transductive support vector machine (TSVM), an innovative semi-supervised learning algorithm, has been proposed for mapping the potential drill targets at a detailed exploration stage. The semi-supervised learning method is a hybrid of supervised and unsupervised learning approach that simultaneously uses both training and non-training data to design a classifier. By using the TSVM algorithm, exploration layers at the Dalli porphyry Cu-Au deposit in the central Iran were integrated to locate the boundary of the Cu-Au mineralization for further drilling. By applying this algorithm on the non-training (unlabeled) and limited training (labeled) Dalli exploration data, the study area was classified in two domains of Cu-Au ore and waste. Then, the results were validated by the earlier block models created, using the available borehole and trench data. In addition to TSVM, the support vector machine (SVM) algorithm was also implemented on the study area for comparison. Thirty percent of the labeled exploration data was used to evaluate the performance of these two algorithms. The results revealed 87 percent correct recognition accuracy for the TSVM algorithm and 82 percent for the SVM algorithm. The deepest inclined borehole, recently drilled in the western part of the Dalli deposit, indicated that the boundary of Cu-Au mineralization, as identified by the TSVM algorithm, was only 15 m off from the actual boundary intersected by this borehole. According to the results of the TSVM algorithm, six new boreholes were suggested for further drilling at the Dalli deposit. This study showed that the TSVM algorithm could be a useful tool for enhancing the mineralization zones and consequently, ensuring a more accurate drill hole planning.

  11. Predicament of Chinese legislation on genetically modified food (GMF) labeling management and solutions - from the perspective of the new food safety law.

    Science.gov (United States)

    Li, Wei; Li, Han

    2017-11-01

    This paper considers the background of Article 69 of the newly revised Food Safety Law in China in combination with the current situation of Chinese legislation on GMF labeling management, compared with a foreign genetically modified food labeling management system, revealing deficiencies in the Chinese legislation with respect to GMF labeling management, and noting that institutions should properly consider the GMF labeling management system in China. China adheres to the principle of mandatory labeling based on both product and processes in relation to GMFs and implements a system of process-centered mandatory labeling under a negotiation-construction form. However, China has not finally defined the supervision mode of mandatory labeling of GMFs through laws, and this remains a challenge for GMF labeling management when two mandatory labeling modes coexist. Since April 2015 and October 1, 2015 when the Food Safety Law was revised and formally implemented respectively, the applicable judicial interpretations and enforcement regulations have not made applicable revisions and only principle-based terms have been included in the Food Safety Law, it is still theoretically and practically difficult for mandatory labeling of GMFs in juridical practices and conflicts between the principle of GMF labeling and the purpose that safeguards consumers' right to know remain. The GMF labeling system should be legislatively and practically improved to an extent that protects consumers' right to know. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  12. Experiences of Supervision at Practice Placement Sites

    Directory of Open Access Journals (Sweden)

    Lesley Diack

    2014-01-01

    Full Text Available Background. Whilst placement supervision and clinical education programmes are of significant value in shaping the behaviours of undergraduate healthcare students, appropriate provisions which are efficacious to the learner are somewhat lacking, particularly for students studying on UK MPharm programmes. Objectives. To explore and explain the value of placement supervision to the personal development and employability of undergraduate pharmacy students. Methods. Students participated in a week long community pharmacy pilot programme, a result of a collaborative effort between the School of Pharmacy and Life Sciences and a small consortium of community pharmacies. Students and stakeholders were asked to evaluate their experiences via separate questionnaires which had been developed to elicit views and attitudes. Key Findings. Feedback from students and stakeholders towards the experience was overwhelmingly positive with multiple benefits being reported. Of particular prominence was the emphasis in student feedback on the value of placement supervision to their professional and personal development. Findings were indicative of a development in clinical practice proficiencies, core skills, and improvement in decision-making practice. Conclusions. The benefits of clinical supervision to the professional and personal development of MPharm students are well documented, although attracting professional pharmacy supervisors is proving a problematic task for educational providers in the UK.

  13. [Supervision of foods containing components of genetically modified organisms and the problems of labeling this type of products].

    Science.gov (United States)

    Onishchenko, G G

    2010-01-01

    Commercial production of genetically modified (GM) crops as food or feed is regarded as a promising social area in the development of modern biotechnology. The Russian Federation has set up a governmental system to regulate the use of biotechnology products, which is based on Russian and foreign experience and the most up-to-date scientific approaches. The system for evaluating the quality and safety of GM foodstuffs envisages the postregistration monitoring of their circulation as an obligatory stage. For these purposes, the world community applies two methods: enzyme immunoassay and polymerase chain reaction. It should be noted that there are various approaches to GM food labeling in the world; this raises the question of whether the labeling of foods that are prepared from genetically modified organisms, but contain no protein or DNA is to be introduced in Russia, as in the European Union.

  14. A model for dealing with parallel processes in supervision

    Directory of Open Access Journals (Sweden)

    Lilja Cajvert

    2011-03-01

    Supervision in social work is essential for successful outcomes when working with clients. In social work, unconscious difficulties may arise and similar difficulties may occur in supervision as parallel processes. In this article, the development of a practice-based model of supervision to deal with parallel processes in supervision is described. The model has six phases. In the first phase, the focus is on the supervisor’s inner world, his/her own reflections and observations. In the second phase, the supervision situation is “frozen”, and the supervisees are invited to join the supervisor in taking a meta-perspective on the current situation of supervision. The focus in the third phase is on the inner world of all the group members as well as the visualization and identification of reflections and feelings that arose during the supervision process. Phase four focuses on the supervisee who presented a case, and in phase five the focus shifts to the common understanding and theorization of the supervision process as well as the definition and identification of possible parallel processes. In the final phase, the supervisee, with the assistance of the supervisor and other members of the group, develops a solution and determines how to proceed with the client in treatment. This article uses phenomenological concepts to provide a theoretical framework for the supervision model. Phenomenological reduction is an important approach to examine and to externalize and visualize the inner words of the supervisor and supervisees. Een model voor het hanteren van parallelle processen tijdens supervisie Om succesvol te zijn in de hulpverlening aan cliënten, is supervisie cruciaal in het sociaal werk. Tijdens de hulpverlening kunnen impliciete moeilijkheden de kop opsteken en soortgelijke moeilijkheden duiken soms ook op tijdens supervisie. Dit worden parallelle processen genoemd. Dit artikel beschrijft een op praktijkervaringen gebaseerd model om dergelijke parallelle

  15. Research of ddi based on multi-label conditional random field

    Directory of Open Access Journals (Sweden)

    Yu Yangzhi

    2017-01-01

    Full Text Available The detection of drug name and drug-drug interaction(DDI is considered as a sequence labeling task in this paper. We present the multi-label CRF method to complete it. Compared to the traditional method, our method can not only identify drug names, but also can identify drug-drug interaction. According to the characteristics of medical texts, this paper extracts the good features of the description of DDI. The proposed method has good performance in DDIExtraction 2013 evaluation corpus.

  16. QUEST : Eliminating online supervised learning for efficient classification algorithms

    NARCIS (Netherlands)

    Zwartjes, Ardjan; Havinga, Paul J.M.; Smit, Gerard J.M.; Hurink, Johann L.

    2016-01-01

    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

  17. Clinical Supervision in Undergraduate Nursing Students: A Review of the Literature

    Science.gov (United States)

    Franklin, Natasha

    2013-01-01

    The concept of clinical supervision to facilitate the clinical education environment in undergraduate nursing students is well discussed within the literature. Despite the many models of clinical supervision described within the literature there is a lack of clear guidance and direction which clinical supervision model best suits the clinical…

  18. QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

    Science.gov (United States)

    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.

  19. 25 CFR 213.43 - Relinquishment of Government supervision.

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false Relinquishment of Government supervision. 213.43 Section 213.43 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR ENERGY AND MINERALS LEASING OF RESTRICTED LANDS OF MEMBERS OF FIVE CIVILIZED TRIBES, OKLAHOMA, FOR MINING Removal of Restrictions § 213.43 Relinquishment of Government supervision....

  20. The supervisor as gender analyst: feminist perspectives on group supervision and training.

    Science.gov (United States)

    Schoenholtz-Read, J

    1996-10-01

    Supervision and training groups have advantages over dyadic supervision and training that include factors to promote group learning and interaction within a sociocultural context. This article focuses on the gender aspects of group supervision and training. It provides a review of feminist theoretical developments and presents their application to group supervision and training in the form of eight guidelines that are illustrated by clinical examples.

  1. Supervision of the ATLAS High Level Trigger System

    CERN Document Server

    Wheeler, S.; Meessen, C.; Qian, Z.; Touchard, F.; Negri, France A.; Zobernig, H.; CHEP 2003 Computing in High Energy Physics; Negri, France A.

    2003-01-01

    The ATLAS High Level Trigger (HLT) system provides software-based event selection after the initial LVL1 hardware trigger. It is composed of two stages, the LVL2 trigger and the Event Filter. The HLT is implemented as software tasks running on large processor farms. An essential part of the HLT is the supervision system, which is responsible for configuring, coordinating, controlling and monitoring the many hundreds of processes running in the HLT. A prototype implementation of the supervision system, using tools from the ATLAS Online Software system is presented. Results from scalability tests are also presented where the supervision system was shown to be capable of controlling over 1000 HLT processes running on 230 nodes.

  2. Improving Supervision for Students at a Distance: Videoconferencing for Group Meetings

    Science.gov (United States)

    Könings, Karen D.; Popa, Daniela; Gerken, Maike; Giesbers, Bas; Rienties, Bart C.; van der Vleuten, Cees P. M.; van Merriënboer, Jeroen J. G.

    2016-01-01

    Every year, thousands of students go abroad for part of their study programme. Supervision from the home institution is then crucial for good study progress. Providing supervision and feedback at a distance is challenging. This project aims to identify bottlenecks for supervision and hypothesises that online supervisory group meetings with…

  3. High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.

    Science.gov (United States)

    Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M

    2016-09-07

    Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Beginning therapists’ experiences of what constitutes good and bad psychotherapy supervision

    DEFF Research Database (Denmark)

    Jacobsen, Claus Haugaard; Pedersen, Lene Tanggaard

    2009-01-01

    events. Also included were the importance of peers in the supervision group and the organisational setting of the supervision. The objective was to give detailed descriptions in the form of condensed narratives of each student’s preferences concerning supervision. Furthermore, a cross-sectional analysis...... in the existing literature in the field. The beginning therapist prefer supervision in which advice and clear and specific instructions are given on how to do the job, where theoretical considerations are included, and the supervisor supports, affirms and structures the sessions. However, of particular interest...

  5. Implementing a sustainable clinical supervision model for Isles nurses in Orkney.

    Science.gov (United States)

    Hall, Ian

    2018-03-02

    The Isles Network of Care (INOC) community nurses work at the extreme of the remote and rural continuum, working mostly as lone practitioners. Following the development of sustainable clinical supervision model for Isles nurses in Orkney, clinical supervision was found to improve both peer support and governance for this group of isolated staff. A literature overview identified the transition of clinical supervision in general nursing over 24 years from 'carrot' to 'stick'. The study included a questionnaire survey that was sent to the 2017 Queen's Nursing Institute Scotland cohort to elicit information about the nurses' experience of clinical supervision. The survey found that 55% provide supervision and 40% receive it. Health board encouragement of its use was found to be disappointingly low at 40%. The INOC nurses were surveyed about the new peer-support (restorative) model, which relies on video-conference contact to allow face to face interaction between isolated isles nurses. Feedback prompted a review of clinical supervision pairings, and the frequency and methods of meeting. The need for supervisor training led to agreement with the Remote and Rural Health Education Alliance to provide relevant support. The perceived benefits of supervision included increased support and reflection, and improved relationships with isolated colleagues.

  6. The Wicked Problem of the Intersection between Supervision and Evaluation

    Directory of Open Access Journals (Sweden)

    Ian M. METTE

    2017-03-01

    Full Text Available The purpose of this research was to explore how principals in eight high-functioning elementary schools in one American school district balanced teacher supervision and evaluation in their role as an instructional leader. Using the theoretical framework of ‘wicked problems’, to unpack the circular used to problematize teacher supervision and evaluation, the findings analyse how elementary principals in these eight buildings acknowledge the tensions and conflicts between supervision and evaluation, specifically as they relate to improving teacher instruction. Specifically, the results of this study highlight not only the differences between supervision and evaluation, but also the intersection between the two functions, as well as how high-performing elementary school principals serve as an instructional coach rather than a manager of teachers. While the two functions of supervision and evaluation are inherently different, it is the acknowledgement of the intersection between the two functions that can allow building principals to progress as instructional coaches who can better develop human resources and create higher-functioning school systems. Overall, this study points toward the importance of elementary principals having the instructional leadership skills to differentiate supervision and professional development need for teachers, which in turn influences the evaluation of a teacher is in her/his respective career.

  7. The wicked problem of the intersection between supervision and evaluation

    Directory of Open Access Journals (Sweden)

    Ian M. Mette

    2017-03-01

    Full Text Available The purpose of this research was to explore how principals in eight high-functioning elementary schools in one American school district balanced teacher supervision and evaluation in their role as an instructional leader. Using the theoretical framework of ‘wicked problems’, to unpack the circular used to problematize teacher supervision and evaluation, the findings analyse how elementary principals in these eight buildings acknowledge the tensions and conflicts between supervision and evaluation, specifically as they relate to improving teacher instruction. Specifically, the results of this study highlight not only the differences between supervision and evaluation, but also the intersection between the two functions, as well as how high-performing elementary school principals serve as an instructional coach rather than a manager of teachers. While the two functions of supervision and evaluation are inherently different, it is the acknowledgement of the intersection between the two functions that can allow building principals to progress as instructional coaches who can better develop human resources and create higher-functioning school systems. Overall, this study points toward the importance of elementary principals having the instructional leadership skills to differentiate supervision and professional development need for teachers, which in turn influences the evaluation of a teacher is in her/his respective career.

  8. Label-Free Detection of Sequence-Specific DNA Based on Fluorescent Silver Nanoclusters-Assisted Surface Plasmon-Enhanced Energy Transfer.

    Science.gov (United States)

    Ma, Jin-Liang; Yin, Bin-Cheng; Le, Huynh-Nhu; Ye, Bang-Ce

    2015-06-17

    We have developed a label-free method for sequence-specific DNA detection based on surface plasmon enhanced energy transfer (SPEET) process between fluorescent DNA/AgNC string and gold nanoparticles (AuNPs). DNA/AgNC string, prepared by a single-stranded DNA template encoded two emitter-nucleation sequences at its termini and an oligo spacer in the middle, was rationally designed to produce bright fluorescence emission. The proposed method takes advantage of two strategies. The first one is the difference in binding properties of single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) toward AuNPs. The second one is SPEET process between fluorescent DNA/AgNC string and AuNPs, in which fluorescent DNA/AgNC string can be spontaneously adsorbed onto the surface of AuNPs and correspondingly AuNPs serve as "nanoquencher" to quench the fluorescence of DNA/AgNC string. In the presence of target DNA, the sensing probe hybridized with target DNA to form duplex DNA, leading to a salt-induced AuNP aggregation and subsequently weakened SPEET process between fluorescent DNA/AgNC string and AuNPs. A red-to-blue color change of AuNPs and a concomitant fluorescence increase were clearly observed in the sensing system, which had a concentration dependent manner with specific DNA. The proposed method achieved a detection limit of ∼2.5 nM, offering the following merits of simple design, convenient operation, and low experimental cost because of no chemical modification, organic dye, enzymatic reaction, or separation procedure involved.

  9. Peptide-membrane Interactions by Spin-labeling EPR

    Science.gov (United States)

    Smirnova, Tatyana I.; Smirnov, Alex I.

    2016-01-01

    Site-directed spin labeling (SDSL) in combination with Electron Paramagnetic Resonance (EPR) spectroscopy is a well-established method that has recently grown in popularity as an experimental technique, with multiple applications in protein and peptide science. The growth is driven by development of labeling strategies, as well as by considerable technical advances in the field, that are paralleled by an increased availability of EPR instrumentation. While the method requires an introduction of a paramagnetic probe at a well-defined position in a peptide sequence, it has been shown to be minimally destructive to the peptide structure and energetics of the peptide-membrane interactions. In this chapter, we describe basic approaches for using SDSL EPR spectroscopy to study interactions between small peptides and biological membranes or membrane mimetic systems. We focus on experimental approaches to quantify peptide-membrane binding, topology of bound peptides, and characterize peptide aggregation. Sample preparation protocols including spin-labeling methods and preparation of membrane mimetic systems are also described. PMID:26477253

  10. Stable isotope labeling-mass spectrometry analysis of methyl- and pyridyloxobutyl-guanine adducts of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone in p53-derived DNA sequences.

    Science.gov (United States)

    Rajesh, Mathur; Wang, Gang; Jones, Roger; Tretyakova, Natalia

    2005-02-15

    The p53 tumor suppressor gene is a primary target in smoking-induced lung cancer. Interestingly, p53 mutations observed in lung tumors of smokers are concentrated at guanine bases within endogenously methylated (Me)CG dinucleotides, e.g., codons 157, 158, 245, 248, and 273 ((Me)C = 5-methylcytosine). One possible mechanism for the increased mutagenesis at these sites involves targeted binding of metabolically activated tobacco carcinogens to (Me)CG sequences. In the present work, a stable isotope labeling HPLC-ESI(+)-MS/MS approach was employed to analyze the formation of guanine lesions induced by the tobacco-specific lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) within DNA duplexes representing p53 mutational "hot spots" and surrounding sequences. Synthetic DNA duplexes containing p53 codons 153-159, 243-250, and 269-275 were prepared, where (Me)C was incorporated at all physiologically methylated CG sites. In each duplex, one of the guanine bases was replaced with [1,7,NH(2)-(15)N(3)-2-(13)C]-guanine, which served as an isotope "tag" to enable specific quantification of guanine lesions originating from that position. After incubation with NNK diazohydroxides, HPLC-ESI(+)-MS/MS analysis was used to determine the yields of NNK adducts at the isotopically labeled guanine and at unlabeled guanine bases elsewhere in the sequence. We found that N7-methyl-2'-deoxyguanosine and N7-[4-oxo-4-(3-pyridyl)but-1-yl]guanine lesions were overproduced at the 3'-guanine bases within polypurine runs, while the formation of O(6)-methyl-2'-deoxyguanosine and O(6)-[4-oxo-4-(3-pyridyl)but-1-yl]-2'-deoxyguanosine adducts was specifically preferred at the 3'-guanine base of 5'-GG and 5'-GGG sequences. In contrast, the presence of 5'-neighboring (Me)C inhibited O(6)-guanine adduct formation. These results indicate that the N7- and O(6)-guanine adducts of NNK are not overproduced at the endogenously methylated CG dinucleotides within the p53 tumor suppressor gene

  11. Self-reflection in cognitive behavioural therapy and supervision.

    Science.gov (United States)

    Prasko, Jan; Mozny, Petr; Novotny, Miroslav; Slepecky, Milos; Vyskocilova, Jana

    2012-12-01

    Supervision is a basic part of training and ongoing education in cognitive behavioural therapy. Self-reflection is an important part of supervision. The conscious understanding of one's own emotions, feelings, thoughts, and attitudes at the time of their occurrence, and the ability to continuously follow and recognize them are among the most important abilities of both therapists and supervisors. The objective of this article is to review aspects related to supervision in cognitive behavioural therapy and self-reflection in the literature. This is a narrative review. A literature review was performed using the PubMed, SciVerse Scopus, and Web of Science databases; additional references were found through bibliography reviews of relevant articles published prior to July 2011. The databases were searched for articles containing the following keywords: cognitive behavioural therapy, self-reflection, therapeutic relationship, training, supervision, transference, and countertransference. The review also includes information from monographs referred to by other reviews. We discuss conceptual aspects related to supervision and the role of self-reflection. Self-reflection in therapy is a continuous process which is essential for the establishment of a therapeutic relationship, the professional growth of the therapist, and the ongoing development of therapeutic skills. Recognizing one's own emotions is a basic skill from which other skills necessary for both therapy and emotional self-control stem. Therapists who are skilled in understanding their inner emotions during their encounters with clients are better at making decisions, distinguishing their needs from their clients' needs, understanding transference and countertransference, and considering an optimal response at any time during a session. They know how to handle their feelings so that these correspond with the situation and their response is in the client's best interest. The ability to self-reflect increases the

  12. Is banking supervision central to central banking?

    OpenAIRE

    Joe Peek; Eric S. Rosengren; Geoffrey M. B. Tootell

    1997-01-01

    Whether central banks should play an active role in bank supervision and regulation is being debated both in the United States and abroad. While the Bank of England has recently been stripped of its supervisory responsibilities and several proposals in the United States have advocated removing bank supervision from the Federal Reserve System, other countries are considering enhancing central bank involvement in this area. Many of the arguments for and against these proposals hinge on the effe...

  13. Optimal Preventive Bank Supervision: Combining Random Audits and Continuous Intervention

    OpenAIRE

    Mohamed Belhaj; Nataliya Klimenko

    2012-01-01

    Early regulator interventions into problem banks are one of the key suggestions of Basel II. However, no guidance is given on their design. To fill this gap, we outline an incentive-based preventive supervision strategy that eliminates bad asset management in banks. Two supervision techniques are combined: continuous regulator intervention and random audits. Random audit technologies differ as to quality and cost. Our design ensures good management without excessive supervision costs, through...

  14. Computer supervision of the core outlet sodium temperatures of FBTR

    International Nuclear Information System (INIS)

    Boopathy, C.

    1976-01-01

    Safety monitoring of the fast breeder test reactor at Kalpakkam (India) is achieved by a CDPS-on-line dual computer system which is dedicated to plant supervision. The on-line subsystem scans and supervises all the 170 core thermocouple signals every second. Organisation of the reactor core instruments, supervision of mean sodium outlet temperature and mean temperature drop across the core, detection of plugging of a fuel assembly are explained. (A.K.)

  15. Botanical origin of dietary supplements labeled as "Kwao Keur", a folk medicine from Thailand.

    Science.gov (United States)

    Maruyama, Takuro; Kawamura, Maiko; Kikura-Hanajiri, Ruri; Goda, Yukihiro

    2014-01-01

    In the course of our study on the quality of dietary supplements in Japan, both the internal transcribed spacer (ITS) sequence of nrDNA and the rps16 intron sequence of cpDNA of products labeled as "Kwao Keur" were investigated. As a result, the DNA sequence of Pueraria candollei var. mirifica, which is the source plant of Kwao Keur, was observed in only about half of the products. Inferred from the determined sequences, source plants in the other products included Medicago sativa, Glycyrrhiza uralensis, Pachyrhizus erosus, and Ipomoea batatas, etc. These inferior products are estimated to lack the efficacy implied by their labeling. In order to guarantee the quality of dietary supplements, it is important to identify the source materials exactly; in addition, an infrastructure that can exclude these inferior products from the market is needed for the protection of consumers from potential damage to their health and finances. The DNA analysis performed in this study is useful for this purpose.

  16. Etiske betragtninger ved supervision

    DEFF Research Database (Denmark)

    Jacobsen, Claus Haugaard; Agerskov, Kirsten

    2007-01-01

    Kapitlet præsenterer nogle etiske betragtninger ved supervision. Mens der længe har eksisteret etiske retningslinjer for psykoterapeutisk arbejde, har der overraskende nok manglet tilsvarende vejledninger på supervisionsområdet. Det betyder imidlertid ikke, at de ikke er relevante. I kapitlet gøres...

  17. Energy efficiency supervision strategy selection of Chinese large-scale public buildings

    International Nuclear Information System (INIS)

    Jin Zhenxing; Wu Yong; Li Baizhan; Gao Yafeng

    2009-01-01

    This paper discusses energy consumption, building development and building energy consumption in China, and points that energy efficiency management and maintenance of large-scale public buildings is the breakthrough point of building energy saving in China. Three obstacles are lack of basic statistics data, lack of service market for building energy saving, and lack of effective management measures account for the necessity of energy efficiency supervision for large-scale public buildings. And then the paper introduces the supervision aims, the supervision system and the five basic systems' role in the supervision system, and analyzes the working mechanism of the five basic systems. The energy efficiency supervision system of large-scale public buildings takes energy consumption statistics as a data basis, Energy auditing as a technical support, energy consumption ration as a benchmark of energy saving and price increase beyond ration as a price lever, and energy efficiency public-noticing as an amplifier. The supervision system promotes energy efficiency operation and maintenance of large-scale public building, and drives a comprehensive building energy saving in China.

  18. Energy efficiency supervision strategy selection of Chinese large-scale public buildings

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Zhenxing; Li, Baizhan; Gao, Yafeng [The Faculty of Urban Construction and Environmental Engineering, Chongqing University, Chongqing (China); Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment, Ministry of Education, Chongqing 400045 (China); Wu, Yong [The Department of Science and Technology, Ministry of Construction, Beijing 100835 (China)

    2009-06-15

    This paper discusses energy consumption, building development and building energy consumption in China, and points that energy efficiency management and maintenance of large-scale public buildings is the breakthrough point of building energy saving in China. Three obstacles are lack of basic statistics data, lack of service market for building energy saving, and lack of effective management measures account for the necessity of energy efficiency supervision for large-scale public buildings. And then the paper introduces the supervision aims, the supervision system and the five basic systems' role in the supervision system, and analyzes the working mechanism of the five basic systems. The energy efficiency supervision system of large-scale public buildings takes energy consumption statistics as a data basis, Energy auditing as a technical support, energy consumption ration as a benchmark of energy saving and price increase beyond ration as a price lever, and energy efficiency public-noticing as an amplifier. The supervision system promotes energy efficiency operation and maintenance of large-scale public building, and drives a comprehensive building energy saving in China. (author)

  19. Energy efficiency supervision strategy selection of Chinese large-scale public buildings

    Energy Technology Data Exchange (ETDEWEB)

    Jin Zhenxing [Faculty of Urban Construction and Environmental Engineering, Chongqing University, Chongqing (China); Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment, Ministry of Education, Chongqing 400045 (China)], E-mail: jinzhenxing33@sina.com; Wu Yong [Department of Science and Technology, Ministry of Construction, Beijing 100835 (China); Li Baizhan; Gao Yafeng [Faculty of Urban Construction and Environmental Engineering, Chongqing University, Chongqing (China); Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment, Ministry of Education, Chongqing 400045 (China)

    2009-06-15

    This paper discusses energy consumption, building development and building energy consumption in China, and points that energy efficiency management and maintenance of large-scale public buildings is the breakthrough point of building energy saving in China. Three obstacles are lack of basic statistics data, lack of service market for building energy saving, and lack of effective management measures account for the necessity of energy efficiency supervision for large-scale public buildings. And then the paper introduces the supervision aims, the supervision system and the five basic systems' role in the supervision system, and analyzes the working mechanism of the five basic systems. The energy efficiency supervision system of large-scale public buildings takes energy consumption statistics as a data basis, Energy auditing as a technical support, energy consumption ration as a benchmark of energy saving and price increase beyond ration as a price lever, and energy efficiency public-noticing as an amplifier. The supervision system promotes energy efficiency operation and maintenance of large-scale public building, and drives a comprehensive building energy saving in China.

  20. Supervision of execution of dismantling; Supervision de ejecucion de desmantelamiento

    Energy Technology Data Exchange (ETDEWEB)

    Canizares, J.

    2015-07-01

    Enresa create and organizational structure that covers various areas involved in effective control of Decommissioning Project. One area is the Technical Supervision of Works Decommissioning Project, as Execution Department dependent Technical Management. In the structure, Execution Department acts as liaison between the project, disciplines involved in developing and specialized companies contracted work to achieve your intended target. Equally important is to ensure that such activities are carried out correctly, according to the project documentation. (Author)

  1. Evaluation of professional supervision in Aotearoa/New Zealand: An interprofessional study.

    Science.gov (United States)

    Davys, Allyson Mary; O'Connell, Michael; May, Janet; Burns, Beverley

    2017-06-01

    The evaluation of professional supervision has been a focus for discussion in the supervision literature over past decades. A review of the literature in this area, however, suggests that evaluation has been differently defined, variously addressed, and a range of outcomes reported. The present study reports the findings of the first stage of a three-stage study of evaluation in professional supervision in Aotearoa/New Zealand. Experienced practitioners from the four professions of counselling, mental health nursing, psychology, and social work were interviewed to explore how evaluation in professional supervision is understood and actioned in practice. Twenty four semistructured interviews were conducted with supervisees, supervisors, and managers from each of the identified professions. The findings from these interviews indicate that a majority of participants applied some form of evaluation to their supervision arrangement. These evaluations, however, did not reflect an overarching organizational or professional culture of formal evaluation, but rather, an individualized ad-hoc process initiated by one or both of the participants (supervisor and supervisee). These evaluations focussed predominantly on the process, rather than the outcomes, of supervision. While many respondents expressed interest in a formal process for evaluating supervision, a number of concerns were also raised. These concerns included a lack of evaluation skills and resource, the potential for formal evaluation to have a negative impact on the supervision relationship, the importance of maintaining the boundaries of confidentiality, and a wariness regarding the possible use of any information gathered. © 2016 Australian College of Mental Health Nurses Inc.

  2. Researching the Parallel Process in Supervision and Psychotherapy

    DEFF Research Database (Denmark)

    Jacobsen, Claus Haugaard

    Reflects upon how to do process research in supervision and in the parallel process. A single case study is presented illustrating how a study on parallel process can be carried out.......Reflects upon how to do process research in supervision and in the parallel process. A single case study is presented illustrating how a study on parallel process can be carried out....

  3. QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms

    Directory of Open Access Journals (Sweden)

    Ardjan Zwartjes

    2016-10-01

    Full Text Available 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.

  4. Quality assurance and supervision of mass concrete construction under EPC mode

    International Nuclear Information System (INIS)

    Peng Hong

    2013-01-01

    Taking one typical general contraction project-Hainan Changjiang nuclear power project as an example, this paper introduces the mass concrete construction of nuclear island foundation of Unit 1 in its installation phase, elaborates how to conduct quality assurance and supervision for concrete production, construction, supervision and management, detects relevant weak points of quality and management in the mass concrete construction through quality assurance supervision, puts forward management requirements for the supervising organizations, accumulates useful experience on how to promote contractors to implement the contract in line with national laws, regulations and to improve the management in equipment installation, commissioning and acceptance. (authors)

  5. Clinical Supervision of Mental Health Professionals Serving Youth: Format and Microskills.

    Science.gov (United States)

    Bailin, Abby; Bearman, Sarah Kate; Sale, Rafaella

    2018-03-21

    Clinical supervision is an element of quality assurance in routine mental health care settings serving children; however, there is limited scientific evaluation of its components. This study examines the format and microskills of routine supervision. Supervisors (n = 13) and supervisees (n = 20) reported on 100 supervision sessions, and trained coders completed observational coding on a subset of recorded sessions (n = 57). Results indicate that microskills shown to enhance supervisee competency in effectiveness trials and experiments were largely absent from routine supervision, highlighting potential missed opportunities to impart knowledge to therapists. Findings suggest areas for quality improvement within routine care settings.

  6. Does training frequency and supervision affect compliance, performance and muscular health?

    DEFF Research Database (Denmark)

    Dalager, Tina; Bredahl, Thomas G V; Pedersen, Mogens Theisen

    2015-01-01

    The aim was to determine the effect of one weekly hour of specific strength training within working hours, performed with the same total training volume but with different training frequencies and durations, or with different levels of supervision, on compliance, muscle health and performance......, behavior and work performance. In total, 573 office workers were cluster-randomized to: 1WS: one 60-min supervised session/week, 3WS: three 20-min supervised sessions/week, 9WS: nine 7-min supervised sessions/week, 3MS: three 20-min sessions/week with minimal supervision, or REF: a reference group without...... training. Outcomes were diary-based compliance, total training volume, muscle performance and questionnaire-based health, behavior and work performance. Comparisons were made among the WS training groups and between 3WS and 3MS. If no difference, training groups were collapsed (TG) and compared with REF...

  7. Academic Writing in Reflexive Professional Writing: Citations of Scientific Literature in Supervised Pre-Service Training Reports

    Directory of Open Access Journals (Sweden)

    Lívia Chaves de Melo

    2013-06-01

    Full Text Available In this paper we investigate citation practices of scientific literature in reflexive writing from the genre of supervised pre-service training report produced by pre-service teachers enrolled in the mandatory pre-service training subject of English Language Teaching, at an undergraduate language teaching course. The aim of this research is to analyze how these pre-services teacher represent themselves based on citation practices of scientific literature, and characterize some of the functions deployed by the citations in the reflexive writing emerging in the academic sphere. We use the dialogic approach to language from Bakhtinian studies as a theoretical base, as well as theoretical and methodological contributions regarding types of sequences and of discourse proposed by Adam and Bronckart. The results of this research show that the practice of citation of scientific literature is an invocation of authority as a form of erudition, amplification and ornamentation of the discourse produced. This practice can also guide pedagogical action developed by pre-service teachers in their supervised training.

  8. Nuclear safety legislation and supervision in China

    International Nuclear Information System (INIS)

    Zhang Shiguan

    1991-02-01

    The cause for the urgent need of nuclear safety legislation and supervision in China is firstly described, and then a brief introduction to the basic principle and guideline of nuclear safety is presented. Finally the elaboration on the establishment of nuclear safety regulatory system, the enactment of a series of regulations and safety guides, and the implementation of licencing, nuclear safety supervision and research for ensuring the safety of nuclear energy, since the founding of the National Nuclear Safety Administration, are introduced

  9. Supervised learning classification models for prediction of plant virus encoded RNA silencing suppressors.

    Directory of Open Access Journals (Sweden)

    Zeenia Jagga

    Full Text Available Viral encoded RNA silencing suppressor proteins interfere with the host RNA silencing machinery, facilitating viral infection by evading host immunity. In plant hosts, the viral proteins have several basic science implications and biotechnology applications. However in silico identification of these proteins is limited by their high sequence diversity. In this study we developed supervised learning based classification models for plant viral RNA silencing suppressor proteins in plant viruses. We developed four classifiers based on supervised learning algorithms: J48, Random Forest, LibSVM and Naïve Bayes algorithms, with enriched model learning by correlation based feature selection. Structural and physicochemical features calculated for experimentally verified primary protein sequences were used to train the classifiers. The training features include amino acid composition; auto correlation coefficients; composition, transition, and distribution of various physicochemical properties; and pseudo amino acid composition. Performance analysis of predictive models based on 10 fold cross-validation and independent data testing revealed that the Random Forest based model was the best and achieved 86.11% overall accuracy and 86.22% balanced accuracy with a remarkably high area under the Receivers Operating Characteristic curve of 0.95 to predict viral RNA silencing suppressor proteins. The prediction models for plant viral RNA silencing suppressors can potentially aid identification of novel viral RNA silencing suppressors, which will provide valuable insights into the mechanism of RNA silencing and could be further explored as potential targets for designing novel antiviral therapeutics. Also, the key subset of identified optimal features may help in determining compositional patterns in the viral proteins which are important determinants for RNA silencing suppressor activities. The best prediction model developed in the study is available as a

  10. Supervision and Performance : The Case of World Bank Projects

    NARCIS (Netherlands)

    Kilby, C.

    1995-01-01

    This paper explores empirical aspects of the relation between supervision and project performance. I focus on development projects funded by the World Bank and on supervision done by the World Bank. The World Bank is the preeminent international development organization both in terms of money lent

  11. Supervision og de tilgrænsende områder

    DEFF Research Database (Denmark)

    Jacobsen, Claus Haugaard

    2007-01-01

    Kapitlet forsøger at indkredse, hvad supervision i det hele taget er. Forskellige tidligere definitioner gennemgås, og forfatteren giver sit eget bud. Derefter sammenholdes supervision kort med nogle af de andre discipliner, som den ofte sammenlignes – og undertiden sammenblandes – med, nemlig...

  12. Distance Supervision in Rehabilitation Counseling: Ethical and Clinical Considerations

    Science.gov (United States)

    Lund, Emily M.; Schultz, Jared C.

    2015-01-01

    Background: The use of technology-mediated distance supervision is a rapidly growing area in rehabilitation counseling and other fields. Distance supervision has both tremendous potential and notable challenges to address, including questions of ethics and evidence. Purpose: This article examines both the ethical and nonethical principles that…

  13. Informal sources of supervision in clinical training.

    Science.gov (United States)

    Farber, Barry A; Hazanov, Valery

    2014-11-01

    Although formal, assigned supervision is a potent source of learning and guidance for psychotherapy trainees, many beginning psychotherapists use other, informal sources of supervision or consultation for advice and support. Results of an online survey of beginning trainees (N = 146) indicate that other than their formally assigned supervisor, trainees most often consult with colleagues in their program, their own psychotherapist, and their significant other; that they're most likely to seek these other sources of help when they're feeling stuck or feel they've made a clinical mistake; that they do so because they need extra reassurance and suggestions; that they feel the advice given from these sources is helpful; and that they don't especially regret sharing this information. Several case examples are used to illustrate these points. Discussing clinical material with informal sources is, apparently, a great deal more common than typically acknowledged, and as such, has implications for training programs (including discussions of ethics) and formal supervision. © 2014 Wiley Periodicals, Inc.

  14. D Semantic Labeling of ALS Data Based on Domain Adaption by Transferring and Fusing Random Forest Models

    Science.gov (United States)

    Wu, J.; Yao, W.; Zhang, J.; Li, Y.

    2018-04-01

    Labeling 3D point cloud data with traditional supervised learning methods requires considerable labelled samples, the collection of which is cost and time expensive. This work focuses on adopting domain adaption concept to transfer existing trained random forest classifiers (based on source domain) to new data scenes (target domain), which aims at reducing the dependence of accurate 3D semantic labeling in point clouds on training samples from the new data scene. Firstly, two random forest classifiers were firstly trained with existing samples previously collected for other data. They were different from each other by using two different decision tree construction algorithms: C4.5 with information gain ratio and CART with Gini index. Secondly, four random forest classifiers adapted to the target domain are derived through transferring each tree in the source random forest models with two types of operations: structure expansion and reduction-SER and structure transfer-STRUT. Finally, points in target domain are labelled by fusing the four newly derived random forest classifiers using weights of evidence based fusion model. To validate our method, experimental analysis was conducted using 3 datasets: one is used as the source domain data (Vaihingen data for 3D Semantic Labelling); another two are used as the target domain data from two cities in China (Jinmen city and Dunhuang city). Overall accuracies of 85.5 % and 83.3 % for 3D labelling were achieved for Jinmen city and Dunhuang city data respectively, with only 1/3 newly labelled samples compared to the cases without domain adaption.

  15. Competencies to enable learning-focused clinical supervision: a thematic analysis of the literature.

    Science.gov (United States)

    Pront, Leeanne; Gillham, David; Schuwirth, Lambert W T

    2016-04-01

    Clinical supervision is essential for development of health professional students and widely recognised as a significant factor influencing student learning. Although considered important, delivery is often founded on personal experience or a series of predetermined steps that offer standardised behavioural approaches. Such a view may limit the capacity to promote individualised student learning in complex clinical environments. The objective of this review was to develop a comprehensive understanding of what is considered 'good' clinical supervision, within health student education. The literature provides many perspectives, so collation and interpretation were needed to aid development and understanding for all clinicians required to perform clinical supervision within their daily practice. A comprehensive thematic literature review was carried out, which included a variety of health disciplines and geographical environments. Literature addressing 'good' clinical supervision consists primarily of descriptive qualitative research comprising mostly small studies that repeated descriptions of student and supervisor opinions of 'good' supervision. Synthesis and thematic analysis of the literature resulted in four 'competency' domains perceived to inform delivery of learning-focused or 'good' clinical supervision. Domains understood to promote student learning are co-dependent and include 'to partner', 'to nurture', 'to engage' and 'to facilitate meaning'. Clinical supervision is a complex phenomenon and establishing a comprehensive understanding across health disciplines can influence the future health workforce. The learning-focused clinical supervision domains presented here provide an alternative perspective of clinical supervision of health students. This paper is the first step in establishing a more comprehensive understanding of learning-focused clinical supervision, which may lead to development of competencies for clinical supervision. © 2016 John Wiley

  16. Availability analysis of supervised protective systems

    International Nuclear Information System (INIS)

    Kontoleon, N.; Kontoleon, J.M.; Chrysochoides, N.G.

    1975-01-01

    The behaviour in time of a nuclear reactor supervised protective system is modelled mathematically by a Markov process, continuous in time and with three discrete states. Failure and repair rates are assumed to be exponentially distributed. An analytical expression of system availability as a function of failure and repair rates as well as the inspection intervals and duration is derived. An optimization problem is then discussed in order to maximize system availability with respect to imposed cost constraints. Finally, an example of a supervised protective system with short inactive times is given, which may be found in many practical situations of modern protective systems. (author)

  17. A Content Analysis of Peer Feedback in Triadic Supervision

    Science.gov (United States)

    Avent, Janeé R.; Wahesh, Edward; Purgason, Lucy L.; Borders, L. DiAnne; Mobley, A. Keith

    2015-01-01

    There is limited research on the types of peer feedback exchanged during triadic supervision. Through a content analysis, the authors found that students provided feedback about counseling performance and cognitive counseling skills most often in supervision sessions. However, there were differences in the types of feedback exchanged across three…

  18. Paediatric trainee supervision: management changes and perceived education value.

    Science.gov (United States)

    van den Boom, Mirjam; Pinnock, Ralph; Weller, Jennifer; Reed, Peter; Shulruf, Boaz

    2012-07-01

    Supervision in postgraduate training is an under-researched area. We measured the amount, type and effect of supervision on patient care and perceived education value in a general paediatric service. We designed a structured observation form and questionnaire to document the type, duration and effect of supervision on patient management and perceived education value. Most supervision occurred without the paediatrician confirming the trainee's findings. Direct observation of the trainee was rare. Management was changed in 30% of patients seen on the inpatient ward round and in 42% of the patients discussed during the chart reviews but not seen by the paediatrician. Management was changed in 48% of the cases when the paediatrician saw the patient with the trainee in outpatients but in only 21% of patients when the patient was but not seen. Changes made to patient management, understanding and perceived education value, differed between inpatient and out patient settings. There was more impact when the paediatrician saw the patient with the trainee in outpatients; while for inpatients, the opposite was true. Trainees rated the value of the supervision more highly than their supervisors did. Trainees' comments on what they learnt from their supervisor related almost exclusively to clinical knowledge rather than professional behaviours. We observed little evidence of supervisors directly observing trainees and trainees learning professional behaviours. A review of supervisory practices to promote more effective learning is needed. Communicating to paediatricians the value their trainees place on their input could have a positive effect on their engagement in supervision. © 2012 The Authors. Journal of Paediatrics and Child Health © 2012 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

  19. Photoaffinity analogues of methotrexate as folate antagonist binding probes. 1. Photoaffinity labeling of murine L1210 dihydrofolate reductase and amino acid sequence of the binding region

    International Nuclear Information System (INIS)

    Price, E.M.; Smith, P.L.; Klein, T.E.; Freisheim, J.H.

    1987-01-01

    N/sup α/-(4-Amino-4-deoxy-10-methylpteroyl)-N/sup epsilon/-(4-azido-5-[ 125 I]iodosalicylyl)-L-lysine, a photoaffinity analogue of methotrexate, is only 2-fold less potent than methotrexate in the inhibition of murine L1210 dihydrofolate reductase. Irradiation of the enzyme in the presence of an equimolar concentration of the 125 I-labeled analogue ultimately leads to an 8% incorporation of the photoprobe. A 100-fold molar excess of methotrexate essentially blocks this incorporation. Cyanogen bromide digestion of the labeled enzyme, followed by high-pressure liquid chromatography purification of the generated peptides, indicates that greater than 85% of the total radioactivity is incorporated into a single cyanogen bromide peptide. Sequence analysis revealed this peptide to be residues 53-111, with a majority of the radioactivity centered around residues 63-65 (Lys-Asn-Arg). These data demonstrate that the photoaffinity analogue specifically binds to dihydrofolate reductase and covalently modifies the enzyme following irradiation and is therefore a photolabeling agent useful for probing the inhibitor binding domain of the enzyme

  20. Theoretical Application of Supervision over Quality and Safety of Agricultural Products

    Institute of Scientific and Technical Information of China (English)

    Xin; CHENG; Ying; ZHANG

    2013-01-01

    Supervision over quality and safety of agricultural products has received high attention of management department.Competent authorities have formulated and issued many measures to strengthen supervision over quality and safety of agricultural products and improve China’s agricultural product quality and safety level.From the perspective of management science,this paper elaborates basic contents of two basic management theories,Broken Windows Effect and Effect of Heat Furnace.Then,it analyzes influence of Broken Windows Effect and Effect of Heat Furnace on supervision over quality and safety of agricultural products.Finally,it comes up with recommendations for supervision over quality and safety of agricultural products.